The objective of this chapter is to assess Indigenous economic development and wellbeing outcomes at the regional level. The chapter begins discussing definitions of Indigenous peoples and statistical frameworks to collect data about them. The chapter then presents socio-economic data about Indigenous peoples at a sub-national level identifying differences in outcomes with non-Indigenous populations. Factors associated with these differences across different types of regions are also assessed with particular challenges identified for rural remote areas. The chapter finishes with an assessment of how to improve statistical frameworks and empower Indigenous peoples through changes to data governance.
Linking Indigenous Communities with Regional Development
Chapter 1. Indigenous economic development and well-being: Statistics and data governance
Abstract
Key findings and recommendations
Key findings
Indigenous peoples are defined by the United Nations as those who inhabited a country prior to colonisation, and self-identify as such due to descent from these peoples and belonging to social, cultural or political institutions that govern them.
Definitions within countries are not applied consistently in statistical systems across different state agencies and between levels of government. Combined with lower levels of trust regarding public institutions and data collection, this contributes to poor or fragmented data about Indigenous peoples.
There are 38 million Indigenous people who live in 13 OECD member countries, which is equivalent to the total population of Poland, the 12th largest OECD member country in terms of the size of population.
Subnational analysis in this chapter focuses on five OECD member countries that have disaggregated data available on Indigenous peoples (Australia, Canada, Mexico, New Zealand and the United States). These countries present 94% of the total Indigenous peoples across OECD member countries.
Across these five countries, Indigenous peoples are distributed unevenly across national territories and are concentrated in rural areas, as compared to non-Indigenous populations.
There are significant gaps in economic outcomes between Indigenous and non-Indigenous populations, and these gaps are larger in rural areas than national averages.
Recommendations
Indigenous statistical frameworks can be improved by:
Developing an agreed national definition that is consistent with the principles of the International Labour Organization’s (ILO) Indigenous and Tribal Peoples Convention 169 (self-identification, descent and belonging to a group).
Applying the agreed national definition consistently across different government agencies and between levels of government.
Including Indigenous territories in the standard geographic classification for the collection and reporting of statistics.
Providing regular reporting of Indigenous well-being outcomes (economic, social and environmental dimensions) at the national and subnational levels (disaggregated by urban, rural and remote regions) and by gender and age dimensions (that are internationally comparable and in line with the Sustainable Development Goals [SDGs]).
Implementing specific population-based surveys on issues that are important to Indigenous peoples and can address gaps in the statistical framework (e.g. subsistence, health, business, and leadership and governance).
Indigenous data governance can be strengthened by:
Including Indigenous representatives in the governance of national statistical agencies to provide advice on strategic and operational issues impacting on Indigenous peoples (e.g. definitions for statistical purposes, the design of well‑being indicators and data collection methods).
Implementing protocols and agreements to enable the pooling of data between different agencies to increase sample sizes and the availability of data.
Adapting data collection methods to the needs of Indigenous peoples through interview-administered surveys in Indigenous languages that include communities in the data collection process.
Providing tools and capabilities for Indigenous organisations to collect their own data on issues that are important to their communities, and support more informed decision-making about development.
Introduction
The objective of this chapter is to assess Indigenous economic development and well‑being outcomes at the regional level. This assessment involves five elements. First, the chapter discusses definitions of Indigenous peoples and frameworks to collect statistics across OECD member countries. Second, the chapter evaluates the distribution of Indigenous populations across OECD member countries, along with their distribution at the subnational level. Third, the chapter discusses Indigenous well-being and presents data about well-being outcomes at the national and subnational level. Fourth, the chapter identifies the factors associated with economic development outcomes across different types of regions (urban, intermediate and rural). Finally, the chapter concludes with a discussion about data governance that focuses on how to improve Indigenous statistical frameworks in ways that empower Indigenous peoples.
Definitions and overview
International definition of Indigenous peoples
In recent decades there have been efforts to develop a clearer international legal framework for the rights of Indigenous peoples (Daes, 2008[1]). In general, the concept of Indigenous peoples is not straightforward as the term “Indigenous” can have different connotations depending on the context, has changed over time and can be applied differently across and within countries. These changes and differences can generate divisions within Indigenous societies, affect the collection of statistics and therefore impact the effectiveness of public policies.
International conventions and declarations have been formative in developing globally encompassing definitions of Indigenous peoples. For instance, the ILO’s Indigenous and Tribal Peoples Convention 169 proposes that self-identification as Indigenous or tribal shall be regarded as a fundamental criterion for determining the groups to which its provisions apply, which include:
Tribal peoples in independent countries whose social, cultural and economic conditions distinguish them from other sections of the national community and whose status is regulated wholly or partially by their own customs or traditions or by special laws or regulations.
Peoples in independent countries who are regarded as Indigenous on account of their descent from the populations which inhabited the country, or a geographical region to which the country belongs, at the time of conquest or colonisation or the establishment of present state boundaries and who, irrespective of their legal status, retain some or all of their own social, economic, cultural and political institutions (ILO, 1989[2]).
Table 1.1 presents how selected OECD member and non-member countries define Indigenous peoples in their legal frameworks and the statistical criteria for Indigenous identity. The majority of OECD member countries and selected partner countries apply the ILO Convention 169 definition framework in their legal and statistical frameworks.
At the national level, Australia bases its definition of Indigenous peoples on three criteria: ancestry, self-identification and community acceptance. Similarly, countries such as Canada tend to define their Indigenous population based on self-identification. However, definitions that use community acceptance might, in some cases, be problematic as some Indigenous peoples may identify themselves as Indigenous, have Indigenous parents but not be part of any Indigenous community for some reason. It may result in some people who self-identify as Indigenous not having the same legal rights and access to resources and services that others have. This type of complexity has been experienced in Canada where some people who have ancestry in First Nations are not recognised as having “Indian1 status” under the Indian Act2 (even though they self-identify themselves as Indigenous) due to weak or absent linkages with an ancestral Indigenous community.
Definitions of Indigenous peoples in northern European countries include specific objective characteristics of Indigenous culture such as when Indigenous language was spoken in the family home and their occupation. For example, Finland, Norway and Sweden attach specific legal rights to the traditional Sámi practice of nomadic reindeer herding. According to (Lantto and Mörkenstam (2008[3]), nomadic reindeer herding is only relevant to a small proportion of the Sámi people today. Particular objective characteristics in the legal definition mean that some Sámi who self-identify are not recognised as Indigenous peoples under the national law, which can create divisions within Indigenous societies (OECD, 2019[4]).
In the United States, self-identification (as American Indian, Native Hawaiian or Alaskan Native) is used as the fundamental criteria for collecting statistics. However, different definitions are used in relation to the application of laws related to Indigenous peoples and access to services and programmes. The legal definition framework of the United States differs from frameworks used in other countries since state governments are able to use their own definitions and procedures. This type of system is complex, as an individual can be recognised as “Indian” under the federal laws but not under the state laws and vice versa. The Federal government recognises 573 tribes and state governments can recognise tribes which are not recognised by the federal government. For example, the definition used in the Bureau of Indian Affairs includes the requirements mentioned above plus other specifications: Indian is an individual, who is qualified to use its services, as an individual who is a “member” of an Indian tribe, band, or community that is “recognised” by the federal government; who lives on “or near” a reserve; and has one‑quarter or more Indian ancestry.3
Table 1.1. Legal definition of Indigenous peoples across selected OECD member and non-member countries
Legal definition |
|
---|---|
Selected OECD member countries |
|
Australia |
An Aboriginal or Torres Strait Islander is a person of Aboriginal and Torres Strait Islander descent who identifies as an Aboriginal or Torres Strait Islander and is accepted as such by the community in which he or she lives. |
Canada |
Indigenous people is a collective name for the original peoples of North America and their descendants. In the Census of Population, “Aboriginal identity” refers to whether the person identified with the Aboriginal peoples of Canada. This includes those who are First Nations (North American Indian), Métis or Inuk (Inuit) and/or those who are Registered or Treaty Indians (that is, registered under the Indian Act of Canada), and/or those who have membership in a First Nation or Indian band. Aboriginal peoples of Canada are identified in the Constitution Act, 1982, Section 35 (2) as including the Indian, Inuit and Métis peoples of Canada. |
Chile |
Indigenous peoples of Chile are the descendants of the human groups that exist in the national territory since pre-Columbian time, which retain their own ethnic and cultural manifestations. The law recognises nine Indigenous groups. |
Finland |
In the Sámi Parliament Act 17.7.1995/974, a Sámi person is defined as a person who identifies him- or herself as Sámi person, provided that he or at least one of his/her parents or grandparents have learnt Sámi language as his/her first language; or s/he is descendant of a person who has entered in a land, taxation or a population register as mountain, forest or fishing Lapp/Lappish; or at least one of his/her parent is entered or could have been registered as a voter to Sámi Delegation or Sámi Parliament elections. |
Mexico |
Indigenous peoples are those that descend from populations that inhabited the current territory of the country at the beginning of colonisation and that preserve their own social, economic, cultural and political institutions, or part of them. |
New Zealand |
Māori means a person of the Māori race of New Zealand, and includes any descendant of such a person. |
Sweden |
Sámi refers to a person who considers him/herself to be Sámi (subjective) and ensures that he or she has or have had the Sámi language spoken at home, or ensures that any of his or her parents or grandparents have or have had the Sámi language spoken at home, or has a parent who is or has been listed on the electoral roll of the Sámi Parliament. This definition refers to eligibility to vote in elections for the Sámi Parliament. |
United States |
Self-identification as American Indian or Native Alaskan for the purposes of collecting statistics. Different criteria used at federal and state level in relation to legal rights, and access programmes and services. |
Select non-member countries |
|
Argentina |
People that are recognised as belonging to or descendant of an Indigenous people or a native of Argentina. Argentina recognises 34 Indigenous groups that speak 10 different languages. |
Colombia |
Belonging to an Indigenous group, identification with Indigenous culture and physical traits, and language spoken at home. There are 87 recognised different Indigenous groups in Colombia that speak 65 languages. |
Peru |
Indigenous peoples are recognised in the constitution but different definitions are used across the national census, population censuses for the Amazon, and the national agrarian census. |
Russian Federation |
Russian legislation recognises Indigenous peoples using the following six criteria: ethnic self-identification (self-awareness as an independent ethnic community); preservation of an original territory or habitat; preservation of a special economic space through the doing of folk crafts; preservation of the original culture; keeping a native language common to all; and have a population in Russia less than 50 000 people. |
Source: Elaboration based on survey responses by countries.
Statistical frameworks used in OECD countries
The simplest statistical definition is one that aligns with the ILO 169 convention in terms of self-identification based on descent and/or belonging and acceptance by a group. Many countries align with this principle and use simple self-identification questions in their statistical frameworks (Table 1.2). This is the case for Australia, Canada, New Zealand and the United States. As discussed in the previous section, other countries also place various types of conditions and restrictions on the characteristics of Indigenous identity (e.g. linguistic, status and occupational, registration or recognition of groups by the state, and geography). Some countries do not collect statistics about Indigenous peoples because of laws prohibiting ethnic identification.
Table 1.2. The statistical framework to identify Indigenous peoples
Statistical identification method |
Question |
Changes in the statistical definition |
|
---|---|---|---|
Selected OECD member countries |
|||
Australia |
Self-identification question based on origin. |
“Are you of Aboriginal or Torres Strait Islander origin?” |
The 1996 Census was the first Census to allow people’s origins to be recorded as both Aboriginal and Torres Strait Islander, prior to this only one or the other could be recorded. |
Canada |
Self-identification question with respect to ethnic or cultural identity. |
Is this person an Aboriginal person, that is, First Nations (North American Indian), Métis or Inuk (Inuit)? Respondents could respond “Yes, First Nations (North American Indian)”, “Yes, Métis”, “Yes, Inuk (Inuit)” or “No, not an Aboriginal person” by checking off the appropriate mark-in circle. As well, respondents can also respond “No” or “yes” as to whether they had Registered or Treaty Indian Status or membership in a First Nations or Indian band. |
This criterion was first used in 1996. Prior to that, the Indigenous population was defined on the basis of reported ancestry. |
Chile |
Self-identification question with respect to ethnic origin. |
Do you consider yourself a member of a community of Indigenous peoples? |
.. |
Finland |
Indigenous people are identified by their first language. |
.. |
The criteria have not changed in the past 10-20 years. |
Mexico |
The National Institute of Statistics and Geography (INEGI) of Mexico use language registration and self-identification with respect to identity asked to every individual age five and older as statistical identification of the Indigenous population of Mexico. |
.. |
Prior to that, the main criterion to define Indigenous population was the Indigenous language spoken at home. |
New Zealand |
Self-identification with respect to identity. |
Which ethnic group do you belong? |
Descent/ancestry unchanged since 1991, Ethnicity (w.r.t Māori) unchanged since 1986. |
Sweden |
Statistics Sweden does not have any legal basis on which to collect or disseminate statistic on individuals with regards to ethnicity. |
.. |
.. |
United States |
Self-identification question with respect to ethnic identity. |
The American Indian and Alaska Native population includes people who marked [on the 2010 Census form/Exhibit 1] the “American Indian or Alaska Native” checkbox or reported entries such as Navajo, Blackfeet, Inupiat, Yup’ik, or Central American Indian groups or South American Indian groups. |
.. |
Select non-member countries |
|||
Argentina |
The criterion used has been the population that is recognised as belonging to or descendant of an Indigenous people or originating in Argentina. |
.. |
.. |
Colombia |
Self-identification with respect to cultural identity. |
.. |
.. |
Peru |
Self-identification with respect to their identity. |
.. |
First time used in 2017 Census. |
Russian Federation |
Self-identification related to national group. |
What is your national identity? |
.. : Missing value or not available.
Source: Own elaboration based on survey responses from countries.
Statistical identification methodologies based on specific objective characteristics are less inclusive and less likely to produce accurate estimates. Specifically, statistical identification based on population’s ancestral territories, or embeddedness in traditional cultures and practices, can lead to underestimation of Indigenous population whenever attachment with traditional groups is lost after migrating to urban areas. Additionally, the addition of linguistic criteria can lead to exclusion (Box 1.1).
Box 1.1. Use of linguistic criteria to define Indigenous peoples, the cases of Finland and Mexico
Although Indigenous language has been acknowledged as a crucial part of Indigenous identity, it does not serve as a good proxy for Indigenous identity since it is not inclusive. In some regions, the Indigenous language has been replaced with the dominant language. Moreover, Indigenous peoples have a greater likelihood to face discrimination, which may force them to give up their first language and to adapt to the mainstream culture. Historically, Indigenous peoples were also coerced into not using their own language (for example through the school system). As a result, the total size of Indigenous populations may be underestimated (Barbary, 2015[5]).
Mexico utilises two definitions, which produces different conclusions about the size of the Indigenous population. Based on self-identification the Indigenous population of Mexico is 25.7 million people or 21.5% of the population. Based on the criteria of speaking an Indigenous language at home, the Indigenous population of Mexico is 12.3 million people or 10.1% of the population. The National Commission for the Development of Indigenous Peoples of Mexico uses both Indigenous language and self‑identification as criteria for identification. The linguistic criterion is based on the principle that language is fundamental to the reproduction of Indigenous culture.
Although the collection of statistics based on ethnicity is not permitted in Finland, the National Statistical Office of Finland has estimated the size of the Sámi population to be around 2 000 people. This is based on individuals who have listed the Sámi language as their first language. However, the population estimate made by the Sámi Parliament is five times higher than the estimate of the Statistical Office Finland.
Sources: Own elaboration based on multiple sources; Barbary, O. (2015), “Social inequalities and indigenous populations in Mexico: A plural approach”, http://dx.doi.org/10.1007/978-3-319-20095-8_11.
Another way the scope of Indigenous data collection is restricted is the limitation of self-identification to specific groups that are legally recognised. This can be problematic depending upon the requirements and procedures put in place to achieve this recognition. The occupation of traditional territory, engagement in traditional occupations and practices, and use of Indigenous languages may all restrict the groups which are recognised. It may also relate to how customary law, kinship relations and traditional knowledge are recognised in state law. Some Indigenous groups in remote areas may also have very limited contact with the state and reliable information about them may be lacking.
Some countries also explicitly forbid the collection of statistics on ethnic identity. Finland, Norway and Sweden are examples of countries that apply this rule. As a result, other forms of data collection become the primary way of recognising and collecting statistics about Indigenous peoples. In Sweden, far more is known about Sámi who participate in what are considered traditional livelihoods and who live in the reindeer husbandry area situated in the Swedish parts of Sápmi (foremost the regions of Jämtland-Härjedalen, Norrbotten, Västerbotten) and the northernmost part of the region of Dalarna, because these activities are captured by reindeer industry codes in official statistics (as opposed to ethnic identification).4 However, it has been estimated that less than 20% of the Sámi population is connected to reindeer herding (Axelsson and Sköld, 2006[6]).
Although some countries have a well-defined statistical framework for Indigenous people, they are not used by all the bodies of government and other organisations that collect data on Indigenous peoples. A common challenge can be the sharing of data between different agencies of government. For example, there may be protocols or rules regarding privacy which inhibit data sharing with Indigenous populations so they can make informed decisions. This may include data about the use of health and education services, law enforcement and justice, land use and environmental assessments, public investment and tax collection.
Data collection and sharing challenges also exist across different levels of government. In federal countries, subnational governments may have responsibility for some of the key areas impacting Indigenous well-being (for example the delivery of health and education services in the case of Australia and Canada). However, disaggregated data regarding how Indigenous peoples use these services and the results generated from them may not be shared between levels of government, or with Indigenous communities. Reducing these barriers to enable better data sharing can result in better policies and more informed decision-making.
The geographic distribution of Indigenous people in OECD regions
There are approximately 38 million Indigenous peoples across 12 OECD member countries, which is equivalent to the total population of Poland, the 12th largest OECD member country in terms of the size of population. Countries that work closely with the OECD, some of whom are on in the process of membership or accession, also have significant Indigenous populations (e.g. Argentina, Brazil, Colombia, Costa Rica, Indonesia and Peru).
A better understanding of the well-being of Indigenous peoples is an important global issue and for OECD countries. The subnational analysis focuses on five OECD member countries that have disaggregated data available on Indigenous peoples (Australia, Canada, Mexico, New Zealand and the United States). These countries present 94% of the total Indigenous peoples across OECD member countries (see Table 1.3 ).
Table 1.3. Indigenous peoples in selected OECD countries
Country |
No. of Indigenous people |
---|---|
Australia |
798 381 |
Canada |
1 673 785 |
Mexico |
25 699 111 |
New Zealand |
692 300 |
United States |
6 706 210 |
Total |
35 569 787 |
Total OECD |
38 026 976 |
Note: The Indigenous population data of the United States refers to the Indigenous population identified as American Indian and Alaska Native, alone or in combination. Total Indigenous population is based on estimates of the number of Indigenous people in OECD countries (see Table 1.4).
