copy the linklink copied!Chapter 1. Why measure well-being in Cordoba?

This chapter discusses the need to assess people’s well-being at the regional and local level and the importance of well-being metrics in improving the impact of well-being policies. It also introduces the multidimensional framework the OECD has developed to measure well-being in regions and cities. It then discusses roles and responsibilities of the province of Córdoba in well-being policies, the resources the province devotes to fulfil those responsibilities and the province’s institutional capacity to develop metrics that will help make its well-being policies more effective and efficient. Lastly, it explains the process of developing a well-being indicator framework in Córdoba.

    

copy the linklink copied!Introduction: Why measure regional well-being?

There is currently a consensus that macroeconomic statistics on their own do not accurately reflect people’s well-being. A multidimensional perspective is required to take into account other aspects that affect people’s lives (OECD, 2014).

Many of the factors that have an impact on people’s well-being, such as jobs, access to education, environmental quality and public safety, differ from community to community. The OECD has shown that the differences between regions within a country in these areas of well-being can be at least as significant as the differences between countries (OECD, 2016a).

Measures of regional well-being reflect differences that can be masked in national averages. The geography of regional well-being can help regions benchmark their performance against that of other regions in their country, or regions in other countries that show similar strengths and face similar challenges. Data on well-being at a subnational level, though sometimes scarce, help give credibility to statistics, as people are more likely to acknowledge the information provided by indicators when they relate to their own community (OECD, 2014).

Public policies – such as those focusing on economic growth, jobs, education, fairness or environmental sustainability – are more likely to achieve their goals and have a deeper impact if they take account of the economic and social realities of the place in which people live and work (OECD, 2014). The determinants of school dropout rates, for instance, can vary considerably between rural and urban areas, between cities, and even between neighbourhoods in the same city. In rural areas, the problem may be lack of transport or schools, whereas in urban neighbourhoods it may have to do with crime rates. Policy makers can more easily identify potential synergies among policy areas in specific places. An education policy that keeps young people out of trouble can be more easily combined with an increase in citizen security if it is attempted at neighbourhood level.

Advantages of regional well-being metrics

Well-being data at the subnational level is often less extensive than at national level. For that reason, many regions and cities have started developing metrics to monitor their own performance and design well-being policies based on evidence. These initiatives may differ in their methods and choice of indicators, but they all aim to develop a multidimensional framework so as to more accurately reflect the synergies among the different well-being dimensions.

The four key benefits of using regional well-being metrics in the design and implementation of public policies can be summed up as follows:

  • Well-being metrics provide a comprehensive picture of material conditions and quality of life in regions, making it possible to assess whether economic growth translates into better outcomes in other dimensions such as health, environmental quality, education, etc. They can also be used to monitor whether the progress experienced by the population varies according to where people live. This is important because spatial concentration of inequality sources can jeopardise opportunities to improve living conditions for households located in certain communities.

  • Regional well-being metrics raise social awareness of policy objectives and increase government accountability. They can empower people to demand action to address the challenges that the indicators have brought to light and, in the mid to long term, enhance trust in their institutions’ ability to meet those challenges.

  • They can help prioritise government actions by indicating where improvements are most needed. The use of well-being metrics helps focus efforts and make government action more effective, especially when public resources are limited.

  • Regional well-being metrics can improve consistency between policy objectives, as the complementary nature of policies is most evident when they relate to specific places. For example, integrating land-use, transport and economic development policies so as to produce outcomes that are greener (increasing reliance on public transport), more equitable (improving access to labour markets for disadvantaged areas) and more efficient (reducing congestion) will be easier if these policies are designed for a specific place, such as a region or metropolitan area (OECD, 2014).

The OECD’s regional well-being framework

In view of the growing interest in well-being metrics at regional and local levels, the OECD decided to adapt its national “How’s life?” framework to the subnational level. In the OECD’s regional framework, well-being is understood as a multidimensional concept that emphasises what matters to people, is focused on outcomes (rather than on inputs and processes) and highlights the need to go “beyond averages” to analyse the distribution of well-being among individuals and social groups (e.g. by gender, age, ethnic origin or nationality), as well as between regions and countries (Figure 1.1). A key feature that “How’s life in your region?” adds to the “How’s life?” framework is the notion that well-being is made up of a combination of individual and place characteristics. Having a job, for example, is a crucial aspect of well-being which is determined, on the one hand, by characteristics of the individual such as skills and education and, on the other, by contextual factors such as access to training, transport and labour markets.

