Poverty, vulnerability, and the middle class in Latin America

Abstract

Between 2000 and 2013, Latin America has considerably reduced poverty (from 46.3 to 29.7 % of the population). In this paper, we use synthetic panels to show that, despite progress, the region remains characterized by substantial vulnerability that also affects the rising middle class. More specifically, we find that 65 % of those with daily income between $4 and 10, and 14 % of those in the middle class experience poverty at least once over a 10-year period. Furthermore, chronic poverty remains widespread (representing 91 and 50 % of extreme and moderate poverty, respectively). Differences between rural and urban areas are substantial. Urban areas, which are now home to most moderate poor and vulnerable, are characterized by higher income mobility, particularly upward mobility. These findings have important implications for the design of effective social safety nets. These need to mix long-term interventions for the chronic poor, especially in rural areas, with flexible short-term support to a large group of transient poor and vulnerable, particularly in urban areas.

1 Introduction

In recent years, Latin America has made remarkable progress in the reduction of poverty and inequality. Between 2000 and 2013, the percentage of the population living on less than $2.5 per capita per day decreased from 28.8 to 15.9 %, while the share of the population living on less than $4 dropped from 46.3 to 29.7 %. Over the same period, the region has also managed to reduce its unfortunately distinctive inequality: the Gini coefficient of the income distribution fell from 0.57 to 0.51.

These improvements were largely driven by sustained economic growth, which led to an expansion of the middle class.¹ However, despite these positive trends, the region is still home to 92 million extreme poor and 77 million moderate poor. In addition, most of those that exited poverty joined the vulnerable class and are still at substantial risk of falling into poverty (Fig. 1).

Fig. 1

Income distribution in Latin America (2000–2013), region aggregate

The trends in the incidence and depth of poverty, however, do not fully capture poverty dynamics, i.e., its duration and how often families enter and exit poverty. This information is very important for the design of effective social safety nets, particularly as far as targeting and recertification are concerned.² Frequent movements in and out of poverty imply the need for flexible safety net entry and exit rules.

The analysis of poverty dynamics and income mobility in developing countries has received relatively limited attention, largely due to the lack of adequate longitudinal data.³ Recently, Ferreira et al. (2013) and Vakis et al. (2015) have analyzed intra-generational mobility in Latin America, with a focus, respectively, on the middle class and the chronic poor. Their analysis is based on the synthetic panel methodology developed by Dang et al. (2014), which is the same we employ in this paper. The two works construct two-period transition matrices [1995–2010 in Ferreira et al. (2013), 2004–2012 in Vakis et al. (2015)] and define the chronic poor as those that were poor in both years. The analysis only captures mobility from the first period to the last period, and not yearly mobility in between the two. Consequently, it depicts the vulnerable and the middle class as consolidated in their position (with a low probability of experiencing poverty).

In this paper, we generate 10-year synthetic panels for a large sample of Latin American countries, and use them to estimate yearly movements in and out of poverty from 2003 to 2013. We provide a novel classification of households based on poverty duration, which distinguishes chronic poor, transient poor, future poor, and never poor. The future poor include those that initially belonged to the vulnerable, middle, and high-income classes, and experienced poverty at any time over the following decade.

We find that 65 % of the vulnerable (i.e., those with daily income between $4 and 10), and 14 % of those in the middle class (with daily income between $10 and 50) of 2003, experienced poverty at least once during the period 2004–13. At the same time, chronic poverty remains widespread, accounting for 91 and 50 % of extreme and moderate poverty, respectively. Differences between rural and urban areas are substantial. Urban areas, which are now home to most moderate poor and vulnerable, are characterized by higher (particularly upward) income mobility.

The remainder of the paper is organized as follows. Section 2 defines poverty and vulnerability, and describes the data and the methodology employed for constructing synthetic panels and forecasting poverty dynamics. Section 3 presents the trends in poverty reduction and shows that the Latin American region is highly heterogeneous in the stage and speed of the socioeconomic transition towards the middle class. Section 4 analyzes poverty dynamics, including transition matrices and poverty duration, and discusses household characteristics of chronic and transient poor. Section 5 highlights the main differences between urban and rural poverty. Section 6 concludes summarizing key findings and policy implications. Along the paper, we discuss the policy implications of the findings for the design and implementation of the social safety nets, with a particular focus on the targeting and recertification processes.⁴

Six annexes provide additional information on data, methods, sensitivity analyses, and country results. Annex 1 lists the data sources. Annex 2 summarizes the existing literature comparing results from genuine panel data with non-parametric, parametric, and point estimate synthetic-panel methods. Annex 3 shows the bounds of selected estimates, providing a visual representation of the quality of our results. Annex 4 presents sensitivity analyses of key chronic poverty results to the adoption of alternative poverty lines. Annex 5 shows that the variation in the share of urban population is limited between 2003 and 2013, which is necessary for the validity of the rural/urban breakdown of the dynamic analyses based on the pseudo panel methodology. Finally, Annex 6 presents country-specific poverty profiles.

2 Data and methodology

Non-technical readers can skip this section with no prejudice to their ability to understand the rest of the paper.

We look at poverty through two lenses, one that focuses on depth and the other on duration. The former is static, and analyzes a picture of poverty through the value of daily per-capita income (expressed in 2005 dollars adjusted to reflect purchasing power parity). It divides the population in five groups: (i) the extreme poor, with income below $2.5; (ii) the moderate poor, between $2.5 and 4; (iii) the vulnerable, between $4 and 10; (iv) the middle class, between $10 and 50 [as in López-Calva and Ortiz-Juárez (2011)]; and (v) the high-income class, above $50.

The $2.5 line corresponds to the median of the official extreme poverty lines in Latin American countries (CEDLAS and World Bank 2012), and has already been used in regional studies (World Bank 2014). It is higher than the international extreme poverty line of $1.25 used by Ravallion et al. (2008), which corresponds to the mean of the official extreme poverty lines of the 15 poorest countries in the world. The use of a higher line reflects the relatively more advanced stage of socioeconomic development (and the higher price levels) of the Latin American region. Similar considerations hold for the $4 poverty line. The vulnerable class is defined by López-Calva and Ortiz-Juárez (2011), as having a per capita daily income between $4 and 10, which is empirically observed to imply a probability greater than 10 % of falling into poverty.

The second lens is dynamic and focuses on the duration of poverty. It divides the population in four groups: (i) the chronic poor, that are poor (either extreme or moderate) in the first year of analysis, and in five or more years over the following decade;⁶ (ii) the transient poor, that are poor in the first year, and again in four or less years over the following decade; (iii) the future poor, that are either vulnerable, middle class, or high income in the first year of analysis, but experience poverty in at least 1 year during the following 10 years; (iv) the never poor, who are always above the $4 poverty line.

Conditioning the definition of chronic and transient poverty on being poor in the first year guarantees that the sum of extreme and moderate poverty equals the sum of chronic and transient poverty. In other words, the incidence of poverty does not change, no matter if one looks at it through the lenses of depth or through those of duration.

The analysis focusing on the static definition of poverty is based on observed micro-data from 216 cross-sectional household surveys collected between 2000 and 2013 in 18 Latin American countries (see Annex 1).⁷ These data are from IDB’s Harmonized Data Bank of Household Surveys from Latin America and the Caribbean (also known as IDB’s Sociometro). Regional estimates of the incidence of poverty are obtained by imputing missing values for years with no survey, then calculating population-weighted averages of country estimates.

