Chapter 3. Social inclusion in Panama

Strong and sustained economic growth over the past 15 years has translated into significant improvements in well-being outcomes. Although economic growth lifted a significant share of the population out of poverty and created jobs, Panama still faces structural challenges preventing the emergence of a consolidated middle class and equity across territories. This chapter discusses the main bottlenecks affecting inclusive growth and well-being. It begins with an overview of income patterns in the past decade and then examines the main drivers of inequality. It looks in particular at the role of income redistribution, differences across regions, urban planning, education and skills, and job quality. Assessing these drivers is key to improve the lives of all Panamanians, especially the most vulnerable.


Pro-growth policies typically focus on actions for improving a population’s income and consumption potential. However, it is equally important to assess non-monetary dimensions that matter for well-being and to monitor the impact of economic trends and policies on different social groups. Employment prospects, job satisfaction and educational opportunities matter both for individuals’ life satisfaction and for cohesion across society.

Panama’s recent economic growth has considerably improved the living standards of most Panamanians, including those among the poorer parts of the population. Nonetheless, while absolute income poverty rates have fallen considerably in the last decade in Panama, relative poverty understood as social inclusion has improved little. While economic growth has been able to lift the income of a substantial share of the population, the improvements in living standards have not benefited all groups equally and income inequality remains high in Panama.

Policy makers have a range of instruments to promote opportunities among specific groups while promoting economy-wide growth. Together with policies that promote good-quality employment, skills and education, and women’s economic participation, efficient tax-and-transfer systems constitute the most direct and powerful instrument to achieve greater equity.

This chapter examines the challenges facing efforts to boost social inclusion in Panama. The first section summarises the main poverty and inequality achievements of the past decades and identifies challenges on the horizon. The second examines the level of social spending and the effects of taxes and transfers on income distribution and poverty alleviation. The third describes territorial differences in inequality, well-being, service provision and poverty. The fourth analyses Panama’s labour markets and the fifth identifies the main constraints on expanding and improving education services. The chapter concludes with the main messages resulting from this assessment.

Inequality and poverty are declining but remain very high

Panama’s recent period of economic growth has considerably improved the living standards of most Panamanians including the poorer parts of the population. Nonetheless, Panama remains a very unequal country. It has the third highest levels of inequality, behind Costa Rica and Colombia, as well as income inequality levels higher than any OECD country and most of the Latin American countries assessed in the study.

Poverty is declining but exclusion remains high

Absolute income poverty rates have fallen considerably in the last decade. Estimates produced by the World Bank suggest that the incidence of poverty in Panama (measured as the share of people living on less than USD 3.10 per day) halved over the last ten years to a level of 8% in 2014. Over the same period, the proportion of people living in extreme poverty (defined as those living on less than USD 1.90 per day) decreased by two-thirds to 3% of the population (Figure 3.1, Panel A). Using other thresholds, national sources show similar trends (Figure 3.1, Panel B). Following the World Bank approach for Latin America and the Caribbean (LAC), poverty in Panama fell and the middle class increased (defined as living on USD 10 to USD 50 per day); while vulnerability was more stable (Figure 3.1, Panel C).

Figure 3.1. Trends in poverty and income distribution

Note: Definitions of poverty, vulnerable and middle class are in Box 3.1.

Source: Panel A: Estimates for relative poverty are based on country micro-data as available through CEDLAS (see Box 3.1 for further details) and World Bank (2017), World Bank Development Indicators; Panel B: Ministry of Economy and Finance of Panama. Panel C: CEDLAS and the World Bank: LAC Equity Lab tabulations.

Nevertheless extreme poverty is high when compared to benchmark economies. Panama has the second highest rate of extreme poverty within the group of benchmark economies for which data are available (Figure 3.2, Panel A).

Figure 3.2. Poverty levels in Panama compared to selected countries (percentage)

Note: Panel A: Latest year is 2013 for Chile and the Dominican Republic and 2014 for others. Panel B: Latest year is 2015 for Costa Rica; 2013 for Belgium, Chile and Portugal; 2012 for New Zealand; 2011 for Colombia; and 2014 otherwise.

Sources: Panel A: World Bank Development Indicators. Panel B: OECD Income Distribution Database for OECD countries; estimates for the Dominican Republic, Ecuador, Panama, Peru and Uruguay are based on country micro-data available from CEDLAS.

Results on poverty, however, are less impressive according to the OECD relative poverty measure, which considers individuals living on 50% of the median household income or less. Between 2000 and 2014, relative income poverty in Panama decreased only by around 2 percentage points, to 23.5% from 25.8% (Figure 3.1, Panel A). As a consequence, relative income poverty in Panama is higher than in any benchmark economy (Figure 3.2, Panel B). While indicators of relative income poverty are defined in relation to a country’s general level of prosperity at a given point in time, absolute poverty measures are based on the population’s ability to afford a given bundle of goods and services (Atkinson et al., 2002). See Box 3.1 for an explanation of the internationally comparable poverty indicators used for Panama.

Box 3.1. Internationally comparable poverty indicators used for Panama

Three different poverty indicators are used: extreme income poverty rate, income poverty rate and relative poverty line.

  • The extreme income poverty rate is defined as the share of the population living on less than USD 1.90 a day at the 2011 purchasing power parity (PPP). The World Bank has used this poverty line since 2015 and it is further defined as the mean of the national poverty lines in the poorest 15 countries. This global poverty line is meant to provide an accurate picture of the costs of basic food, clothing and shelter needs around the world.

  • The income poverty rate is defined as the share of the population living on less than USD 3.10 a day at 2011 international prices. As most countries in Latin America and the Caribbean (LAC) have low rates of poverty using international thresholds, and given the level of economic development in the region, it is important also to use higher thresholds to describe the distribution of income. These are USD 4 a day for overall poverty, USD 10 a day for vulnerability and USD 50 a day for the middle class. Poverty lines and incomes are expressed in 2005 USD PPP per day. LAC countries are Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Peru, Paraguay and Uruguay.

  • The relative poverty line is defined as 50% of the median household disposable income.

Both the World Bank and the OECD estimates are computed using the Encuesta de Mercado Laboral (INEC). However, there are a number of methodological differences between the approaches of the OECD and the World Bank. World Bank estimates are based on per capita income including implicit rent from house ownership. OECD estimates are based on equivalised income excluding imputed rent. Details about the OECD income Distribution Database methods and definitions are available at

The OECD Income Distribution Database estimates for Panama were computed for the 2015-16 OECD project, “Monitoring Inequalities and Fostering Inclusive Growth in Emerging Economies”. These estimates are based on micro-data from the main household surveys for Argentina, Bolivia, Dominican Republic, Ecuador, Panama, Paraguay, Peru and Uruguay, as available through the Centre for Distributive, Labour and Social Issues in Latin America (CEDLAS) Universidad Nacional de La Plata, Argentina. They are also based on the same definitions and methodologies used to generate estimates for OECD countries, as available through the OECD Income Distribution Database (OECD, 2016a). However, owing to differences in survey methodologies and questionnaires’ design (e.g. in terms of the recording of taxes paid and transfers received and paid by households), estimates for these Latin American countries are not fully comparable to those available for OECD countries.

However, poverty goes well beyond income. It is a question not only of monetary resources, but also of a complex range of deprivations in areas such as work, health, nutrition, education, services, housing and assets, among others. This view of poverty as multidimensional is today widely supported by poor communities as well as governments and development agencies. The Panamanian authorities (under the co-ordination of the Ministry of Social Development) together with the Oxford Poverty and Human Development Initiative (OPHI) are developing a multidimensional measure of poverty that should be available from mid-2017.

Almost one out of in five Panamanian live in multidimensional poverty households, according to the country’s first Multi-dimensional Poverty Index (OPHI, 2017). This index is comprised of seventeen indicators or deprivations spread over five dimensions: education; housing, basic services and internet access; environment, neighbourhood and sanitation; employment; and health1 . A household is considered to be in multidimensional poverty if it is deprived in five or more of the indicators. Ngäbe Bugle region is the one with the largest share of poor people with 93.4% of people are multidimensional poor, followed by the Guna Yala region (91.4%), Emberá Wounaan (70.8%), Bocas del Toro (44.6%) and Darién (40%). Coclé (22.6%) and Veraguas (19.1%) are on par with the national level. In contrast, in Colón (16.4%), West Panama (15.6%), Chiriquí (12.4%), Panama City (8.5%), Herrera (8.5%) and Los Santos Province (4.2%) the share of the population in multidimensional poverty is smaller than the national level (Gobierno de la República de Panamá, 2017).

High but slowly declining income inequality

Income inequality in Panama is high but declining slowly (Figure 3.3). Based on the OECD Income Distribution Database definitions, the Gini index was 50.7 in 2014. This level is much higher than most of the benchmark economies and significantly above the OECD average. In the past two decades, income inequality in Panama has been falling. According to CEDLAS data, the Gini index of income inequality fell on average by half a point every year to 48 in 2014 from 55 in 2000. This rate of decrease was around the midline for Latin American countries as inequality fell at a slower rate in 9 of the 18 LAC countries (Tsounta and Osueke, 2014). However, this decrease slowed down between 2007 and 2014.

Figure 3.3. Income inequality levels in Panama and benchmark economies (Gini index)

Note: The notation 2014 or latest refers to: 2015 for Costa Rica; 2013 for Belgium, Chile and Portugal; 2012 for New Zealand; 2011 for Colombia; and 2014 otherwise. The notation 2007 refers to: 2010 for Costa Rica; 2008 for Australia, Colombia and New Zealand; and 2006 for Chile.

Source: OECD Income Distribution Database for OECD countries, Estimates for Dominican Republic, Ecuador, Panama, Peru and Uruguay are based on country micro-data as available through CEDLAS (Box 3.1 for further details).

This moderate decline of income inequality partly explains the gap between the trends of absolute and relative measures. Indeed, poverty reduction can be explained by disentangling the effects of growth and income distribution. For example, poverty can be declining either as a result of growth – in which case relative poverty would remain stable while absolute poverty decreased – or changes in the distribution of income. Growth benefited all income groups in absolute terms (Figure 3.4). Even though growth has been slightly higher for those in the middle of the distribution, the heterogeneity of growth across income groups is rather low. Using the Datt-Ravallion Decomposition Analysis,2 the Economic Commission for Latin America and the Caribbean (ECLAC) reaches a similar conclusion: the reduction in poverty in Panama was mainly driven by a growth effect (explaining up to 83% of the change between 2010 and 2014) while the reduction of inequality over time had a much lower effect during the period (ECLAC, 2016a; World Bank, 2015a). This differs from the rest of Latin America, where the drivers of poverty reduction were more balanced. Indeed, over the Latin America subcontinent during the same 2010-14 period, growth would have accounted for slightly less than 60% of poverty reduction while the changes of income distribution would have explained more than 40% (World Bank, 2015a).