Sources: Data is based on Australian Bureau of Statistics (2017[7]) Feature Article 1: Aboriginal and Torres Strait Islander Population Estimates, 2016 for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population for Canada; INEGI (n.d.[9]), Encuesta Intercensal [Intercensal Survey], 2015 data for Mexico; Statistics New Zealand (n.d.[10]), 2013 Census (database) for New Zealand; U.S. Census Bureau (n.d.[11]), 2012-2016 American Community Survey 5-Year Estimates, Table DP05 using American FactFinder for the United States.
National distribution
The size of Indigenous populations differs significantly across OECD member and non‑member countries. Table 1.4 provides estimates of Indigenous populations for OECD member and selected non-member countries that report having Indigenous population. These population numbers are likely to be underestimated as they are highly dependent on the Indigenous peoples’ identification method. At the national level, Indigenous peoples form a relatively small population group with regards to the dominant population. There is also a significant range in the proportion and size of the population. The country with the largest proportion of Indigenous peoples is New Zealand with 16.3% and the smallest is Japan with 0.02%. The largest Indigenous population within OECD countries is found in Mexico with an estimated population of 12.3 million (based on the spoken language of Indigenous household). If the definition is extended to those who self-identify as Indigenous, the estimated size is 25.7 million or 21.5% of the population (Table 1.4).
Table 1.4. Estimated Indigenous populations in OECD member and select non-member countries
OECD member countries |
Indigenous peoples |
Population |
Percentage of national population |
---|---|---|---|
Australia |
Aboriginal |
798 381 |
3.3 |
Canada |
First Nation/Inuit/Métis |
1 673 785 |
4.9 |
Chile |
Various |
2 185 722 |
9 |
Denmark (Greenland)* |
Inuit |
50 220 |
(85) |
Finland |
Sámi |
10 000 |
|
France (New Caledonia)* |
Kanak |
104 958 |
(39.1) |
Japan |
Ainu |
28 782 |
0.02 |
Mexico |
Various |
12 250 947-25 699 111 |
10.1-21.5 |
New Zealand |
Māori |
692 300 |
16.3 |
Norway |
Sámi |
50 000-65 000 |
1-1.3 |
Sweden |
Sámi |
20 000 |
0.2 |
United States |
American Indian/Alaskan native |
3 739 506-6 706 210 |
1.2-2 |
Total population |
38 026 969* |
||
Select non-member countries |
|||
Argentina |
Various groups |
955 032 |
2.4 |
Colombia |
Various (65 Amerindian languages) |
1 392 623 |
3.4 |
Costa Rica |
Various incl. Bruca and Bribri |
104 143 |
2 |
Brazil |
Various incl. Guarani |
896 917 |
0.47 |
South Africa |
San people and Khoekhoe |
529 819 |
1 |
Peru |
Various incl. Quechua and Aymara |
4 000 000 |
4 |
Russian Federation |
Various |
257 895 |
0.2 |
Total select non-member |
8 136 429 |
||
Total Indigenous population |
46 163 398* |
*: Estimate of the total Indigenous population. For the United States, the first population figure refers to race alone and the second to race alone or in combination. For Mexico, the first population figure refers to the population that speaks Indigenous language/s and the second one to the population that self-identify as Indigenous.
Note: Population data for Greenland refers to population born in Greenland. Greenland is defined as an autonomous country within Denmark, whilst New Caledonia is a special collectively of France. Data refer to 2017 for Chile; 2016 for Australia, Canada and the United States; 2015 for Mexico; 2014 for France; 2013 for New Zealand; 2011 for Costa Rica; 2010 for Brazil; 2005 for Colombia.
Sources: Data is based on Australian Bureau of Statistics (2017[7]), Feature Article 1: Aboriginal and Torres Strait Islander Population Estimates, 2016 for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population for Canada; National Institute of Statistics Chile (2018[12]), 2017 Census Results [Resultados Censo 2017] for Chile; Sámi Parliament Finland (n.d.[13]), The Sámi in Finland for Finland; National Institute of Statistics and Economic Studies of New Caledonia (2015[14]) for France;, Statsbank Greenland (2018[15]), 2018 Population in Greenland for Denmark, The Food and Agriculture Organization (FAO) (n.d.[16]), Indigenous peoples (country data) for Japan, Norway, Argentina, Peru, South Africa and Russian Federation; INEGI (n.d.[9]), Encuesta Intercensal [Intercensal Survey], 2015 data for Mexico; Statistics New Zealand (n.d.[10]), 2013 Census (database) for New Zealand; Sámi Parliament (2018[17]), Background: The State and the Sami Parliament for Sweden; U.S. Census Bureau (n.d.[11]), 2012-2016 American Community Survey 5-Year Estimates, Table PEPASR6H & PEPASR5H, using American FactFinder for the United States; National Institute of Statistics and Census of Costa Rica (n.d.[18]) Census 2011 Ethnic groups [Grupos étnicos - raciales] for Costa Rica; The Government of Colombia's National Administrative Department of Statistics (DANE) (n.d.[19]), 2005 Census for Colombia; and The Brazilian Institute of Geography and Statistics (IBGE) (n.d.[20]), 2010 Census for Brazil.
Subnational distribution of Indigenous peoples: The importance of rural areas
In most countries, Indigenous people are highly concentrated in specific locations. For instance, Indigenous people populate the northern areas of Finland, Sweden and Norway. In Denmark and France, Indigenous populations are respectively in the territories of Greenland and New Caledonia. Although the Ainu constitute a very small proportion of Japan’s total population they are concentrated in their ancestral home on the island of Hokkaido.
This section discusses the distribution of Indigenous peoples across Territorial Level 2 (TL2) and Territorial Level 3 (TL3) regions, and across types of TL3 regions (see Box 1.2). The OECD extended typology has also classified TL3 regions into four categories: predominantly urban, intermediate, predominantly rural close to a city and predominantly rural remote.
Box 1.2. OECD TL3 regional typology
OECD regional levels and their classification
Territorial Level 2 (TL2) and Territorial Level 3 (TL3) regions are two main territorial levels used by the OECD for comparative statistical analysis across member countries. TL2 regions consist of macro-regions within each OECD country, such as states in the United States of America or provinces in Argentina. TL3 regions consist of smaller micro-regions within TL2 regions. The OECD has developed a regional typology of Territorial Level 3 (TL3) regions to compare regional performance across member countries.
The OECD taxonomy defines TL3 regions as predominantly urban (hereafter referred to as urban), intermediate and predominantly rural (hereafter referred to as rural). This taxonomy, established in 1991, is designed for facilitating international comparability of data. With this aim, it applies the same criterion and selects comparable units among OECD member countries. The OECD scheme distinguishes between two levels of geography within countries: a local community level and a regional level. Local communities are defined as basic administrative units or small statistical areas. They are classified as either rural or urban using a population density threshold. In a second step, TL3 regions, which correspond to larger administrative units or functional areas, are defined as predominantly urban, intermediate or rural with a criterion measuring the share of the population living in rural communities.
The first step in the OECD territorial typology is that of classifying “local units” (administrative entities at a geographical level lower than TL3) as rural if their population density is below 150 inhabitants per km2. In a second step, the local units are aggregated into TL3 regions and classified as “predominantly urban”, “intermediate” and “predominantly rural” using the percentage of population living in rural local units. A third step takes into account possible reclassification of predominantly rural and intermediate units based on the population size of their main agglomeration.
Source: Brezzi, M., L. Dijkstra and V. Ruiz (2011[21]), “OECD Extended Regional Typology: The Economic Performance of Remote Rural Regions”, http://dx.doi.org/10.1787/5kg6z83tw7f4-en.
This typology has been created for statistical purposes because each of these types of regions tends to have different kinds of development challenges and opportunities. Rural areas can be classified into different types according to their proximity to urban centres for the purpose of defining specific challenges and opportunities related to their geographic location (Table 1.5).
Table 1.5. Summary of challenges and opportunities by type of rural region
Type |
Challenges |
Opportunities |
---|---|---|
Rural inside functional urban area (FUA) |
Loss of control of future-activities concentrate in core. Loss of rural identity. |
More stable future-potential to capture benefits of urban, and avoid negatives. |
Rural outside, but in close proximity to an FUA |
Conflicts between new residents and locals. May be too far away for some firms, but too close for others. |
Potential to attract high-income households seeking a high quality of life. Relatively easy access to advanced services and urban culture. Good access to transport. |
Rural remote |
Highly specialised economies subject to booms and busts-limited connectivity and large distances between settlements. High per capita costs of services. |
Absolute advantage in production of natural resource-based outputs. Attractive for firms that need access to an urban area, but not on a daily basis. Can offer unique environments that can be attractive to firms and individuals. |
Source: OECD (2016[22]), OECD Regional Outlook 2016: Productive Regions for Inclusive Societies, https://dx.doi.org/10.1787/9789264260245-en.
Territorial Level 2 (TL2) distribution
The high geographical concentration and the share of Indigenous people highlight the significant role of Indigenous peoples in some OECD regional economies. Approximately three-quarters of all Indigenous peoples concentrate in one-third of all TL2 regions in the five selected countries (38 TL2 regions). Table 1.6 highlights the significance of Indigenous peoples in certain regions. Within these regions, the share of Indigenous population varies from 1.66% (California) to 85.86% (Nunavut). In regions such as Nunavut (Canada), Oaxaca (Mexico), Yucatán (Mexico) and Northwest Territories, Indigenous people represent more than 50% of the total regional population. Defined by the number of Indigenous populations living in the region, the region with the largest estimated number of Indigenous peoples is found in the State of Mexico, Mexico with its total Indigenous population of 2 751 672.
Table 1.6. Regional distribution of the Indigenous population in five study countries, regions with the greatest share and size of Indigenous peoples
OECD member countries |
Top TL2 region |
Population |
% Indigenous population of the region |
% of total national Indigenous population |
---|---|---|---|---|
Australia |
Northern Territory |
58 806 |
27 |
9 |
New South Wales |
216 000 |
3 |
34 |
|
Canada |
Nunavut |
30 550 |
86 |
2 |
Ontario |
374 395 |
3 |
22 |
|
Mexico |
Oaxaca |
2 608 093 |
66 |
10 |
State of Mexico |
2 751 672 |
17 |
11 |
|
New Zealand |
Gisborne |
19 683 |
49 |
3 |
Auckland Region |
163 920 |
12 |
24 |
|
United States |
Alaska |
139 762 |
18 |
2 |
California |
1 026 741 |
3 |
15 |
Note: The Indigenous population data of the United States refers to the Indigenous population identified as American Indian and Alaska Native, alone or in combination.
Sources: Data is based on Australian Bureau of Statistics (ABS) (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population for Canada; INEGI (n.d.[24]), Estimadores de la Población Total y su Distribución Porcentual Según Autoadscripción Indígena por Entidad Federativa, Sexo y Grandes Grupos de Edad [Total Population Estimators and Their Percentage Distribution according to Indigenous Self-identification], 2016 for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), 2012-2016 American Community Survey 5-Year Estimates, Table PEPASR5H, using American FactFinder for the United States.
Territorial Level 3 (TL3) distribution
Across Australia, Canada, Mexico, New Zealand and the United States a larger proportion of Indigenous people live in predominantly rural regions (compared to the non-Indigenous population). On average, 44% of the Indigenous peoples in these five countries live in predominantly rural areas (Figure 1.1). Moreover, Indigenous peoples in rural areas represent about 8% of the total rural population. On the contrary, 30% of the total Indigenous populations of the five OECD countries live in urban areas, about 25 percentage points less than the share for the non-Indigenous population living in urban areas. About 5% of the total urban population across these five countries is Indigenous.
Indigenous peoples represent much higher shares in rural regions than non-Indigenous peoples. Around 44% of the Indigenous population live in predominantly rural regions across the selected countries, 19 percentage points more than the average of 25% for the non-Indigenous population (Figure 1.2). Canada holds the largest share of Indigenous peoples in rural areas: in 2016, 59% of the Indigenous Canadians lived in rural areas, representing a difference of 33 percentage points compared to the share of non‑Indigenous peoples living in rural areas. A large difference also occurs in Australia: 48% of the total Indigenous population and only 34% of non-Indigenous peoples are living in rural areas (a difference of 14 percentage points).
However, recent trends show that Indigenous populations are becoming increasingly urbanised. While the majority of the Indigenous population still lives in rural regions, the share of Indigenous people in urban regions increased (4.6%), particularly in Australia and Mexico during 2010‑16, and it is expected to keep rising. Simultaneously, rural regions have experienced falling rates (-2.8%) of peoples who self-identify themselves as Indigenous during 2011‑16. For example, the share of Indigenous peoples in urban regions of Mexico has increased by approximately 15% and the share of Indigenous peoples in rural regions has decreased by 8% (Figure 1.3). A similar pattern is observed in the change in the distribution of non-Indigenous peoples over the same time period: urban regions experienced an increase in the share of the population of non-Indigenous peoples (1.5%) while rural regions experienced a decrease (-2.3%) in the share of the non‑Indigenous population.
Two reasons may explain this urbanisation trend. First, Indigenous peoples migrate from rural areas to cities as people seek employment opportunities and access to public goods and services. In developing and middle-income countries, this can also occur in the context of decreased demand for labour in rural regions as a result of modernisation in the agricultural sector. Second, the higher propensity to self-identify as Indigenous may be more concentrated in urban areas. Australia, Canada, New Zealand and the United States experienced a large increase in the number of people self-reporting an Indigenous ancestry in recent census waves that cannot be explained by population growth alone (Balestra and Fleischer, 2018[27]). For example, the increase in the urban population of Indigenous people in Canada is mainly due to increases in self-identification, particularly for the Métis population (Survey response to OECD, Canada, 2018). These trends in Indigenous migration and population mobility are worthy of further investigation in future studies.
Indigenous well-being and development
Frameworks to measure well-being
Well-being has gained attention as a regional development policy concept because it captures a number of factors that are important to the competitiveness of places, and helps to reinforce the importance of complementarities between different sectoral policies. Regional well-being can be assessed through the OECD well-being framework which encompasses 11 dimensions: income and wealth, jobs and earnings, housing, health, work-life balance, environment, education, safety, civic engagement and governance, social connections, and subjective well-being (see Box 1.3). In its adaptation to the regional context, access to services is additionally considered in the Well-being Framework. This multi-dimensional framework covers both material and non-material factors, focuses on people’s quality of life instead of just the economic system. Well‑being indicators related to this framework include both objective and subjective measures since perceptions are a complement of well-being as experienced by people. Along these lines, the importance of the distribution of resources both within and across societies is considered as an integral part of development.
Box 1.3. The OECD Well-being Framework
The OECD has established a well-being framework for measuring individual well-being which is developed from the capabilities approach that conceives development as a process that can expand individual’s choices and opportunities to live the lives that they value (OECD, 2017[28]; Sen, 2005[29]). The approach for well-being is people-centric and the framework focuses on well-being outcomes rather than inputs (for example educational attainment rather than access to schools or the number of teachers) (Figure 1.4). The framework incorporates 11 dimensions of current well-being and 4 types of capital stocks (natural, economic, human and social) to guarantee the sustainability of future well-being.
The values and perspectives of Indigenous peoples have generally not been incorporated into countries well-being frameworks and policy agendas. Current debates and perspectives about how to better reflect Indigenous values and perspectives in the Sustainable Development Goals is a good example of this (see Box 1.4) (ILO, 2015[30]). Only a few countries have created frameworks that focus on the well-being of Indigenous people from their perspective (Stats NZ, 2013[31]). The incorporation of Indigenous values and perspectives into well-being frameworks is vital as it helps policymakers to better tailor policies to the needs and aspirations of Indigenous peoples, and monitor progress over time.
Box 1.4. Global approaches to measuring well-being and Indigenous peoples
International legal instruments provide another starting point for considering how to measure well-being and development outcomes for Indigenous peoples. The United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) was endorsed in 2007 by 144 nations as a universal framework for the basic rights and well-being of Indigenous peoples. The UNDRIP has 46 articles which identify a number of elements which are important when considering place-based economic development issues for Indigenous peoples. This includes rights to participate in decision-making about development, facilitating cross-border trade and economic activities, free, prior and informed consent about development on Indigenous lands, measures that ensure productivity and conservation of Indigenous lands, and maintaining distinct institutions. It also identifies a number of aspects that should be considered when measuring Indigenous well-being such as traditional knowledge and cultural practices, and the maintenance of language.
The UNDRIP was also developed in the context of increasing recognition of the need to go beyond gross domestic product (GDP) and other economic measures to develop a better understanding of how societies are performing. This recognition is reflected in the United Nations (UN) Sustainable Development Goals (SDGs). The SDGs were adopted by member countries in 2015 and outline shared development goals and indicators across 17 different areas (Figure 1.5).
The SDGs include a commitment to “leave no one behind” which is particularly relevant given the poorer socio-economic outcomes generally experienced by Indigenous peoples across different countries. Indigenous peoples make up only 5% of the global population; however, it is estimated that they make up 15% of the world’s poor and about one-third of the world’s 900 million extremely poor rural people (UN Department of Economic and Social Affairs, 2019[33]). The SDGs include six specific references to Indigenous peoples including SDG2 (agricultural output of Indigenous small-scale farmers) and SDG4 (equal access to education for Indigenous children). The UN Permanent Forum on Indigenous Issues has identified a number of ways to strengthen the Indigenous perspectives within the SDGs including developing indicators of land use, disaggregation of measures for Indigenous populations and strengthening the capacity of Indigenous peoples to participate in reporting on the implementation of the SDGs (UN, 2018[34]). The subnational dimension is particularly important given the heterogeneous conditions facing Indigenous peoples across national territories.
Sources: Elaboration based on multiple sources; (UN, 2018[34])
Across countries, significant gaps between Indigenous and non-Indigenous populations have been identified with respect to life expectancy, child development, food security and employment outcomes, among others. For example, a study for Australia, Canada, New Zealand and the United States found that while these countries have high human development according to the United Nations Development Programme (UNDP), their Indigenous populations have only medium levels of human development (Cooke et al., 2007[35]). The key economic development issues identified in the literature on Indigenous communities across a group of developed countries including Australia, Canada, New Zealand and the United States are: high poverty and deprivation rates, low diversity in the sources of income and high dependency on government transfers, low integration in the labour market, substance abuse, mental health issues and high suicide rates, among others (OECD, 2016[36]). In Latin American countries, Indigenous peoples rank at the bottom of multi-dimensional poverty and deprivation indicators, and the areas where Indigenous lands are located often lack basic infrastructure such as access to clean water and sewage systems (World Bank, 2015[37]). The difference in the intensity of economic activity generated by Indigenous peoples compared with national and regional economies could be due to a higher emphasis on customary activities and subsistence relative to market activities, and/or it could be indicative of lower opportunities available and different kinds of barriers (education levels, health, location and inter-generational poverty).
National well-being outcomes
This sub-section of the chapter provides an overview of the level of well-being outcomes and differences in the well-being of Indigenous and non-Indigenous people at a national level, based on the selected dimensions (income and wealth, jobs and earnings, housing, health status, and education and skills) of the OECD Well-being Framework. The analysis focuses on countries where disaggregated data on Indigenous peoples are available: Australia, Canada, Mexico, New Zealand and the United States. The selection is limited by data availability and for this reason, the quantitative analysis conducted in this chapter leaves out important aspects of Indigenous people’s well-being such as the importance of social connections. The section focuses on the dimensions and indicators specified in Table 1.7.