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Figure 1.1. OECD regional well-being framework: How’s life in your region?
Figure 1.1. OECD regional well-being framework: How’s life in your region?

Source: OECD (2014), How’s Life in Your Region?: Measuring Regional and Local Well-being for Policy Making, http://dx.doi.org/10.1787/9789264217416-en.

Information about people and places helps better understand the particular advantages and disadvantages of a territory and whether the various sources of inequality, both individual and place-based, are mutually reinforcing (OECD, 2014). A similar approach to measure well-being, i.e. combining individual and place-based characteristics, was recently adopted in the “Good Life” initiative in Southern Denmark (OECD, 2016b) and in Australia’s Socio-Economic Indexes for the Areas (SEIFA) (Australian Bureau of Statistics, 2011).

To put the OECD Regional Well-being Framework into effect, a set of comparable indicators was developed to measure outcomes in 11 well-being dimensions in 391 OECD regions.1 Many of these indicators are equivalent to the ones used in the “How’s life?” framework at national level. The regional framework includes an “Accessibility to services” dimension, instead of the Work-life balance dimension used in the How’s life? Framework since the latter could not be included due to lack of harmonised data for OECD regions.

copy the linklink copied!Roles and responsibilities for well-being policies in the province of Córdoba

Because of Argentina’s federal structure, Córdoba province and its municipalities are responsible for many of the policies that have a very direct impact on people’s lives (Box 1.1). Many decisions in sectors such as education, health, access to services, etc. are taken at provincial and municipal level. The provincial-level responsibilities may include both policy making and policy execution, which translates into expenditure and investment by these sub-national levels of government.

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Box 1.1. Federal structure of Argentina

Argentina is a federal state with three levels of government: i) the national level, with a democratically elected executive and a bicameral legislature; ii) the provincial level, with 23 provinces plus the autonomous city of Buenos Aires; and iii) the municipal level. All responsibilities and powers not delegated by the constitution to the national government are in the hands of the provinces. Moreover, each province has its own constitution and government institutions. The provincial constitutions define the institutional, political, administrative, economic and financial scope of each provincial government. The provinces may create regions (sometimes called departments) within their administrative boundaries for the purpose of economic and social development. They may also enter into international agreements, provided such agreements are notified to the national Congress, are not incompatible with national foreign policy and do not infringe upon the delegated powers of the national government. The national constitution requires that provincial governments guarantee municipal autonomy and establish municipal systems and rules as part of their own provincial constitutions.

Source: OECD (2016b), OECD Territorial Reviews: Córdoba, Argentinahttps://doi.org/10.1787/9789264262201-en.

Well-being responsibilities between levels of government

The province has exclusive responsibilities in some policy areas that have an impact on dimensions of the OECD regional well-being framework (Table 1.1). The provincial government has exclusive responsibility for pre-school, primary and secondary education, education for special groups and adult education as well as citizen security.

The province also shares some regional well-being responsibilities with the federal government and the municipalities. The federal government and the province share responsibilities in areas such as income compensation and unemployment protection, employment promotion and funding plans, tertiary education (universities) and internet access (Table 1.1). The responsibilities shared with the municipalities are mainly related to the provision of basic services such as electricity, water, and secondary and tertiary hospitals. Some policy areas are the exclusive responsibility of the municipalities; these include sewers, solid waste collection and disposal, primary hospital care, urban development and regulation.

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Table 1.1. Assignment of well-being responsibilities across levels of government

Well-being dimension

Policy area

Institutional level

Federal

Provincial

Municipal

Work-life balance

Public transport

X

X

X

Public services

Electricity

X

X

Gas

X

X

Telephone

X

X

Internet

X

X

Water

X

X

Sewers

X

Solid waste collection

X

Solid waste disposal

X

Jobs

Regulation

X

X

X

Employment promotion and funding plans

X

X

Formal training

X

X

X

Education

Pre-school, primary and secondary education, education for special groups and adult education

X

Tertiary (university)

X

X

Professional and technical training

X

X

Healthcare

Primary

X

Hospitals (secondary and tertiary)

X

X

Housing

Social housing

X

X

Urban development

X

Income

Income compensation

X

X

Unemployment protection

X

X

Social care

X

X

X

Support for people with disabilities

X

X

Citizen security

Prevention

X

Police

X

Note: The assignment of responsibilities to the different institutional levels may vary between provinces, as each province has its own constitution.

Source: OECD (2016b), OECD Territorial Reviews: Córdoba, Argentinahttps://doi.org/10.1787/9789264262201-en.