Figure 3.4. Growth incidence curve (average annual growth 2007–2014), total population (percentage)

Source: Estimates are based on country micro-data available at CELDAS (Box 3.1 for further details).

Social expenditure is low and redistribution could be more efficient

Panama faces the challenge of increasing the effectiveness of both social spending and public resources to promote inclusiveness. On the expenditure side, higher levels of social spending, in particular on social protection programmes, is fundamental to increase inclusiveness. As is the case for other Latin American economies, improvements in the effectiveness of the taxation and transfer systems to reduce income inequalities are fundamental.

Social expenditure is low and increasing slowly

Social expenditure in Panama is considerably below what is spent on average in the benchmark economies (see Box 3.2 on definition of social expenditure used in this chapter). In 2013, public and mandatory private social expenditures were slightly below 600 USD per capita, while the benchmark average is 3 500 USD per capita (Figure 3.5); only the Dominican Republic and Peru spent less per inhabitant among the group of benchmark economies. For example, Panama had the second highest per capita public spending (below Costa Rica) but among the lowest in Latin America and the Caribbean region (Acosta et al., 2015).

Box 3.2. What do we talk about when we talk about social expenditure?

The United Nations Economic Commission for Latin America and the Caribbean (UN ECLAC) – the source used for Panama and the other Latin American benchmark economies besides Chile (which is an OECD member) – follows a different classification of social expenditures than the OECD Social Expenditure Database (SOCX). ECLAC divides public social spending into the following categories: social security (including programmes for old age, survivors, incapacity, family, active labour market programmes, unemployment and other social policy areas such as social insurance), education, health and housing. However, in order to be as comparable as possible, spending on education is not in the scope of the current analysis but will be discussed later in the chapter.

Figure 3.5. Social expenditure in Panama and benchmark economies, latest year, per capita

Note: Latest year refers to 2015 for Chile; 2013 for Panama, Colombia, Netherlands, Portugal and Belgium; 2012 for Peru; and 2011 for the Dominican Republic and Uruguay.

Sources: OECD (2016b), Social Expenditure Database, for OECD countries; and ECLAC (2016b), CEPALSTAT Statistics and Indicators, Per capita social public expenditure by sector, for Latin American countries except Chile.

While spending on housing is relatively high, social protection expenditure remains low. Social spending on housing accounts for almost USD 300 per capita, half of total social spending and higher than in any other country of the benchmarking group. Expenditure on social security only amounts to USD 124 per capita. The very low amounts going to social protection expenditure put Panama at the bottom ranks of benchmark economies. Health-care expenditure reaches USD 171 per capita, which is also relatively low and around half the average level of expenditure in Latin America.

Social spending in Panama is higher than it was 25 years ago and has remained stable, below USD 600 per capita, since 2010 (Figure 3.6). In the 1990s, growth in social spending was mainly driven by health spending; social security spending was volatile; and spending on housing was flat and negligible (from USD 10 to USD 20 per capita). In the 2000s, housing spending jumped to USD 70 per capita and steadily increased since then to close to USD 300 per capita since 2010 (housing is discussed in more in detail below) In contrast, social security and health expenditure levels have been more stable over the same period.

Figure 3.6. Social expenditure trends in Panama, USD constant 2010 prices (per capita)

Note: In June 2017, the ECLAC revised its methodology to allow monitoring the volume of resources spent on policies related to six functions: social protection; education; health; housing and community services; recreation, culture and religion; and environmental protection. However, for the sake of comparability, the present analysis is using 2016 data disaggregated into four functions: social protection; education; health; housing and community services.

Source: ECLAC (2016b), CEPALSTAT Statistics and Indicators, Per capita social public expenditure by sector,

Social assistance comprises four distinct programmes: Red de Oportunidades (2006), a conditional cash transfer; 120 a los 65 (2014) to support the elderly; Beca Universal (2010), a cash transfer for households with children to encourage school attendance; and Angel Guardian (2012), a programme targeting poor or vulnerable people with disabilities. Red de Oportunidades is the only programme that has been formally evaluated. Arráiz and Rozo (2011) found that this programme increased school enrolment and was able to reduce child labour in both indigenous and rural non-indigenous areas, but found no evidence of impact on the numbers of visits to health-care providers or the number of vaccines that children received. The effects of the universal scholarship and the non-contributory pension programmes have not been evaluated. Despite the impact of public transfers on poverty, challenges related to targeting and take-up of programmes remain (World Bank, 2015b). For example, 18% of the people who make up the poorest 20% of the population receive no social assistance of any sort, while slightly more than 30% of the spending on social programmes goes to the wealthiest 60% of the population.

The housing sector is a major policy priority for Panamanian authorities and construction has also been a main driver of economic growth (see Chapter 2). The current administration has set a goal of providing 100 000 housing solutions through public construction and refurbishment. The state also provides a USD 10 000 means-tested grant for households purchasing a new home, which has helped sustain construction of housing for low-income households. However, existing programmes are not implemented on the basis of a needs assessment. Nor do they necessarily account for their increasing impact on the construction sector; in 2010, 39% of new housing built was covered by a state programme (INEC, 2015). Moreover, the ongoing decentralisation in zoning and titling and the overlapping responsibilities for extending sanitation require significant co-ordination efforts.

Assessing the impact of taxes and transfers, the Commitment to Equity (CEQ)

The Commitment to Equity (CEQ) Institute analysis suggests that taxes and transfers play a small role in shaping the income distribution in Panama. Income inequality and poverty would be slightly higher without redistribution through taxes and transfers. The CEQ analysis suggests that under the scenario where pensions are considered differed market income, direct and indirect taxes and transfers reduce the Gini index by less than 3 percentage points (Figure 3.7). This reduction is lower than those of other Latin American countries, especially compared to countries with similar levels of per capita income such as Argentina, Chile, Costa Rica and Uruguay (Lustig, 2017).

Figure 3.7. Panama’s fiscal incidence analysis
Reduction of poverty and inequality explained by taxes and transfers, percentage points

Note: Consumable income includes social security contributions, direct taxes, direct transfers and subsidies but does not include indirect taxes.

Source: OECD based on national household survey, INEC (2016).

Most of the impact on inequality is explained by transfers rather than taxes. Indeed, around 60% of the Gini reduction can be attributed to direct transfers. Additionally, the fiscal incidence analysis on poverty measures shows an even higher effect of direct transfers, explaining most of the poverty reduction efforts.

The CEQ Institute analysis had been designed to assess the distributional impact of a country’s taxes and transfers. Essentially, this fiscal incidence analysis allocates taxes (personal income taxes and consumption taxes) and public spending (social spending) to households or individuals so their impact on the distribution of income can be compared. Transfers include both cash transfers and in-kind benefits such as publicly provided government services in education and health care. Transfers may also include consumption subsidies such as those for food, electricity and fuel. This analysis will be further developed in the second volume of the Multi-dimensional Country Review of Panama (In-depth Analysis and Recommendations) but provisional results are presented in this chapter.

Territorial inequalities challenge inclusive growth

The improvement in living standards and the reduction of poverty levels have not benefited all groups equally. Indeed, access to public infrastructure and services differs substantially across regions, contributing to large discrepancies in the well-being of the population. A great divergence exists between the urban and rural areas in various dimensions such as income, education, health, housing and sanitation, and between those areas with high concentrations of indigenous populations versus the rest of the country.

Well-being indicators differ considerably across regions

Improvements in living standards and the reduction of inequality and poverty levels over the past decade have not benefitted all groups equally. Access to public infrastructure and services differ substantially across regions, contributing to large discrepancies in the well-being of the population. As discussed in Chapter 2, high discrepancies are also present in terms of productivity across provinces. A great divergence exists between urban and rural areas in various dimensions such as income, education, housing and sanitation, health and education, and also between those areas with high concentrations of indigenous populations versus the rest of the country.

Panama is divided into ten provinces and three semi-autonomous indigenous regions organised by ethnic group (known as the Comarcas). The three provinces along the Canal (Panamá, Panamá Oeste3 and Colón) account for almost 60% of the total population (INEC, 2010). These are also mostly urban while the provinces along the borders (Bocas del Toro and Chiriquí at the border with Costa Rica, and Darién at the border with Colombia) are mainly rural (Figure 3.8). The 2010 census found that only three-quarters of Panamanians who were born in the Comarcas regions are still living in a Comarca; the others live mainly in Bocas del Toro (7%), the province of Panamá (6%), and to a lesser extent Panamá Oeste (4%) and Chiriquí (4%).

Figure 3.8. Share of urban population by provinces and Comarcas (percentage)

Source: INEC (2010), Distribución Territorial y Migración Interna en Panamá: Censo 2010,

There is also great divergence in terms of well-being outcomes between the Comarcas regions and the rest of the country. Despite lower levels of unemployment, people living in the Comarcas are much more likely to live in poverty and to report lower levels of satisfaction about their living conditions. They are also at greater risk of having an informal job or not having access to drinkable water in their dwelling. However, low outcomes regarding material and living conditions do not stop at the borders of the Comarcas. Bocas del Toro, where according to the 2010 census 63% of the population is of indigenous origin, reports comparable outcomes, as does Darién, where indigenous people account for 30% of the population (Figure 3.9).

Figure 3.9. Material and living conditions by regions – Z-scores

Note: This analysis looks at the original province of Panamá, although Panamá and Panamá Oeste recently split. Z-score or standard score stands for the signed number of standard deviations by which the regional outcome is above or below the national average. This normalisation enables an assessment of how much a region’s performance is deviating from that average.

Source: INEC (2016) and Gallup (2016) Gallup World Poll,

In addition to sanitation, access to basic services is a key area where large differences between indigenous areas and the rest of the country are observed. Panama has the lowest level of electricity coverage among the indigenous population and the largest gap between indigenous and non-indigenous coverage in the region (World Bank, 2015a). Similar inequalities are observed for piped water and Internet access.