Table 1.7. Indicators comparing Indigenous well-being across countries
Domain |
Indicator |
---|---|
Material conditions |
Median income Rooms per person (housing) Employment rate Unemployment rate |
Quality of life |
Life expectancy at birth Educational attainment rate |
Material conditions
An individuals’ material living conditions include household disposable income, labour market outcomes such as employment and unemployment rates, and housing conditions. Levels of income and wealth have a major impact on living standards. Without an adequate level of income, people have lower capabilities and choices about their lives. More importantly, with low levels of income, it is challenging for individuals to meet their basic needs such as sufficient housing and good nutrition.
Income and wealth
Indigenous people in all countries tend to have lower levels of income. Factors contributing to differences in household income between Indigenous peoples and non‑Indigenous people are low labour market force participation rates, high unemployment rates, low wages among Indigenous peoples and higher levels of participation in the informal economy. Figure 1.6 illustrates income levels of Indigenous and non-Indigenous peoples in four countries (Canada, Mexico, New Zealand and the United States). The income gap is greatest in Mexico (USD 11 600) and smallest in New Zealand (USD 4 000).
Across the most recent intercensal period, the median Indigenous income increased in Canada, New Zealand and the United States.5 In Canada the growth of median income was greater than in other countries, the median Indigenous income grew by 23.3%. Simultaneously, the median household income of non-Indigenous peoples increased, but the growth was more moderate than the growth of Indigenous peoples’ median income, which led to a smaller Indigenous and non-Indigenous people’s income gap. In Canada, the income gap decreased by five percentage points in the most recent intercensal period.
The income figures analysed here do not include non-monetary income of Indigenous peoples. Non-monetary sources of income include traditional activities such as subsistence hunting, fishing and farming. Usually, the market prices of these income sources cannot be estimated. This may be due to the reluctance of Indigenous populations to monetise these activities because of perceived risks associated with taxation of this income and intrusion of government institutions into customary and traditional activities (OECD – interviews on fact finding missions to Australia, Canada and the United States). Non-monetary income is likely to be more significant for the quality of life of Indigenous peoples than for non-Indigenous peoples, particularly in rural remote areas, due to the role of subsistence hunting, fishing and harvesting.
To address the disadvantaged situation of Indigenous peoples, many countries provide transfer payments for Indigenous people. As a consequence, Indigenous households are usually more likely to be dependent on government transfers than non-Indigenous households. Indigenous women are most/more likely than men to receive government transfers because of their role in managing households and caring for children. For example, statistics from Australia shows that Indigenous women have a higher likelihood of receiving transfers from the government than Indigenous men (Australian Health Ministers' Advisory Council, 2014[38]).
Housing
While the vast majority of non-Indigenous peoples across the OECD countries have adequate housing, Indigenous peoples have a higher tendency to live in overcrowded and lower quality housing, which contributes to serious challenges for Indigenous well-being. Housing has impacts on individuals’ quality of life and well-being. The number of rooms per person is a standard measure of whether people are living in crowded conditions. As Figure 1.10 shows, the highest housing gap is reported in the United States and lowest in Australia and Mexico where the gap is about 0.1 rooms.
However, it should be noted that the figures below do not account for individuals living in unsuitable dwellings or homelessness and as such do not fully reflect the housing situation of Indigenous peoples. For instance, urban Indigenous peoples in Canada are eight times more likely to end up being homeless than non-Indigenous people living in cities (Homeless Hub, 2019[40]). Housing challenges among Indigenous peoples are most often a cause of a combination of low income, limited access to finance, low levels of inter-generational wealth, and challenges with land tenure.
Employment rate
The employment rate is calculated as a ratio of the employed to the working age population and is an important indicator of economic participation. At the national level, Indigenous peoples have lower employment rates than rest of the population. Participation in the labour market has important implications in many Indigenous peoples’ lives as it can provide economic security and increase quality of life. Finding a job and being employed under secure, well-paid and stable work conditions can help Indigenous peoples break dependency relationships with governments by giving them independent sources of income. Across the sample countries, the employment rate of Indigenous peoples averages 53%. New Zealand records the highest Indigenous employment rate of 59% and the lowest employment rate of Indigenous peoples is reported in Australia with 45%.
Although the employment rate of Indigenous peoples across the five countries is quite similar to one another, the employment rates of non-Indigenous peoples in these countries are more heterogeneous. The gap in employment rates of Indigenous and non-Indigenous peoples is largest in Australia, approximately 28 percentage points, followed by Canada, where the employment rate gap is 8 percentage points and Mexico with 3 percentage points.
The evolution of employment rates of Indigenous peoples is mixed across countries. It showed the largest decrease in New Zealand, where it changed by approximately five percentage points between 2006 and 2013. During the same period, the employment rate of non-Indigenous decreased by three percentage points, so the gap in the employment rate of Indigenous and non-Indigenous peoples decreased by three percentage points. In Canada, the employment rate for Indigenous people stayed the same between 2011 and 2016, while the employment rate of non-Indigenous showed a small decrease, resulting in a small decrease in the employment rate gap of less than one percentage points. Meanwhile, Australia recorded a slightly larger increase in the employment rate of Indigenous compared to non-Indigenous (1.75 percentage points versus 2.95 percentage points), leading to a decrease in the employment rate gap of 1.2 percentage points.
Unemployment
The unemployment rate is the number of unemployed people as a percentage of the labour force, where the latter consists of the unemployed plus those in paid or self-employment. Unemployed people are those who report that they are without work, that they are available for work and that they have taken active steps to find work. The criteria used to define unemployment varies between countries. It is not a perfect measure of slack in the labour market because it excludes people who have given up looking for work.
Unemployment rates for Indigenous peoples are much higher than for non-Indigenous peoples in all the countries under study (Figure 1.9). The unemployment rate of Indigenous peoples is on average 16% and 10 percentage points higher than the average unemployment rate of non-Indigenous peoples. Australia has the highest Indigenous unemployment rate (18%). Among the five countries under study, Mexico is the only country where the unemployment rate of Indigenous peoples is significantly lower than the unemployment rate of non-Indigenous peoples. There, approximately 4% of the Indigenous labour force is unemployed.
The United States is the only country where the unemployment rate of Indigenous peoples decreased in a 5-year period while in the other countries the unemployment increased. The highest increase in unemployment rates of Indigenous peoples was in New Zealand, where the unemployment rate of Indigenous peoples changed from 11% to 16% between 2006 and 2013. In other countries, the change was more moderate or the rate has stayed unchangeable. Similarly, the unemployment rate of non-Indigenous did not change significantly. The biggest change was in unemployment rates of non‑Indigenous peoples in New Zealand, where it increased by two percentage points. Respectively to the change of rates, the gap only widened in New Zealand by three percentage points from 2006-11 to 2013-16.
Quality of life
Quality of life encompasses participation in work, skills and competencies, and whether people are healthy and motivated enough to contribute to the economy and society. In advanced OECD economies, the level of skills attainment is becoming a more important predictor of accessing higher quality jobs. In the context of ageing populations, it is also important that people have the health to continue to participate in work and social activities.
Health status
Health is one of those aspects that impact on every dimension of individuals’ life and therefore it is a crucial element of well-being for every people of all ages. Poor health is associated with lower subjective well-being as well as the individual’s ability to take part in the labour market and further education and training (OECD, 2015[42]).
The life expectancy of Indigenous peoples is more than 70 years in every country. In Canada, the life expectancy of Indigenous peoples is the highest, on average 78.2 years. On the contrary, the lowest life expectancy is reported in Australia, the life expectancy of Indigenous Australians is 4.1 years less than the average Indigenous Canadians life expectancy.
In all five studying countries, Indigenous peoples’ life expectancy at birth is lower than non-Indigenous peoples. In Australia, the life expectancy gap between Indigenous and non-Indigenous peoples is 10 years (Figure 1.10). The life expectancy gap is smallest in Mexico where the average life expectancy gap is less than two years. Between different Indigenous groups, the life expectancy at birth varies widely. For example, in Canada, Inuit have the lowest life expectancy rates among the three Indigenous groups. In fact, the difference between Inuit and Métis estimated life expectancy at birth is 10 years (Statistics Canada, 2015[43]). As with the non-Indigenous population, Indigenous women have longer life expectancies than men.
However, life expectancy is not informative about perceived health or whether individuals live healthy lives. Unfortunately, there is no internationally comparable data available on Indigenous people’s perceived health. Nevertheless, empirical evidence from Australia shows that in 2015, only 40% of Aboriginals and Torres Strait Islanders reported having excellent or very good health. Compared to non-Indigenous Australians, Aboriginals and Torres Strait Islanders had a lower likelihood of reporting their health as excellent and more likely to report health as poor or fair (Australian Bureau of Statistics, 2016[46]). Moreover, Aboriginal women had a higher probability to report their health as poor than Aboriginal men.
Education
Education has an important role to play in improving Indigenous well-being outcomes and supporting the development of Indigenous communities. Individuals with at least upper secondary degree are more likely to be part of the formal economy, have higher income and have better health than individuals with lower or no degree.
Indigenous peoples with at least upper secondary degree vary widely across the five countries, New Zealand (60%) and the United States (79%) have more highly educated Indigenous population than other selected OECD countries. Indigenous peoples in Mexico are less likely to be educated; there, the share of Indigenous peoples aged 2564 with at least upper secondary degree is 20%.
The educational attainment level of Indigenous is lower than that of the non-Indigenous population (in terms of upper secondary attainment) across all selected countries. The education gap is smallest in the United States (8.9 percentage points) and largest in Australia (39 percentage points) (Figure 1.11).
Despite the differences in educational attainment, evidence from census of population surveys shows that the share of Indigenous peoples with at least upper secondary education increased in all countries. The largest increase is reported in Mexico and New Zealand, where the educational attainment rate has changed by 7 percentage points between 2010 and 2015, and 2006 and 2013 respectively. In Canada and the United States, the change was smaller between 2011 and 2016. Yet, the increase in the share of Indigenous peoples did not lead to a significant change in the gap with the non-Indigenous population, except in New Zealand where the education gap increased by four percentage points.
These outcomes represent a disadvantage for Indigenous populations in terms of accessing high income “knowledge economy” jobs in the future. Succeeding in the labour market requires foundational skills (literacy, numeracy) along with high-level communication, interpersonal and problem-solving skills. Results from the 2012 OECD Survey of Adult Skills (PIAAC), indicated that on average Indigenous peoples in Canada had lower outcomes in literacy, numeracy and problem-solving in technology-rich environments than the average non-Indigenous Canadians. However, the gap in mean numeracy score was relatively small (4 points) compared to the gap in literacy score (13 points lower) (Aboriginal Affairs and Northern Development Canada, 2015[47]).
Summary
At a national level, well-being outcomes of Indigenous peoples (in income and wealth, jobs and wages, housing, health, and education and skills) are significantly lower than non-Indigenous peoples. Table 1.8 highlights the observed gaps in outcomes between Indigenous and non-Indigenous peoples in five well-being dimensions and changes in the gaps in the country’s most recent intercensal period. The results indicate mixed performance across countries in terms of reducing gaps in outcomes between Indigenous and non-Indigenous populations. In terms of median income, the average gap is USD 7 720. Canada and the United States reduced the gap in the most recent intercensal period between Indigenous and non-Indigenous peoples. Meanwhile, in New Zealand, the gap has increased (data not available for Australia and Mexico). The gap in the employment rate is 13 percentage points across the 5 sample countries. This gap has increased by 6.3 percentage points in the most recent intercensal period across these countries. The average difference in the unemployment rate is five percentage points and the average gap has increased by one percentage point. The gap reduced in Australia and Mexico but increased in New Zealand. The average gap in educational attainment is 20 percentage points but this gap has narrowed in Mexico and the United States and widened in New Zealand.
Table 1.8. Summary table of gaps in selected well-being indicators
Indicator |
Average gap |
Closing the gap |
Gap widened |
---|---|---|---|
Median income |
USD 7 720 |
Canada and United States |
New Zealand |
Room per person |
0.3 rooms |
.. |
.. |
Employment rate |
13 percentage points |
Canada |
Australia, Mexico, New Zealand and United States |
Unemployment rate |
5 percentage points |
Australia and Mexico |
New Zealand |
Life expectancy at birth rate |
5.73 years |
.. |
.. |
Educational attainment rate |
20 percentage points |
Mexico and United States |
New Zealand |
.. : Missing value.
Note: Average gap of median household income refers to after-tax median personal income for Canada; to median household income for Mexico; to median personal income for New Zealand; and to median earnings for the United States. The non-Indigenous peoples’ income corresponds to the median earnings of the total population for the United States.
Subnational well-being outcomes
National averages tell only one side of the story – to understand the factors contributing to the differences in well-being and development outcomes between Indigenous and non‑Indigenous peoples, it is necessary to look at the performance at the subnational level. This is because Indigenous communities are highly heterogeneous and embedded in different regional economies across national territories. This analysis utilises the OECD Well-Being Framework, which has been adapted to measure multi-dimensional well‑being at the regional level and focuses on four dimensions (due to data availability) (Table 1.9).
Table 1.9. OECD Regional Well-being Indicators
Dimensions |
Regional indicator |
Indigenous analysis |
---|---|---|
1. Income and wealth |
Regional disposable income per capita Household disposable income |
X* |
2. Jobs |
Employment rate |
X |
Long-term unemployment rate |
||
Unemployment rate |
X |
|
3. Housing |
Number of rooms per person |
|
4. Health status |
Life expectancy at birth |
|
5. Education and skills |
Educational attainment rate |
X |
6. Environmental quality |
Air quality (PM2.5) |
|
7. Personal security |
Homicide rate |
|
8. Civic engagement and governance |
Voter turnout |
|
9. Accessibility of services |
Broadband connection |
|
10. Social connections |
Quality of support network |
|
11. Subjective well-being |
Self-evaluation of life satisfaction |
* Uses the poverty rate from the United States.
Source: OECD (2019[48]), OECD Regional Well-Being, https://www.oecdregionalwellbeing.org/ (accessed on 07 February 2019).
The analysis of each of these dimensions is organised as follows:
At the TL2 level, it first examines each of the 4 well-being indicators across 37 TL2 regions from 5 countries. This analysis looks at the subnational variation across TL2 regions within and between countries, comparing it to the variation of the outcomes of non-Indigenous peoples. It also identifies the regions with the highest and lowest outcomes for each indicator.
At the TL3 level, it covers 214 TL3 regions from 5 countries. Annex 1.A outlines the criteria for including regions. It first examines the outcome of well-being indicators across predominantly urban against predominately rural regions. It then examines the gaps in well-being indicators across predominantly urban, intermediate and predominantly rural regions within five countries in levels and growth rates over the period 2011-16.
The next section undertakes further analysis of the factors associated with higher labour force participation of Indigenous peoples.
Selection of regions
The analysis in this section exclusively considers a subgroup of TL2 and TL3 regions fulfilling predetermined criteria in terms of share or size of Indigenous populations. Annex 1.A contains the list of selected TL2 and TL3 regions.
TL2 regions where Indigenous peoples represent more than 10% of the total population of the region were selected,6 leading to a subsample of 37 TL2 regions. TL3 regions were selected based on two criteria: the percentage share of the region’s Indigenous population and the absolute size of Indigenous populations compared to the national averages. Regions included all exceed the national average in terms of size and percentage share. The population size criterion was used to include urban regions that may have relatively large Indigenous populations that only constitute a small proportion of the overall population. This selection process led to the selection of 214 TL3 regions in Australia, Canada, Mexico, New Zealand and the United States. Out of the 214 TL3 regions, 140 are predominantly rural, 27 is intermediate and 47 is predominantly urban (Table 1.10).
Table 1.10. Two hundred and fifteen TL3 regions selected for the subnational analysis of Indigenous well-being, by country
Country |
Predominantly urban |
Intermediate |
Predominantly rural |
Share of TL3 regions (%) |
---|---|---|---|---|
Australia |
5 |
5 |
10 |
41 |
Canada |
10 |
7 |
63 |
28 |
Mexico |
19 |
11 |
53 |
40 |
New Zealand |
1 |
4 |
1 |
43 |
United States |
12 |
x |
13 |
14 |
Total |
47 |
27 |
141 |
x |
x: Not applicable.
Sources: OECD analysis based based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2012-2016 American Community Survey 5-Year Estimates, Tables B01001A, B01001B, B01001C, B01001D using American FactFinder http://factfinder2.census.gov for the United States.
Material conditions
Income
Data on household income between Indigenous and non-Indigenous peoples that are aggregated at the TL2 level is available for New Zealand. Income-related data at the TL3 level is only currently available for the United States and relates to poverty rates. Even under these data constraints, the evidence from New Zealand and the United States does reveal findings which can inform wider considerations about Indigenous household incomes such as the relatively poorer outcomes in regions with a larger Indigenous population and in rural areas.
New Zealand
Regional disparities in median household income emerge among New Zealand’s Indigenous households. The median household income of Indigenous households varies from USD 16 982 to USD 26 220 in 2013 within the selected regions (Figure 1.12). The highest median household income was in Wellington Region and the lowest in Northland Region. Auckland Region and Wellington Region were the only regions in 2013 that had a higher median household income of Indigenous households than the national median household income of Indigenous households. The rest of the selected TL2 regions had lower Indigenous household income than the national median.
Indigenous household’s median income is significantly lower than the median household income of non-Indigenous. The gap is largest in Gisborne Region, where the Indigenous household’s median household income is USD 7 064 lower than the median household income of non-Indigenous households. On the contrary, the smallest gap is in Manawatu-Wanganui Regions where the difference was about USD 22 785 in 2013.
Across different types of regions, the median Indigenous household income is higher predominantly urban regions than in intermediate or predominantly rural regions. The median rural Indigenous household income was about USD 9 200 lower than the median urban Indigenous household income. Furthermore, all intermediate regions have a lower median Indigenous household income than the national level. The region with the lowest median Indigenous household income, Northland, is a predominantly rural region. On the other hand, Auckland and Wellington, the two regions with the highest median Indigenous household income, are predominantly urban regions.
While at a national and regional level, the median household income increased in 2006‑13 in predominantly rural and intermediate regions, the income gap widened between Indigenous and non-Indigenous households, regardless of the higher median Indigenous household income in the regions. Wellington reported the highest increase in the median Indigenous household income in this period (an increase from USD 21 058 to USD 26 016). As expected, the lowest increase in the median Indigenous household income was in Northland, where the median income changes from USD 14 537 to USD 16 982. Due to increases in median income in Auckland and Wellington, the income gap between Indigenous and non-Indigenous households for New Zealand was reduced in the period 2006-13.
United States
The poverty rate is an important economic indicator that provides information about the material well-being of individuals for policymakers.7 In the United States, poverty rates among Indigenous peoples are higher than non-Indigenous peoples. In 2016, the poverty rate8 of Indigenous peoples was 14 percentage points higher than non-Indigenous peoples. Approximately, 28% of Indigenous peoples had an income lower than the poverty rate and in the 5 years to 2016, the poverty rate experienced a small increase (0.6 percentage points). The poverty gap between Indigenous and non‑Indigenous peoples remained unchanged, as the increase of the national poverty rate of non-Indigenous peoples was similar to the increase of Indigenous peoples’ poverty rate.