Provincial spending on well-being policy areas

The bulk of provincial spending in Córdoba goes toward fulfilling responsibilities in the areas of well-being. Around 48% of expenditure in the 2018 budget went to social services, including health, social promotion and care, education and culture, science and technology, work, housing and city planning (Figure 1.2). Education takes the largest share (68.5%), followed by health (18.2%) (Table 1.2). In addition to the budget item classified as Social Services, 12% of provincial spending goes to security and justice. This includes expenditure on domestic security and the penal system (which could fall under the well-being dimension of “citizen security”).

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Figure 1.2. Budget expenditures (2018)
Figure 1.2. Budget expenditures (2018)

Note: The numbers in the table are expressed in thousands of ARS.

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

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Table 1.2. Spending on social services (2018)

Social services

Amount

Percentage of total social services spending

Health

Medical Care

11 685 707

15.76

Environmental health

262 196

0.35

Health administration

1 559 828

2.10

Total

13 507 731

18.22

Social promotion and care

Social promotion

2 336 784

3.15

Social Care

4 445 731

6.00

Administration of social promotion and care

82 252

0.11

Total

6 864 767

9.26

Education and culture

Initial and primary education

12 953 824

17.47

Intermediate and technical education

14 662 314

19.77

Higher and university education

2 377 605

3.21

Special education

2 000 277

2.70

Education management

17 038 762

22.98

Culture

1 448 658

1.95

Sports and recreation

290 043

0.39

Total

50 771 483

68.47

Science and technology

Total

278 961

0.38

Work

Total

251 503

0.34

Housing and city planning

Total

2 480 768

3.35

Total

74 155 213

100.00

Note: The numbers in the table are expressed in thousands of ARS.

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

Spending on social services at large remained at the same levels throughout the 2014-18 period, albeit with slight changes in the areas that consumed the most resources. Apart from a small peak in 2016, when social spending reached almost 52% of total provincial spending, the level of social spending has stayed within the 47%-48% range. It is worth noting that the proportion of spending on education and culture fell four percentage points between 2014 and 2018, mainly to the benefit of social promotion and care, whose share increased by almost five percentage points over that period (Table 1.3).

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Table 1.3. Spending on social services, 2014–18
This table shows social spending as a percentage of the province’s total spending in one budget year and the distribution of social spending by policy area

 

2014

2015

2016

2017

2018

Social services spending as a percentage of total spending

48.43

48.42

51.71

47.43

48.24

Health

19.87

19.91

20.35

20.20

18.22

Social promotion and care

4.35

4.05

5.72

7.46

9.26

Education and culture

72.32

72.47

69.26

67.89

68.47

Science and technology

0.32

0.30

0.27

0.38

0.38

Work

0.32

0.36

0.34

0.35

0.34

Housing and city planning

2.81

2.91

4.06

3.74

3.35

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

Income generation

The province of Córdoba has some financial leeway in exercising its responsibilities in well-being (OECD, 2016b). Some 87.40% of projected total current revenue in the 2018 provincial budget consists of tax revenue (Table 1.4), approximately 51% of which comes from the share of federal taxes, 40% from provincial taxes and 9.5% from national taxes (Figure 1.3). This level of revenue-generating capacity is in line with the average for subnational governments in OECD countries (42%) (OECD, 2018).

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Table 1.4. Current revenue in Córdoba province’s 2018 budget

Current revenue

Amount

% of total revenue

Tax revenue

Provincial taxes

51 178 000

34.61

Share of federal taxes

65 840 739

44.52

National taxes

12 229 341

8.27

Total

129 248 080

87.40

Non-tax revenue

Charges for services

1 494 120

1.01

Non-tax funds

11 170 872

7.55

Total

12 664 992

8.56

Rest

Total

5 971 743

4.04

Total

147 884 815

100

Note: The numbers in the table are expressed in thousands of Argentine pesos.

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

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Figure 1.3. Tax revenues in the province of Córdoba by origin (%)
Figure 1.3. Tax revenues in the province of Córdoba by origin (%)

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

Córdoba is in a good position to finance well-being policies that contribute to regional development. A certain consensus has emerged that enabling subnational governments generate their own revenue helps promote more efficient resource management at subnational level and greater democratic responsibility, while also making subnational governments more resilient to economic impacts and crises. Taxes on immovable assets, such as the property tax, are also said to be especially appropriate at the subnational level, as they are relatively stable and therefore help prevent major budgetary fluctuations (Kim and Vammalle, 2012). Accordingly, since 2014 Córdoba has witnessed an increase in the rate of real estate tax, which has risen more than three percentage points, from 7.4% to 10.6% in 2018 (Table 1.5). Gross income tax, meanwhile, though still Córdoba’s main source of tax revenue (71.2% in 2018), has decreased as a proportion of the total since 2014.