The data are representative both at the national level and at the urban–rural level, with the exception of Argentina, Uruguay, and Venezuela. In Argentina, the household survey is only urban. In Uruguay, rural areas have been surveyed only since 2006; we restrict the analysis to urban areas to ensure comparability over the period 2000–2013. In Venezuela, since 2004, the survey does not contain a variable that allows separating rural and urban areas.

Given the unavailability of real-panel data sets, in which the same households are surveyed across time, the analysis of poverty duration is based on the construction of synthetic panels a la Dang et al. (2014).⁸ This method was originally designed to analyze transitions in and out of poverty based on two (or more) rounds of cross-sectional data. In addition, the literature, so far, has focused on proving the reliability of the methodology (Cruces et al. 2011; Fields and Viollaz 2013; Haynes et al. 2013). Our objective is slightly different, as we aim to investigate poverty duration, or more specifically in how many years a family has been poor over a decade. For this purpose, we calculate yearly point estimates of per-capita income based on yearly cross-sectional data.⁹

The sample is made of families surveyed in the first year (t = 0). For each of the following 10 years (s = 1,10), we estimate per-capita income using time-invariant variables observed in t = 0, coefficients estimated in t = s, and empirical residuals.¹⁰ The methodology assumes a linear structure of the income equation, and is based on the following two assumptions: (i) households do not change, which ensures that time-invariant variables observed in t = 0 can be used to estimate income in t = s, and (ii) the correlation of the error terms across time ($\varepsilon_{t = 0}$ and ɛ _t=s ) is not negative. This is a reasonable assumption given that income shocks show persistence over time, and factors leading to a negative correlation of income over time are unlikely to apply to all households at the same time. The methodology requires estimating the following equations:

$$y_{i,t} = \beta^{\prime}_{t} x_{i,t} + \varepsilon_{i,t} \quad {\text{for }}t = 0,10$$

(1)

i.e., for the first period and for the following 10 years, where y _i,t is the logarithm of household i’s per-capita income at time t, and x _i,t is a vector of variables measuring household i’s characteristics at time t. Our specification of the model includes variables typically employed in the literature (Dang et al. 2014; Cruces et al. 2011), plus statistically significant variables at the regional level. The vector x contains the following variables:

• (i) Household head characteristics: sex, age, age squared, years of schooling, years of schooling squared, and agricultural work;

• (ii) Region (first-level administrative country subdivision) characteristics: average years of schooling of the household heads, and proportion of workers in agriculture;

• (iii) Geographic controls: rural–urban residence;

• (iv) Retrospective regressors at regional level in the initial year (2003): inequality (standard deviation of log income), extreme poverty headcount ($2.5 a day), average per capita income, average household size, and average years of schooling of the household heads.

The regressions produce 11 estimates of vectors β and ε ($\hat{\beta }_{t}$ and $\hat{\varepsilon }_{t}$, one for each time period). They also produce 11 estimates of the error term variance ($\hat{\sigma }_{{\varepsilon_{t} }}$). These parameters are used to produce the synthetic-panel estimates of yearly per-capita income.

Following Cruces et al. (2011), Fields and Viollaz (2013), and Haynes et al. (2013), we use the “non-parametric” version of the method, i.e., we make no assumptions on the structural form of the joint distribution of the errors terms. Two extreme assumptions on the non-parametric time correlation of the error terms lead to a lower and upper bound estimate of per-capita income mobility. At one extreme, one can assume zero correlation between $\varepsilon_{t = 0}$ and ɛ _t=s , i.e., that the two error terms are independent from each other. The logarithm of per capita income of household i in t = s ($\hat{y}_{i,t = s}^{U}$) is estimated as follows:

$$\hat{y}_{i,t = s}^{U} = \hat{\beta }_{t = s}^{'} x_{i,t = 0} + \hat{\tilde{\varepsilon }}_{i,t = s}$$

(2)

where the apex U indicates uncorrelated error terms, and $\hat{\tilde{\varepsilon }}_{i,t = s}$ is the mean of 50 random draws (with replacement) from the vector of estimated residuals in t = s. At the other extreme, one can assume perfect correlation between $\varepsilon_{t = 0}$ and ɛ _t=s . Under this assumption, the logarithm of per capita income of household i in t = s ($\hat{y}_{i,t = s}^{C}$) is estimated as follows:

$$\hat{y}_{i,t = s}^{C} = \hat{\beta }_{t = s}^{'} x_{i,t = 0} + \gamma \hat{\varepsilon }_{i,t = 0}$$

(3)

where the apex C indicates correlated error terms, $\hat{\varepsilon }_{i,t = 0}$ is (the time-invariant) household i’s empirical error term estimated in t = 0, and $\gamma = \hat{\sigma }_{{\varepsilon_{t = 0} }} /\hat{\sigma }_{{\varepsilon_{t = s} }}$. is a scale factor.

Dang et al. (2014) and Cruces et al. (2011) show that: (i) Eq. (2) produces upper-bound estimates of income mobility, due to the high variation in the error term, and overestimates people’s movements in and out of poverty; (ii) Eq. (3) produces lower-bound estimates of income mobility, due to the constant error term, and underestimates poverty transitions; and (iii) the average of (2) and (3) approximates well the observed income mobility, providing a satisfactory estimation of movements in and out of poverty. This last point is proved empirically by comparing synthetic-panel estimates of mobility with those observed in genuine panel data. We, therefore, calculate point estimates of per-capita income of the households in the synthetic-panel as follows:¹¹Recently, Dang and Lanjouw (2013) have developed a point estimate synthetic panel approach, which generalizes the use of non-parametric and parametric methods to produce point estimates of poverty transitions. This could have been used, as alternative to Eq. (4), to produce the estimates of poverty duration presented in this paper. We preferred to rely on Eq. (4), because the two methods have been shown to be empirically equivalent in terms of accuracy, and because Dang and Lanjouw (2013) indicate that the point-estimate methodology is most accurate when short time periods are analyzed. The existing literature comparing results from genuine panel data with non-parametric, parametric, and point estimate synthetic-panel methods is summarized in Annex 2.

$$\hat{y}_{i,t = s} = \hat{\beta }_{t = s}^{'} x_{i,t = 0} + \frac{{\left( {\hat{\tilde{\varepsilon }}_{i,t = s} + \gamma \hat{\varepsilon }_{i,t = 0} } \right)}}{2}.$$

(4)

As a result, our analysis of income mobility is based on income observed in 2003 along with income estimated for the years between 2004 and 2013. The quality of the predictions is essential to guarantee that results are credible. As is usual practice, we carefully ensured the quality of the fit (value of R-squared, significance of coefficients, over-fitting). In Annex 3, we show for selected countries that the upper and lower bounds of predicted incomes produce poverty rates that are very close to the rates directly observed from household surveys. We also show the bounds for the estimates of chronic poverty, transient poverty, and future poverty in selected countries.

Our methodology can only be applied to 12 countries that have household survey data for each year between 2003 and 2013 (Argentina, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Honduras, Panama, Paraguay, Peru, El Salvador, and Uruguay). Regional numbers were obtained pooling micro-data from the 12 countries and using survey weights.¹²

3 Static analysis: an heterogeneous and still vulnerable region

Latin America is a very heterogeneous region in terms of the stage of socioeconomic transition, defined as the process of transition out of poverty towards the middle class. Countries such as Argentina, Chile, and Uruguay, are at an advanced stage, being mainly made of middle and high-income class (with the incidence of poverty around 10 %). On the other hand, countries such as Guatemala and Honduras, are at the earliest stages: almost half of their population still lives in extreme poverty, and the incidence of overall poverty exceeds 65 % (Table 1).