In 2016, the poverty in Indigenous peoples stood at 30% against 13% in non-Indigenous peoples, representing a gap of 17 percentages points within the selected large (TL2) regions. The smallest gap is found in Oklahoma where the difference in poverty rates of Indigenous and non-Indigenous peoples is 7 percentage points and the largest in South Dakota where the gap is almost 38 percentage points. The region with the highest Indigenous poverty rate is South Dakota, where almost half of Indigenous peoples have income below the poverty line. Otherwise, the poverty rate varies from 22.2% to 48.6%. Regions with a higher proportion of Indigenous population also tend to have higher poverty rates. This highlights the inequality between and within regions when considering Indigenous and non-Indigenous differences.
Indigenous peoples are worse off in rural areas compared to urban areas in the United States. The difference in poverty rates between rural and urban regions is seven percentage points. A greater share of Indigenous peoples living in urban areas has incomes above the poverty line than Indigenous Americans who live in rural areas. Furthermore, the gap in poverty rates between Indigenous and non-Indigenous peoples is smaller in urban areas than in rural regions. In 2016, the difference between the poverty rates of Indigenous peoples and non-Indigenous peoples was 17 percentage points in rural areas and 10 percentage points in urban areas. Even though Indigenous peoples in urban areas are less likely to have income under the poverty rate than Indigenous peoples in rural areas, the poverty rate or urban Indigenous peoples experienced a greater increase between 2010 and 2016 than the poverty rate in rural areas (two percentage points compared to one percentage point change).
Employment rate
The previous section showed that in Australia, Canada, Mexico, New Zealand and the United States, the employment rate of Indigenous peoples is on average 53%, 13 percentage points lower than the employment rates of non-Indigenous peoples (Figure 1.13).9 When looking at the employment rates of Indigenous and non-Indigenous peoples at the subnational level across the selected TL2 regions, a similar pattern emerges. Regional disparities in employment rates of Indigenous peoples are larger within the selected TL2 regions than disparities across the five countries at a national level (a difference of 26 percentage points). Northern Territory in Australia is the TL2 region with the lowest share of employed Indigenous peoples (29%) and Wellington in New Zealand is the region with the highest employment rate of Indigenous peoples (63%).
Inequalities between Indigenous and non-Indigenous peoples are also large within regions. The gap in the shares between employed Indigenous and non-Indigenous peoples is particularly large in Australia, Canada and the United States. In these countries, the TL2 region with the lowest rate of employment among Indigenous peoples is also the region that recorded the highest employment rates of non-Indigenous peoples (Northern Territory, Nunavut and South Dakota). In particular, in Northern Territory (Australia) and Nunavut (Canada), the share of employed Indigenous peoples is 56 and 43 percentage points lower than the share of employed non-Indigenous peoples.
Variations in the employment participation rate are also observed across different types of regions and rural and urban areas. Across the selected TL3 regions, Indigenous peoples have higher employment rates in urban and intermediate regions than in predominantly rural regions, on average Indigenous peoples in urban regions had 11 percentage points higher rate of employment than Indigenous peoples in rural regions in 2013-16. In rural areas, the highest share of employed Indigenous peoples is found in the United States where 53% of the working-age Indigenous peoples are employed and the lowest in Australia where 40% of Indigenous working age peoples are employed. The employment rates of Indigenous peoples in urban areas ranges from 54% (Australia) to 60% (New Zealand). Compared to the national average of the Indigenous employment rate, Indigenous peoples living in urban areas have also higher likelihood to be employed (on average about five percentage points higher) than average Indigenous citizen in the country. Conversely, the employment rate of rural Indigenous peoples is about seven percentage points lower than the national average.
When looking at the differences in employment rates between Indigenous and non‑Indigenous peoples at a TL3 level, the gap in rural regions is systematically higher than the gap in urban regions in every country. In rural regions, the gap ranges from 5 (Mexico) to 35 (Australia) percentage points (Table 1.11). Respectively the gap in the employment rate between Indigenous and non-Indigenous peoples in urban regions ranges from 1 (Mexico) to 20 (Australia) percentage points. In urban Mexico, there is no significant difference between Indigenous and non-Indigenous employment rates. Australia, Canada and New Zealand have the widest gap in rural regions which can be explained by the high rate of non-Indigenous employment in rural regions.
Consistent with the national trends, employment rates of Indigenous and non-Indigenous peoples have decreased as well as the selected TL3 regions in the most recent intercensal period. The highest decrease in Indigenous employment rates in urban areas is reported in New Zealand where the difference in employment rates of Indigenous peoples in 2006‑13 is six percentage points. Urban regions in Australia were the only regions where employment rates of Indigenous peoples increased. Respectively, within rural regions, employment rates decreased everywhere else than in Canada (where the average employment rate of Indigenous peoples has remained unchanged). Similarly, as in urban regions, the highest decrease in rural regions is recorded in rural New Zealand where the share of employed Indigenous peoples was six percentage points lower in 2013 than in 2006. For more details on labour market outcomes for Australia and New Zealand, see Box 1.5.
Table 1.11. Employment rates for Indigenous and non-Indigenous peoples by type of region, 2016 or latest year available
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
AUS |
54 |
74 |
-20 |
46 |
76 |
-30 |
40 |
75 |
-35 |
CAN |
58 |
62 |
-4 |
52 |
61 |
-9 |
45 |
60 |
-15 |
MEX |
59 |
58 |
1 |
49 |
54 |
-5 |
45 |
50 |
-5 |
NZL |
60 |
71 |
-11 |
57 |
75 |
-18 |
52 |
72 |
-20 |
USA |
59 |
68 |
-9 |
59 |
72 |
-13 |
53 |
70 |
-17 |
Note: The latest available year is 2013 for New Zealand; 2015 for Mexico; and 2016 for Australia, Canada and the United States. For Canada, the employment rate refers to Aboriginal and non-Aboriginal populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2012-2016 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Box 1.5. Labour market outcomes of Indigenous women: Evidence from Australia and New Zealand
Inequalities in labour market outcomes do not only emerge between Indigenous and non‑Indigenous peoples but inequalities are also apparent between Indigenous men and women. Evidence from Australia and New Zealand shows that a gap also exists in average well-being outcomes between Indigenous women and men at the national and subnational level. Indigenous women tend to be worse off with regards to labour market outcomes.
Based on data drawn from a census of population surveys, In Australia and New Zealand, Indigenous women have on average lower labour force participation rates and therefore lower employment rates than Indigenous men. The gender gap is smaller in Australia than in New Zealand. In Australia, the difference between employment rates of Indigenous women and men is about three percentage points while in New Zealand the difference is nine percentage points. Similar trends are found when considering the gender gap of non‑Indigenous peoples: non-Indigenous men in New Zealand are more likely to be employed than non-Indigenous women.
However, the gender gap in labour market outcomes decreased in these countries in 2011‑16 (Australia) and 2006‑13 (New Zealand). The gender gap in employment in Australia decreased due to the increase in Indigenous women employment rates. In New Zealand, the change was caused by a greater decline in the employment rates of Indigenous men.
Subnational trends for gender gaps in labour market outcomes are similar to national trends. The largest gender gap in New Zealand occurs in rural regions, where the difference in Indigenous women and men employment is about eight percentage points. In contrast, in Australia, the largest gender gap of Indigenous and non-Indigenous peoples is found in urban regions. Indigenous women in urban regions have a higher likelihood to be employed than Indigenous women in intermediate or rural regions. On the contrary, Indigenous women in rural regions are less likely to be employed and more likely to be unemployed.
Labour market outcomes between women and men can differ due to family responsibilities and specialisation in unpaid work, larger negative association with a criminal record, and cultural and customary responsibilities (Savvas, Boulton and Jepsen, 2011[49]).
Sources: Authors’ elaboration, based on data drawn from Australian Bureau of Statistics (n.d.[23]) 2011 and 2016 Census of Population and Housing (database), TableBuilder for Australia; and Statistics New Zealand (n.d.[10]) 2006 and 2013 Census (database).
Unemployment
Unemployment rates are significantly higher for Indigenous peoples than non-Indigenous peoples at a subnational level in all countries with the exception of Mexico, where Indigenous peoples have equal shares of unemployed Indigenous and non-Indigenous peoples. In 2016, the regions with the highest share of unemployed Indigenous peoples was Northern Territory (Australia) and Nunavut (Canada) with a share of 28% of the Indigenous labour force unemployed (Figure 1.14).
Furthermore, regions with a high proportion of Indigenous people show significant variation in unemployment rates. In fact, the variation in unemployment rates of Indigenous peoples is higher than variation among non-Indigenous peoples’ unemployment rates. The range between the regions with the highest unemployment rate of Indigenous peoples and the regions with the lowest unemployment rate is on average six percentage points higher than the regional disparities in unemployment rates of non‑Indigenous peoples. Countries with the greatest regional variation in unemployment rates of Indigenous peoples are Australia, Canada and the United States, where the difference in Indigenous unemployment rates between the regions with the highest and lowest unemployment rates is about 12.8 percentage points.
Besides Mexico, the gap in the shares between unemployed Indigenous and non‑Indigenous peoples is large in every country (on average 15 percentage points). In Australia, Canada and the United States, TL2 regions with the highest rate of unemployment among Indigenous peoples also recorded the lowest unemployment rates of non-Indigenous peoples (Northern Territory, Nunavut and South Dakota). In Nunavut, Canada, where the total Indigenous population is 85% of the total population, the unemployment rate of Indigenous peoples is 27.6% and of non-Indigenous peoples only 3%, representing a considerable gap of 24.6 percentage points.
The variations across rural and urban regions are also notable. The lowest unemployment rate of Indigenous peoples is reported in urban regions and Indigenous peoples in rural regions have the highest unemployment rates. The unemployment rate of Indigenous peoples in urban regions varies from 3% (Mexico) to 16% (New Zealand) and in rural regions from 4% (Mexico) to 21% (Australia, Canada) (Table 1.12). The difference between the unemployment rate among urban and rural Indigenous peoples was on average about five percentage points in 2013‑16. Indigenous peoples in urban regions have lower unemployment rates than the average Indigenous citizen in Australia, Canada and the United States (on average three percentage points lower). On the contrary, in rural regions of Australia, Canada, New Zealand and the United States, the average unemployment rate of Indigenous peoples is 4.4 percentage points higher than the national average unemployment rate of Indigenous peoples.
Australia has the widest gap between unemployment rates of Indigenous and non‑Indigenous peoples in every TL3 region, which indicates a challenge in terms of inequalities between Indigenous and non-Indigenous populations within regions. The difference in Indigenous and non-Indigenous peoples’ unemployment rates is highest in predominantly rural regions in every country, with gaps ranging from 0 (Mexico) to 15 (Australia) percentage points. In urban regions, the unemployment gap between Indigenous and non-Indigenous peoples ranges from 1 (Mexico) to 9 (New Zealand) percentage points.
Unemployment rates have primarily increased in rural areas in Australia, Canada and New Zealand in 2011-16 from 1 (Canada) to 6 (New Zealand) percentage points. In urban areas, the unemployment rate increased only in New Zealand by five percentage points. Among non-Indigenous peoples, the unemployment rates increased notably in urban areas in Australia and New Zealand and rural areas in Australia, Canada and New Zealand. However, the rise in unemployment rates of non-Indigenous peoples was more moderate than in Indigenous peoples. As a consequence, the gaps in unemployment rates shrank in urban areas of Australia and widened in rural areas of Australia, Canada, Mexico and New Zealand.
Table 1.12. Unemployment rates for Indigenous and non-Indigenous peoples by type of region, 2016 or latest year available
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
AUS |
15 |
7 |
-8 |
19 |
7 |
-12 |
21 |
6 |
-15 |
CAN |
12 |
7 |
-5 |
14 |
7 |
-7 |
21 |
8 |
-13 |
MEX |
3 |
4 |
1 |
4 |
4 |
0 |
4 |
4 |
0 |
NZL |
16 |
7 |
-9 |
17 |
5 |
-12 |
20 |
6 |
-14 |
USA |
13 |
8 |
-5 |
13 |
7 |
-6 |
15 |
6 |
-9 |
Note: The latest available year is 2013 for New Zealand; 2015 for Mexico; and 2016 for Australia, Canada and the United States. For Canada, the unemployment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2012-2016 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Quality of life
Health status
Data on health status between Indigenous and non-Indigenous peoples at the TL2 level is only available for New Zealand. National-level data indicates that while Indigenous peoples have lower life expectancy than non-Indigenous peoples, Indigenous women have a higher life expectancy (83.9 years) than Indigenous men (73 years). At a regional level, similar trends emerge. Non-Indigenous peoples have longer life expectancies, especial non-Indigenous women. The gender national differences between Indigenous men and women apply at the regional level. Box 1.6 contains more detail on the regional level.
Box 1.6. Life expectancy across regions – Evidence from New Zealand
Across regions, the life expectancy of Indigenous men and women vary from 70.4 years to 74.7 years and 74.8 years to 78.6 years. The regions with the highest life expectancy of Indigenous peoples are Auckland and Wellington, where the median life expectancy of Indigenous women was 78.6 years and median of Indigenous men was 74.7 (Figure 1.15). Even in the region with the highest level of life expectancy of Indigenous peoples, the median life expectancy is lower than the median life expectancy of non-Indigenous peoples at the national level. The difference was 5.2 years difference between Indigenous and non-Indigenous women and 9.9 years between Indigenous and non-Indigenous men. The large differences at the national level translate into large differences at the regional level. The region with the largest difference between both Indigenous and non-Indigenous women and Indigenous and non-Indigenous men was Northland in 2012-14, where the respective figures were 8.2 years and 9.3 years. Wellington was the region with the smallest differences (5.1 years and 5.6 years).
When applying OECD TL3 typology, the results show that intermediate and rural regions have generally lower median life expectancy rates of Indigenous peoples than the national median, while the opposite applies to urban regions. An intermediate region (Gisborne) has the lowest life expectancy rates for Indigenous peoples while urban regions (Auckland and Wellington) the highest life expectancy rates. The largest difference between urban and rural regions was between Indigenous women in rural regions, approximately 2.7 years, and 3.4 years between Indigenous men.
Recent evidence indicates that the life expectancy of Indigenous peoples is rising. Between the two survey periods (2005-07 and 2012-14), the life expectancy of Indigenous men has increased by 3% while the life expectancy of Indigenous women increased by 2%.
The growth rate was as fast in every region as the national average and, therefore, there were no significant differences in the growth rates between urban and rural regions. Because of the general increase of life expectancy rate of Indigenous peoples, the gap in life expectancy of Indigenous and non-Indigenous peoples has narrowed. The gap decreased the most in an urban region (Wellington), from 6.8 years to 5.6 years between Indigenous and non-Indigenous men and from 6.2 to 5.1 years between Indigenous and non-Indigenous women.
Source: Authors’ elaboration, based on data provided by New Zealand (2018[50]) on the 21st December 2018.
Education and skills
Country averages do not tell the complete story about the educational attainment of Indigenous peoples across the five sample countries. Although subnational results indicate that Indigenous peoples have lower educational levels than non-Indigenous peoples (in line with results from the national level), differences across selected OECD regions in terms of educational levels of Indigenous peoples are significant (Figure 1.16). The share of Indigenous peoples with at least upper secondary education varies widely across the selected regions, from 11% (Chiapas, Mexico) to 84% (Oklahoma, United States). This variation is larger than the variation in non-Indigenous education rates across the selected regions (30%-94%).
When looking at the regional differences within countries, the largest gaps between Indigenous peoples’ education level is found in Canada (28 percentage points difference between the regions with the highest and lowest educational attainment rate) and smallest in the United States (11 percentage point difference). Again, inequalities within regions can be observed in Nunavut (Canada) (48 percentage point difference), and the Northern Territory (Australia) (40 percentage point difference). Northern Territory also has the lowest level of educational attainment for Indigenous peoples and the highest for the non-‑Indigenous population.
Analysis across different types of regions again reveals the challenge that Indigenous peoples face in rural areas with regards to education. Indigenous peoples in urban regions are generally more likely to obtain at least an upper secondary degree than Indigenous peoples in rural areas. The share of educated Indigenous peoples in urban areas ranges from 29% (Mexico) to 64% (New Zealand) while in rural regions it ranges from 17% (Mexico) to 54% (New Zealand) (Table 1.13).
When comparing the share of educated Indigenous peoples to the national average, Indigenous peoples in rural areas have generally lower educational attainment rates than the average Indigenous citizen (on average 7% lower). In urban areas, Indigenous peoples have higher educational attainment rates than the average Indigenous citizen (on average 4%). In rural regions, Indigenous peoples are less likely to have at least an upper secondary degree than Indigenous peoples in urban regions. On average Indigenous education attainment rate in rural areas is approximately 13 percentage points less than in urban areas. For non-Indigenous peoples, the educational attainment rate is about 11 percentage points lower in rural areas compared to educational attainment rate in urban areas.
Educational attainment rates of Indigenous peoples have increased both in urban and rural areas, the only exception being urban regions in Canada where the educational attainment rate has decreased by one percentage point. On average, the educational attainment rate of Indigenous peoples in rural areas was approximately five percentage points higher in 2013-16 than it was in 2006-11 in Canada, Mexico and New Zealand. Similarly, the rate in urban areas was about six percentage points higher in 2013-16 than in 2006-11 in Mexico and New Zealand. The education gap increased in rural areas of Canada (one percentage point) and New Zealand (three percentage points). Similarly, the education gap reported in urban areas of Mexico and New Zealand widened on average by three percentage points.
Table 1.13. Educational attainment rates for Indigenous and non-Indigenous peoples by type of region, 2016 or latest year available
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
AUS |
44 |
78 |
-34 |
38 |
72 |
-34 |
28 |
65 |
-37 |
CAN |
53 |
68 |
-15 |
51 |
63 |
-12 |
40 |
58 |
-18 |
MEX |
29 |
48 |
-19 |
17 |
35 |
-17 |
17 |
32 |
-15 |
NZL |
64 |
70 |
-13 |
54 |
67 |
-13 |
54 |
66 |
-12 |
Note: The latest available year is 2013 for New Zealand; 2015 for Mexico; and 2016 for Australia and Canada. For Canada, the educational attainment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; and Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand,
Current stage of Indigenous well-being and how it compares with non‑Indigenous peoples
This section has set up a framework to assess Indigenous well-being and development at a subnational level. The evidence presented above reveals some of the challenges Indigenous peoples face, including limited access to economic opportunities, compared to non-Indigenous peoples across the sample countries. Indigenous peoples report lower outcomes in well-being at both the national and subnational levels: Indigenous peoples are more likely to: live in overcrowded houses; have lower income; higher dependency on government transfer payments; and have lower levels of education and poorer health than non-Indigenous peoples.