The divergence between indigenous areas and the rest of the country is not so clear cut for quality of life dimensions as it is for indicators of material and living conditions. However, the Comarcas, Bocas del Toro and Darién still significantly underperform in at least two dimensions across education, health, life satisfaction and, to a lesser extent, social connections (Figure 3.10). People living in Los Santos also report lower well-being outcomes. However the structure of Los Santos’ population is different from that in those four areas, with almost no people of indigenous origin (less than 1%). The dimensions in which they report being are also different (environment, social connections and life satisfaction).

Figure 3.10. Quality of life by regions – Standardised scores

Note: This analysis looks at the original province of Panamá, although Panamá and Panamá Oeste recently split. Z-score or standard score stands for the signed number of standard deviations by which the regional outcome is above or below the national average. This normalisation enables an assessment of how much a region’s performance is deviating from that average.

Source: INEC (2016) and Gallup (2016), Gallup World Poll,

Greater and well-targeted investments in basic infrastructure would definitely benefit the Comarcas, where the population suffers from multiple deprivations from lower incomes, to lower access to services or poorer outcomes in health or education hindering their overall level of life satisfaction. The same is true for other rural areas such as Darién, Bocas del Toro or Los Santos. However, ensuring that such investments improve the well-being of all groups requires that proper attention be paid to the cultural norms and habits of the distinct ethnic groups that make up Panamanian society, to ensure that they lead to progress in the eyes of indigenous peoples and that investments are compatible with the degree of self-rule granted to Comarcas by law.

Urban planning and organisation are pressing challenges in Panama

Panama has experienced a constant and high rate of population growth in the past decades, in particular at the urban level. The 1950 census reported around 800 000 inhabitants in Panama. By 2010 the population had grown to nearly 3.5 million (Figure 3.11). The World Urbanization Prospects report (UN, 2014) estimates that the population will reach 6 million by 2050. The large migration outflows from rural areas, mainly toward urban centres near the Canal (primarily to Ciudad de Panamá), coupled with a process of demographic transition have led to dramatic changes for the Panamanian population structure and size. Over the same period, the urban population grew by 3.5% per year while rural areas grew by 1.4%; a more granular approach even shows a slight decrease in the rural population during the 1990s. This rapid growth of cities in Panama creates challenges for citizens’ well-being and will require innovative policies to ensure equal quality of public services for all citizens. In that context, a better linkage between urban and rural development policies is needed to avoid pressure on cities and improve well-being in Panama.

Figure 3.11. Population of urban and rural areas (thousands)

Sources: INEC (2010) and UN (2014), World Urbanization Prospects.

This rapid urban growth has resulted in disorderly sprawl. According to UN Habitat, Panama is the only one of the benchmark economies (for which data are available) where the share of the urban population living in slums increased, to 25.8% in 2014 from 23% in 2005 (UN, 2015) (Figure 3.12). More worryingly, it is estimated that 41% of the dwellings in the Panamá Metropolitan Area were constructed informally (Espino and Gordón, 2015). In addition, the Ministry of Housing estimates that there are between 300 and 415 informal settlements in the country, including at least 25 that are on private land.

Figure 3.12. Population living in slums (percentage of urban population)

Source: UN Habitat data from UN (2015), Millennium Development Goals Indicators (database),

Rapid urban growth not only creates slums but also more challenges in the extension of public services. In Panama, access to drinkable water in urban areas is almost universal, and in rural areas access has progressed to 89% in 2015 from 76% in 2000. However, improvements in sanitation have been much slower. Access to improved sanitation increased to 75% from 59% between 2000 and 2015, which means Panama is at the bottom of the benchmark economies, just after Peru, at both rural and urban levels (Figure 3.13). Access to improved sanitation barely reaches 85% in urban areas, although data from INEC show that connections to piped sewer systems have levelled off at around 45%. A notable government response is the 100/0 programme, which aims to universalise access to improved drinking water and improved sanitation through the construction of bathrooms to replace latrines.

Figure 3.13. Population with access to improved sanitation in urban and rural areas (percentage)

Source: WHO/UNICEF (2015), Joint Monitoring Programme (JMP) for Water Supply and Sanitation (database),

Lack of quality jobs hinder equity

The gaps in labour market performance across different regions and socio-economic groups are large. Labour is one of the most important assets of the poor and vulnerable, and helping them get engaged in productive activities also helps reduce poverty. Growth is translated into higher incomes and greater well-being through productive employment, improvements to real wages, and the coverage and characteristics of workers’ social protection (ECLAC, 2016a); while 61% of the decline in poverty in Latin America and the Caribbean (LAC) in the past decade can be attributed to higher labour incomes, with more people working and workers earning more (World Bank, 2013).

Growth has translated into more jobs

Strong growth and macroeconomic conditions have benefitted job creation in Panama. The recent labour market performance has been remarkable and the country enjoys one of the lowest unemployment rates among Latin American countries. The employment rate has increased almost 5% since 2005 as a result of strengthening labour demand and the subsequent rise in the number of new salaried jobs created (ECLAC/ILO, 2016). Yet Panama’s strong period of rising employment creation, which began in 2005 in a scenario of high growth rates, has started to slow down (Figure 3.14). Moreover, Panama ranks relatively well in terms of labour market efficiency, at 67th out of 138 countries in labour market rankings (World Economic Forum, 2017).

Figure 3.14. Labour participation and employment in Panama

Source: INEC (2016) and ILO (2016).

This rise in employment creation is also reflected in significantly lower unemployment. Panama’s unemployment rate fell to 5.8% in 2015 from 12.1% in 2005. Likewise, the length of unemployment fell drastically to two months in 2013 from almost 15 months in 1991 (Figure 3.15).

Figure 3.15. Unemployment rate in Panama

Source: CEDLAS and the World Bank (2016), SEDLAC (Socio-economic Database for Latin America and the Caribbean) (database),

The improvement in labour market outcomes has especially benefitted women and youth, yet inequalities persist (Figure 3.15). In terms of unemployment, women benefitted the most, with their unemployment falling to 6.7% in 2015 from 15% in 2005 (ECLAC/ILO, 2016). Still, a 3% gap between women and men has remained consistently high over the last decade. Similarly, unemployment levels by age group have decreased since 2007 although youth unemployment (for 15-24 year-olds) remains quite high at close to 11%. Panama’s youth unemployment rates in 2014 (9.5% for 15-29 years-olds) are comparable to the average in the LAC region (10.3%) (OECD/CAF/ECLAC, 2016).

The perception of job insecurity is low in Panama. The percentage of workers who report being very concerned that they will be left without work in the next 12 months is among the smallest in the region and has been declining over time (Figure 3.16). The fear of job loss in Panama fell 8 percentage points since 2004. Only 12% of Panamanian workers in 2015 feared they could be left without work. This reflects the country’s relatively low job-loss rate and high job-finding rates. In other Latin American countries the share of workers reporting subjective job insecurity in 2015 was 28% in Mexico, 27% in Venezuela, 25% in Colombia, and 20% in Ecuador, Honduras, and Nicaragua – all levels considerably higher than in Panama.

Figure 3.16. Subjective job insecurity

Note: Data for “fear of job loss” show the percentage of people responding very concerned to the question: “How concerned would you say you are that you will be left unemployed”.

Source: Latinobarometro (2015),

Jobs are concentrated in a few sectors

Employment creation reflected the macroeconomic conditions between 2005 and 2015, strengthening the concentration in a few sectors. The employment shares by sector changed relatively little during that period, with most employment concentrated in the services sector (63% in 2015, and 66% in 2006). The agriculture and mining sector share of employment remained stable (from 19% to 16% variation in the 2006-15 period), as did the manufacturing sector (which had a constant share of around 18%). While agriculture and mining labour productivity was stagnant, labour productivity in the service sector increased considerably in particular owing to the “within effect” (see Chapter 2 for the macroeconomic conditions and growth across economic sectors). The employment elasticity of growth is higher for services (39%) than for the other sectors (agriculture and mining 29%; manufacture 26%). As such, further relaying on the growing service sector has the potential of continuing the expansion of employment.

More than half of workers in Panama are employed in commerce and logistics (19%), agriculture (14%), construction (10%) and transport and storage (8%). The biggest job-creating sector was commerce and trade, with more than 65 000 new jobs created (19% of all new jobs created). The construction sector, which created 14% of the new jobs from 2007 through 2015, and the financial service sectors are the fastest-growing in terms of employment, followed by health and social services, hotels and restaurants (Figure 3.17).

Figure 3.17. Employment by economic sectors in Panama

Source: INEC (2016).

The occupation structure is shifting towards higher-skilled workers

The composition of the labour force in Panama has changed significantly towards more skilled workers from 2004 to 2015 (Figure 3.18, Panel A). The proportion of the labour force with a low education level (i.e. less than eight years of education) decreased to close to 30% in 2014 from 50% in 1990. Consequently, the gap with the proportion of highly educated workers has narrowed. In 2014, more than 25% of the labour force has attained a high education level, equivalent to more than 13 years of education, against nearly 15% in 1990. In 2016, close to 30% of workers were non-qualified or plant and machine operators, assemblers or drivers; 23% of workers were managers or professionals (Figure 3.18, Panel B). During 2005-16, the biggest proportional growth was in skilled workers (Figure 3.18, Panel C).

Figure 3.18. The occupation structure in Panama

Note: The three skills level groups are formed according to years of formal education: low = 0 to 8 years, medium = 9 to 13 years, and high = more than 13 years.

Source: Panel A: INEC (2016); Panel B: CEDLAS and the World Bank (2016), SEDLAC database,; Panel C: INEC (2013).

The shift in the skills composition in Panama is noteworthy when considering the wage premia by education level, which privileges those with more advanced levels of education (Figure 3.18, Panel D). People with low qualifications face poor labour market prospects. Workers with complete tertiary education earn nearly twice as those with secondary education.

Ongoing shifts in the occupation structure of the labour force signal an increasing demand for individuals with a higher education degree. The demand for managers, professionals and technicians has increased over the past decade, with a reduction in the share of agriculture workers. However, the median salary of managers, professionals and technicians increased at a slower pace than that of lower-skilled jobs, meaning the salary gap remains wide.

A scarcity of technicians, engineers and skilled-trade workers is a recurrent complaint of employers. Nearly 46% of Panamanian firms report difficulties finding the necessary skills to operate (ManPower Group, 2016). As do other countries in the region, Panama registers a wide gap between the available pool of skills and those skills that its economy and society require (OECD/CAF/ECLAC, 2014). The size of the foreign workforce remains significant, owing to skills shortages across most economic sectors. This suggests scope for a stronger investment in education to increase the number of secondary graduates, as well as a larger role of technical and vocational education and training (TVET) at all levels; fewer students pursue TVET than in other countries of the region (UNESCO, 2016).