Table 1 Income distribution in Latin American countries (2000–2013).

One feature, however, is common to all countries: the large size of the vulnerable class. This represents in most cases 30–40 % of the population, suggesting that an important share of the population remains at substantial risk of falling into poverty. Countries with low poverty rates and large middle classes are no exception. In these countries, the vulnerable class is the back end of the socioeconomic transition; while in the poorest countries, the vulnerable class leads the way.

Country heterogeneity is also high in the speed of the socio-economic transition. For example, Colombia and Ecuador reduced the incidence of poverty by more than 25 percentage points (pp), and expanded their middle and upper classes by more than 15 pp (Table 1). In contrast, progress was sluggish in Mexico and Dominican Republic, despite the fact that these countries started from poverty headcounts around 40 %.

Table 2 summarizes the region’s heterogeneity by classifying the Latin American countries based on the stage and speed of their socioeconomic transition. In the countries in the upper-left cell, for example, Nicaragua and El Salvador, the poor still represents the largest share of the population, and poverty reduction has been relatively slow (less than 25 % between 2000 and 2013). These are the countries with the highest need for reforming and/or expanding the social safety net, as poverty is widespread and resilient. These are also the countries with less financial resources for its implementation, so efficiency should be at the top of their policy agenda.

Table 2 Categorization of Latin American countries, by income distribution and poverty reduction (2000–2013).

4 Dynamic analysis: poverty is still largely chronic

Income mobility between 2003 and 2013 was considerable. Poverty reduction was the net effect of many exiting poverty, while fewer were falling back. Upward mobility was particularly high for those that started in moderate poverty.

Most of the moderate poor rose to the vulnerable class, and a few (6 %) made it to the middle class (Table 3).¹³ In contrast, 73 % of those that were initially extreme poor were still poor after a decade, although many enjoyed less severe poverty and another quarter rose to the vulnerable class. As may be expected (as they started from higher initial living standards), also the vulnerable enjoyed less upper mobility. Only 28 % of them rose to the middle class, while 62 % remained in the initial income category and 10 % fell into poverty.

Table 3 Poverty transition matrix in Latin America (2003–2013), region aggregate.

Chronic poverty was widespread among both the extreme and the moderate poor. Many of those that were initially moderate poor, despite enjoying a high likelihood of rising to the vulnerable class in 2013, were poor in at least 5 years over the period 2004–2013. This may be explained by an ascending trajectory that only rose above the poverty line in the last part of the period of analysis.

On average, 91 % of extreme poverty were chronic (Table 4), with very little country heterogeneity (Fig. 2). In almost all countries with available data, about 90 % or more of the extreme poor in 2003 remained poor in at least five of the following 10 years. The only exceptions were Argentina and Uruguay, for which data are urban only.

Table 4 Poverty duration in Latin America (2003–2013), region aggregate.

Fig. 2

Chronic poverty in Latin American countries (2003–2013)

More surprisingly, also half of the moderate poor in 2003 was chronically poor.¹⁴ This has important implications for the design and implementation of the social safety nets. In particular, it implies that long-term interventions are not only needed for the extreme poor, but also for an important share of those in moderate poverty. In this respect, however, country heterogeneity was substantial (Fig. 2). For example, while extreme poverty was equally chronic in Ecuador and Colombia, in the former moderate poverty was much more transient than in the latter.

An important share of the vulnerable and, more surprisingly, of the middle class experienced poverty over the period 2004–13. More precisely, 65 % of the vulnerable group and 14 % of the middle class of 2003 were poor at least once over the following decade. We call these families “future poor”, a group whose share ranged from 10 % of the population in Argentina to 38 % in Costa Rica (Fig. 3). Finally, the share of the population that was never poor ranged from 8 % in Honduras to 57 % in Uruguay (Fig. 3).

Fig. 3

Poverty dynamics in Latin American countries (2003–2013)

The identification of the chronic and transient poor in the samples of 2003 allows investigating the household characteristics that are associated with different poverty durations. In other words, it allows studying who are the chronic poor, how they differ from the transient poor and, for comparison, from the non-poor. We address these questions by looking at Paraguay and Honduras, two countries at different stages of the socio-economic transition.

Household characteristics of the chronic poor broadly mimic those that, in the literature, are commonly associated with extreme poverty. They include larger household size, more children, lower levels of education, more engagement in self-employment, less wage employment, and residence in rural areas. Table 5 reports average household characteristics by dynamic poverty status in Paraguay and Honduras. Despite a few differences between the two countries, most patterns are common and the similarities are striking. In both countries, for example, chronically poor households had no member with complete tertiary education. In Honduras, they did not even have any member with complete secondary education; while in Paraguay, only one in six chronically poor households had one member with this level of schooling. Their likelihood to live in rural areas was ten times higher than among the non-poor. Self-employment decreased and wage employment grew as one moved from chronic poverty to non-poverty. The low level of human capital and the remote location suggest that, at least among the chronic poor, the graduation strategies with which many Latin American countries are attempting to complement the social safety nets have low probability of being successful.

Table 5 Household Characteristics in Paraguay and Honduras (2003), by Poverty Status.

5 Differences between urban and rural areas

The region has undergone a process of urbanization, which has been slowing down in recent years. The urban share of the population has been growing from 49 % in 1960 to 80 % in 2013, and is expected to reach 83 % in 2025 (ECLAC 2013). In our sample of countries, this figure has increased from 72 % in 2000 to 74 % in 2013 (Table 6, panel B). In this context, it is extremely important to understand the different urban–rural trends in poverty reduction, as when it comes to poverty, cities and countryside remain two worlds apart.¹⁵

Table 6 Geographic profile of poverty in Latin America (2000–2013), region aggregate.

Extreme and overall poverty have decreased substantially in both urban and rural areas. Yet, in the latter, one-third of the population still lives in extreme poverty, and the incidence of total poverty exceeds 50 % (Table 6, panel A).

The growth of a middle class is an eminently urban phenomenon. In rural areas, poverty reduction has been accompanied by an expansion of the vulnerable class, and only 13 % of the population had per-capita income above $10 in 2013. In contrast, the size of the vulnerable class remained fairly constant in urban areas. This is where the middle class expanded more rapidly (by over 10 pp).

As a result, the rural nature of poverty has intensified, with a substantial increase of the share of poor living in rural areas. While in 2000 the rural areas were home to 54 % of the extreme poor and 30 % of the moderate poor, these figures increased to 58 and 38 %, respectively, in 2013. In addition, the rural share of vulnerable expanded, and only the high-income class became more urban during the period of analysis.

In 2013, the majority of the extreme poor lived in urban areas only in four countries (Brazil, Chile, Colombia and Dominican Republic). In contrast, with few exceptions, moderate poverty was fairly equally distributed between urban and rural areas (Fig. 4). This suggests that long-term social safety net programs are best suited for rural areas, while short-term interventions are equally needed in urban and rural areas.

Fig. 4

Rural percentage of poverty and population in Latin American countries (2013)

In the near future, in urban areas, poverty is expected to leave way to a rising middle class (Fig. 5). This forecast is obtained by combining economic growth and demographic projections with the estimated growth elasticity of poverty. While the size of the vulnerable class will remain fairly stable (at around 40 % of the urban population), by 2025 the incidence of urban poverty is expected to fall to 13 %. The middle class will rise to represent 42 % of the urban population.