Inequalities do not only appear between Indigenous and non-Indigenous peoples but also between men and women, and Indigenous peoples across different types of regions. The evidence shows that Indigenous peoples, particularly in rural regions, are in the most disadvantaged position. The levels of measured outcomes for the average Indigenous citizen in rural regions are lower with respect to the non-Indigenous population in terms of employment, unemployment and educational attainment rates (Table 1.14). Moreover, the gaps between Indigenous and non-Indigenous peoples in outcomes are wider within rural regions than in other types of regions. Particularly, in rural areas in Australia, the gap is wider in all measured outcomes. By contrast, Indigenous peoples in urban regions appear to perform better. On average, Indigenous peoples in urban regions have higher well-being outcomes than the average Indigenous citizen in all countries.
Table 1.14. Average gaps in key indicators between Indigenous and non-Indigenous populations, urban and rural regions, across sample countries
Indicator |
Gap in urban regions |
Gap in rural regions |
---|---|---|
Employment rate |
-8.6 |
-18.4 |
Unemployment rate |
-5.2 |
-10.2 |
Educational attainment rate |
-20.3 |
-20.5 |
Note: Gap refers to the percentage point difference between Indigenous and non-Indigenous populations.
Over the years, the gap in different outcomes between Indigenous and non-Indigenous peoples has either remained unchanged or worsened. This further highlights the need to move beyond national averages and develop a better understanding of why these differences in prosperity and well-being exist across different types of regions for Indigenous peoples.
Understanding how regional characteristics shape well-being outcomes in rural and urban regions
The impact of regional characteristics on labour market outcomes
The analysis in the previous section demonstrated inequalities in key economic and educational outcomes between Indigenous and non-Indigenous peoples across different regions within countries, particularly in the case of rural areas. Regional differences in development outcomes evidenced in wider OECD work are the result of a combination of interconnected factors such as demographics, access to markets and services, physical and human capital, infrastructure and the regions capacity to innovate (OECD, 2009[51]; 2012[52]).
This section examines factors associated with different levels of labour force participation for Indigenous peoples at a regional level. This indicator was chosen as it reflects the economically active population within a region. The factors examined in the analysis are as follows: employment rate of Indigenous peoples; unemployment rate of Indigenous peoples; participation rate of non-Indigenous peoples; educational attainment rate of Indigenous peoples; population size; share of Indigenous population; proximity to the nearest cities (in rural areas); and the dependency ratio of Indigenous peoples. There are multiple factors that might influence Indigenous labour force participation. However, the analysis is limited by data availability and the exclusion of relevant factors such as community leadership, sectoral specialisation, infrastructure, the quality of institutions, and innovative capacity.
Labour force participation rates across small regions
Indigenous people in predominantly rural regions are more likely to have lower labour force participation rates. The median value for Indigenous labour force participation in predominantly urban regions is 66% and in predominantly rural regions it is 59%. This is due to the larger share of predominantly urban regions with a labour force participation rate in the 60%-70% category. The probability of a predominantly urban region having a labour force participation rate below 50% is zero, while this is not the case for predominantly rural regions: 16% of predominantly rural regions have labour force participation rates below 50% (Figure 1.17).
At a country level, Indigenous peoples in urban regions of Canada (66%) and New Zealand (71%) have the highest labour force participation rate within and across countries (Table 1.15). By contrast, Indigenous peoples living in rural areas have a lower probability of being part of the labour force. The labour force participation rate ranges in rural regions from 51% (Australia, Mexico) to 55% (New Zealand). The difference in Indigenous peoples’ labour market outcomes across different types of regions is largest generally between rural and urban regions. The largest difference is recorded in Mexico, where the difference is 13 percentage points.
Table 1.15. Labour force participation of Indigenous peoples by type of region, 2016 or latest available year
Calculated as the labour force divided by the total working-age population aged 15-64
Predominantly urban (%) |
Intermediate (%) |
Predominantly rural (%) |
|
---|---|---|---|
Australia |
63 |
58 |
51 |
Canada |
66 |
61 |
56 |
Mexico |
64 |
54 |
51 |
New Zealand |
71 |
69 |
66 |
United States |
68 |
68 |
62 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the labour force participation rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2012-2016 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Predominantly rural regions
Rural regions that have higher labour force participation of Indigenous peoples show a positive relationship with those who have higher employment rates. This finding is not surprising since labour force participation is a measure of the ratio of employed and unemployed working-age population to the total working-age population of the region. However, the working-age population is more likely to be employed (55%) in the top performing regions than in low performing regions where the share of employed Indigenous peoples is 33%. Furthermore, the level of the unemployment rate is five percentage points higher in the low performing regions.
Regions with higher levels of human capital, a larger and denser population, smaller share of Indigenous population, and with a younger demographic tend to have high levels of Indigenous labour market participation (Figure 1.18). The labour force participation rate is lower in smaller regions and in regions with lower levels of Indigenous peoples’ human capital of where the size of the population is smaller. Indigenous peoples living in rural regions with a larger population have more economic opportunities and are, therefore, more likely to participate in economic activities. Furthermore, rural regions with lower dependency ratios, measured by the ratio of non-working-age population to working-age population, have a higher share of Indigenous peoples in the labour force.
The differences in outcomes in Indigenous labour force participation between top and performing regions may be explained by the travelling distance (measured in minutes) to the closest city. There is a positive relationship between labour force participation and the median travel time to the closest city10 in rural regions (Figure 1.22). Rural regions that have greater labour force participation have generally shorter travel time to the closest city than those rural regions that have lower labour force participation. Shorter travel distance to the closest city can translate to greater non-rural economic participation possibilities for Indigenous peoples living in rural regions.
Predominantly urban regions
In predominantly urban regions, findings are quite similar to the observations made from rural regions. Regions with better outcomes in Indigenous labour force participation have also a higher share of Indigenous peoples that are employed (Figure 1.20). The difference in the employment rates between top and bottom performing regions is on average less than in rural regions (11 percentage points less). Similarly, the education level of Indigenous peoples in top performing regions is higher than in regions with lower outcomes. However, the difference is not as significant as in rural regions (12 percentage points in urban regions compared with 22 percentage points in rural regions). Urban regions with relatively larger population size have higher levels of Indigenous labour force participation. This indicates that Indigenous peoples in large metropolitan regions tend to be better integrated into labour markets.
Exploring factors associated with labour force outcomes
Education tends to be an important factor in influencing positive labour force outcomes for Indigenous peoples at a regional level – therefore Indigenous peoples with lower levels of education are less likely to participate in the labour market (i.e. being employed or looking for a job) (Figure 1.21). There are also differences in educational outcomes within similar types of regions. Better educational attainment is generally associated with improved employment possibilities and higher incomes. Moreover, education impacts on other aspects of individuals’ well-being than just material ones and is correlated with better health outcomes and satisfaction to life in general (Easterbrook, Kuppens and Manstead, 2016[53]).
Regions with a higher share of Indigenous peoples tend to have lower participation rates combined with lower rates of education (Figure 1.22 and Figure 1.23). Most often Indigenous communities are characterised by kinship systems. Empirical evidence has shown that the kinship system may create obstacles when entering to the market or labour force (Hoff and Sen, 2005[54]). Therefore, a strong concentration of Indigenous peoples may exacerbate levels of socio-economic disadvantage. Indigenous peoples in regions with a larger and denser population are more likely to be part of the labour force than Indigenous peoples living in low-density economies. The analysis also identifies the negative relationship between labour force participation and the age structure of the region that can be measured by relating the number of individuals that are likely to be “dependent” on the support of others for their daily living – youths and the elderly – to the number of those individuals who are capable of providing such support – the working-age population.
Summary
The analysis in this section has broken down some characteristics that may explain the variation of labour market outcomes across and within urban and rural regions. The results from the analysis highlight that well-being outcomes vary not only across different types of regions but also within regions. Among the factors considered, several common patterns have been identified among the top performing and bottom performing regions (Table 1.16). For both urban and rural regions, the top performers systematically have higher employment rates, a higher share of Indigenous peoples with at least upper secondary education and a larger population.
Significant challenges exist for rural areas that have a larger share of Indigenous population. In these regions, a higher share of Indigenous population has a negative relationship with labour force participation. This is also compounded by ageing populations, which is a common trend across rural areas in OECD countries. The analysis also shows that there are high levels of inequality between Indigenous and non‑Indigenous populations in these regions. In these regions, there is likely to be two economies. One is a non-Indigenous economy based on natural resource exploitation or tourism, local services and public administration. The other is an Indigenous economy that is likely to be based on smaller scale enterprises, low-paid employment, government transfers and subsistence. Finding ways to link these two economies in ways that are mutually beneficial, is a key inclusive growth challenge.
Table 1.16. Factors associated with top performers on the Indigenous labour force participation rate, urban and rural regions
Type of region |
Factors |
---|---|
Urban |
● Higher Indigenous employment rates ● Higher participation rate of non-Indigenous population ● Larger urban population ● Higher levels of Indigenous educational attainment rates |
Rural |
● Higher Indigenous employment rates ● Higher levels of Indigenous educational attainment rates ● Lower share of the Indigenous population ● Younger population |
Indigenous data governance
The empirical analysis in this chapter has been limited by data availability. There are three key areas of change that are needed in the field of Indigenous statistics to support the production of data to better inform decision-making about economic development. The first is to address gaps in official data collected by national governments and statistical offices. The second is to collect data about more dimensions of well-being and develop indicators that are inclusive of Indigenous values and perspectives. The third, and most important, is to include Indigenous peoples in the process of data collection and empower them to own and use their data.
Addressing gaps in data collected by governments
For a long period, in many countries, Indigenous peoples have been invisible in the mainstream collection of statistics from international to subnational level (Balestra and Fleischer, 2018[27]). Invisibility in statistics is due to the fact that Indigenous peoples have been invisible in societies (Connolly, 2018[55]). This issue has long been raised in international fora such as the United Nations Permanent Forum on Indigenous Issues (UNPFII). Better and more accurate measures of the well-being and development of Indigenous peoples and their communities are needed to enumerate (establish presence) and assess outcomes and inequalities. This can support better policies, more informed decisions and help empower Indigenous peoples. Better statistics are key to self-determination.
To make better policies that are fit-for-purpose and relevant for Indigenous peoples, policymakers need accurate data on Indigenous peoples, including measures that could help to support the implementation of the Sustainable Development Goals (SDGs). Only five OECD member countries collect disaggregated data on Indigenous peoples. The data collection in these countries is centralised in national statistical agencies, such as Australian Bureau of Statistics in Australia, Statistics Canada, Mexico, New Zealand and the U.S. Census Bureau, are responsible for the data on Indigenous peoples in the population census. For many countries, this is the only source of data on Indigenous peoples. Only a few countries have sample surveys that are targeted to collect socio‑economic information on Indigenous peoples (e.g. Aboriginal and Torres Strait Islanders Social Survey and Aboriginal and Torres Strait Islanders Health Survey in Australia). Data availability has many limitations across OECD member and non-member countries.
First, many of the existing data sources are not designed specifically to Indigenous peoples but for the dominant population which leads to surveys that do not include questions that are specifically important for Indigenous peoples. Furthermore, as the sample frames are generally designed for the total population, the sample size of Indigenous peoples is not sufficient to provide reliable data at the national and subnational level. For the reasons presented above, existing information fails to capture or provide the essential and relevant information that is needed to make an informed decision on how to improve the quality of life for Indigenous peoples.
Second, there is a need for appropriate and consistent identification method of Indigenous peoples (Balestra and Fleischer, 2018[27]). A fundamental question is how to identify Indigenous peoples and how it is applied through different mechanisms to collect data. For example, Australia has introduced a Standard Indigenous Question that has been drawn from the Commonwealth definition framework, which is used at all the levels of government and by non-governmental organisations. This based on the principles of self-identification, descent and belonging to a group. Some countries put additional conditions and requirements on Indigenous identification that makes it less inclusive and there are also differences in definitions within countries.
Third, even with a consistent identification method, the data about Indigenous peoples can be challenging to collect because Indigenous peoples are harder to reach. Obviously, this can be because Indigenous people tend to live more remote areas than non‑Indigenous people with limited access to telecommunications services and connections to other places. Indigenous peoples tend to have higher rates of non‑responses that non-Indigenous peoples for a number of reasons including lack of trust, more geographically mobile populations and language barriers (Hunter and Smith, 2000[56]; Smylie and Firestone, 2015[57]). In this case, interview-administered surveys that involve Indigenous peoples are likely to yield higher response rates (Hunter and Smith, 2000[56]; Balestra and Fleischer, 2018[27])
Along with poor quality and inappropriate data, the existing data for policy use is limited with respect to the lack of up-to-date information about Indigenous people is a common data limitation across OECD member and non-member countries. For example, in Argentina and Colombia, data about Indigenous communities are only collected in the national census, which is carried out every ten years. One solution, in this case, is to link survey data and administrative records pertaining to these populations and pool data across multiple years to increase sample sizes (Balestra and Fleischer, 2018[27]).
Statistical agencies also tend not to consider how Indigenous peoples understand territory or geography. National statistical agencies work within their standard statistical geography, which provides them with a framework for survey design, sample selection and data collection that has a geographical dimension. The boundaries, determined in the standard statistical geography, reflect how countries are divided into administrative units and in some cases functional economic areas. They tend not to consider how territorial lands of Indigenous peoples are formed. Indigenous geography can exist within or cut across the borders of the standard statistical geographies. Without this geography, statistics are not going to be as useful as they could be for Indigenous peoples. The United States has sought to address this problem by introducing a Hierarchy of American Indian, Alaska Native and Native Hawaiian Areas which works as a tool for data agents to collect more useful and accurate data for Indigenous peoples (U.S. Census Bureau, 2018[58]).
Incorporating Indigenous values and perspectives into measuring economic development and well-being
Comparative analysis at a national and subnational level is limited by the lack of indicators about Indigenous peoples and their well-being outcomes in different domains. For this reason, the analysis in this chapter has concentrated only a few aspects of an individual’s well-being, excluding some vital determinants of individuals’ well-being as social connections and subjective well-being. There are a number of key dimensions that should be included in this discussion and provide further guidance for the development of Indigenous well-being measures at the subnational, national and international levels.
Material conditions
Income
One of the main issues in regards to measuring material conditions for Indigenous peoples is regarding subsistence hunting, fishing and harvesting. This is important to food security, the reproduction of culture, and it can be a major form of economic activity for Indigenous peoples in rural areas. Rural remote Indigenous communities can exist in a hybrid economy that mixes subsistence with wage labour and other forms of income including government transfers (Altman, 2004[59]). Subsistence is not only about meeting basic nutritional needs, but also relates to bartering and trading within and between kinship groups, and has an important cultural and relational component as well (Southcott and Natcher, 2018[60]). It can also be understood as a form of imputed income, which does deliver welfare benefits that can potentially be monetised (Sangha et al., 2017[61]). Indigenous groups also need to balance economic development with the use of land for subsistence activities and cultural values. This may also constrain certain economic activities that may otherwise be viable (e.g. energy, infrastructure and mining projects). To support decisions about natural resource management and economic development, good information and data are needed about the nature of subsistence economies (see Box 1.7 and Box 1.8).
Box 1.7. Alaska Department of Fish and Game, Division of Subsistence
Since the 1980s the Division of Subsistence within the Alaskan Department of Fish and Game has built an extensive evidence-based about subsistence economies in the state. The mission of the division is to scientifically gather, quantify, evaluate and report information about customary and traditional uses of Alaska’s fish and wildlife resources. The division provides the following services:
Compile and analyse existing data, and conduct research to gather data on the role of hunting and fishing by Alaskans for customary and traditional uses.
Disseminate current subsistence use information to the public and government agencies.
Evaluate the customary and traditional uses of fish and wildlife resources and provide advice to government agencies on limits to the use of these resources.
Ensure resource management plans incorporate data about customary and traditional uses of fish and wildlife resources.
Research is conducted in partnership with local communities and governed by ethical research guidelines. When a new project is undertaken, division researchers use a range of scientific methods including systematic and comprehensive household surveys, key respondent interviews, resource mapping and participant observation. An online database has been created (the Community Subsistence Information System) that contains harvest information for over 260 Alaskan communities collected by the division from household surveys.
Source: Alaska Department of Fish and Game (2019[62]), Mission: Subsistence Division, Alaska Department of Fish and Game, http://www.adfg.alaska.gov/index.cfm?adfg=divisions.subsmission (accessed on 25 January 2019).
Box 1.8. Measuring material conditions: Indigenous peoples and subsistence activities
Indigenous peoples in rural areas can be embedded in hybrid economies that combine wage income, government transfers and subsistence activities. Measurement of subsistence activities and food security should be done in partnership with communities through household surveys that can cover issues such as:
Amount of food sourced from subsistence activities for own use.
Giving and receiving food.
Seasonal patterns and changes over time.
Other sources of income.
Communities can also be empowered to map these activities across traditional territories to inform environmental management, land use planning and resource management. These activities can also be monetised to ensure appropriate compensation in the case of the expropriation of land or through disasters (e.g. storms, wildfires, mining accidents and oil spills).
Subsistence activities are currently absent from the indicator framework of the SDGs. However, they are relevant for SDG Goal 1 (End poverty in all its forms everywhere), SDG Goal 2 (End hunger, achieve food security and improved nutrition and promote sustainable agriculture) and SDG Goal 8 (Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all). Goals 1 and 2 should recognise subsistence in relation to the vulnerability of poor people to natural disasters and as a sustainable form of food production. There is an opportunity for Goal 8 to recognise the role of subsistence as part of a mixed economy for Indigenous peoples.
Sources: Adapted from Aslksen, I. et al. (2008[63]), Interdependency of Subsistence and Market Economies in the Arctic, https://www.ssb.no/a/english/publikasjoner/pdf/sa112_en/kap6.pdf (accessed on 07 February 2019); Alaska Department of Fish and Game (2019[62]), Mission: Subsistence Division, Alaska Department of Fish and Game, http://www.adfg.alaska.gov/index.cfm?adfg=divisions.subsmission (accessed on 5 January 2019).
Quality of life
Social connections and subjective well-being
Standard measures of cultural and social capital are designed for societies which place less emphasis on kinship and family relations compared to Indigenous communities (O’Brien, Phillips and Patsiorkovsky, 2005[64]). In this sense, subjective well-being for Indigenous communities may have a stronger collective and relational component (Yap and Yu, 2016[65]), which can be incorporated as part of subjective well-being questions in the OECD framework. The framework could also be extended to reflect the key role of social capital for Indigenous development and broaden the concept to give more weight to cultural components. This includes the continuation of language, cultural artefacts and representations, protection of sacred sites, and traditional knowledge (Taylor, 2008[66]; Australian Bureau of Statistics, 2010[67]; Productivity Commission, 2014[68]). Alternative ways of measuring social capital stocks in Indigenous communities can also be incorporated to capture their relation to other forms of capital and their contribution to current and future development. In particular, in Indigenous communities where there is a strong connection between cultural and natural capital, policies focusing on expanding economic capital need to balance the community views on the way in which their resources are used (Sangha et al., 2017[61]) (see Box 1.9).
Box 1.9. Indigenous peoples and measuring social connections and culture
The National Aboriginal and Torres Strait Islander Survey in Australia includes a number of questions that highlight issues that are important to Indigenous well-being:
Continuation of language and whether Aboriginal and Torres Strait Islander children speak an Australian Indigenous language at home.