Labour earnings are low and very unequal

Inequality in Panama is closely linked to labour market inequalities, especially wage inequality. A large share of the working-age population encounters labour-market difficulties. Barriers are related to insufficient work-related skills, lack of quality jobs and territorial disparities. Improving job quality, reducing informality and increasing employment levels – especially for women and youth – remain key challenges in Panama.

Labour earnings are low and unequal in Panama (Figure 3.19). In recent years, Panama has enjoyed relatively good labour market outcomes, with a low unemployment rate, high employment creation and higher participation of women in the labour market. Still, income inequality is still large compared to other Latin American countries, benchmark economies and OECD countries. An uneven distribution of skills and productivity is related to this inequality. The high inequality is also associated with the large share of informal employment and the current inclusion gaps, particularly for the young, women and indigenous people, which need to be addressed.

Figure 3.19. Earnings in Panama compared to benchmark economies

Note: Calculations are based on net hourly earnings and concern 2010 values, except for Brazil (2009), Chile (2009), China (2009) and India (2011). Earnings inequality is measured as the Atkinson inequality index with a high level of inequality aversion. The index ranges from 0 (when earnings are equally distributed) to 1 (when all earnings are concentrated in the hands of a single person).

Source: OECD Earnings Distribution Database; OECD (2015), OECD Employment Outlook 2015,; and CEDLAS and the World Bank (2016), SEDLAC Database,

Informality enhances income inequality

Informality is one of the main obstacles to making the labour market more inclusive. The informal sector in Panama is smaller than in most Latin American countries, but it is large by OECD standards. Informal work, by definition, leaves workers without the right to a pension, health insurance and the general entitlements of the formal sectors (this report uses this definition). As in other Latin American countries, informality has declined in Panama, in the past decade. In 2016 informal employment accounted for 40% of total workers and comprised those with fewer skills and in lower-paying jobs, thus contributing to inequality (INEC, 2016). The Comarcas and Darién are the regions with the highest incidence of informal work. While nearly 90% of workers in the primary sector are informal, 10% of workers are informal in selected services such as financial, electricity and water services (Figure 3.20).

Figure 3.20. Labour informality is decreasing but still high

Note: Data for Argentina and Panama are from 2016, and from 2014 for all other countries. Legal definition of informality: informality is defined as workers without the right to a pension, health insurance, social protection, work contracts and the general entitlements of the formal sectors.

Source: CEDLAS and the World Bank (2016), SEDLAC (Socio-economic Database for Latin America and the Caribbean), and INEC (2016).

Informality in Panama especially affects youth and less-educated workers: 65% of the working young population work in the informal sector. Likewise, 73% of the working population with only complete primary education are employed in unregistered jobs, compared to only 3% of those who attained a tertiary education degree. Unlike other LAC countries, an equal share of women and men hold informal jobs (Figure 3.21, Panel A).

Figure 3.21. Labour informality and gender, education, skills and earnings

Note: Productive definition of informality: A worker is considered informal if (s)he is a salaried worker in a small firm, a non-professional self-employed, or a zero-income worker. A firm is considered small if it employs fewer than five workers. The three skills level groups are formed according to years of formal education: low = 0 to 8 years, medium = 9 to 13 years, and high = more than 13 years.

Source: CEDLAS and the World Bank (2016), SEDLAC (Socio-economic Database for Latin America and the Caribbean),

Informality within the formal sector is particularly significant in Panama. Over 15% of informal workers are employed by a formal firm, and represent 11% of formal firm workers (Figure 3.20, Panel A). The authorities exercise little control over the working conditions of salaried workers. In 2016, the Ministry of Labour levied only 674 fines for violations of labour conditions. Enforcement mechanisms through inspection and penalties are insufficient for firms to formalise their workers. Likewise, 75% of domestic workers are informally employed despite a special law to encourage domestic work formalisation.

Panama’s tax wedge, a measure of the difference between the labour costs and an employee’s take-home pay, is similar to that of the rest of Latin American economies but differs considerably from that of OECD countries. The tax wedge on average wage earnings in Panama is 22.9% of total labour costs. This is 1.2 percentage points higher than the average in Latin American and Caribbean countries (21.7%) but lower than the OECD average of 35.9% (Figure 3.22). The tax wedge includes compulsory social security contributions (SSCs), which for employees are 9.9% and for employers 13%. No personal income tax (PIT) is paid on an average wage. While these figures are similar to those for the region – employees pay 7.7% as SSC, employers pay 13.6% SSC, and PIT is 0.3% of labour costs – they contrast with the significant income taxes paid by average wage workers in OECD economies where employee SSCs are 8.3%, employer SSCs are 14.3%, and PIT is 13.3% of labour costs (OECD/CIAT/IDB, 2016). On average, the higher the tax wedge, the more costly labour becomes.

Figure 3.22. Income tax plus employee and employer social security contributions, 2013
As percentage of labour costs

Source: OECD/CIAT/IDB (2016), Taxing Wages in Latin America and the Caribbean,

Formalisation costs from labour taxes do not explain informality. Higher informality rates among wage earners do not relate to higher formalisation costs in Panama. This is a distinctive feature that differentiates Panama from the rest of the region (Figure 3.23). Theoretical formalisation costs are defined as the proportion of workers’ income that grants them access to health care and pension savings. The interaction of average income levels and the existence of a legally mandated lower earning threshold to participate in these social security programmes increase their price in most countries in Latin America. However, the existing earnings threshold in Panama is so low relative to reported income that the formalisation cost for individuals is proportional (23% of the worker’s income) throughout the income distribution. Therefore other factors influence an individual’s or employer’s choice between formality and informality. These include job security; labour regulations (i.e. monetary and non-monetary registration costs, firing costs, vacations); the valuation a person places on the programme or services; expectations of receiving future benefits; and a component of myopic behaviour by the individual or employer. The role of institutions in performing inspections and setting up enforcement mechanisms may also perhaps explain informality levels in Panama. Therefore, tackling informality will require a comprehensive strategy, including a combination of development policies at the regional level, better incentives to be formal, and stronger enforcement that go beyond the formalisation costs.

Figure 3.23. Informality and formalisation costs in Panama versus Latin America and the Caribbean
Percentage of a worker’s income by decile

Note: LAC is the arithmetic mean of Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay and Venezuela.

Source: OECD/CIAT/IDB (2016), Taxing Wages in Latin America and the Caribbean,

Employment Protection Legislation (EPL) in Panama is flexible for permanent contracts, but restrictive for short-term contracts which could explain the recourse to informal work. The OECD indicators of employment protection legislation measure the procedures and costs involved in dismissing individuals or groups of workers and the procedures involved in hiring workers on fixed-term or temporary work agency contracts. They measure regulation on a range from 0 (least restrictive) to 6 (most restrictive). The OECD EPL Indicator places Panama (1.73), on par with other LAC countries, but below the protection offered by most OECD countries (the OECD average is 2.3 points) and benchmark economies (2.1 points). On the other hand, Panama is among the four countries with the most stringent regulation on temporary work with a score of 4.29 points. The country is only surpassed by Venezuela (5.21 points), Turkey (4.96 points) and Uruguay (4.54 points), and well above the ranks of other LAC countries (2.5 points), benchmark economies (2.3 points) and OECD countries (2 points). Evidence is not conclusive regarding the link between EPL in general and informality (Kucera and Roncolato, 2008). Studies that find a positive link between EPL and informality find a weaker relationship for Latin American countries than for other regions (Lehman and Muravyev, 2012). On the other hand, evidence suggests that very restrictive employment protection rules are associated with dual labour markets and high informality (Schwab, 2016), as firms seek flexibility outside of formal rules. It is important to note that employment protection refers to only one dimension of the complex set of factors that influence labour market flexibility.

Vulnerable youth face severe challenges

Most youth leaving school enter inactivity or informal low-quality jobs (60%). The most disadvantaged youth suffer most from such precariousness. Poor employment opportunities result in lower well-being, and affect young women, the poor and the vulnerable more deeply. Starting with an informal job can leave permanent scars on workers’ careers. Youth employment policy should assist young workers to get on a good career path early in their working lives. The incidence of informality is much larger for youth from poor and vulnerable households than for those belonging to the middle class. Nearly 35% of young Panamanians from extremely poor households are employed in an informal job, compared to 25% in the LAC region for this group (OECD/CAF/ECLAC, 2016). Lack of good employment opportunities is a significant factor hindering the inclusion of youth in society.

One out of five young Panamanians is not in education, employment or training (NEET). The NEET rate of young women in Panama was close to 30% in 2014, similar to the LAC average but considerably higher than the NEET rate for men of 11% (Figure 3.24, Panel A). This contrasts to the OECD average, where the gap between women and men is less than 5 percentage points (Figure 3.24, Panel B). The NEET phenomenon is strongly linked to socio-economic background: 76% of NEET women and 75% of NEET men come from poor or vulnerable households. However, the NEET category should not hide the fact that NEET women doing forms of domestic work, in particular, are productive and contribute to the total economy: 84% of NEET women in Panama are engaged in unpaid domestic work or caregiving, compared to 10% of NEET men.

Figure 3.24. Youth activities in Panama versus Latin America

Note: LAC is the weighted average of 17 countries: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru and Uruguay. NEETs are youth not in employment, education or training.

Source: OECD/CAF/ECLAC (2016).

The challenges that young Panamanians face on their path to work are particularly severe among those from disadvantaged socio-economic backgrounds. Their transition from school to work helps explain the poor labour market outcomes experienced by young people in Panama. Youth from these disadvantaged households leave school earlier than their peers in better-off households and when employed mainly work in informal jobs (Figure 3.25). At age 15, almost seven out of ten young people living in poor households are in school. At age 24, however, almost five out of ten youth in this group are NEET, three out of ten work in the informal sector, only two work in the formal sector, and less than one is either a working student or a student. In vulnerable households, 55% of young people aged 29 are working in the informal sector or NEET. In contrast, in consolidated middle-class households around 90% of youth are in school at age 15 and more than 73% of youth are working at age 29, 80% of them in the formal sector (Figure 3.25).