Fig. 5

Poverty, vulnerability, and middle class in Latin America (2000–2025), region aggregate

In contrast, the growth of the middle class will be slow in rural areas. Poverty will be mostly replaced by vulnerability. The vulnerable class is expected to become the single largest group in 2021, and grow to 47 % of the rural population in 2025.

Failing to account for substantial rural to urban migration may bias the results of the poverty dynamic analysis based on the pseudo-panel methodology (which assumes that household characteristics, including residence in rural or urban areas, are constant over time). For example, one may overestimate the number of poverty episodes in rural areas, if some rural families have migrated to urban areas and have managed, through migration, to transition to the vulnerable class. The direction of the bias will depend on who migrates (usually not the poorest) and how migration affects their income.

In Annex 5, we analyze the variation in the proportion of urban population over the period 2003–2013. We show that its magnitude is small, and does not threaten the validity of our findings. This result is consistent with the slowdown in the process of urbanization documented in CELADE—Population Division of ECLAC (2015).

The urban and rural poverty dynamics analyses confirm that most of the mobility out of poverty took place in urban areas. In the cities, 35 % of the extreme poor and 73 % of the moderate poor in 2003 had exited poverty after 10 years, against only 15 and 53 % in rural areas (Table 7). A similar pattern can be observed for upward mobility from the vulnerable class. Symmetrically, the risk of falling from the middle class to the vulnerable class or into poverty was more than double in rural than in urban areas (44 versus 21 %). This may also be due to the differential urban–rural impacts of the world recession in the second part of the period of analysis.

Table 7 Urban and rural poverty transition matrices in Latin America (2003–2013), region aggregate.

Rural areas are characterized by high incidence of chronic poverty and future poverty. 99 % of the extreme poor and 78 % of those that were moderate poor in 2003 experienced chronic poverty between 2004 and 2013. Furthermore, 86 % of the vulnerable and 37 % of the middle class were poor at least once during the period of analysis. The picture is relatively rosier in urban areas, where “only” 86 % of extreme poverty and 42 % of moderate poverty were chronic, and where “only” 62 % of the vulnerable experienced at least one episode of poverty (Fig. 6).

Fig. 6

Urban and rural poverty dynamics in Latin America (2003–2013), region aggregate

Cross-country analysis shows that Ecuador and Panama present the widest gap between rural and urban areas, a result that is driven by the highly transient nature of urban moderate poverty. Variability is limited in the percentage of extreme poor that are chronic poor, both in rural and urban areas. More differences emerge when looking at the percentage of moderate poor that experience chronic poverty. This is, particularly, the case in urban areas. While in El Salvador 71 % of urban moderate poor experience chronic poverty over the following decade, the same happens to only one every five urban moderate poor in Ecuador and Panama. This indicates that in these countries, urban moderate poverty is particularly transient (Fig. 7). Complete data by country is presented in Annex 6, for the 12 countries for which we can construct synthetic panels.

Fig. 7

Urban and rural chronic poverty in Latin American countries (2003–2013)

6 Conclusions and implication for the design and implementation of social safety nets

In the absence of information on poverty dynamics, development practitioners frequently assume that extreme poverty is chronic and rural, while moderate poverty is transient and urban. Similarly, they tend to expect that the vulnerable are at risk of falling into poverty, while the middle class has reached a safe place and no longer needs a social safety net.

In this paper, we construct synthetic panels and analyze poverty dynamics for a large sample of Latin American countries, with the aim to provide policy makers and development practitioners (engaged in project design) with estimates of the duration of poverty. While the availability of real long panel data would allow refining and deepening the analysis, we believe that our results constitute a useful proxy and hope they will stimulate further data collection and research. Our analysis contributes to debunking a few common assumptions.

First, we show that chronic poverty is widespread also among the moderate poor. This type of poverty, characterized by long duration, accounts for 91 % of extreme poverty and, surprisingly, 50 % of moderate poverty. As expected, chronic poverty is more frequent in rural areas, where 99 % of the extreme poor and as many as 78 % of the moderate poor are chronic poor.

Second, we show that also the middle class is still exposed to a substantial risk of falling back into poverty. More specifically, we find that 14 % of those that belonged to the middle class in 2003 experienced at least one poverty episode during the following decade.

Our results differ from those of Ferreira et al. (2013) and Vakis et al. (2015), although they are based on the application of a similar synthetic panel methodology. These authors analyze mobility between two periods only, and find that the vulnerable and the middle class are more consolidated in their status. For example, Ferreira et al. (2013, Table 4.1) estimate that only 2.7 % of the vulnerable and 0.5 % of the middle class fall back into poverty.

Our findings have important implications for the design and implementation of social safety nets. First, they suggest that interventions that target the rural poor and the urban extreme poor need to adopt a long-term perspective. The frequent recertification of the beneficiaries might not be needed and, probably, represents a loss of administrative and financial resources.

Second, our findings suggest that interventions that target the urban moderate poor need to adopt flexible entry and exit rules in response to this group’s high income mobility. Targeting mechanisms based on proxy means tests are unlikely to perform satisfactorily. The Brazilian model based on declared income may represent a better alternative, if it can be coupled with frequent recertification and electronic audits of eligibility based on crossing information from the roster of beneficiaries with other sources of administrative data (e.g., social security contributions, ownership of assets).

Third, we show that the chronic poor have extremely low levels of human capital and live in rural areas with limited opportunity of wage employment. These are key factors for escaping poverty. Consequently, our findings suggest that, at least for this group, graduation strategies aimed at increasing income-generation capacity have low probabilities of success.¹⁶

Finally, the finding that both the vulnerable and the middle class are likely to experience poverty in the future implies that the social safety nets remain relevant for many that are currently out of poverty.¹⁷

A caveat is worth mentioning. Our dynamic analysis is based on 12 countries for which data are available. Further work is needed to incorporate results for more countries and increase the representativeness of our findings.

Appendices

Annex 1: Data sources

IDB’s Harmonized Data Bank of Household Surveys from Latin America and the Caribbean (also known as IDB’s Sociometro) contains harmonized household data sets for Latin American and Caribbean countries starting from the late 1980s. Variable names, definitions, and contents are kept constant across countries and time. Table 8 shows the number of data sets used for the preparation of this paper.

Table 8 Data sets used in this paper, by Country, 2000–2013

Although it is well known that per-capita consumption is a better proxy for well-being, we use per-capita income, because few countries in the region routinely conduct surveys with a consumption module, while all of them include questions on income. We calculate per-capita income by dividing total household income by the number of household members, without using any adult equivalence scale.

Income components are reported after-tax whenever possible. Extraordinary income sources are not considered. Similarly, we do not include the implicit rent from owned or occupied housing, because not all countries capture the information that allows estimating it.¹⁸ As is common practice in academic and official studies, we do not make any imputation for missing, null or outlying values in addition to those already contained in the data sets provided by the national statistical offices. Finally, we do not make adjustments for differences in urban–rural prices.

Annex 2: Synthetic-panel methodology

Table 9 summarizes the existing literature comparing results from genuine panel data with non-parametric, parametric, and point estimate synthetic-panel methods. All results reported are based on the use of household time-invariant characteristics, sub-national controls, and region fixed effects, consistently with the definition of our own model. They show that the estimates based on the average of the bounds (Eq. (4)) approximate well the estimates based on genuine panel data, irrespective of the length of the period analyzed (2 years in Peru, versus 10 in Chile), the width of the bounds, the type of poverty transition, and the number of replications used to obtain the upper bound (50, 100, 500). These estimates are found to be as accurate as those obtained with either the parametric approach (for Indonesia and Vietnam) or the point estimate approach (Bosnia-Herzegovina).