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Table 1.5. Trend and composition of provincial tax revenues

 

2018

2017

2016

2015

2014

Tax revenue from within the province (%)

39.60 

38.56 

38.50 

40.35 

39.25 

% of total provincial tax

(by type of tax)

Tax on gross income

71.17 

73.67 

78.66 

80.36 

79.81 

Real estate tax

10.61 

9.40 

7.59 

6.55 

7.38 

Stamp duty

13.85 

12.78 

10.33 

9.99 

9.13 

Tax on vehicle ownership

4.35 

4.15 

3.41 

3.10 

3.68 

Source: Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

Governance of well-being statistics and metrics

Argentina has a decentralised statistical infrastructure framework in which provincial statistics departments cooperate with the national institute (Figure 1.4). Law no. 17622 (1968) created the National Statistics and Census Institute (Instituto Nacional de Estadística y Censos, INDEC) as the main governing body of the National Statistical System (Sistema Estadístico Nacional, SEN). SEN is made up of INDEC and the statistical services of the central, provincial and municipal government levels. INDEC’s role is to structure and coordinate the national statistical system and comply with the principle of regulatory centralisation and executive decentralisation (Government of Argentina, 1968). For practical purposes, this means that INDEC must ensure technical cooperation with the provincial statistics departments.

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Figure 1.4. Decentralised structure of the statistical infrastructure in Argentina
Figure 1.4. Decentralised structure of the statistical infrastructure in Argentina

Source: Prepared by the authors.

Service agreements (convenios) are the instrument used in Argentina to coordinate the production of statistics. These service agreements are contracts between INDEC and the provincial statistics departments that specify the services that the provincial departments are to provide in return for a certain budget. The service agreements ensure unity of methodologies and synchronised operation, e.g. when the National Census is carried out every 10 years. The agreements may be general, covering a number of services (field work, microdata processing, etc.) or more than one project (national census, continuous household survey, etc.), or they may be specific, e.g. for a new security survey or an industrial activity survey.

Córdoba’s Statistics and Census Department (Dirección General de Estadística y Censos, DGEyC) is part of SEN and, as such, is subject to certain obligations, which are regulated through the service agreements. The province of Córdoba created the DGEyC in 1972 through Provincial law no. 5454, in which INDEC is recognised as the body with oversight competencies for official statistics, the intention being that the DGEyC should respond to requests for statistics and information submitted by the provincial government (Córdoba Provincial Government, 1972). The services the DGEyC provides in collaboration with INDEC are specified in service agreements. A total of 16 surveys, censuses and statistical programmes are carried out by agreement, including the national consumer price index (IPCN), the continuous household survey (EPH) and the annual urban household survey (EAHU).

Like INDEC, the DGEyC is also responsible for coordinating statistics with government bodies at provincial level and with the municipalities and is also free to launch its own statistical programmes. Provincial law no. 5454 stipulates that the DGEyC may draw up an annual statistics and censuses programme that accommodates INDEC’s requirements. It also gives the DGEyC the competence to launch its own statistical programmes to meet specific data requests at the provincial level. The Well-being Survey 2018 is an example of an initiative exclusive to the province of Córdoba, aimed at meeting the demand for data to provide a multidimensional picture of well-being (access to services, life satisfaction, work-life balance, etc.), beyond the purely monetary dimensions. This initiative is financed out of provincial funds and the survey design and implementation is led by the General Secretariat of Government (Secretaría General de Gobernación), where the DGEyC is located.

copy the linklink copied!Well-being Survey 2018

In view of the volume of resources devoted to fulfilling its well-being responsibilities and the growing demand for information by both governmental and non-governmental provincial actors, the provincial government was prompted to initiate the development of a well-being indicator framework that can meet some of the data demands. The OECD Territorial Review of the province of Córdoba (2016) emphasised that the lack of reliable and accurate statistics for policy design, monitoring and assessment was one of the main challenges faced by the province of Córdoba. The demand for data is accentuated in the province’s rural areas, where basic well-being indicators such as employment and unemployment rates, total household income, incidence of poverty and deprivation are produced using census data every 10 years.