Figure 3.25. Youth from disadvantaged socio-economic backgrounds face severe challenges
Percentage of youth aged 15-29

Note: Socio-economic classes are defined using the World Bank classification. “Extreme poor” = youth belonging to households with a daily per capita income lower than USD 2.5. “Moderate poor” = youth belonging to households with a daily per capita income of USD 2.5 to USD 4. “Vulnerable” = individuals with a daily per capita income of USD 4 to USD 10. “Middle class” = youth from households with a daily per capita income higher than USD 10. Poverty lines and incomes are expressed in 2005 USD PPP per day.

Source: OECD/CAF/ECLAC (2016).

Women’s participation in the workforce is low

Participation rates for Panamanian women are slightly lower than levels in OECD economies, but the gap with men is relatively large. Increasing the participation of women in the labour market should have a significant positive impact on productivity, economic growth and income equality in Panama (OECD, 2012). The changes in female employment in Latin America over the past decades contributed to the observed fall in income poverty and inequality (Gasparini and Marchionni, 2015). Panama has made progress in providing more opportunities for women to have both more and better jobs. Still, the gender employment gap remains above that of OECD economies, and women have lower access to managerial jobs then men (Figure 3.26).

Figure 3.26. Women’s participation in employment

Source: ILO (2016) and INEC (2016).

Recent evidence shows the entry of women into the labour market has slowed down in the years (Figure 3.26, Panel A). Among the most affected are the most vulnerable women, i.e. those with low education, living in rural areas or Comarcas, with children or married to low-earning spouses (Gasparini and Marchionni, 2015). This trend suggests the emergence of a dual scenario. On the one hand, skilled higher-income women living in large cities have labour participation levels similar to those of OECD countries; and, on the other, low-skilled vulnerable women living in rural areas or Comarcas with poorer services have substantially lower levels, leading to increasing inequality and poverty cycles (Gasparini and Marchionni, 2015; OECD/CAF/ECLAC, 2016). Employment initiatives are needed for groups that have fewer attractive job prospects and are more predisposed to leave, given the significant slowdown of labour participation among vulnerable women.

Spending on overall active labour market policies is low, but is high for training

Labour markets can become more inclusive and resilient when active labour market policies (ALMPs) are scaled up to satisfy the needs of all workers including youth, women, indigenous populations, the vulnerable and the middle class. ALPMs such as training, public employment services and incentives for job creation and entrepreneurship, and that involve people in full-time activities, increase the employability of job seekers and contribute to keeping workers productive in a cost-effective manner (OECD, 2015). Many vulnerable workers, such as informal workers, and job seekers fall out of these categories.

Spending on ALMPs is low in Panama, although spending on training is relatively high. In contrast to other countries in the region, Panama performs well in offering training programmes, and a high share of skills spending (0.17% of gross domestic product [GDP]) is estimated to be concentrated in this area. OECD countries, in comparison, spend nearly 0.15% of GDP in training (Figure 3.27). Additionally, the proportion of formal firm workers offered formal public or privately financed training (68%) is relatively high for the region (62%), and higher than other parts of the world (53%) (World Bank, 2010). However, current training programmes lack a proper evaluation mechanism and do have a real monitoring framework. No impact evaluations have been implemented to assess the efficiency of training expenditure, and therefore evidence of their efficiency is lacking.

Figure 3.27. Although spending on training is high, overall LMP spending is low

Note: Panel A: Includes active, intermediary and passive policies. Data for Costa Rica and Guatemala are for 2012; Nicaragua, for 2013; Argentina, Australia, Belgium, Brazil, Chile, Honduras, Korea, Netherlands, New Zealand, Panama, Portugal and OECD average for 2014. The LAC average includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Granada, Guatemala, Honduras, Mexico, Nicaragua, Panama, Peru and Uruguay. Panel B: Data for Argentina, Australia, Belgium, Brazil, Chile, Korea, Netherlands, New Zealand, Panama, Portugal and OECD average are from 2014; Costa Rica, Guatemala, Nicaragua and Peru is from 2013, Dominican Rep, Honduras and Mexico is from 2012, Ecuador is from 2011, and Colombia is from 2010. The LAC average includes Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Guatemala, Honduras, Mexico, Nicaragua, Panama and Peru.

Source: OECD (2016c) and World Bank (2016a), ASPIRE: The Atlas of Social Protection Indicators of Resilience and Equity (database),

Panama has recently developed a number of training and lifelong learning programmes for youth, particularly in less advantaged socio-economic groups and women. The Pro Joven (Pro Youth) programme, created in 2015, promotes employability of youth through internships in enterprises. The beneficiaries are youth in the last year of technical and vocational programmes. Participating enterprises receive a government subsidy for hiring interns and are required to hire at least 50% of those young workers once their internship contracts end. The programme started as a pilot with 1 000 beneficiaries and is now being scaled up. Additionally, the Instituto Nacional de Formación Profesional y Capacitación para el Desarrollo Humano (INADEH), the public entity in charge of technical and vocational training, is developing a comprehensive training programme designed to create the skills that the productive sector needs, in order to increase the pool of prospective candidates for this programme. INADEH, which is one of the largest agencies of its kind in the region, offers short technical courses that combine classroom teaching with workplace learning to more than 70 000 students each year (see section below on education and skills). The Nuevas Oportunidades de Empleo para Jóvenes (New Employment Opportunities) programme also offers job training and placement services to low-income youth in Ciudad de Panamá. Likewise, the Autoridad De La Micro, Pequeña Y Mediana Empresa (AMPYME), the public entity in charge of promoting small and medium enterprise development, has also introduced a series of programmes to promote business training, with the goal of increasing formalisation among young entrepreneurs. The programmes Desarrollo Financiero y Empresarial (Financial and Business Development) and Fondo Emprende aim to increase opportunities for entrepreneurship and promote creation of new companies.

To improve the effectiveness of these programmes and increase spending on ALMPs, and especially training, is a challenge. Multiple programmes and a lack of appropriate data currently reduce the scope for systematic evaluations and limit the capacity for improving spending efficiency (OECD/CAF/ECLAC, 2016). Encouraging private firms to provide better and more frequent on-the-job training, as well as training prospective employees, could contribute to improving the skills of the labour force at a low cost.

Strengthening education and skills

Access to education in Panama has gradually expanded over the past decades for all levels of education. Panamanians are becoming more educated, with many more people reaching higher levels of education than in the past. Likewise, the average number of years of education reached 10.5 in 2014, up from 9.6 in 2004. Between 1980 and 2014, the share of the population having completed secondary education has increased to 52% from 20% (Figure 3.28, Panel A). The corresponding increase in the share of the population completing tertiary education to 15%, from 5%, is remarkable. Still, pre-primary, secondary and tertiary education coverage is below that of benchmark economies and OECD countries. The increasing levels of incomplete secondary and incomplete tertiary education also indicate that completion rates overall in Panama are still low.

Figure 3.28. Educational attainment has improved with time

Source: Barro and Lee (2013); OECD and World Bank tabulations of SEDLAC (CEDLAS and the World Bank); and INEC (2013).

There are great territorial disparities in terms of educational attainment. In some provinces and the Comarcas, more than 90% of the population have only completed primary education or less. Conversely, more than 55% of the population in Ciudad de Panamá have completed secondary education, while less than 10% have done so in the Comarcas (Figure 3.28, Panel B).

Panama’s education system is based on the Organic Law 47 of 1946 on Education, which covers a first level of general basic education (from pre-primary, primary and lower secondary), a second level of lower and higher secondary education and a tertiary level. The Ministry of Education is in charge of establishing, organising and executing all activities related to education activities. The management of the education sector has been increasingly decentralised since 1995, transferring decision making, co-ordination and control to regions and schools. The regional education directorates (i.e. Direcciones regionales de educación) are in charge of implementing, supervising and co-ordinating the actions at the regional level.

Enrolment rates are still low

Despite improvements in the past decade to increase coverage in education, enrolment rates remain below OECD and benchmark economies across all education levels (Figure 3.29, Panel A). Similar to Latin American economies, Panama exhibits low tertiary education enrolment rates (40% of gross enrolment rate), while in the OECD this ratio is higher than 70%. Furthermore, considerable efforts should be achieved at earlier stages of education, in particular at secondary levels when compared to both benchmark and OECD economies (Figure 3.29, Panel A).

Figure 3.29. Enrolment rates are low and enhance inequalities

Note: Gross enrolment rates in tertiary education from Peru are from 2010.

Source: UNESCO (2016) and CEDLAS and the World Bank (2016).

Enrolment is higher among students living in cities and in richer families than those who live in rural areas or are from poor families for all levels of education (Figure 3.29, Panel B; Figure 3.30). As in many other aspects of Panama’s development, finding solutions to territorial differences is key to constructing a more equitable education system.

Figure 3.30. Education access is unequal across regions (percentage)

Note: Rural areas include Comarcas.

Source: CEDLAS and the World Bank (2016).

Pre-primary education enrolment is low preventing advancement towards equal education opportunities for all children in Panama, in particular for the poorest households. Less than half of the children in the poorest households are enrolled in pre-primary while 86% of their peers in the richest households are enrolled (Figure 3.29, Panel B). Moreover, 96% of the Panamanian children from households in the highest quintile of the income distribution attend secondary school, while only 56% of those from the lowest quintile do so (OECD/CAF/ECLAC, 2014).

Given the disparities in the education system, pre-primary education becomes a key equity building block. This is particularly relevant, as pre-primary education has a long-term impact on student performance: secondary-school performance improves by the equivalent of almost a full school year among those who had pre-primary education (OECD/CAF/ECLAC, 2014). Students from poor households benefit the most since starting education “early” allows them to “catch up”, at least partly, with their peers.

Primary education coverage has expanded, but there is still work to be done at the Comarcas. One of the achievements of the last decade has been the expansion of primary education and improving primary completion. By 2014, the share of youth with a primary school degree reached 96% of the population (CEDLAS and the World Bank, 2016), with similar distribution among male and female. Across socio-economic groups, the difference in the completion shares in primary education between the first income quintile (88%) and the fifth quintile (99%) has been reduced in recent years, attesting to the increasing equity of access to primary education. Between rural and urban areas, if there is still a difference in completion rates (90% vs 98%), the gap has also lessened since 2008 (from 10.9% to nearly 8.0%), but remains substantial (Figure 3.30). Behind this gap, the provision of basic education at the Comarca level remains a challenge, and keeping students within the education system in the Comarcas is a key issue for equity. The difference in years of schooling between Comarcas (4.2 years in 2010) and the national average (10.5 years) is revealing (UNICEF, 2010). The difference in repetition rates among the Comarcas (14.3%) and the national average (5.5%), with the subsequent increase in dropping out, reflects the challenges that Panamanian authorities face to reduce regional disparities in completion at primary level.