Table 9 Summary of the literature comparing estimates from synthetic and genuine panel data

Annex 3: Estimate bounds

See Figs. 8, 9, 10.

Fig. 8

Observed versus predicted extreme poverty headcounts in selected countries

Fig. 9

Observed versus predicted poverty headcounts in selected countries

Fig. 10

Bounds for the estimates of transient poverty, chronic poverty and future poverty in selected LAC countries

Annex 4: Sensitivity analysis of the percentage of chronic poverty to the adoption of alternative poverty lines

Poverty lines are defined with a degree of arbitrariness. To show that our findings are robust to the adoption of alternative poverty lines, we perform sensitivity analysis of our key chronic poverty results. In Sect. 4, we showed that chronic poverty accounted for 91 % of extreme poverty and 50 % of moderate poverty. This occurs when using a 2.5$ extreme poverty line and a 4$ moderate poverty line. In Figs. 11 and 12, we verify how these findings change when considering poverty lines that are 20 % lower or higher.

Fig. 11

Percentage of extreme poor that are chronic poor, sensitivity analysis to the adoption of alternative poverty lines

Fig. 12

Percentage of moderate poor that are chronic poor, sensitivity analysis to the adoption of alternative poverty lines

With lower poverty lines, i.e., using a 2$ extreme poverty line and a 3.2$ moderate poverty line, we find that chronic poverty accounted for 87 % of extreme poverty and 41 % of moderate poverty. With higher poverty lines, i.e., using a 3$ extreme poverty line and a 4.8$ moderate poverty line, chronic poverty accounted for 94 % of extreme poverty and 58 % of moderate poverty.

Overall, the higher the poverty lines, the higher are the percentages of both extreme and moderate poverty that are found to be chronic. The result is less sensitive for extreme than for moderate poverty. Finally, different poverty lines do not alter the order of magnitude of our key results, nor country rankings.

Annex 5: Variation in the percentage of urban population

As a proxy for rural to urban migration, we test whether the percentage of urban population has changed significantly over the period 2003–2013, which is the timeframe of our poverty dynamics analysis. Given the large size of our samples, the standard error of each sample mean tends to be very close to zero. As a consequence, the t test is likely to reject the null hypothesis of means equality even when the difference is trivial (producing type I–false positive–errors).

We, therefore, adopt an alternative hypothesis testing framework by conducting an effect size type analysis, in which the measure of statistical difference is the standard deviation (which is not shrunk by definition by the size of the sample). Specifically, we use the Cohen’s d indicator (Cohen 1988), which is equal to the difference between the two sample means, divided by the standard deviation of the pooled samples. Cohen explains that absolute values of d around 0.2 reflect a small effect size, while 0.5 is a medium effect size and 0.8 indicates a large effect size. The last column of Table 10 shows that the absolute values of Cohen’s d are all smaller than 0.2 in our sample of countries, suggesting that rural-to-urban migration is not likely to threaten the validity of our poverty dynamic results.

Table 10 Effect size analysis of the variation in the percentage of urban population.

Annex 6: Country profiles

Country profiles—Argentina.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	–	–	–	–	–	–
Urban	14.9	15.4	36.5	31.3	2.0	100.0
Rural	–	–	–	–	–	–
Incidence in 2013—total	–	–	–	–	–	–
Urban	4.0	6.9	34.4	52.5	2.2	100.0
Rural	–	–	–	–	–	–
Share rural in 2000	–	–	–	–	–	–
Share rural in 2013	–	–	–	–	–	–
Transition probabilities—total
Extreme poverty	–	–	–	–	–	–
Moderate poverty	–	–	–	–	–	–
Vulnerable class	–	–	–	–	–	–
Middle class	–	–	–	–	–	–
High income	–	–	–	–	–	–
Transition probabilities—urban
Extreme poverty	5.9	20.5	63.7	7.3	2.7	100.0
Moderate poverty	0.5	2.0	65.2	31.2	1.2	100.0
Vulnerable class	0.1	0.6	27.2	71.1	1.0	100.0
Middle class	0.0	0.1	2.6	90.7	6.7	100.0
High income	0.0	0.0	0.0	33.3	66.7	100.0
Transition probabilities—rural
Extreme poverty	–	–	–	–	–	–
Moderate poverty	–	–	–	–	–	–
Vulnerable class	–	–	–	–	–	–
Middle class	–	–	–	–	–	–
High income	–	–	–	–	–	–
% of chronic poverty—total	–	–				–
Urban	45.7	1.2				27.7
Rural	–	–				–
% future poor—total			–	–	–	–
Urban			25.6	2.5	0.0	16.3
Rural			–	–	–	–

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	11.1	29.0	9.8	50.1	100.0
Male household head	0.476	0.483	0.507	0.476	0.481
Household size	6.222	5.294	4.389	3.577	4.448
Number of children (aged 0–5)	1.096	0.709	0.524	0.284	0.521
Adult members
Self-employed	0.348	0.342	0.349	0.309	0.327
Salaried	1.060	1.147	1.372	1.233	1.202
Unemployed	0.538	0.388	0.205	0.178	0.282
Inactive	0.851	0.980	0.854	0.825	0.876
Primary education or less	0.527	0.355	0.321	0.144	0.265
Incomplete secondary educ.	0.759	0.725	0.632	0.386	0.550
Complete secondary educ.	0.298	0.495	0.537	0.582	0.521
Incomplete tertiary educ.	0.136	0.250	0.263	0.514	0.371
Complete tertiary educ.	0.025	0.122	0.113	0.512	0.306
Rural (share)	–	–	–	–	–

1. – Not available

Country Profiles—Brazil.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2001—total	27.1	16.8	32.5	21.3	2.3	100.0
Urban	21.9	16.6	34.5	24.4	2.7	100.0
Rural	54.3	18.3	21.9	5.3	0.3	100.0
Incidence in 2013—total	10.4	10.8	38.5	36.7	3.6	100.0
Urban	7.5	9.6	38.6	40.2	4.1	100.0
Rural	26.5	17.5	37.6	17.8	0.6	100.0
Share rural in 2001	32.4	17.6	10.9	4.0	2.1	16.2
Share rural in 2013	39.3	24.9	15.1	7.5	2.4	15.4
Transition probabilities—total
Extreme poverty	36.2	37.0	26.0	0.7	0.0	100.0
Moderate poverty	5.9	23.7	65.9	4.5	0.0	100.0
Vulnerable class	1.3	6.6	67.7	24.4	0.0	100.0
Middle class	0.1	0.8	22.1	75.6	1.4	100.0
High income	0.0	0.0	0.7	64.9	34.4	100.0
Transition probabilities—urban
Extreme poverty	31.8	38.1	29.2	0.8	0.0	100.0
Moderate poverty	5.7	23.1	66.5	4.6	0.0	100.0
Vulnerable class	1.2	6.4	67.3	25.1	0.0	100.0
Middle class	0.1	0.7	21.6	76.2	1.4	100.0
High income	0.0	0.0	0.7	64.7	34.6	100.0
Transition probabilities—rural
Extreme poverty	45.4	34.7	19.4	0.5	0.0	100.0
Moderate poverty	6.6	26.3	63.4	3.7	0.0	100.0
Vulnerable class	1.7	8.6	71.7	18.0	0.0	100.0
Middle class	0.4	1.9	35.2	62.3	0.1	100.0
High income	0.0	0.0	0.0	79.9	20.1	100.0
% of chronic poverty—total	94.6	51.3				77.8
Urban	92.8	48.2				73.4
Rural	98.4	65.6				89.8
% future poor—total			65.2	11.5	0.3	42.1
Urban			63.5	11.0	0.3	40.0
Rural			79.1	23.0	0.0	67.5