Connection to culture in terms of direct contact with a leader or elder each week, and whether Indigenous peoples have a recognised homeland or traditional territory.
Indigenous peoples may face discrimination that creates barriers to economic and social participation so the survey includes a question about whether people feel that they were treated unfairly at least once in the previous 12 months because they were of Aboriginal or Torres Strait Islander origin.
Care for people with a disability or long-term health condition given the higher prevalence of some chronic health conditions amongst Indigenous populations.
These elements can complement mainstream measures of social capital such as participation in volunteering.
Cultural issues have limited coverage within the SDG framework (related to tourism and education for cultural appreciation) and it does not refer to the reproduction or strengthening of languages. However, cultural and social connections are very important to the well-being of Indigenous peoples. There is an opportunity to incorporate these measures into SDG Goal 3 (Ensure healthy lives and promote well-being for all at all ages) and SDG Goal 4 (Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all).
Source: Australian Bureau of Statistics (2016[69]), National Aboriginal and Torres Strait Islander Social Survey, 2014-15: Key Findings, http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/4714.0/.
Civic participation and governance
Across advanced OECD nations, there has been a shift toward self-determination (the right for Indigenous communities to govern their own affairs and shape relations with institutions with the framework of the nation-state) (Daes, 2008[1]). Putting self-determination at the centre of the Indigenous economic development allows better alignment between policies and development goals determined at the level of communities, as well as more participation throughout the policy design and implementation process (Cornell, 2006[70]). Political capital for Indigenous peoples needs to encompass issues such as representation, the role of community-controlled organisations, the legitimacy and cultural match of Indigenous representative and decision-making bodies, and consultation by governments about matters that impact upon Indigenous peoples (Hunt, 2008[71]; Tsey et al., 2012[72]) (see Box 1.10).
Box 1.10. Indigenous peoples and measuring civic participation and governance
There are not many examples of discrete measures related to civic participation and governance for Indigenous peoples that have been put into practice. However, there are some sources that give an indication of the types of measures that could be operationalised. This could relate to representation in decision-making institutions, participation in decision-making and the recognition of legal rights.
Number/proportion of Indigenous peoples represented in parliament and senior levels of the civil service.
Perceptions amongst Indigenous peoples about opportunities to have a real say on issues that are important (consistent with the principle of free, prior and informed consent).
Recognition of a duty to consult with Indigenous peoples before adopting or implementing legislative and administrative measures that may affect them.
Recognition of the rights of Indigenous peoples and their specific forms of participation and government.
Recognition of Indigenous people’s rights to maintain cross-border contacts and collaboration.
These measures relate to SDG Goal 16 (Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels) and Goal 17 (Strengthen the means of implementation and revitalise the Global Partnership for Sustainable Development). Issues that are specific to Indigenous peoples, such as the principle of free prior and informed consent (FIPC) and respect for their specific forms of government, are currently not visible in these goals or indicators. Some existing indicators could be disaggregated by Indigenous status by countries to provide a more holistic view of well-being and progress (e.g. proportion of Indigenous people in positions in public institutions).
Sources: UN (n.d.[73]), “Indigenous Peoples major group: Policy brief on sustainable development goals and post‑2015 development agenda: A working draft”, https://sustainabledevelopment.un.org/content/documents/6797IPMG%20Policy%20Brief%20Working%20Draft%202015.pdf (accessed on 16 October 2018); Georgetown University (2019[74]), Indigenous Peoples, Democracy and Political Participation, http://pdba.georgetown.edu/IndigenousPeoples/introduction.html (accessed on 16 October 2018); Indigenous Navigator (n.d.[75]), Indicators ‑ For Monitoring the UN Declaration on the Rights of Indigenous Peoples, http://www.indigenousnavigator.org/ (accessed on 22 October 2018).
Environmental quality
Natural capital is a way of understanding the underlying stocks that produce environmental quality and it encompasses three dimensions. The first is the use of renewable and non-renewable natural resources (sub-soil resources, water, forests) in the production process to generate income (Brandt, Schreyer and Zipperer, 2013[76]). The second is about the asset value of ecosystems and the flow of ecosystem goods and services (air, clean water, climate, cultural and recreational benefits) into the future (UN, 2014[77]) (see Box 1.11). The third is that social and economic relations are a sub-set of natural ecosystems, and cultural, social and economic relationships with nature are central to well-being (Sangha et al., 2017[61]). For Indigenous peoples, examples of the first dimension include mining and extractive activities on Indigenous lands with legal frameworks that enable the flow of benefits to community members. In terms of the second dimension, ecosystem services are also a potential source of income recognising how Indigenous peoples manage resources to ensure long‑term productivity of the land. For example, carbon emissions may be priced in some jurisdictions and mitigation of carbon emissions through management practices on Indigenous lands can deliver monetary benefits directly from governments or through markets (Sangha et al., 2017[61]).
These first two concepts embed the natural environment within an economic framework whether it is through the utilisation of natural resources in the production, or monetising environmental stocks and flows. As discussed earlier, Indigenous use and harvesting of land can exist outside the formal market through traditional food production that provides subsistence for community members. Indigenous peoples also have spiritual and cultural values related to land, for example, ceremonies and sacred sites. These factors cannot have a price put on them but are important to Indigenous well-being and contribute to the overall “duty of care” that Indigenous peoples have with the land and natural resources (Taylor, 2008[66]; Jiménez, Cortobius and Kjellén, 2014[78]).
Box 1.11. Indigenous peoples and measuring environmental quality
Adapting environmental measures for Indigenous peoples should capture issues such as ownership and control over the use of natural resources and access to traditional lands (Australian Bureau of Statistics, 2010[67]). The role of Indigenous people in managing lands and waters, and their access and rights to them, are not directly acknowledged in the SDGs. Importantly, the cultural value and significance of land and how it might be protected is also not mentioned. These could be embedded in: (SDG 12) Ensure sustainable consumption and production patterns; (SDG 13) Take urgent action to combat climate change and its impacts; (SDG 14) Conserve and sustainably use the oceans, seas and marine resources for sustainable development; and, (SDG 15) Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss.
Source: Australian Bureau of Statistics (2010[67]), Framework for Measuring Wellbeing: Aboriginal and Torres Strait Islander Peoples, http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/CE9E58A5F67093CDCA2576DC00142E79?opendocument (accessed on 25 January 2019).
Accessibility to services
Another important aspect of well-being is access to affordable, safe and high-quality living environments (Australian Bureau of Statistics, 2010[67]). In terms of physical capital (built infrastructure and housing), this can include access to potable water, electricity and sanitation and waste systems and services, and the resulting impacts on the environmental and public health in communities (Jiménez, Cortobius and Kjellén, 2014[78]). It also encompasses the stock and quality of housing, and whether these assets are managed by Indigenous communities (discussed earlier). In remote areas accessibility is a key issue in terms of the capacity to deliver services and access markets (phone network coverage, Internet and broadband, roads, and airports), which can also be impacted by seasonal conditions (winter, dry and monsoon seasons) (Infrastructure Australia, 2012[79]; Conference Board of Canada, 2014[80]). Rural accessibility issues are not given strong prominence in the SDG framework relative to cities. SDG Goal 1 (End poverty in all its forms everywhere) includes an indicator on the proportion of the population with access to basic services and SDG Goal 9 (Build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation) includes an indicator on the proportion of the rural population who live within 2 km of an all-season road. Again, there is an opportunity to disaggregate these indicators for Indigenous peoples and communities.
Adapting well-being frameworks for Indigenous peoples
Global, national and regional frameworks to measure well-being and development need to be adapted to include the unique needs, values and perspectives of Indigenous peoples. Self-determined economic development should enable Indigenous peoples to make a range of different informed choices about the development of their community, clan or nation. This requires investing in different forms of capital and linking them to governance and policies to make sure they are effectively managed to deliver benefits for community members. Indigenous communities also need to lead the process of developing objectives and designing measures of progress. A number of key considerations have been identified in terms of measuring community assets and the well‑being and economic development for Indigenous peoples (Table 1.17).
Table 1.17. Considerations for incorporating Indigenous perspectives into well-being frameworks
Dimensions |
Description |
Considerations for Indigenous peoples to measure well-being |
---|---|---|
Material conditions |
Money, access to credit, equity |
Indigenous-owned businesses, collective forms of asset ownership, and customary activities and subsistence (imputed income) |
Work skills, leadership, educational attainment, health |
Customary activities and traditional knowledge |
|
Built infrastructure – roads, buildings, houses |
Access to basic services, Indigenous ownership of assets |
|
Quality of life |
Social connections |
Kinship and family relations (e.g. contact with elders), discrimination, language |
Air, water, land, flora and fauna |
Land stewardship, control over access and use of land, spiritual and cultural values of land |
|
Civic participation and governance |
Self-determination, duty to consult, legitimacy and cultural match of representative institutions |
|
Cultural aspects |
Incorporation of traditional knowledge into decision-making, protection of cultural artefacts and sites |
Empowering Indigenous communities to collect and use data to support local decision-making
Many of the challenges presented above could also be addressed by involving Indigenous peoples to the data collection process from designing the methods to data analysis. This can be achieved through targeted strategies undertaken by national statistical agencies. For example, New Zealand has begun to proactively address the decline in the number of non-response rates among Māori population by developing a Māori Census Strategy. The strategy includes principles which some of them follow Māori tikanga which is the Māori way of doing things. These principles are the foundation of the census approach to working with and for Māori and they are applied in the 2018 census programme.
Empowering Indigenous peoples also requires a different orientation about the use of data, from one that is government-led, to one that is led by Indigenous peoples. This orientation connects to global debates about Indigenous data sovereignty, which is defined as the right of Indigenous peoples to govern the creation, collection, ownership and use of their data (Kukutai and Taylor, 2016[81]). It means developing social and economic indicators in a way that blends traditional and modern knowledge. (Taylor, 2008[82]) conceptualises this as a ‘recognition space’ that is based on meaningful engagement and creating indicators that reflect Indigenous values and perspectives. Enabling Indigenous peoples’ “data sovereignty” will ensure better alignment between data collection and the needs and aspirations of Indigenous peoples and also empower them to use it to inform decision-making (see Box 1.12 and Box 1.13).
Box 1.12. Indigenous data sovereignty – Why it matters
A lack of quality and disaggregated data on Indigenous peoples has long been raised in an international forum such as the United Nations Permanent Forum on Indigenous Issues. As noted by Kukutai and Taylor in their edited volume on Indigenous Data Sovereignty,
“The absence or lack of data that reflect where and how many Indigenous peoples there are, and how they are faring in relation to the realisation of their individual and collective rights is directly related to the weakness of governments and intergovernmental bodies in formulating and implementing Indigenous-sensitive decisions and programs.” (Kukutai and Taylor, 2016, p. xxi[83])
This has raised the growing need for more effective and inclusive forms of data collection and data disaggregation on Indigenous peoples, including measures that could help to support the implementation of the Millennium Development Goals and the Sustainable Development Goals in relation to realising Indigenous peoples’ rights. What these researchers emphasise is that: “any such initiative must be firmly positioned in an Indigenous (rights) approach, including the right of the Indigenous peoples to themselves determine, define and hold ownership over such initiatives and databases”.
Source: Kukutai, T. and J. Taylor (2016[83]), Indigenous Data Sovereignty, Australian National University.
Data also needs to be collected at a local level because each Indigenous community, and the information that is relevant for them, is different. In addition, the definition of the measurable concepts differs from one community or language group to another. This linguistic and cultural dimension has an important role to play in the development of indicators. For example, some Indigenous cultures do not necessarily have concepts and words related to western forms of business, markets and wealth creation.
Indigenous peoples and communities’ vision on economic development and well-being also may differ from the view of the dominant population. Issues such as connection to the land, culture and kinship relationships tend to be more important. Therefore, it is crucial that Indigenous peoples define measures and methodologies that provide a basis for more informed decisions about realising their aspirations and objectives for development.
Box 1.13. The Yawuru Nation: “Knowing our Community” and well-being survey
The Yawuru “Knowing our Community” household survey is a good example of how Indigenous-led survey design and data collection can lead to improved quality of data and meaningful use of information for changes.
The survey was established together with the Kimberley Institute, a not-for-profit organisation, and the Australian National University. The need for own survey first occurred after a land settlement that gave Yawuru Nation assets that needed to be allocated efficiently. As a result, NBY, a not-for-profit organisation owned by the Yawuru native title holders, started to look for socio-economic information to support the negotiations with public and private investors. However, the lack of data about the Yawuru community and the poor quality of official data lead to the decision of designing an own-household survey. The results from Yawuru’s own-community survey showed how ABS provides under-estimated population counts; it therefore provided more accurate information about the community. The Yawuru “Knowing our Community” household survey is first of its kind in Australia since no other Indigenous community has ever been responsible for designing a survey, or collecting and analysing data about their own community before.
After conducting its first community survey, the Yawuru Nation has continued providing data about their community. In 2015, they conducted a well-being survey that they designed to measure the community’s well-being. Through interviews, they conceptualised their well-being framework and identified the key indicators to describe the well-being of their people. The well-being framework is grounded in the concepts of bugarringarrn (traditional knowledge and practices of time immemorial) and mabu liyan (Yawuru idea of the good life based on interconnectedness between country, people and culture) and finding an appropriate balance between them and the modern world.
The final indicators included more Indigenous community specific indicators such as access to fishing spots and sharing a catch with family and friends to measure the connection to the country, together with some of the standard socio-economic indicators. The Yawuru well-being survey is a great example of why and how Indigenous peoples’ well-being should be measured at the local level. One of the key findings was that an individual’s well-being is interlinked with the overall well-being of the community.
The results from these two surveys highlight how designing well-being surveys at the community level is essential for providing meaningful information about the community for the community, to measure and monitor their well-being and make improvements. Indigenous-led survey design enabled the Yawuru Nation, important actors in the Broome society, to work towards fulfilling their goals and responsibilities.
Sources: Taylor, J. et al. (2014[84]), “Statistics for community governance: The Yawuru Indigenous Population Survey, Western Australia”, http://apo.org.au/system/files/39420/apo-nid39420-151506.pdf
(accessed on 16 October 2018); Yap, M. and E. Yu (2016[85]), Community Wellbeing from the Ground Up: A Yawuru Example, https://www.curtin.edu.au/local/docs/bcec-community-wellbeing-from-the-ground-up-a-yawuru-example.pdf (accessed on 16 October 2018).
References
[16] (FAO), T. (n.d.), Indigenous peoples (country data), http://www.fao.org/indigenous-peoples/country-data/en/.
[20] (IBGE), T. (n.d.), 2010 Census, https://censo2010.ibge.gov.br/resultados.html.
[12] (INE), N. (2018), Resultados CENSO 2017: 5.1 Población que se considera perteneciente a un pueblo originario, por nombre del pueblo originario, según sexo, https://resultados.censo2017.cl/Home/Download.
[47] Aboriginal Affairs and Northern Development Canada (2015), Skills in Canada - Preliminary Results of the Programme for the International Assessment of Adult Competencies, https://www.aadnc-aandc.gc.ca/DAM/DAM-INTER-HQ-AI/STAGING/texte-text/ncr_5a_1429704264288_eng.pdf (accessed on 20 October 2018).
[62] Alaska Department of Fish and Game (2019), Mission: Subsistence Division, Alaska Department of Fish and Game, http://www.adfg.alaska.gov/index.cfm?adfg=divisions.subsmission (accessed on 25 January 2019).
[59] Altman, J. (2004), “Economic development and Indigenous Australia: Contestations over property, institutions and ideology”, Australian Journal of Agricultural and Resource Economics, Vol. 48/3, pp. 513-534, http://dx.doi.org/10.1111/j.1467-8489.2004.00253.x.
[63] Aslksen, I. et al. (2008), Interdependency of Subsistence and Market Economies in the Arctic, https://www.ssb.no/a/english/publikasjoner/pdf/sa112_en/kap6.pdf (accessed on 7 February 2019).
[7] Australian Bureau of Statistics (2017), “Aboriginal and Torres Strait Islander Population Estimates, 2016”, http://www.abs.gov.au/AUSSTATS/abs@.nsf/featurearticlesbytitle/3D177246389F9763CA2581F500101011?OpenDocument (accessed on 28 March 2019).
[46] Australian Bureau of Statistics (2016), Australian Aboriginal and Torres Strait Islander Health Survey: Updated Results 2012-13, https://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/4727.0.55.006 (accessed on 7 February 2019).
[69] Australian Bureau of Statistics (2016), National Aboriginal and Torres Strait Islander Social Survey, 2014-15 - Key Findings, http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/4714.0/ (accessed on 22 October 2018).
[67] Australian Bureau of Statistics (2010), Framework for Measuring Wellbeing: Aboriginal and Torres Strait Islander Peoples, http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/CE9E58A5F67093CDCA2576DC00142E79?opendocument (accessed on 25 January 2019).
[23] Australian Bureau of Statistics (ABS) (n.d.), Census TableBuilder, https://www.abs.gov.au/websitedbs/D3310114.nsf/home/About+TableBuilder.
[38] Australian Health Ministers’ Advisory Council (2014), Aboriginal and Torres Strait Islander Health Performance Framework 2014 Report, https://www.pmc.gov.au/sites/default/files/publications/indigenous/Health-Performance-Framework-2014/index.html (accessed on 21 October 2018).
[44] Australian Institute of Health and Welfare for Australia (2018), Deaths in Australia, https://www.aihw.gov.au/reports/life-expectancy-death/deaths-in-australia/contents/life-expectancy.
[6] Axelsson, P. and P. Sköld (2006), “Indigenous populations and vulnerability. Characterizing vulnerability in a Sami context”, Annales de Démographie historique, Vol. 111/1, p. 115, http://dx.doi.org/10.3917/adh.111.0115.
[27] Balestra, C. and L. Fleischer (2018), “Diversity statistics in the OECD: How do OECD countries collect data on ethnic, racial and indigenous identity?”, OECD Statistics Working Papers, No. 2018/09, OECD Publishing, Paris, https://dx.doi.org/10.1787/89bae654-en.
[5] Barbary, O. (2015), “Social inequalities and indigenous populations in Mexico: A plural approach”, in Simon, P., V. Piché and A. Gagnon (eds.), Social Statistics and Ethnic Diversity: Cross-National Perspectives in Classifications and Identity Politics, IMISCOE Research Series, Springer, New York, http://dx.doi.org/10.1007/978-3-319-20095-8_11.
[76] Brandt, N., P. Schreyer and V. Zipperer (2013), “Productivity Measurement with Natural Capital”, OECD Economics Department Working Papers, No. 1092, OECD Publishing, Paris, https://dx.doi.org/10.1787/5k3xnhsz0vtg-en.
[21] Brezzi, M., L. Dijkstra and V. Ruiz (2011), “OECD Extended Regional Typology: The Economic Performance of Remote Rural Regions”, OECD Regional Development Working Papers, No. 2011/6, OECD Publishing, Paris, http://dx.doi.org/10.1787/5kg6z83tw7f4-en.
[26] Bureau, U. (n.d.), American FactFinder, https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml.