Students leave the education system too early

Few students graduate from secondary education, preventing strong skill acquisition. Dropping out of school before completing secondary education truncates students’ path towards higher education, exacerbates inequalities and narrows the skill base of the labour force. Although enrolment rates have improved, many young Panamanians find themselves out of the school system before completing a degree. This is shown by the country’s high secondary drop-out rates and the low completion rates in tertiary education (Figure 3.31). More than 180 000 young Panamanians (aged 15 to 29), or 20% of the youth population of the country, have not completed secondary education and are not enrolled in school (OECD/CAF/ECLAC, 2016).

Figure 3.31. Enrolment rate by single year of age

Source: Berniell et al. (2016).

Lack of secondary education infrastructure challenges further education advances. To counter the high drop-out levels in secondary education, particularly in disadvantaged households, Panama’s government has sponsored support programmes for enrolled students. However, programmes for disadvantaged students have not been enough to improve the low completion rates in secondary schooling. Some evidence suggests that insufficient infrastructure to both lower- and upper-secondary schools impairs young Panamanians’ path towards 12 years of education (while only lower-secondary education is compulsory, the government is committed to providing free and quality education to upper-secondary level). The current infrastructure plan has more than doubled the number of classrooms for secondary education since 2004, but still they are half that of primary education.

The education system has made progress in reaching disadvantaged children, but could be improved. Panama has invested human and financial resources to address some of the inequalities in access, completion and performance by socio-economic background. The Beca Universal programme, established in 2010, is one of the main initiatives in this area. The programme provides financial support to all students registered at primary and secondary levels, both in public and private education centres (provided they are certified by the Ministry of Education), according to their achievements. Students in private schools can benefit from the grant if the yearly total of the tuition fee and monthly payments does not exceed a threshold (1 000 balboas until 2017 and 2 000 balboas from 2018). Since its inception, the programme’s scale has increased significantly: from an initial coverage of 70% of students in the poorest income quintile to 100% of children in the same quintile covered in 2014 (World Bank, 2016b). Although no impact evaluation has been undertaken, the programme has aimed at addressing high-school drop-out in public schools, particularly in poor areas.

Few tertiary education graduates confront Panama’s capacity to innovate. Higher education in Panama includes five major universities which account for nearly 90 000 students whereas private education institutions include an extra 50 000 students. Enrolment rates have been on the rise, reflecting increasing demand for skilled labour in the country. Private institutions have played a role in channelling part of this demand, as the whole system is unprepared for providing tertiary education for the population that potentially could have access estimated at 360 000 (ICEF, 2016).

The National Council for University Evaluation and Accreditation (CONEAUPA) undertook in 2010 a new evaluation process for meeting quality standards and emphasising skills training and curriculum unification. These efforts, together with the government’s expanded support to INADEH, the national vocational training institute, have resulted in an increasing enrolment of students in a wider number of areas. Some fields, however, remain under-enrolled, including engineering, logistics and health sciences. This uneven distribution also highlights the challenges Panama is facing to create a critical mass for innovation and development.

Panama needs to develop its non-university tertiary education. Very few institutions offer tertiary technical education degrees. As a result less than 10% of tertiary education graduates, only 2 000 students a year, are instructed in technical careers which are in high demand in the country. The government of Panama is building the Instituto Técnico Superior del Este. (ITSE) that will address this problem for students living in Ciudad de Panamá, but further action needs to be taken at national level.

Learning outcomes are poor

Panama faces great challenges to improve learning outcomes in both primary and secondary schooling, which currently impede students from advancing to higher stages of education. The quality of Panama’s education system remains poor at all levels, as evidenced by the available national and international assessments (see Box 3.3. for Panama’s participation in the OECD’S Programme for International Student Assessment [PISA] 2018). The increase in access has not been accompanied by parallel improvements in quality. As a result, more than 90% of sixth-grade students perform in the lowest two levels of UNESCO’s Third Regional Comparative and Explanatory Study (TERCE) mathematics proficiency test and more than 75% do so in the reading test. TERCE scale ranks students across four proficiency levels. Likewise, 15-year old Panamanians perform poorly in international evaluations, including PISA 2009 (the latest PISA test in which Panama has participated), where proficiency in reading, mathematics and science are, as in the case of most Latin American countries, lower than OECD member countries.4

Box 3.3. Panama in the Programme for International Student Assessment (PISA)

Panama has rejoined PISA for the 2018 cycle after successfully taking part in PISA 2009. PISA is a triennial international survey which aims to evaluate education systems worldwide by testing the skills and knowledge of 15-year-old students. In 2015 over half a million students, representing 28 million 15-year-olds in 72 countries and economies, took the internationally agreed two-hour test. Students were assessed in science, mathematics, reading, collaborative problem solving and financial literacy.

In addition, Panama will be also be taking part in the out-of-school component of the OECD’s PISA for Development project (PISA-D). PISA-D will enable Panama to assess the out-of-school 15-year-olds to complement the information PISA gives about the in-school population, and build capacity for managing and using the results of large-scale student learning assessment to support policy dialogue and decision making. The field trial of both studies is being implemented during 2018 and the results will be available at the end of 2019.

The overall quality of the education system is low, particularly at secondary level. Panamanian students, on average, performed 122 points lower than the OECD average in reading in 2009, and only one out of three students performed above the first level of proficiency (Figure 3.32). More than 70% of young Panamanians enrolled in high school do not acquire basic-level proficiency in reading and mathematics, according to PISA results (OECD, 2010a). Additionally, less than 1% of Panamanian students perform among the highest levels of proficiency in mathematics, reading or science (OECD, 2010b). This constitutes an obstacle to further development of more specific skills and, at the same time, the small portion of top performers may hamper innovation and entrepreneurship. This presents a major challenge for countries that are transitioning into knowledge-based economies where citizens need to innovate, adapt and leverage advanced human capital.

Figure 3.32. Performance in PISA 2009 reading test

Note: The distribution by performance levels in Latin America and OECD refers to the simple mean of attainment level weighted at the national level for participating countries in PISA 2009.

Source: Based on data from PISA 2009.

Student performance is strongly linked to socio-economic background

Low performance in Panama is associated with students’ socio-economic background, their school history and the education practices within the household. UNESCO TERCE test results in primary education show that about 50% of Panamanian students reaching third grade do not have the skills to read and understand a text (UNESCO, 2015a). Between 30% and 70% of students in third to sixth grade do not perform well in tests in mathematics, science and Spanish. This is worrisome, as these basic abilities undermine children’s capacity to learn other subjects in the future. Time for study in Panama is relatively high in comparison with other countries in the region. While 69% of Latin American parents surveyed said their children spend time studying daily, in Panama 82% of households reported daily studying activities (UNESCO, 2015b). Other procedures, related to teacher preparation, schoolroom practices and material conditions in schools, also seem to be important determinants of educational outcomes in Panama (UNESCO, 2015a).

Ensuring that a large base of the population acquires core literacy and numeracy skills is fundamental for the diffusion of knowledge and innovation that sustains economic growth (Hanushek and Woessmann, 2007). An increase of one standard deviation in cognitive skills (measured using PISA-type exams) is associated with approximately a 2% increase in annual growth of per capita GDP (Hanushek and Woessmann, 2012). The inability of individuals from poor socio-economic backgrounds to access quality education and develop skills to participate in productive activities hinders growth and perpetuates income inequality (Causa and Johansson, 2010).

The socio-economic background of students and the school has a significant influence on educational outcomes in Panama. In OECD countries, socio-economic background explains less than 14% of the total variation in students’ PISA results; in Panama it explains a higher proportion (18%) of the variation. The percentage of variance of reading performance in Panama that is explained by various aspects of family background ranks fourth among participating countries in the 2009 PISA round. Moreover, the distribution of educational outcomes among groups is also uneven. Indeed, the gap in performance between urban and rural schools in Panama is significantly large (more than 80 points), which is equivalent to almost two years of education (OECD, 2010b).

Like the large differences in performance among different groups, the distribution of educational resources appears to be linked to the socio-economic background of students. Generally, educational resources need to be allocated for the purpose of reducing inequalities, by targeting students from poorer socio-economic backgrounds. Some of the best-performing OECD countries in the PISA tests such as Finland, Germany and Korea tend to distribute educational resources more equitably. This is not the case in Panama. The correlation between the school mean socio-economic background and the index of educational resources (including the share of certified teachers, books, instructional material and laboratories) in Panama (0.68 in 2009) is considerably higher than in OECD economies (0.13 in 2009). Improving the distribution of educational resources is an important challenge for improving both performance and equity in Panama’s educational systems.

Teacher training is key to boosting students’ performance

Teachers are an essential resource to improve Panama’s education quality. Studies show that teachers’ knowledge of the subject they teach and the quality of the instruction time are important determinants of student performance, even stronger than teachers’ level of education, experience, qualifications, work status or salaries (Avendaño et al., 2016; Hanushek, Piopiunik and Wiederhold, 2014; Metzler and Woessmann, 2012; Hanushek and Rivkin, 2006; Palardy and Rumberger, 2008; Allison-Jones and Hirt, 2004). Panama has made a significant effort to strengthen training, management and professional development of teachers and principals. In terms of assessment, teachers are evaluated each school year, including inspectors’ evaluations, principals’ evaluation and self-evaluations for training purposes.

Teacher recruitment has improved in Panama in recent years. At primary and secondary level, the Ministry of Education regulates the teacher hiring process. At tertiary level, universities in Panama have discretionary power to decide on recruitment, career structure, compensation and leadership of the teaching body. Introducing a solid recruiting process for teachers is an essential component for attracting talent to the profession and improving educational outcomes.

Panama has to make the teaching profession more attractive by proposing higher compensation. As in other countries in the region such as Brazil, Nicaragua and Peru, average teacher salaries tend to be lower, after controlling for dedication time, than for other professions (Bruns and Luque, 2014; Mizala and Nopo, 2012). Teachers’ wage evolution in Panama is relatively flat compared to other fields.