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	27.5	10.0	25.0	37.5	100.0
Male household head	0.495	0.496	0.487	0.487	0.490
Household size	4.872	4.289	3.661	3.471	3.986
Number of children (aged 0–5)	0.784	0.426	0.315	0.211	0.416
Adult members
Self-employed	0.423	0.354	0.401	0.349	0.383
Salaried	0.786	0.945	1.189	1.197	1.057
Unemployed	0.171	0.215	0.121	0.107	0.139
Inactive	0.652	0.912	0.633	0.735	0.704
Primary education or less	1.323	1.196	1.156	0.694	1.033
Incomplete secondary educ.	0.107	0.179	0.191	0.159	0.155
Complete secondary educ.	0.134	0.397	0.477	0.753	0.478
Incomplete tertiary educ.	0.007	0.057	0.082	0.570	0.242
Complete tertiary educ.	0.000	0.001	0.002	0.052	0.020
Rural (share)	0.310	0.123	0.125	0.044	0.145

Country Profiles—Colombia. Source: authors’ calculations based on household survey data from IDB’s Sociometro

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	40.1	19.5	26.7	12.7	1.0	100.0
Urban	30.3	20.2	31.8	16.5	1.3	100.0
Rural	66.2	17.8	13.3	2.5	0.1	100.0
Incidence in 2013—total	18.6	15.4	36.7	27.2	2.2	100.0
Urban	11.4	13.2	39.2	33.4	2.8	100.0
Rural	42.3	22.7	28.4	6.6	0.1	100.0
Share rural in 2000	45.2	25.0	13.7	5.4	3.5	27.4
Share rural in 2013	53.2	34.5	18.1	5.7	1.0	23.4
Transition probabilities—total
Extreme poverty	49.7	29.4	19.2	0.6	1.0	100.0
Moderate poverty	12.6	29.9	53.4	3.3	0.8	100.0
Vulnerable class	3.5	12.6	59.1	23.7	1.0	100.0
Middle class	0.3	0.9	24.1	70.8	3.9	100.0
High income	0.0	0.0	0.0	25.8	74.2	100.0
Transition probabilities—urban
Extreme poverty	35.9	35.4	27.0	1.0	0.7	100.0
Moderate poverty	9.4	24.2	61.1	4.6	0.8	100.0
Vulnerable class	2.6	10.4	59.5	26.4	1.1	100.0
Middle class	0.2	0.8	23.0	72.0	4.1	100.0
High income	0.0	0.0	0.0	29.7	70.3	100.0
Transition probabilities—rural
Extreme poverty	67.6	21.6	9.2	0.1	1.5	100.0
Moderate poverty	20.7	44.8	33.6	0.0	0.9	100.0
Vulnerable class	9.6	27.1	56.6	6.4	0.2	100.0
Middle class	3.8	3.4	51.5	41.3	0.0	100.0
High income	0.0	0.0	0.0	3.9	96.1	100.0
% of chronic poverty—total	93.0	59.4				80.4
Urban	88.9	46.8				70.7
Rural	98.3	91.8				96.5
% future poor—total			74.5	23.5	0.6	56.0
Urban			71.7	22.7	0.7	53.0
Rural			92.2	44.4	0.0	81.2

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	45.0	11.0	24.7	19.4	100.0
Male household head	0.743	0.810	0.712	0.791	0.752
Household size	5.814	5.194	4.603	3.928	5.082
Number of children (aged 0–5)	0.986	0.773	0.458	0.384	0.716
Adult members
Self-employed	0.944	0.774	0.770	0.476	0.792
Salaried	0.466	0.811	1.056	1.198	0.791
Unemployed	0.326	0.447	0.290	0.245	0.315
Inactive	0.947	0.813	0.875	0.753	0.877
Primary education or less	0.887	0.372	0.466	0.122	0.578
Incomplete secondary educ.	0.559	0.755	0.663	0.376	0.571
Complete secondary educ.	0.381	0.925	0.823	0.780	0.627
Incomplete tertiary educ.	0.040	0.157	0.253	0.513	0.197
Complete tertiary educ.	0.017	0.084	0.150	0.737	0.196
Rural (share)	0.453	0.068	0.153	0.045	0.258

Country Profiles—Costa Rica.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	15.2	14.9	40.6	28.1	1.3	100.0
Urban	8.7	11.6	40.0	37.9	1.9	100.0
Rural	24.5	19.5	41.4	14.3	0.4	100.0
Incidence in 2013—total	8.5	10.6	37.7	39.2	4.0	100.0
Urban	5.1	7.1	34.0	48.1	5.8	100.0
Rural	14.0	16.4	43.8	24.7	1.1	100.0
Share rural in 2000	66.5	54.0	42.1	21.0	11.8	41.3
Share rural in 2013	62.8	59.0	44.3	24.1	10.9	38.2
Transition probabilities—total
Extreme poverty	42.7	20.2	33.9	2.1	1.1	100.0
Moderate poverty	26.8	19.2	40.9	11.9	1.3	100.0
Vulnerable class	10.0	13.8	42.2	33.1	0.8	100.0
Middle class	1.2	3.4	22.1	66.6	6.6	100.0
High income	0.0	0.4	0.7	49.2	49.7	100.0
Transition probabilities—urban
Extreme poverty	30.1	21.4	43.5	3.3	1.7	100.0
Moderate poverty	14.1	16.9	50.3	17.3	1.3	100.0
Vulnerable class	4.8	8.6	42.2	43.8	0.6	100.0
Middle class	0.8	1.9	17.7	71.5	8.1	100.0
High income	0.0	0.5	0.5	44.5	54.5	100.0
Transition probabilities—rural
Extreme poverty	48.3	19.7	29.6	1.6	0.8	100.0
Moderate poverty	35.5	20.7	34.4	8.2	1.3	100.0
Vulnerable class	17.0	20.8	42.2	18.9	1.0	100.0
Middle class	2.7	8.4	37.4	49.7	1.8	100.0
High income	0.0	0.0	1.5	73.3	25.2	100.0
% of chronic poverty—total	89.8	58.3				74.4
Urban	78.1	38.5				56.0
Rural	95.1	71.9				84.6
% future poor—total			73.4	30.0	3.4	53.1
Urban			63.3	23.9	3.1	41.8
Rural			86.9	50.9	4.5	75.6

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	21.6	7.4	37.7	33.3	100.0
Male household head	0.740	0.745	0.786	0.798	0.777
Household size	5.426	5.216	4.542	4.183	4.664
Number of children (aged 0–5)	0.825	0.735	0.473	0.379	0.537
Adult members
Self-employed	0.331	0.329	0.322	0.283	0.311
Salaried	0.668	0.778	1.295	1.411	1.160
Unemployed	0.190	0.178	0.111	0.080	0.123
Inactive	1.203	1.102	0.972	0.910	1.011
Primary education or less	0.803	0.484	0.480	0.137	0.436
Incomplete secondary educ.	0.416	0.826	0.900	1.029	0.833
Complete secondary educ.	0.008	0.031	0.046	0.073	0.045
Incomplete tertiary educ.	0.034	0.119	0.215	0.677	0.322
Complete tertiary educ.	0.002	0.023	0.060	0.325	0.133
Rural (share)	0.732	0.387	0.477	0.175	0.425