Assisted by the OECD, the General Secretariat of Government conducted a consultation with the various ministries and agencies responsible for regional well-being policies and also with non-governmental actors to select a set of indicators for measuring the 12 dimensions of well-being. Interviews were conducted with the Secretariat of Equity and Employment Promotion, the Ministry of Social Development, Ministry of Interior, Ministry of Education, Ministry of Health, Ministry of Water, Environment and Public Services and the Municipalities of Córdoba, Rio Cuarto, Villa María and San Francisco. In addition, a workshop was conducted with the Provincial Council for Social Policies (Consejo de Políticas Sociales Provincial), which brings together organisations from the public, private, non-profit and academic sectors (Box 1.2).

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Box 1.2. Provincial Council for Social Policies

The Provincial Council for Social Policies (CPSP) is a platform designed to involve provincial actors across the public, private, non-profit and academic sectors, in designing and implementing social programmes. It is a consultative body for planning and coordinating the provincial policies in different social areas. The CPSP was established by Provincial decree 234/09, is chaired by the Minister of Social Development and is made up of civil society actors that have a commitment to and influence in provincial social policies (including representatives of NGOs, religious organisations, public and private universities, private actors, and municipalities and communes (comunas)).

It has two main objectives: first, to improve participation and coordination with civil society actors in monitoring and implementing social programmes and plans; and second, to be a body for consulting these actors on the planning and coordination of provincial policies. In line with the first objective, the CPSP started the Social Policy Observatory (Observatorio de Políticas Sociales). The Observatory is preparing a mapping of existing social programmes and their main features (goals, beneficiaries, resources, etc.). This mapping is intended to serve as a baseline for setting indicators to measure programme effectiveness and efficiency over time. As a response to the second objective, the CPSP launched “Ayudar”, a system for promoting social solidarity. This system has created a bank of social projects to be implemented by non-profit actors (NGOs) whose suitability has been validated by the CPSP. The projects will be eligible for public and private funding, since the decree establishing the “Ayudar” programme allows private sector actors (both organisations and individuals) to make donations to support project implementation.

Source: Córdoba Provincial Government (2009), Provincial Decree no. 234/09http://web2.cba.gov.ar/web/leyes.nsf/85a69a561f9ea43d03257234006a8594/ebf91cb9c0f2be5d0325793400482ac5?OpenDocument.

Demand and need for well-being data in Córdoba

The first step in designing the well-being indicator framework was to map provincial actors’ demands for data in the different phases of the policy cycle, including design, monitoring and implementation. These needs involved many of the dimensions of well-being, including education, health, housing and the environment. For policy makers in the ministries, monitoring and impact assessment of well-being programmes is perceived as a challenge and a more pressing need than the design phase. On the other hand, however, the general perception is that the DGEyC succeeds in meeting the demand for statistics in the province of Córdoba, even though the indicators are often based on estimates drawn from sources that are not very recent (e.g. the 2010 Census) but which the actors nevertheless consider sufficient, given the lack of other information.

The following sections present the main conclusions of the consultation with provincial actors.

Approximate data for policy and programme design

To design policies and programmes that effectively and efficiently meet the needs of the population, policy makers require data in a wide range of domains. These data should help estimate target population (potential beneficiaries of a programme), resources required (e.g. food resources for a nutritional programme or economic resources for a subsidy), staff needed, timeframe of the programme (whether it is a one-off or a more long-term action) or the scale at which it should be implemented (for a particular agglomeration or in a rural area).

The DGEyC has provided solutions that have enabled the various ministries and secretariats to design their programmes, although sometimes the information it provides consists of rough estimates. The DGEyC has being using approximate methods to provide target population estimates. The Ministry of Social Development’s programme “Plan Vida Digna” (Decent Life Programme), for instance, is intended to deliver economic assistance to deprived households, so that they can make improvements to their homes. Over a four-year period, up to 30 000 loans of ARS 30 000 have been made available to the provincial population under this programme. To enable the ministry to design the programme, the DGEyC used the 2010 Census to calculate the distribution of dwellings in which there were likely to be people living in overcrowded conditions or without a bathroom. Another example is the “Tarifa Solidaria” (Social Tariff) programme, which helps vulnerable households by offering subsidised tariffs for electricity and water supply. The potential beneficiaries were estimated using census data cross-checked against employment, unemployment and underemployment data. In some cases, data on one particular programme that are known to be reliable have been used to estimate the potential beneficiaries of another programme. Examples include the PAICOR programme and the “Más Leche Más Proteínas” (More milk More proteins) nutritional programme. PAICOR has been delivering services to schoolchildren for nearly 30 years and so has reliable data on the target population and how it has evolved over the years. The Más Leche programme distributes milk powder to children in schools and the eligibility requirements are very similar to those of PAICOR. The authorities therefore decided to use the register of PAICOR beneficiaries to estimate the quantities of milk needed for the Más Leche programme and thus also the programme budget.