[25] Center, M. (2018), Integrated Public Use Microdata Series International: Version 7.1 [dataset], https://doi.org/10.18128/D020.V7.1 (accessed on 19 June 2018).
[80] Conference Board of Canada (2014), Study on Addressing the Infrastructure Needs of Northern Aboriginal Communities, http://www.naedb-cndea.com/reports/northern-infrastructure-report.pdf (accessed on 25 January 2019).
[55] Connolly, M. (2018), “Improving lives of Indigenous people through better statistics: Meeting policy and program needs”, http://www.oecd.org/iaos2018/programme/IAOS-OECD2018_Connolly.pdf (accessed on 21 October 2018).
[35] Cooke, M. et al. (2007), “Indigenous well-being in four countries: An application of the UNDP’S Human Development Index to Indigenous Peoples in Australia, Canada, New Zealand, and the United States”, BMC International Health and Human Rights, http://dx.doi.org/10.1186/1472-698X-7-9.
[70] Cornell, S. (2006), Indigenous Peoples, Poverty and Self-Determination in Australia, New Zealand, Canada, and the United States, http://nni.arizona.eduhttp://www.ksg.harvard.edu/hpaied (accessed on 25 January 2019).
[1] Daes, E. (2008), “An overview of the history of indigenous peoples: Self-determination and the United Nations”, Cambridge Review of International Affairs, http://dx.doi.org/10.1080/09557570701828386.
[19] Department, T. (n.d.), 2005 Census [Censo nacional de población y vivienda], https://censo2018.dane.gov.co/.
[53] Easterbrook, M., T. Kuppens and A. Manstead (2016), “The education effect: Higher educational qualifications are robustly associated with beneficial personal and socio-political outcomes”, Social Indicators Research, Vol. 126/3, pp. 1261-1298, http://dx.doi.org/10.1007/s11205-015-0946-1.
[74] Georgetown University (2019), Indigenous Peoples, Democracy and Political Participation, http://pdba.georgetown.edu/IndigenousPeoples/introduction.html (accessed on 16 October 2018).
[54] Hoff, K. and A. Sen (2005), The Kin System as a Poverty Trap?, The World Bank, http://dx.doi.org/10.1596/1813-9450-3575.
[40] Homeless Hub (2019), Indigenous Peoples, https://www.homelesshub.ca/about-homelessness/population-specific/indigenous-peoples.
[56] Hunter, B. and D. Smith (2000), “Surveying mobile populations: Lessons from recent longitudinal surveys of Indigenous Australians”, https://core.ac.uk/download/pdf/156615660.pdf (accessed on 27 January 2019).
[71] Hunt, J. (2008), Between a Rock and a Hard Place: Self-determination, Mainstreaming and Indigenous Community Governance, https://researchers.anu.edu.au/publications/46970.
[30] ILO (2015), The 2030 Agenda for Sustainable Development, International Labour Organization, https://www.ilo.org/wcmsp5/groups/public/---ed_emp/---ifp_skills/documents/publication/wcms_503715.pdf (accessed on 22 October 2018).
[2] ILO (1989), Convention 169 - Indigenous and Tribal Peoples Convention, International Labour Organization, https://www.ilo.org/dyn/normlex/en/f?p=NORMLEXPUB:12100:0::NO::P12100_ILO_CODE:C169 (accessed on 25 January 2019).
[45] Indian Health Service for the United States (2018), Disparities, https://www.ihs.gov/newsroom/factsheets/disparities/.
[75] Indigenous Navigator (n.d.), Indicators - For Monitoring the UN Declaration on the Rights of Indigenous Peoples, http://www.indigenousnavigator.org/ (accessed on 22 October 2018).
[9] INEGI (n.d.), Encuesta Intercensal [Intercensal survey].
[24] INEGI (n.d.), Estimadores de la Población Total y su Distribución Porcentual Según Autoadscripción Indígena por Entidad Federativa, Sexo y Grandes Grupos de Edad [Total Population Estimators and Their Percentage Distribution according to Indigenous Self-identification].
[79] Infrastructure Australia (2012), “Essential Indigenous infrastructure”, in 2012 Report to COAG and Assessments, https://infrastructureaustralia.gov.au/policy-publications/publications/files/P195_IACOAG_2012_Chapter4_7_WS.pdf (accessed on 25 January 2019).
[78] Jiménez, A., M. Cortobius and M. Kjellén (2014), “Water, sanitation and hygiene and indigenous peoples: A review of the literature”, Water International, Vol. 39/3, pp. 277-293, http://dx.doi.org/10.1080/02508060.2014.903453.
[83] Kukutai, T. and J. Taylor (2016), Indigenous Data Sovereignty, Australian National University.
[81] Kukutai, T. and J. Taylor (2016), Indigenous data sovereignty: towards an agenda, ANU Press.
[3] Lantto, P. and U. Mörkenstam (2008), “Sami rights and Sami challenges”, Scandinavian Journal of History, Vol. 33/1, pp. 26-51, http://dx.doi.org/10.1080/03468750701431222.
[18] National Institute of Statistics and Census, C. (n.d.), Ethnic groups [Grupos étnicos - raciales], http://www.inec.go.cr/social/grupos-etnicos-raciales.
[14] National Institute of Statistics and Economic Studies of New Caledonia (ISEE) (2015), Population des différentes communautés d’appartenance de Nouvelle-Calédonie en 2009 et 2014, http://www.isee.nc/population/recensement/communautes?highlight=WyJrYW5hayJd (accessed on 28 March 2019).
[64] O’Brien, D., J. Phillips and V. Patsiorkovsky (2005), “Linking indigenous bonding and bridging social capital”, Regional Studies, Vol. 39/8, pp. 1041-1051, http://dx.doi.org/10.1080/00343400500327984.
[4] OECD (2019), Linking the Indigenous Sami People with Regional Development in Sweden, OECD Rural Policy Reviews, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264310544-en.
[48] OECD (2019), OECD Regional Well-Being, https://www.oecdregionalwellbeing.org/ (accessed on 7 February 2019).
[28] OECD (2017), How’s Life? 2017: Measuring Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/how_life-2017-en.
[36] OECD (2016), Linking Indigenous Communities with Rural and Regional Development, OECD, Paris, http://www.oecd.org/cfe/regional-policy/Indigenous-Commuities-project.pdf (accessed on 25 January 2019).
[22] OECD (2016), OECD Regional Outlook 2016: Productive Regions for Inclusive Societies, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264260245-en.
[42] OECD (2015), How’s Life? 2015: Measuring Well-being, OECD Publishing, Paris, http://dx.doi.org/10.1787/how_life-2015-en.
[52] OECD (2012), Promoting Growth in All Regions, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264174634-en.
[51] OECD (2009), How Regions Grow: Trends and Analysis, OECD Publishing, Paris, http://www.oecd.org/cfe/regional-policy/howregionsgrowtrendsandanalysis.htm (accessed on 22 October 2018).
[86] OECD (n.d.), OECD Regional Statistics, OECD, Paris, https://doi.org/10.1787/region-data-en.
[68] Productivity Commission (2014), Measuring the Wellbeing of Aboriginal and Torres Strait Islander Australians, https://www.pc.gov.au/research/ongoing/overcoming-indigenous-disadvantage/2014/oid-2014-factsheet2.pdf (accessed on 25 January 2019).
[41] Ruggles, S. et al. (2018), IPUMS USA: Version 9.0 [dataset], https://doi.org/10.18128/D010.V9.0 (accessed on 19 June 2018).
[13] Sámi Parliament (n.d.), The Sámi in Finland, https://www.samediggi.fi/sami-info/?lang=en (accessed on 28 March 2019).
[17] Sámi Parliament Sweden (2018), Background: The State and the Sami Parliament, https://www.sametinget.se/9688.
[61] Sangha, K. et al. (2017), “Challenges for valuing ecosystem services from an Indigenous estate in northern Australia”, Ecosystem Services, Vol. 25, pp. 167-178, http://dx.doi.org/10.1016/J.ECOSER.2017.04.013.
[49] Savvas, A., C. Boulton and E. Jepsen (2011), “Influences on Indigenous labour market outcomes”, http://dx.doi.org/10.2139/ssrn.2006294.
[29] Sen, A. (2005), “Human rights and capabilities”, Journal of Human Development, Vol. 6/2, pp. 151-166, http://dx.doi.org/10.1080/14649880500120491.
[57] Smylie, J. and M. Firestone (2015), “Back to the basics: Identifying and addressing underlying challenges in achieving high quality and relevant health statistics for indigenous populations in Canada”, Statistical journal of the IAOS, Vol. 31/1, pp. 67-87, http://dx.doi.org/10.3233/SJI-150864.
[60] Southcott, C. and D. Natcher (2018), “Extractive industries and Indigenous subsistence economies: A complex and unresolved relationship”, Canadian Journal of Development Studies/Revue canadienne d’études du développement, Vol. 39/1, pp. 137-154, http://dx.doi.org/10.1080/02255189.2017.1400955.
[15] Statbank Greenland (2018), Population statistics, http://bank.stat.gl/pxweb/en/Greenland/?rxid=32ef5e7f-f5c7-44ba-94b5-5ef2d4ddb7f7 (accessed on 28 March 2019).
[43] Statistics Canada (2015), Aboriginal Statistics at a Glance: 2nd Edition, http://www.statcan.gc.ca.
[8] Statistics Canada (n.d.), Census of Population for Canada, https://www.statcan.gc.ca/eng/start.
[39] Statistics New Zealand (2014), 2013 Census QuickStats about income, http://archive.stats.govt.nz/Census/2013-census/profile-and-summary-reports/quickstats-income/personal-income-ethnic.aspx.
[10] Statistics New Zealand (n.d.), NZ.Stat (database), http://nzdotstat.stats.govt.nz/wbos/index.aspx.
[31] Stats NZ (2013), Te Kupenga, http://archive.stats.govt.nz/browse_for_stats/people_and_communities/maori/te-kupenga.aspx (accessed on 25 January 2019).
[66] Taylor, J. (2008), “Indigenous Peoples and indicators of well-being: Australian perspectives on United Nations Global Frameworks”, Social Indicators Research, Vol. 87/1, pp. 111-126, http://dx.doi.org/10.1007/s11205-007-9161-z.
[82] Taylor, J. (2008), “Indigenous Peoples and Indicators of Well-being: Australian Perspectives on United Nations Global Frameworks”, Social Indicators Research, Vol. 87, pp. 111-126, http://dx.doi.org/10.1007/s11205-007-9161-z.
[87] Taylor, J. (2007), “Indigenous Peoples and Indicators of Well-being: Australian Perspectives on United Nations Global Frameworks”, Social Indicators Research, Vol. 87/1, pp. 111-126, http://dx.doi.org/10.1007/s11205-007-9161-z.
[84] Taylor, J. et al. (2014), “Statistics for community governance: The Yawuru Indigenous Population Survey, Western Australia”, The International Indigenous Policy Journal, Vol. 5/2, http://apo.org.au/system/files/39420/apo-nid39420-151506.pdf (accessed on 16 October 2018).
[72] Tsey, K. et al. (2012), Improving Indigenous Community Governance through Strengthening Indigenous and Government Organisational Capacity, Resource Sheet no. 10, Produced for the Closing the Gap Clearinghouse, http://www.aihw.gov.au/closingthegap (accessed on 25 January 2019).
[58] U.S. Census Bureau (2018), Hierarchy of American Indian, Alaskan Native and Native Hawaiian Areas, https://www2.census.gov/geo/pdfs/reference/aianhh_diag.pdf (accessed on 25 January 2019).
[11] U.S. Census Bureau (n.d.), American FactFinder, http://factfinder2.census.gov.
[34] UN (2018), The Permanent Forum and the 2030 Agenda, United Nations For Indigenous Peoples, https://www.un.org/development/desa/indigenouspeoples/focus-areas/post-2015-agenda/the-sustainable-development-goals-sdgs-and-indigenous/recommendations.html (accessed on 7 February 2019).
[77] UN (2014), System of Environmental-Economic Accounting 2012 Central Framework, United Nations, https://seea.un.org/sites/seea.un.org/files/seea_cf_final_en.pdf (accessed on 25 January 2019).
[32] UN (n.d.), About the Sustainable Development Goals, United Nations, http://www.un.org/sustainabledevelopment/sustainable-development-goals.
[73] UN (n.d.), “Indigenous Peoples major group: Policy brief on sustainable development goals and post-2015 development agenda: A working draft”, United Nations, https://sustainabledevelopment.un.org/content/documents/6797IPMG%20Policy%20Brief%20Working%20Draft%202015.pdf (accessed on 16 October 2018).
[33] UN Department of Economic and Social Affairs (2019), United Nations - Indigenous Peoples, https://www.un.org/development/desa/indigenouspeoples/mandated-areas1/economic-and-social-development.html (accessed on 27 March 2019).
[88] Weiss, D. et al. (2018), “A global map of travel time to cities to assess inequalities in accessibility in 2015”, Nature, Vol. 553/7688, pp. 333-336, http://dx.doi.org/10.1038/nature25181.
[37] World Bank (2015), “Indigenous Latin America in the twenty-first century”.
[85] Yap, M. and E. Yu (2016), Community Wellbeing from the Ground Up: A Yawuru Example, Bankwest Curtin Economics Centre, https://www.curtin.edu.au/local/docs/bcec-community-wellbeing-from-the-ground-up-a-yawuru-example.pdf (accessed on 16 October 2018).
[65] Yap, M. and E. Yu (2016), “Operationalising the capability approach: Developing culturally relevant indicators of indigenous wellbeing – An Australian example”, Oxford Development Studies, http://dx.doi.org/10.1080/13600818.2016.1178223.
[50] Zealand, S. (2018), data provided by Stats NZ (21th of December 2018).