Country Profiles—Dominican Republic.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	24.0	17.7	34.9	21.9	1.4	100.0
Urban	17.6	15.1	38.1	27.3	1.9	100.0
Rural	35.5	22.5	29.3	12.3	0.5	100.0
Incidence in 2013—total	22.7	20.7	38.7	17.2	0.8	100.0
Urban	18.5	18.7	40.3	21.5	1.1	100.0
Rural	31.3	24.7	35.6	8.4	0.0	100.0
Share rural in 2000	53.1	45.5	30.1	20.2	11.5	35.9
Share rural in 2013	45.1	39.0	29.9	15.8	1.4	32.6
Transition probabilities—total
Extreme poverty	50.5	34.7	14.7	0.1	0.0	100.0
Moderate poverty	13.9	36.4	48.1	1.5	0.0	100.0
Vulnerable class	2.8	16.5	69.4	11.1	0.1	100.0
Middle class	0.1	2.2	42.4	53.8	1.6	100.0
High income	0.0	0.0	3.7	83.2	13.0	100.0
Transition probabilities—urban
Extreme poverty	45.2	36.8	17.8	0.1	0.0	100.0
Moderate poverty	10.3	34.4	53.3	2.0	0.0	100.0
Vulnerable class	2.3	14.4	70.1	13.1	0.1	100.0
Middle class	0.1	2.2	39.9	55.9	1.9	100.0
High income	0.0	0.0	1.6	84.8	13.6	100.0
Transition probabilities—rural
Extreme poverty	57.6	31.9	10.4	0.1		100.0
Moderate poverty	21.5	40.7	37.2	0.6		100.0
Vulnerable class	4.3	22.5	67.6	5.6		100.0
Middle class	0.0	2.0	55.2	42.7		100.0
High income	0.0	0.0	56.3	43.7		100.0
% of chronic poverty—total	97.9	65.8				85.1
Urban	96.9	56.0				78.9
Rural	99.2	86.2				94.8
% future poor—total			82.0	21.9	0.2	62.6
Urban			78.3	17.9	0.2	56.9
Rural			92.7	42.7	0.0	81.8

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	42.6	7.5	31.3	18.7	100.0
Male household head	0.492	0.464	0.507	0.489	0.494
Household size	5.100	5.110	4.345	4.086	4.675
Number of children (aged 0–5)	0.820	0.654	0.517	0.405	0.635
Adult members
Self-employed	0.579	0.556	0.712	0.477	0.600
Salaried	0.542	0.851	0.967	1.208	0.822
Unemployed	0.132	0.184	0.114	0.101	0.125
Inactive	1.251	1.170	0.879	0.781	1.041
Primary education or less	1.189	0.949	0.984	0.398	0.959
Incomplete secondary educ.	0.353	0.486	0.461	0.325	0.391
Complete secondary educ.	0.218	0.425	0.397	0.517	0.345
Incomplete tertiary educ.	0.079	0.245	0.233	0.485	0.216
Complete tertiary educ.	0.025	0.187	0.129	0.764	0.208
Rural (share)	0.411	0.150	0.269	0.127	0.294

Country Profiles—Ecuador.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	40.8	20.8	27.5	10.1	0.9	100.0
Urban	30.5	21.0	33.4	13.8	1.3	100.0
Rural	59.0	20.3	17.0	3.4	0.3	100.0
Incidence in 2013—total	13.4	16.4	42.0	26.8	1.4	100.0
Urban	7.9	13.3	43.0	33.9	1.9	100.0
Rural	24.8	22.7	40.1	12.0	0.4	100.0
Share rural in 2000	52.0	35.1	22.2	12.0	11.2	35.9
Share rural in 2013	60.3	45.1	31.0	14.6	8.2	32.6
Transition probabilities—total
Extreme poverty	34.4	36.6	28.5	0.4	0.1	100.0
Moderate poverty	4.5	22.3	67.1	6.1	0.0	100.0
Vulnerable class	1.0	5.7	63.7	29.5	0.0	100.0
Middle class	0.1	0.5	18.2	78.8	2.4	100.0
High income	0.0	0.0	0.2	71.9	27.9	100.0
Transition probabilities—urban
Extreme poverty	24.1	36.7	38.4	0.7	0.2	100.0
Moderate poverty	3.0	16.7	71.9	8.4	0.0	100.0
Vulnerable class	0.5	3.6	61.2	34.8	0.0	100.0
Middle class	0.1	0.4	16.2	80.7	2.7	100.0
High income	0.0	0.0	0.2	71.2	28.6	100.0
Transition probabilities—rural
Extreme poverty	43.2	36.5	20.0	0.2	0.0	100.0
Moderate poverty	7.1	32.1	58.7	2.1	0.0	100.0
Vulnerable class	2.7	12.7	71.9	12.7	0.0	100.0
Middle class	0.1	1.5	39.3	59.1	0.0	100.0
High income	0.0	0.0	0.0	81.8	18.2	100.0
% of chronic poverty—total	87.5	38.1				69.6
Urban	75.5	18.8				50.6
Rural	97.8	71.5				90.4
% future poor—total			59.1	11.7	0.0	43.0
Urban			49.9	9.5	0.0	34.5
Rural			88.7	34.4	0.0	80.0

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	37.4	16.4	19.9	26.3	100.0
Male household head	0.491	0.467	0.484	0.499	0.488
Household size	6.077	5.738	5.027	4.437	5.380
Number of children (aged 0–5)	1.061	0.856	0.573	0.444	0.768
Adult members
Self-employed	0.635	0.585	0.640	0.526	0.599
Salaried	0.759	1.103	1.361	1.358	1.093
Unemployed	0.114	0.181	0.084	0.108	0.117
Inactive	0.994	1.090	0.872	0.825	0.941
Primary education or less	0.705	0.391	0.462	0.146	0.458
Incomplete secondary educ.	0.402	0.708	0.550	0.427	0.488
Complete secondary educ.	0.209	0.605	0.550	0.760	0.487
Incomplete tertiary educ.	0.065	0.275	0.277	0.683	0.304
Complete tertiary educ.	0.014	0.100	0.101	0.522	0.179
Rural (share)	0.619	0.150	0.349	0.066	0.343

Country Profiles—Honduras.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2001—total	47.4	15.5	25.0	11.6	0.5	100.0
Urban	21.7	18.2	38.0	21.1	1.1	100.0
Rural	69.3	13.2	13.9	3.5	0.1	100.0
Incidence in 2013—total	49.5	17.0	24.9	8.5	0.2	100.0
Urban	27.5	18.8	37.9	15.3	0.5	100.0
Rural	69.2	15.3	13.3	2.3	0.0	100.0
Share rural in 2001	78.9	45.8	30.0	16.4	8.6	53.9
Share rural in 2013	73.7	47.6	28.1	14.1	0.0	52.7
Transition probabilities—total
Extreme poverty	89.0	8.0	2.6	0.0	0.4	100.0
Moderate poverty	46.6	29.3	22.6	0.8	0.7	100.0
Vulnerable class	21.1	25.7	48.2	4.6	0.4	100.0
Middle class	3.2	8.6	46.0	41.1	1.1	100.0
High income	0.0	0.0	6.3	40.6	53.1	100.0
Transition probabilities—urban
Extreme poverty	68.4	22.1	9.1	0.0	0.5	100.0
Moderate poverty	33.3	34.6	29.5	1.3	1.3	100.0
Vulnerable class	13.8	24.4	55.2	6.2	0.4	100.0
Middle class	2.4	6.8	45.3	44.2	1.3	100.0
High income	0.0	0.0	6.3	52.4	41.3	100.0
Transition probabilities—rural
Extreme poverty	94.8	4.1	0.7	0.0	0.4	100.0
Moderate poverty	64.6	22.2	13.1	0.0	0.0	100.0
Vulnerable class	40.5	29.3	29.3	0.5	0.3	100.0
Middle class	9.5	23.4	52.6	14.5	0.0	100.0
High income	0.0	0.1	6.4	3.2	90.3	100.0
% of chronic poverty—total	98.7	77.3				94.0
Urban	95.5	65.1				82.6
Rural	99.6	93.7				98.8
% future poor—total			89.4	42.9	3.6	74.6
Urban			86.2	38.3	2.7	69.1
Rural			98.2	82.1	6.5	93.4