Insufficient policy monitoring and evaluation

The main provincial actors agree that monitoring and evaluation should be implemented for all policy areas that have an impact on citizens’ well-being. Regular, continuous monitoring of outcomes is a vital prerequisite to be able to effectively modify or redesign programmes that are proving less effective than they should be or that are found to be operating inefficiently and thus wasting public resources. Programme impact evaluation is crucial to decide whether a programme should be renewed, whether the target population should be adjusted so as to obtain a better return on the investment, or whether the programme has failed to meet its objective and so should be cancelled.

An obstacle to measure provincial programme impact evaluation was the failure to quantify non-monetary income as a share of household income. The continuous household survey (EPH) does not record whether an individual receives any kind of non-monetary income from sources such as social programmes. For example, PAICOR delivers nutritional aid to children of resource-poor households and so boosts a household’s income by allowing it to save part of what would otherwise be spent on feeding the child. As explained in the next section of this document, the 2017 Living Conditions Monitoring Survey (Encuesta de Monitoreo de Condiciones de Vida, MCV) included an exercise aimed at quantifying the value of non-monetary programmes, which has been repeated in 2018 within the framework of the regional well-being survey.

Few impact evaluations have been carried out at provincial level. In 2012, CAF (Corporación Andina de Fomento, CAF), jointly with the provincial government, carried out an impact assessment of the ninth edition of the “Programa Primer Paso” (First Step Programme). The First Step Programme is a provincial programme aimed at providing apprenticeships for young people aged 18 to 25. The results of the assessment led to numerous conclusions, which served to better understand the programme’s effectiveness in combating informality. Some 60% of young people in the province between the ages of 16 and 25 are in informal employment. However, one year after completing the First Step Programme the proportion of beneficiaries registered as “formal workers” was 40% higher than that of non-beneficiaries. Another example is the former national education scheme, ONE (Operativo Nacional de Educación), now renamed to national learning scheme, ONA (Operativo Nacional Aprender), carried out by the national Ministry of Education. Although ONA is not an impact assessment for any specific programme, it allows, based on the assessment of student performance in each province in subjects such as mathematics and languages, to draw conclusions about education policies and their effects on the quality of education. One of the main challenges regarding the data from the former ONE scheme, however, was the delay of almost two years in becoming available to the provinces. With the new ONA, data gathering has improved and is now carried out in November, so that data are available by the following May.

Asymmetry of data availability in the province’s urban and rural areas

Provincial urban and rural areas are subject to a data and information asymmetry, with the more remote areas suffering a greater shortage of data for assessing regional well-being. According to the 2010 Census, 70% of the province’s population lives in six departments (Capital, Punilla, Colón, Río Cuarto, San Justo and General San Martín) and the remaining 30%, in the other 20 departments. Those six departments contain the bulk of the province’s urban population, while most of the population of the other 20 departments is located in rural areas. Basic indicators for assessing well-being, such as the employment and unemployment rate, long-term unemployment, employees working long hours, total household income and incidence of poverty and deprivation, are only calculated with any regularity for urban areas, whereas in rural areas the only data available are those provided by the 2010 Census.

Design of the 2018 Well-being Survey

To meet data demand in the province of Córdoba, even if only partially, the provincial government decided to launch a statistical programme through a well-being survey. The survey was largely based on the 2017 living conditions monitoring survey (MCV 2017) carried out in Gran Córdoba. The MCV 2017 survey was designed using INDEC’s household survey’s (EPH) indicators for employment conditions, monetary income, education and housing. One of the main objectives of MCV 2017 was to shed light on people’s material living conditions in Gran Córdoba and quantify the impact on poor and deprived households of the provincial government’s non-monetary programmes. Among the non-monetary social plans considered were PAICOR, “Más leche Más proteínas”, “Alimentos para Celíacos” (Food for celiac patients), the subsidised electricity and water rates (“Tarifas Sociales”) and the real estate tax (rents), among others.

The 2018 Well-being Survey expanded both the geographic coverage and the issues covered by MCV 2017, in an attempt to align itself with the OECD’s regional well-being framework.