Annex 1.A. Selected TL2 and TL3 regions
Annex Table 1.A.1. Selected TL2 regions
Country |
Region |
Indigenous population |
Indigenous share of total regional population (%) |
Indigenous populations share of total Indigenous population (%) |
---|---|---|---|---|
Australia |
New South Wales |
210 520 |
3 |
34 |
Northern Territory |
56 816 |
25 |
9 |
|
Queensland |
164 707 |
4 |
27 |
|
Tasmania |
22 400 |
4 |
4 |
|
Canada |
Manitoba |
223 310 |
18 |
13 |
Northwest Territories |
20 860 |
51 |
1 |
|
Nunavut |
30 545 |
86 |
2 |
|
Saskatchewan |
175 020 |
16 |
10 |
|
Yukon |
8 195 |
23 |
0.5 |
|
Mexico |
Campeche |
400 811 |
45 |
2 |
Chiapas |
1 886 104 |
36 |
7 |
|
Guerrero |
1 198 362 |
34 |
5 |
|
Hidalgo |
1 035 059 |
36 |
4 |
|
Jalisco |
872 531 |
11 |
3 |
|
Mexico |
2 751 672 |
17 |
11 |
|
Michoacán |
1 269 309 |
28 |
5 |
|
Morelos |
535 249 |
28 |
2 |
|
Oaxaca |
2 607 917 |
66 |
10 |
|
Puebla |
2 176 593 |
35 |
8 |
|
Quintana Roo |
667 336 |
44 |
3 |
|
San Luis Potosí |
630 604 |
23 |
2 |
|
Tabasco |
617 203 |
26 |
2 |
|
Tlaxcala |
321 310 |
25 |
1 |
|
Veracruz |
2 373 093 |
29 |
9 |
|
Yucatán |
1 371 625 |
65 |
5 |
|
New Zealand |
Auckland Region |
163 920 |
12 |
24 |
Bay of Plenty Region |
7 3962 |
28 |
11 |
|
Gisborne Region |
20 013 |
46 |
3 |
|
Hawke's Bay Region |
36 825 |
24 |
5 |
|
Manawatu-Wanganui Region |
47 424 |
21 |
7 |
|
Northland Region |
47 979 |
32 |
7 |
|
Waikato Region |
91 632 |
23 |
13 |
|
Wellington Region |
65 310 |
14 |
9 |
|
United States |
Alaska |
109 515 |
15 |
3 |
New Mexico |
219 237 |
11 |
5 |
|
Oklahoma |
355 795 |
9 |
9 |
|
South Dakota |
76 698 |
9 |
2 |
Annex Table 1.A.2. Selected TL3 regions
Country |
Region |
Type of region |
Share of Indigenous peoples (%) |
---|---|---|---|
Australia |
Mid North Coast |
Predominantly rural |
6 |
Western Australia - Outback |
Predominantly rural |
16 |
|
South Australia - Outback |
Predominantly rural |
10 |
|
New England and North West |
Predominantly rural |
10 |
|
Far West and Orana |
Predominantly rural |
17 |
|
Queensland - Outback |
Predominantly rural |
25 |
|
Hunter Valley Excl. Newcastle |
Predominantly rural |
6 |
|
Wide Bay |
Predominantly rural |
4 |
|
Northern Territory - Outback |
Predominantly rural |
51 |
|
Central West |
Predominantly rural |
6 |
|
Richmond - Tweed |
Intermediate |
4 |
|
Fitzroy |
Intermediate |
5 |
|
Townsville |
Intermediate |
7 |
|
Darwin |
Intermediate |
8 |
|
Cairns |
Intermediate |
8 |
|
Sydney |
Predominantly urban |
1 |
|
Perth |
Predominantly urban |
2 |
|
Illawarra |
Predominantly urban |
3 |
|
Newcastle and Lake Macquarie |
Predominantly urban |
4 |
|
Brisbane |
Predominantly urban |
2 |
|
Canada |
Division 18, AB |
Predominantly rural |
23 |
Yukon, YT |
Predominantly rural |
23 |
|
Baffin, NU |
Predominantly rural |
81 |
|
Pontiac, QC |
Predominantly rural |
18 |
|
Minganie-Basse-Côte-Nord, QC |
Predominantly rural |
31 |
|
Division 13, MB |
Predominantly rural |
17 |
|
Division 11, NL |
Predominantly rural |
92 |
|
Kitimat-Stikine, BC |
Predominantly rural |
36 |
|
Skeena-Queen Charlotte, BC |
Predominantly rural |
45 |
|
La Vallée-de-la-Gatineau, QC |
Predominantly rural |
23 |
|
Division 18, SK |
Predominantly rural |
87 |
|
Sudbury (District), ON |
Predominantly rural |
18 |
|
Division 5, NL |
Predominantly rural |
23 |
|
Division 17, SK |
Predominantly rural |
33 |
|
Keewatin, NU |
Predominantly rural |
92 |
|
Manitoulin, ON |
Predominantly rural |
41 |
|
Avignon, QC |
Predominantly rural |
17 |
|
Division 10, NL |
Predominantly rural |
39 |
|
La Tuque, QC |
Predominantly rural |
30 |
|
Region 5, NT |
Predominantly rural |
59 |
|
Stikine, BC |
Predominantly rural |
49 |
|
Mount Waddington, BC |
Predominantly rural |
31 |
|
Region 4, NT |
Predominantly rural |
86 |
|
Yarmouth, NS |
Predominantly rural |
19 |
|
Division 21, MB |
Predominantly rural |
53 |
|
Division 10, SK |
Predominantly rural |
22 |
|
Region 2, NT |
Predominantly rural |
76 |
|
Alberni-Clayoquot, BC |
Predominantly rural |
20 |
|
Division 12, SK |
Predominantly rural |
16 |
|
Division 3, AB |
Predominantly rural |
22 |
|
Central Coast, BC |
Predominantly rural |
62 |
|
Northern Rockies, BC |
Predominantly rural |
28 |
|
Division 6, MB |
Predominantly rural |
18 |
|
Division 16, MB |
Predominantly rural |
30 |
|
Division 17, AB |
Predominantly rural |
41 |
|
Rainy River, ON |
Predominantly rural |
27 |
|
Nord-du-Québec, QC |
Predominantly rural |
67 |
|
Division 18, MB |
Predominantly rural |
28 |
|
Region 3, NT |
Predominantly rural |
95 |
|
Bulkley-Nechako, BC |
Predominantly rural |
20 |
|
Division 14, SK |
Predominantly rural |
16 |
|
La Haute-Côte-Nord, QC |
Predominantly rural |
21 |
|
Division 23, MB |
Predominantly rural |
84 |
|
Sept-Rivières-Caniapiscau, QC |
Predominantly rural |
19 |
|
Richmond, NS |
Predominantly rural |
20 |
|
Division 9, MB |
Predominantly rural |
30 |
|
Division 20, MB |
Predominantly rural |
20 |
|
Kitikmeot, NU |
Predominantly rural |
92 |
|
Region 6, NT |
Predominantly rural |
24 |
|
Division 22, MB |
Predominantly rural |
80 |
|
Cochrane, ON |
Predominantly rural |
16 |
|
Division 17, MB |
Predominantly rural |
30 |
|
Kenora, ON |
Predominantly rural |
49 |
|
Cariboo, BC |
Predominantly rural |
17 |
|
Division 1, MB |
Predominantly rural |
20 |
|
Division 8, MB |
Predominantly rural |
27 |
|
Division 4, NL |
Predominantly rural |
40 |
|
Division 19, MB |
Predominantly rural |
95 |
|
Peace River, BC |
Predominantly rural |
15 |
|
Region 1, NT |
Predominantly rural |
79 |
|
Division 16, SK |
Predominantly rural |
35 |
|
Division 15, SK |
Predominantly rural |
30 |
|
Division 12, AB |
Predominantly rural |
23 |
|
Lambton, ON |
Intermediate |
6 |
|
Thunder Bay, ON |
Intermediate |
15 |
|
Greater Sudbury/Grand Sudbury, ON |
Intermediate |
9 |
|
Algoma, ON |
Intermediate |
14 |
|
Division 11, SK |
Intermediate |
11 |
|
Brant, ON |
Intermediate |
5 |
|
Division 6, SK |
Intermediate |
11 |
|
Capital, BC |
Predominantly urban |
5 |
|
Gatineau, QC |
Predominantly urban |
4 |
|
Division 6, AB |
Predominantly urban |
3 |
|
Nanaimo, BC |
Predominantly urban |
7 |
|
Toronto metropolitan municipality, ON |
Predominantly urban |
1 |
|
Division 11, MB |
Predominantly urban |
12 |
|
Greater Vancouver, BC |
Predominantly urban |
3 |
|
Middlesex, ON |
Predominantly urban |
2 |
|
Division 11, AB |
Predominantly urban |
6 |
|
Ottawa-Carleton, ON |
Predominantly urban |
3 |
|
Mexico |
Yucatán, R1 |
Predominantly rural |
78 |
Hidalgo, R4 |
Predominantly rural |
41 |
|
Oaxaca, R3 |
Predominantly rural |
67 |
|
Sinaloa, R1 |
Predominantly rural |
32 |
|
San Luis Potosí, R1 |
Predominantly rural |
62 |
|
Sonora, R11 |
Predominantly rural |
31 |
|
Yucatán, R8 |
Predominantly rural |
87 |
|
Puebla, R1 |
Predominantly rural |
47 |
|
Campeche, R3 |
Predominantly rural |
41 |
|
Veracruz, R7 |
Predominantly rural |
29 |
|
Oaxaca, R7 |
Predominantly rural |
73 |
|
Veracruz, R2 |
Predominantly rural |
51 |
|
Durango, R8 |
Predominantly rural |
42 |
|
Michoacán, R5 |
Predominantly rural |
28 |
|
Oaxaca, R1 |
Predominantly rural |
64 |
|
Mexico, R7 |
Predominantly rural |
35 |
|
Campeche, R1 |
Predominantly rural |
87 |
|
Queretaro, R2 |
Predominantly rural |
43 |
|
Guerrero, R6 |
Predominantly rural |
46 |
|
Yucatán, R2 |
Predominantly rural |
88 |
|
Puebla, R6 |
Predominantly rural |
30 |
|
Jalisco, R1 |
Predominantly rural |
31 |
|
Oaxaca, R2 |
Predominantly rural |
77 |
|
Mexico, R8 |
Predominantly rural |
37 |
|
Oaxaca, R5 |
Predominantly rural |
80 |
|
Queretaro, R5 |
Predominantly rural |
48 |
|
Colima, R1 |
Predominantly rural |
35 |
|
Veracruz, R1 |
Predominantly rural |
56 |
|
Guerrero, R4 |
Predominantly rural |
90 |
|
Chiapas, R5 |
Predominantly rural |
53 |
|
Campeche, R2 |
Predominantly rural |
39 |
|
Tabasco, R3 |
Predominantly rural |
32 |
|
Chiapas, R6 |
Predominantly rural |
80 |
|
Morelos, R7 |
Predominantly rural |
36 |
|
Yucatán, R5 |
Predominantly rural |
93 |
|
Tabasco, R4 |
Predominantly rural |
30 |
|
Nayarit, R5 |
Predominantly rural |
83 |
|
Guerrero, R3 |
Predominantly rural |
39 |
|
Yucatán, R7 |
Predominantly rural |
89 |
|
Chihuahua, R4 |
Predominantly rural |
31 |
|
Chihuahua, R11 |
Predominantly rural |
62 |
|
Chihuahua, R8 |
Predominantly rural |
39 |
|
Hidalgo, R5 |
Predominantly rural |
37 |
|
Oaxaca, R8 |
Predominantly rural |
68 |
|
Yucatán, R3 |
Predominantly rural |
73 |
|
Oaxaca, R6 |
Predominantly rural |
63 |
|
Sonora, R12 |
Predominantly rural |
57 |
|
Hidalgo, R9 |
Predominantly rural |
73 |
|
Campeche, R4 |
Predominantly rural |
31 |
|
Hidalgo, R8 |
Predominantly rural |
33 |
|
Morelos, R2 |
Predominantly rural |
55 |
|
Yucatán, R4 |
Predominantly rural |
85 |
|
Hidalgo, R13 |
Predominantly rural |
73 |
|
Hidalgo, R6 |
Intermediate |
75 |
|
Morelos, R6 |
Intermediate |
28 |
|
Puebla, R7 |
Intermediate |
43 |
|
Hidalgo, R10 |
Intermediate |
88 |
|
Puebla, R2 |
Intermediate |
66 |
|
Chiapas, R2 |
Intermediate |
78 |
|
Veracruz, R4 |
Intermediate |
33 |
|
Hidalgo, R7 |
Intermediate |
40 |
|
Oaxaca, R4 |
Intermediate |
57 |
|
Morelos, R5 |
Intermediate |
31 |
|
Michoacán, R2 |
Intermediate |
34 |
|
Puebla, R5 |
Predominantly urban |
25 |
|
Tlaxcala, R8 |
Predominantly urban |
30 |
|
Mexico, R2 |
Predominantly urban |
11 |
|
Tlaxcala, R1 |
Predominantly urban |
22 |
|
Jalisco, R10 |
Predominantly urban |
8 |
|
Puebla, R4 |
Predominantly urban |
27 |
|
Tlaxcala, R3 |
Predominantly urban |
45 |
|
Hidalgo, R3 |
Predominantly urban |
22 |
|
Mexico, R3 |
Predominantly urban |
12 |
|
Michoacán, R6 |
Predominantly urban |
27 |
|
Quintana Roo, R2 |
Predominantly urban |
44 |
|
Morelos, R1 |
Predominantly urban |
23 |
|
Mexico, R5 |
Predominantly urban |
65 |
|
Tlaxcala, R2 |
Predominantly urban |
30 |
|
Yucatán, R6 |
Predominantly urban |
51 |
|
Morelos, R4 |
Predominantly urban |
37 |
|
Mexico, R1 |
Predominantly urban |
22 |
|
Distrito Federal (MX), R2 |
Predominantly urban |
8 |
|
Morelos, R3 |
Predominantly urban |
29 |
|
New Zealand |
Northland Region |
Predominantly rural |
32 |
Waikato Region |
Intermediate |
23 |
|
Bay of Plenty Region |
Intermediate |
28 |
|
Hawke's Bay Region |
Intermediate |
24 |
|
Gisborne Region |
Intermediate |
46 |
|
Wellington Region |
Predominantly urban |
14 |
|
United States |
Minot, ND |
Predominantly rural |
12 |
Flagstaff, AZ |
Predominantly rural |
26 |
|
Aberdeen, SD |
Predominantly rural |
18 |
|
Santa Fe-Espanola, NM |
Predominantly rural |
7 |
|
Farmington, NM |
Predominantly rural |
24 |
|
Fort Smith, AR-OK |
Predominantly rural |
7 |
|
Oklahoma City-Shawnee, OK |
Predominantly rural |
6 |
|
Billings, MT |
Predominantly rural |
8 |
|
Great Falls, MT |
Predominantly rural |
15 |
|
Anchorage, AK |
Predominantly rural |
15 |
|
Phoenix-Mesa-Scottsdale, AZ |
Predominantly rural |
6 |
|
Tulsa-Bartlesville, OK |
Predominantly rural |
11 |
|
Rapid City, SD |
Predominantly rural |
17 |
|
San Antonio, TX |
Predominantly urban |
1 |
|
Los Angeles-Long Beach-Riverside, CA |
Predominantly urban |
2 |
|
Chicago-Naperville-Michigan City, IL-IN-WI |
Predominantly urban |
1 |
|
New York-Newark-Bridgeport, NY-NJ-CT-PA |
Predominantly urban |
1 |
|
Buffalo-Niagara-Cattaraugus, NY |
Predominantly urban |
1 |
|
Dallas-Fort Worth, TX |
Predominantly urban |
1 |
|
Albuquerque, NM |
Predominantly urban |
8 |
|
El Paso, TX |
Predominantly urban |
2 |
|
San Diego-Carlsbad-San Marcos, CA |
Predominantly urban |
1 |
|
Sacramento--Arden-Arcade--Truckee, CA-NV |
Predominantly urban |
2 |
|
Houston-Baytown-Huntsville, TX |
Predominantly urban |
1 |
|
Austin-Round Rock, TX |
Predominantly urban |
1 |
Sources: OECD calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2016 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2016 Census of Population, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2013 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2012-2016 American Community Survey 5-Year Estimates, Tables B01001A, B01001B, B01001C, B01001D using American FactFinder http://factfinder2.census.gov for the United States.
Annex 1.B. Labour market outcomes for Indigenous and non-Indigenous peoples, 2011
Annex Table 1.B.1. Labour force participation rates for Indigenous and non-Indigenous peoples, 2011 or latest available year
Country |
Indigenous |
Non-Indigenous |
Gap |
---|---|---|---|
Australia |
53 |
76 |
-23 |
Canada |
61 |
66 |
-5 |
Mexico |
56 |
60 |
-4 |
New Zealand |
72 |
79 |
-7 |
United States |
65 |
76 |
-11 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the labour force participation rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.B.2. Employment rates for Indigenous and non-Indigenous peoples, 2011 or latest available year
Country |
Indigenous |
Non-Indigenous |
Gap |
---|---|---|---|
Australia |
44 |
72 |
-28 |
Canada |
52 |
61 |
-9 |
Mexico |
54 |
57 |
-3 |
New Zealand |
56 |
69 |
-13 |
United States |
64 |
76 |
=11 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the employment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.B.3. Unemployment rates for Indigenous and non-Indigenous peoples, 2011 or latest available year
Country |
Indigenous |
Non-Indigenous |
Gap |
---|---|---|---|
Australia |
17 |
6 |
-12 |
Canada |
15 |
7 |
-7 |
Mexico |
4 |
5 |
+1 |
New Zealand |
11 |
4 |
-7 |
United States |
14 |
8 |
-6 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the unemployment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.B.4. Labour force participation rates for Indigenous and non-Indigenous peoples by type of region, 2011 or latest available year
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
Australia |
59 |
76 |
-17 |
55 |
76 |
-21 |
49 |
74 |
-25 |
Canada |
67 |
68 |
-1 |
61 |
66 |
-5 |
55 |
67 |
-12 |
Mexico |
63 |
62 |
+1 |
54 |
58 |
-4 |
51 |
55 |
-3 |
New Zealand |
73 |
78 |
-5 |
71 |
81 |
-10 |
68 |
79 |
-11 |
United States |
68 |
74 |
-6 |
69 |
78 |
-9 |
63 |
76 |
-13 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the labour force participation rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.B.5. Employment rates for Indigenous and non-Indigenous peoples by type of region, 2011 or latest available year
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
Australia |
50 |
72 |
-22 |
45 |
72 |
-27 |
40 |
71 |
-31 |
Canada |
59 |
63 |
-4 |
52 |
62 |
-10 |
44 |
62 |
-18 |
Mexico |
61 |
59 |
+2 |
52 |
56 |
-4 |
49 |
52 |
-3 |
New Zealand |
65 |
74 |
-9 |
63 |
78 |
-15 |
58 |
75 |
-17 |
United States |
60 |
68 |
-8 |
59 |
72 |
-13 |
53 |
71 |
-18 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the employment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.B.6. Unemployment rates for Indigenous and non-Indigenous peoples by type of region, 2011 or latest available year
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
Australia |
15 |
6 |
-9 |
19 |
6 |
-14 |
18 |
5 |
-13 |
Canada |
12 |
7 |
-5 |
15 |
7 |
-8 |
19 |
7 |
-12 |
Mexico |
4 |
5 |
+1 |
3 |
4 |
+1 |
4 |
4 |
0 |
New Zealand |
11 |
5 |
-6 |
12 |
4 |
-9 |
14 |
4 |
-10 |
United States |
13 |
8 |
-5 |
14 |
7 |
-7 |
15 |
7 |
-8 |
Note: The latest available year is 2013 for New Zealand; and 2015 for Mexico. For Canada, the unemployment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Australian Bureau of Statistics (n.d.[23]), Census of Population and Housing, 2011 (database), TableBuilder for Australia; Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C23002A, C23002B, C23002C, C23002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex 1.C. Educational attainment rate for Indigenous and non-Indigenous peoples, 2011
Annex Table 1.C.1. Educational attainment rates for Indigenous and non-Indigenous peoples, 2011 or latest available year
Country |
Indigenous |
Non-Indigenous |
Gap |
---|---|---|---|
Australia |
.. |
.. |
.. |
Canada |
48 |
65 |
-16 |
Mexico |
16 |
34 |
-18 |
New Zealand |
53 |
66 |
-12 |
United States |
77 |
86 |
-10 |
.. : Missing value or not available.
Note: The latest available year is 2006 for New Zealand; 2010 for Mexico; and 2011 the United States. For Canada, educational attainment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand; and U.S. Census Bureau (n.d.[11]), American Community Survey, 2006-2010 American Community Survey 5-Year Estimates, Tables C15002A, C15002B, C15002C, C15002D using American FactFinder http://factfinder2.census.gov for the United States.
Annex Table 1.C.2. Educational attainment rates for Indigenous and non-Indigenous peoples by type of region, 2011 or latest available year
Predominantly urban |
Intermediate |
Predominantly rural |
|||||||
---|---|---|---|---|---|---|---|---|---|
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
Indigenous |
Non-Indigenous |
Gap |
|
Australia |
.. |
.. |
.. |
... |
.. |
.. |
.. |
.. |
.. |
Canada |
53 |
68 |
-15 |
53 |
62 |
-9 |
38 |
57 |
-19 |
Mexico |
22 |
41 |
-20 |
13 |
29 |
-16 |
13 |
29 |
-14 |
New Zealand |
57 |
68 |
-11 |
51 |
64 |
-13 |
48 |
63 |
-15 |
United States |
.. |
.. |
.. |
.. |
.. |
.. |
.. |
.. |
.. |
.. : Missing value or not available.
Note: The latest available year is 2006 for New Zealand; and 2010 for Mexico. For Canada, educational attainment rate refers to populations aged 15 and over.
Sources: Calculations based on data drawn from Statistics Canada (n.d.[8]), 2011 National Household Survey, products of Statistics Canada for Canada; Minnesota Population Center (2018[25]), INEGI Population census 2010 and 2015 and Population and Housing Census available from the Integrated Public Use Microdata Series, International website (https://international.ipums.org/international/) for Mexico; and Statistics New Zealand (n.d.[10]) 2006 Census (database) for New Zealand.
Notes
← 1. The word “Indian” is a contested term that is not accepted by all Indigenous peoples in the Americas and that was never used prior to colonisation. Christopher Columbus is believed to have first used it to describe the people he encountered on his voyage in 1492, mistakenly thinking he had found India.
← 2. The Indian Act (1876) is the Federal statute in Canada that governs the relationship between the national government and recognised Indigenous tribes (now commonly referred to as “First Nations”).
← 3. Historically, the Bureau of Indian Affairs used blood quantum as a criterion to determine the status of Indians and membership of a tribe. Some tribes continue to use this criterion today. For further discussion, see: http://genetics.ncai.org/tribal‑sovereignty‑and‑enrollment‑determinations.cfm.
← 4. Reindeer herding companies have their own identity marker (SNI code 01491) within the SOS system.
← 5. Comparable figures available only for Canada, New Zealand and the United States.
← 6. For Australia and the United States, criteria differ due to the small number of TL2 regions with high proportion of Indigenous populations. We have therefore selected four regions with a largest share of Indigenous populations from each of these countries.
← 7. Calculations based on data drawn from the U.S. Census Bureau; American Community Survey, 2006-10 American Community Survey 5-Year Estimates and 2012-16 American Community Survey 5-Year Estimates, Table B17001A, B17001B, B17001C and B17001D; using American FactFinder; http://factfinder2.census.gov (17 September 2018).
← 8. The poverty rate indicator is a share of population aged 15 and over with total income below the poverty level. The poverty level is defined by the U.S. Census Bureau. Income thresholds vary by size of household ‑ https://www.census.gov/data/tables/time‑series/demo/income‑poverty/historical-poverty-thresholds.html
← 9. Most recent years available; in this case the years range from in 2013 to 2016.
← 10. The accessibility to cities grid as described in (Weiss et al., 2018[88]) is used to calculate the median TL3 time to the closest city across grid-cells that fall within TL3 boundaries. A city is defined as an urban centre in the GHSL SMOD layer, that is, “contiguous cells with a density of at least 1 500 per km2 or a density built up greater than 50% and a minimum population of 50 000 inhabitants” (Weiss et al., 2018[88]). Travel times are based on an impedance travel grid capturing the availability of roads, railroads, waterways and topographical conditions.