Technical education is underdeveloped

Technical and vocational education and training (TVET) in Panama remains underutilised. TVET in Panama has a double role, serving on the one hand to upgrade the skills of workers, and on the other promoting equity by providing dropouts and poorly educated workers with better employability prospects. Vocationally oriented upper-secondary training often leads to better employment prospects than academically oriented training for students who do not pursue further studies (Cedefop, 2014). Still, 14% of secondary students in Panama are enrolled in TVET programmes (Figure 3.33), which is similar to the LAC regional average (15%) but lower than in OECD economies (26%) (OECD/CAF/ECLAC, 2016). Panama offers a wide variety of training programmes through the national vocational training institute, INADEH. This institute is in charge of executing the strategy and programmes on training, learning-at-work programmes and business training for both public and private sectors. It has full autonomy in terms of financial resources, and its spending on training programmes is above the average (0.17% of GDP in 2014 compared to 0.12% and 0.15% of GDP for LAC and OECD, respectively). However, quality is heterogeneous: quality courses that are highly respected and generate positive returns for students and employers coexist with low quality ones. Although TVET represents an important source of innovation and experimentation in the design of technical education that benefits the sector as a whole, there are too few mid- and high-level technical and professional programmes to drive a change in quality.

Figure 3.33. Enrolment in technical vocational education and training (percentage of secondary students)

Source: UNESCO (2016), Institute for Statistics,

Matching qualifications to labour market needs

Education in Panama is disassociated from the skills demanded by the labour market. The current mismatch, between the provision of tertiary programmes and the current demand for skills driven by infrastructure projects, highlights the need for improving access to and quality of post-secondary education. The Ministry of Labour has recently worked on anticipating skills demands, but these have not been matched. In 2016, 36% of formal firms in Panama reported not being able to find the workforce with the skills they need (ManPower Group, 2016) (Figure 3.34). Both the secondary and the tertiary education systems are heavily biased towards social sciences and humanities, producing few science, technology, engineering and mathematics (STEM) graduates. For example, while the Ministry of Labour has identified a lack of human capital with technical expertise in logistics, tourism and construction, 65% of tertiary education students are enrolled in humanities, health or business degrees. Current skills mismatches could be aggravated in a context where technological change, globalisation and trade are responsible for job destruction and new types of job creation. The capacity of countries to improve the skills of their populations and adjust to these changes will partially determine labour markets’ outcomes, economic growth, productivity and competitiveness (OECD/CAF/ECLAC, 2015). Likewise, Panama has several restrictions to the free flow of migrant labour that affect skills-based development and economic diversification in the country (Hausmann, Espinoza and Santos, 2016).

Figure 3.34. Formal firms cannot find the skills they need

Notes: OECD average includes Australia, Austria, Belgium, Canada, Czech Republic, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom and United States; LAC average includes Argentina, Brazil, Colombia, Costa Rica, Guatemala, Mexico, Panama and Peru.

Source: ManPower Group (2016) and World Bank (2010).

In Panama training programmes play an important role in providing basic technical skills to low-skilled workers, and especially to high-school dropouts. Although the government’s vocational training institute, INADEH, covers more than 70 000 students per year, its capacity is limited given the large number of low-skilled high school dropouts in Panama.

Reducing skill mismatches entails policy action on the supply side and on the demand side. On the demand side, effective and well-informed career guidance at the end of lower-secondary education plays an important role in achieving a good match between students’ preferences and labour market needs (OECD, 2014). The existing student bias towards the humanities might lead to career paths with low demand. A lack of information about labour market prospects might be one reason behind these decisions, which could be addressed by better career guidance. Providing reliable and free information on line about employment options in the country, wage levels in different industries, and labour market status by degree, university could help young students better understand the relative value of different qualifications in the labour market and encourage students to enrol in those careers and institutions that offer the best employment and earnings prospects. This would also create greater competition among higher education institutions, raising overall quality standards.

There is little information available on the skills that firms demand and supply in the population other than by education. Although there is a consensus that Panama should provide more and better-prepared talent to the labour market, assessment is needed to determine the real needs. Firms report an inadequately educated workforce as the third biggest constraint for business development (19% of the total), after corruption and practices of the informal sector (World Bank, 2010). Estimates of the competencies among production workers suggest that only 35% of them are skilled. However, little information is available at the sector and geographical level to better understand the skills needs. Some information is available for specific sectors. In the logistics sector, there is a need for 35 000 technicians, 28 000 new skilled workers in construction and 4 000 workers in services (Centro Nacional de Competitividad, 2014). A more detailed information system is required to better understand the dynamics of skills demand and supply.

Public spending on education is low

Overall investment in education is low, especially compared to countries with similar income per capita. Government expenditure on education in Panama was 3.6% of GDP in 2015, below the regional average (Figure 3.35). Although spending has increased in absolute terms during the last decade it decreased as a yearly percentage of GDP.

Figure 3.35. Investment in education lags behind regional and OECD levels
Education spending as percentage of GDP

Source: OECD calculations based on INEC (2016) and UNESCO (2016), UNESCO Institute for Statistics database,

The distribution of expenditure among the three levels of education also contrasts with the OECD trend. Whereas Panama had a similar expenditure per student as share of GDP per capita in primary (6.2%) and secondary (9.2%) education, tertiary education – mainly university – expenditure per student is much higher (18.8%). On the other hand, OECD countries allocate a similar expenditure per student across the three education levels (between 21% and 24% as share of GDP per capita) (Figure 3.36). The distribution of education spending in Panama has changed slightly in recent years, moving towards more similar shares allocated to pre-primary, primary, secondary and tertiary levels; yet, the significant need for Panama to improve access to and quality of secondary education, as well as the low levels of tertiary enrolment, suggests that this allocation could be reconsidered.

Figure 3.36. Education spending in Panama
Spending per student as a percentage of GDP per capita, 2013

Source: OECD calculations based on UNESCO (2016), UNESCO Institute for Statistics database,


Panama has made great social and economic progress in the past decade. Absolute poverty levels have fallen dramatically but income inequality remains high. The gaps between different socio-economic groups and between territories are still large, and too many Panamanians are at risk of falling back into poverty if they are not protected adequately. In this context, redistribution, education and skills as well as formal jobs are key drivers to improve the well-being of all. The analysis presented in this chapter shows old and new challenges that are holding the country back on its path towards sustainable and inclusive development.

Access to public infrastructure and services differs substantially across regions, contributing to large discrepancies in the well-being of the population that are a constraint for inclusive development. A great divergence has been observed between urban and rural areas in various dimensions such as income, education and skills, housing, sanitation and health as well as between those areas with high concentrations of indigenous populations and the rest of the country. However, spatial planning is not only a challenge for rural or indigenous areas. The constant and high rate of population growth created slums in urban areas but also more generally challenged the extension of public services.

The efforts to expand pre-primary and secondary education access have not been as successful as those to expand primary education. Large gaps remain when compared to LAC and OECD standards, in particular for those of lower socio-economic backgrounds. The poor quality, relevance and completion of education are also persistent constraints for development as are the low levels of financial resources devoted to pre-primary, primary and secondary education. Public investment in education in Panama is well below the OECD average, has been declining as a share of GDP, and in particular has been insufficiently directed to primary and secondary education.

Key policy objectives arise to improve quality of education for all Panamanians. Reducing overall inequalities by investing more in infrastructure and teacher training across territories should be a priority. Panama also needs to improve the quality of teachers. It is important to design a real policy in terms of teacher hiring, career structure, compensation and incentives for mobility. The alignment of Panama’s education and skills system seems to be out of synchronisation with the current demands of the economy and the rapid changes brought by technology in some sectors, including services. The lack of qualified workers in certain sectors, including those related to infrastructure development and specialised services, is a major bottleneck for Panama’s productive strategy.

Panama stands out as an economy with a low unemployment rate but high informality. Informal work accounts for a large share of employment, job quality is poor and there are large inequalities in the workforce, especially in terms of earnings. Higher informality rates among wage earners do not correlate with higher formalisation costs in Panama. This is a distinctive feature that differentiates Panama from the rest of the region, and one that makes poor controls and enforcement much more relevant. Strong policies are needed to increase formalisation and improve working conditions, in particular for disadvantaged youth. To reduce informality, a combination of policies should be adopted such as programmes facilitating companies’ and workers’ registration in the formal sector; stricter and more frequent workplace controls; higher fines for those companies that do not register workers; and better quality training programmes in mid- and high-level trade; and technical, professional and management skills to improve labour productivity.


Acosta, P.A. et al. (2015), “Panama – Central America social expenditures and institutional review”, Social Sector Expenditure and Institutional Review, Report No. 102301-PA, World Bank Group, Washington, DC.

Allison-Jones L.L. and J.B. Hirt (2004), “Comparing the teaching effectiveness of part-time & full-time clinical nurse faculty”, Nursing Education, Vol. 25/5, pp. 238-243.

Arráiz, I. and S.V. Rozo (2011), “Same bureaucracy, different outcomes in human capital? How indigenous and rural non-indigenous areas in Panama responded to the CCT”, Office of Evaluation and Oversight Working Paper, No. 03, Inter-American Development Bank (IDB), Washington, DC.

Atkinson, T. et al., (2002), Social Indicators: The EU and Social Inclusion, Oxford University Press, Oxford.

Avendaño, R. et al. (2016), “Understanding student performance beyond traditional factors: Evidence from PISA”, OECD Development Centre Working Papers, No. 331, OECD Publishing, Paris,

Barro, R. and J-W. Lee (2013), “A new data set of educational attainment in the world, 1950-2010”, Journal of Development Economics, Seoul, Korea, Vol. 104, pp. 184-198.

Berniell, L. et al. (2016), Más habilidades para el trabajo y la vida: los aportes de la familia, la escuela, el entorno y el mundo laboral, [More Skills for Work and Life: The Contributions of the Family, the School, the Environment and the Working World], Development Bank of Latin America (CAF), Bogotá.

Bruns, B. and J. Luque (2014), Great Teachers: How to Raise Student Learning in Latin America and the Caribbean, World Bank Publications, Washington, DC.

Causa, O. and A. Johansson (2010), “Intergenerational social mobility in OECD Countries”, OECD Journal: Economic Studies, Volume 2010, OECD Publishing, Paris.

Cedefop (2014), “Annual Report 2013”, Cedefop Information Series, Cedefop (European Centre for the Development of Vocational Training), Publications Office of the European Union, Luxembourg.

CEDLAS and the World Bank (2016), SEDLAC (Socio-Economic Database for Latin America and the Caribbean) (database), Centro de Estudios Distributivos, Laborales y Sociales, Universidad Nacional de La Plata, La Plata, Argentina, (accessed 1 March 2017).