The Well-being Survey broadened the geographic coverage to include the province of Córdoba’s four main agglomerations: Gran Córdoba, Gran Río Cuarto (Río Cuarto-Las Higueras), Villa María-Villa Nueva and San Francisco. The 2018 survey thus covers around 2 million people (55% of the province’s population), according to 2010 Census data. Gran Córdoba accounts for nearly 96% of the population that resides in the two departments it covers (Capital and Colón), Río Cuarto-Las Higueras for 67% of Río Cuarto department, Villa María-Villa Nueva for 78% of General San Martín department, and San Francisco for 30% of San Justo department (Table 1.6).

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Table 1.6. Territorial characteristics of the Córdoba agglomerations

Agglomeration

Departments in which located

Area of the agglomeration (km²)

% of the departments’ area

% of the province’s area

2010 population of the agglomerations (persons)

% of the departments’ population

% of the province’s population

Gran Córdoba

Capital and Colón

532.86

18.29

0.32

1 490 629

95.88

45.05

Río Cuarto-Las Higueras

Río Cuarto

69.88

0.38

0.04

164 500

66.76

4.97

Villa María-Villa Nueva

General San Martín

42.68

0.86

0.03

99 308

77.92

3.00

San Francisco

San Justo

37.60

0.24

0.02

62 211

30.15

1.88

Córdoba agglomerations

683.02

1.62

0.41

1 816 648

85.09

54.90

Note: The municipalities included in each of the four agglomerations are as follows. Gran Córdoba: Agua de Oro, Rio Ceballos, El Manzano, Córdoba, Parque Norte, La Calera, La Granja, Malvinas Argentinas, Mendiolaza, Estación, Juárez Celman, Río Ceballos, Saldán, Salsipuedes and Unquillo. Río Cuarto-Las Higueras. Villa María agglomeration: Villa María and Villa Nueva. San Francisco agglomeration: San Francisco.

Source: INDEC (2010), National Census on Population, Households, and Housing, https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-135.

The Statistics and Demography Institute at the Economics Faculty of the Universidad Nacional de Córdoba (National University of Córdoba) assisted the DGEyC with the design of the sample selection and survey estimation weights. The survey was carried out by the DGEyC, while Universidad Nacional de Córdoba supervised the quality of the data gathering process.

The Well-being Survey also broadens the subjects covered by MCV 2017 to include other dimensions of well-being. The well-being dimensions to be included in the Well-being Survey and those that will be assessed through a different survey or using other sources of information, were decided based on the provincial government’s priorities and on the interviews conducted during the OECD’s visit (14-17 November 2017) with the various ministries, municipalities and social sectors.

The new questions added to the questionnaire make it possible to calculate indicators for the following well-being dimensions:

  • Work-life balance: this dimension has been strengthened, given that with the MCV 2017 it was only possible to estimate the percentage of employees working long hours. With the new Well-being Survey it is possible to know in what municipality the respondent lives and works, travel time to the place of work and the type of transport used.

  • Health: this new dimension has been added to assess citizens’ perception of their own health status.

  • Civic engagement and governance: a section has been added to assess the level of participation in civic and volunteering activities.

  • Access to services: households’ access to internet is measured.

  • Community and social support: serves to assess people’s perceived social support network. Specifically, the survey assesses whether people have someone they can rely on when needed.

  • Life satisfaction: citizens’ perceived level of life satisfaction.

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Figure 1.5. Location of the Córdoba agglomerations with respect to the province
Figure 1.5. Location of the Córdoba agglomerations with respect to the province

Source: OECD based on INDEC (2010), National Census on Population, Households, and Housing, https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-135.

The OECD uses various data sources when assessing well-being in a particular country or region. That is because the data needed to calculate OECD’s well-being indicators do not all come from the same sources. Whereas a household survey can measure material living conditions, administrative records are required to estimate mortality and homicide rates, specialised examinations to measure cognitive skills or satellite images to calculate air pollution. On the other hand, regardless of whether a single survey might be sufficient to cover a large number of topics, it was considered important to limit the length of the survey and ensure consistency - an overlong, muddled survey could compromise the quality of the information obtained. For these reasons, any well-being dimensions and indicators that could not be assessed through the Well-being Survey were covered using other data sources.

Indicators for health, civic engagement and governance, environment and personal security that were not included in the Well-being Survey have been calculated using alternative sources:

  • Infant mortality rates and life expectancy at birth are calculated using administrative records of vital events (e.g. births and deaths), as most of such records are generated at the municipal level.

  • For the civic engagement and governance dimension, the voter turnout indicator can be obtained of the most recent elections, which are disaggregated by municipality.

  • The air pollution indicator (annual population exposure to PM2.5 fine particles) will be calculated using the OECD’s methodology (available only at the level of the province and the departments).

  • For the personal security dimension, it was decided to use official records to calculate the homicide rate (which is available for the province as a whole but also for the agglomerations).

copy the linklink copied!Conclusion

Regional well-being frameworks arise to meet the need of subnational governments to design and implement public policies that consider the economic and social realities of the place where citizens live and work. There is a wide consensus that macroeconomic statistics on their own do not accurately reflect well-being and that a multidimensional approach is required to encompass different aspects that affect people’s lives. Many of the factors that have an impact on people’s well-being differ from one community to another, including key dimensions such as jobs, education, environmental quality and public safety.

Because of Argentina’s federal structure, the province of Córdoba and its municipalities have major responsibilities in many of the policies that have a very direct impact on people’s well-being. Accordingly, the bulk of provincial government spending in the province of Córdoba goes to fulfilling responsibilities with respect to areas of well-being. Some 48% of expenditure in the 2018 budget went to social services, including health, social promotion and care, education and culture, science and technology, work, housing and land-use planning. Some policy areas are the exclusive responsibility of the municipalities, including sewers, solid waste, primary hospital care, urban development and regulation.

The province decided to design a regional well-being framework tailored to its needs and territorial characteristics, and aligned with the OECD regional well-being framework. To that end, assisted by the OECD, the General Secretariat of Government conducted a consultation with the various ministries, secretariats and agencies responsible for regional well-being policies to select a set of outcome indicators to measure 12 dimensions of well-being. It also consulted non-governmental actors through the Provincial Council for Social Policies (CPSP).

The 2018 Well-being Survey is the vehicle through which the province of Córdoba seeks to meet data demands for assessing multidimensional well-being. The Well-being Survey is an exclusive initiative of the province of Córdoba, which in combination with other data sources serves to calculate more than 30 well-being indicators in the four main agglomerations: Gran Córdoba, Río Cuarto-Las Higueras, Villa María-Villa Nueva and San Francisco.

References

Australian Bureau of Statistics (2011), Socio-Economic Indexes for Areas (SEIFA), Australian Bureau of Statistics, Canberra.

Córdoba Provincial Government (2018), Presupuestos [Budget], http://www.cba.gov.ar/presupuestos/ (accessed on 26 August 2018).

Córdoba Provincial Government (2009), Provincial Decree no. 234/09, CPSP, http://web2.cba.gov.ar/web/leyes.nsf/85a69a561f9ea43d03257234006a8594/ebf91cb9c0f2be5d0325793400482ac5?OpenDocument.

Córdoba Provincial Government (1972), LEY Nº 5454: Dirección de Informática, Estadística y Censos [Law no. 5454: Directorate for Informatics, Statistics, and Census] http://web2.cba.gov.ar/web/leyes.nsf/0/119566D80654E95603257234006305CC?OpenDocument&Highlight=0,5454,censos.

Government of Argentina (1968), Ley 17622: Créase el Instituto Nacional de Estadísticas y Censos [Law no. 17622: Establishment of National Statistics and Census Institute], https://www.argentina.gob.ar/normativa/nacional/ley-17622-24962.

INDEC (2010), National Census on Population, Households, and Housing, https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-135.

Kim, J. and C. Vammalle (eds.) (2012), Institutional and Financial Relations across Levels of Government, OECD Fiscal Federalism Studies, OECD Publishing, Paris,https://doi.org/10.1787/9789264167001-en.

OECD (2018), Subnational Governments in OECD Countries: Key Data (brochure), http://www.oecd.org/regional/regional-policy.

OECD (2016a), OECD Regional Outlook 2016: Productive Regions for Inclusive Societies, OECD Publishing, https://doi.org/10.1787/9789264260245-en.

OECD (2016b), OECD Territorial Reviews: Córdoba, Argentina, OECD Territorial Reviews, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264262201-en.

OECD (2014), How’s Life in Your Region?: Measuring Regional and Local Well-being for Policy Making, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264217416-en.

Note

← 1. Some OECD reports use more than 391 regions, this is due to the request of some countries to include also their small regions (TL3: second sub-national division, e.g., departments) in the analysis.

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Chapter 1. Why measure well-being in Cordoba?