Centro Nacional de Competitividad (2014), “Análisis detallado de la competitividad”, [“Detailed analysis of competitivity”], CNC/CAF, Panama,

Datt, G. and M. Ravallion (1992), “Growth and redistribution components of changes in poverty measures: A decomposition with applications to Brazil and India in the 1980s”, Journal of Development Economics, Vol. 38(2), pp. 275-295.

ECLAC (2016a), Social Panorama of Latin America 2015, Economic Commission for Latin America and the Caribbean, United Nations Publication, Santiago de Chile.

ECLAC (2016b), CEPALSTAT Statistics and Indicators, Economic Commission for Latin America and the Caribbean, (accessed 20 March 2017).

ECLAC/ILO (2016), Employment Situation in Latin America and the Caribbean: Recent Improvements and Persistent Gaps in Rural Employment, No. 14, May 2016, Economic Commission for Latin America and the Caribbean / International Labour Organization, United Nations Publication, Santiago de Chile,

Espino, A. and C. Gordón (2015), “Los asentamientos informales en el área metropolitana de Panamá: Cuantificación e implicaciones para la política de vivienda y urbanismo”, Foro y Observatorio Urbano de Panamá (FOBUR), Panama City, Panama.

Gallup (2016), Gallup World Poll, (accessed 1 February 2017).

Gasparini, L. and M. Marchionni (2015), “Bridging gender gaps? The rise and deceleration of Female Labor Force Participation in Latin America”, CEDLAS Working Papers, No. 0185, Centro de Estudios Distributivos, Laborales y Sociales, Universidad Nacional de La Plata, La Plata, Argentina.

Gobierno de la República de Panamá (2017), Report on the Multi-dimentional Porverty Index in Panama [Informe del Índice de Pobreza Multidimensional de Panamá 2017], Panama City.

Hanushek, E.A., M. Piopiunik and S. Wiederhold (2014), “The value of smarter teachers: International evidence on teacher cognitive skills and student performance”, NBER Working Paper, No. 20727, National Bureau of Economic Research, Cambridge, MA.

Hanushek, E.A. and S. Rivkin (2006), “Chapter 18 teacher quality”, Handbook of the Economics of Education, Vol. 2, pp. 1 051-1 078, Elsevier, Amsterdam.

Hanushek, E.A. and L. Woessmann (2012), “Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation”, Journal of Economic Growth, Vol. 17/4, pp. 267–321.

Hanushek, E.A. and L. Woessmann (2007), Education Quality and Economic Growth, World Bank, Washington, DC.

Hausmann, R., L. Espinoza and M.A. Santos (2016), “Shifting gears: A growth diagnostic of Panama”, Center for International Development Working Papers, No. 325, Center for International Development at Harvard University, Boston.

ICEF (2016), “Panama’s rising economy funding new investments in education and English training”, ICEF Monitor blog, 14 January,

ILO (2016), Key Indicators of the Labour Market, 9th Edition (database), International Labour Organization, Geneva, (accessed 1 March 2017).

INEC (2016), Encuesta Continua de Hogares [National Household Survey], Instituto Nacional de Estadística y Censo (National Institute of Statistics and Census), Panama,

INEC (2015), Sistema Integrado de Indicadores para el Desarrollo (SID), Instituto Nacional de Estadística y Censo (National Institute of Statistics and Census), Panama, (accessed 1 February 2017).

INEC (2013), Encuesta Continua de Hogares [National Household Survey], Instituto Nacional de Estadística y Censo (National Institute of Statistics and Census), Panama,

INEC (2010), Distribución Territorial y Migración Interna en Panamá: Censo 2010 (Territorial Distribution and Internal Migration in Panama: 2010 Census), Instituto Nacional de Estadística y Censo (National Institute of Statistics and Census), Panama,

Kucera, D. and L. Roncolato (2008), “Informal employment: Two contested policy issues”, in International Labour Review, Vol. 147 (4), 321-348.

Latinobarometro (2015), Latinobarometro 2015 (database), (accessed 1 March 2017).

Lehman, H. and A. Muravyev (2012), “Labor market institutions and informality in transition and Latin American Countries”, in Frölich, M. et al. (eds), Social Insurance ad Labor Markets: How to Protect Workers while Creating Good Jobs, Oxford University Press.

Lustig, N. (2017), “El impacto del sistema tributario y el gasto social en la distribución del ingreso y la pobreza en América Latina: Argentina, Bolivia, Brasil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras, México, Nicaragua, Perú, República Dominicana, Uruguay y Venezuela” (“The impact of the tax system and social spending on income distribution and poverty in Latin America: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaaragua, Dominican Republic, Uruguay and Venezuela), in CEQ Working Paper No. 62, Commitment to Equity Institute, Tulane University, February.

ManPower Group (2016), Talent Shortage Survey Research Results, ManPowerGroup, Milwaukee, Wisc.

Metzler, J. and L. Woessmann (2012), “The impact of teacher subject knowledge on student achievement: Evidence from within-teacher within-student variation”, Journal of Development Economics, Vol. 99/2, pp. 486-496.

Mizala, A. and H.R. Nopo (2012), “Evolution of teachers’ salaries in Latin America at the turn of the 20th Century: How much are they (under or over) paid?”, Discussion Paper, No. 6806, Institute for the Study of Labor (IZA), Bonn.

OECD (2016a), Income Distribution Database (IDD), (accessed 1 March 2017).

OECD (2016b), OECD Social Expenditure (database),

OECD (2016c), OECD Employment Outlook 2016, OECD Publishing, Paris,

OECD (2015), OECD Employment Outlook 2015, OECD Publishing, Paris,

OECD (2014), OECD Employment Outlook 2014, OECD Publishing, Paris,

OECD (2012), Closing the Gender Gap: Act Now, OECD Publishing, Paris.

OECD (2010a), PISA 2009 Results: What Students Know and Can Do: Student Performance in Reading, Mathematics and Science (Volume I), OECD Publishing, Paris,

OECD (2010b), PISA 2009 Results: Equity in Learning Opportunities and Outcomes (Volume II), OECD Publishing, Paris,

OECD/CAF/ECLAC (2016), Latin American Economic Outlook 2017: Youth, Skills and Entrepreneurship, OECD Publishing, Paris,

OECD/CAF/ECLAC (2015), Latin American Economic Outlook 2016: Towards a New Partnership with China, OECD Publishing, Paris,

OECD/CAF/ECLAC (2014), Latin American Economic Outlook 2015: Education, Skills and Innovation for Development, OECD Publishing, Paris,

OECD/CIAT/IDB (2016), Taxing Wages in Latin America and the Caribbean, OECD Publishing, Paris,

OPHI (2017), “Panama Launches its First Multidimensional Poverty Index (MPI) and Adopts the Annual Measurement” available in

Palardy, G.J. and R.W. Rumberger (2008), “Teacher effectiveness in first grade: The importance of background qualifications, attitudes, and instructional practices for student learning”, Educational Evaluation and Policy Analysis, Vol. 30/2,

Schwab (2016), “Employment protection and the labour information of the youth: Evidence from India”, Institute for Economic Development Working Papers Series from Boston University Department of Economics, No. dp-280, Boston University, Department of Economics, Boston,

Tsounta, E. and A.I. Osueke (2014), “What is behind Latin America’s declining income inequality?”, International Monetary Fund Working Paper, No. WP/14/24, IMF, Washington, DC.

UN (2015), Millennium Development Goals Indicators (database), UN Department of Economic and Social Affairs, Statistics Division, United Nations, New York,

UN (2014), World Urbanization Prospects, 2014 Revision, UN Department of Economic and Social Affairs, Population Division, United Nations, New York.

UNESCO (2016), Education (database), UNESCO Institute for Statistics, Montreal (accessed 1 March 2017).

UNESCO (2015a), Informe de Resultados TERCE. Tercer Estudio Regional Comparativo y Explicativo. Factores Asociados (TERCE Results Report: Third Regional Comparative and Explanatory Study, Associated Factors), UNESCO, Santiago de Chile.

UNESCO (2015b), Data to Transform Lives: Education and Literacy (database), UNESCO Institute for Statistics, Montreal, (accessed 1 March 2017).

UNICEF (2010), La Educación en Panamá: 5 Metas para Mejorar, (Education in Panama: 5 Goals to Improve), UNICEF, Panama,

WHO/UNICEF (2015), Joint Monitoring Programme (JMP) for Water Supply and Sanitation (database), (accessed 1 February 2017).

World Bank (2017), World Bank World Development Indicators (database), Washington, DC. (accessed 1 March 2017).

World Bank (2016a), ASPIRE: The Atlas of Social Protection Indicators of Resilience and Equity (database), World Bank, (accessed 1 March 2017).

World Bank (2016b), Implementation Completion Report (ICR) Review, World Bank Group, Washington, DC.

World Bank (2015a), “Locking in success: A, systematic country diagnostic”, World Bank Group, Washington, DC,

World Bank (2015b), Social protection for the harder road ahead: Containing the social costs of lower growth in Latin America and the Caribbean, World Bank Group, Washington, DC,

World Bank (2013), “Shifting gears to accelerate shared prosperity in Latin America and the Caribbean”, Latin America and the Caribbean Poverty and Labor Brief, June, World Bank, Washington, DC.

World Bank (2010), World Bank Enterprise Survey 2010 (database), World Bank, Washington, DC, (accessed 1 March 2017).

World Economic Forum (2017), Global Competitiveness Report 2016-2017, World Economic Forum (WEF), Geneva,


← 1. The education dimension contributes to 23.9% of the total MPI percentage, employment follows with 20.9%, environment, neighbourhood and sanitation 20.7%, housing, basic services and internet access 19.8% and, finally, health with 14.7%.

← 2. The growth-inequality decomposition introduced by Datt and Ravallion (1992) quantifies the relative contributions of economic growth and redistribution to changes in poverty. With this methodology, the change in a poverty measure (e.g. headcount index, poverty gap, or poverty gap squared) is decomposed into three components: growth, redistribution and the residual.

← 3. Panamá Oeste is the newest province in Panama. It was created from the five districts of Panamá Province west of the Panama Canal on 1 January 2014.

← 4. Panama’s participation in PISA tests is only comparable for the year 2009. The country is currently part of the PISA for Development Programme. First results for the country should be available in 2018.