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	64.3	4.1	23.6	8.0	100.0
Male household head	0.774	0.759	0.748	0.787	0.769
Household size	6.489	5.753	4.781	4.310	5.881
Number of children (aged 0–5)	1.280	0.925	0.598	0.419	1.035
Adult members
Self-employed	0.890	0.487	0.512	0.335	0.739
Salaried	0.462	0.870	1.204	1.452	0.734
Unemployed	0.192	0.374	0.224	0.223	0.209
Inactive	1.177	1.153	1.014	0.931	1.117
Primary education or less	0.706	0.280	0.353	0.107	0.557
Incomplete secondary educ.	0.549	1.095	0.834	0.694	0.651
Complete secondary educ.	0.191	0.580	0.590	0.793	0.350
Incomplete tertiary educ.	0.038	0.170	0.232	0.572	0.132
Complete tertiary educ.	0.009	0.038	0.090	0.491	0.068
Rural (share)	0.779	0.231	0.381	0.100	0.608

Country Profiles—Panama.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	23.7	14.8	34.0	25.2	2.2	100.0
Urban	11.0	13.1	37.7	34.9	3.3	100.0
Rural	45.4	17.6	27.7	8.9	0.4	100.0
Incidence in 2013—total	15.6	11.1	36.1	34.7	2.6	100.0
Urban	5.0	7.8	38.2	45.3	3.7	100.0
Rural	36.4	17.5	31.9	13.8	0.5	100.0
Share rural in 2000	70.9	44.1	30.2	13.1	6.2	37.0
Share rural in 2013	78.6	53.2	29.8	13.4	6.2	33.7
Transition probabilities—total
Extreme poverty	35.6	31.5	31.4	1.5	0.0	100.0
Moderate poverty	3.1	17.1	69.9	9.8	0.0	100.0
Vulnerable class	0.8	4.0	56.1	39.0	0.1	100.0
Middle class	0.1	0.3	12.9	84.0	2.7	100.0
High income	0.0	0.0	0.1	59.6	40.3	100.0
Transition probabilities—urban
Extreme poverty	14.8	31.9	49.8	3.5	0.0	100.0
Moderate poverty	2.2	13.3	72.6	11.9	0.0	100.0
Vulnerable class	0.6	2.8	53.8	42.8	0.0	100.0
Middle class	0.0	0.1	11.6	85.3	3.0	100.0
High income	0.0	0.0	0.1	58.9	41.0	100.0
Transition probabilities—rural
Extreme poverty	43.2	31.3	24.7	0.8	0.0	100.0
Moderate poverty	4.4	21.8	66.5	7.3	0.0	100.0
Vulnerable class	1.5	7.1	62.1	29.2	0.1	100.0
Middle class	0.1	1.3	22.5	74.9	1.2	100.0
High income	0.0	0.0	0.0	74.1	25.9	100.0
% of chronic poverty—total	91.1	40.2				72.3
Urban	71.7	18.9				42.8
Rural	98.2	66.5				89.8
% future poor—total			59.1	10.8	0.1	37.2
Urban			50.0	8.1	0.1	28.9
Rural			83.1	30.0	0.0	69.3

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	29.3	11.2	22.1	37.4	100.0
Male household head	0.487	0.465	0.505	0.485	0.487
Household size	5.931	5.976	5.114	4.644	5.274
Number of children (aged 0–5)	0.885	0.685	0.505	0.392	0.594
Adult members
Self-employed	0.973	0.805	0.780	0.591	0.768
Salaried	0.461	0.848	1.268	1.499	1.071
Unemployed	0.080	0.165	0.150	0.118	0.119
Inactive	0.716	1.403	0.974	1.078	0.985
Primary education or less	0.803	0.262	0.401	0.115	0.396
Incomplete secondary educ.	0.428	0.512	0.470	0.237	0.376
Complete secondary educ.	0.458	1.174	1.104	0.957	0.868
Incomplete tertiary educ.	0.096	0.310	0.368	0.543	0.347
Complete tertiary educ.	0.080	0.375	0.540	1.248	0.652
Rural (share)	0.598	0.043	0.102	0.012	0.207

Country Profiles—Peru.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	34.8	18.2	34.3	12.4	0.4	100.0
Urban	14.6	20.2	46.7	18.0	0.5	100.0
Rural	72.4	14.4	11.3	1.9	0.0	100.0
Incidence in 2013—total	19.3	13.7	40.5	25.7	0.8	100.0
Urban	9.2	11.8	45.6	32.4	1.0	100.0
Rural	49.9	19.5	25.0	5.6	0.1	100.0
Share rural in 2000	72.7	27.7	11.6	5.3	0.0	35.0
Share rural in 2013	64.4	35.3	15.4	5.4	4.0	24.9
Transition probabilities—total
Extreme poverty	52.4	26.2	18.2	0.5	2.7	100.0
Moderate poverty	6.3	21.9	62.8	6.8	2.2	100.0
Vulnerable class	1.4	6.6	62.9	28.2	1.0	100.0
Middle class	0.4	0.6	21.7	74.9	2.3	100.0
High income	0.0	0.0	0.1	69.5	30.5	100.0
Transition probabilities—urban
Extreme poverty	28.1	31.5	32.7	0.9	6.8	100.0
Moderate poverty	4.2	16.3	68.3	8.5	2.7	100.0
Vulnerable class	1.1	5.7	62.3	29.8	1.1	100.0
Middle class	0.5	0.6	21.2	75.5	2.3	100.0
High income	0.0	0.0	0.0	69.5	30.5	100.0
Transition probabilities—rural
Extreme poverty	67.4	22.9	9.3	0.2	0.2	100.0
Moderate poverty	13.0	40.3	44.9	1.2	0.5	100.0
Vulnerable class	3.7	16.5	69.6	10.3	0.0	100.0
Middle class	0.0	4.3	50.6	45.1	0.0	100.0
High income	0.0	0.0	20.1	70.5	9.4	100.0
% of chronic poverty—total	94.1	55.0				81.8
Urban	85.4	43.6				65.4
Rural	99.5	92.0				98.4
% future poor—total			73.6	27.2	1.0	58.9
Urban			71.6	26.4	1.0	56.6
Rural			94.7	66.8	0.0	92.3

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	46.3	10.3	25.6	17.9	100.0
Male household head	0.506	0.516	0.513	0.483	0.505
Household size	6.663	6.461	5.023	4.662	5.865
Number of children (aged 0–5)	1.219	1.060	0.619	0.483	0.917
Adult members
Self-employed	1.019	0.683	0.785	0.448	0.823
Salaried	0.454	0.991	1.103	1.484	0.859
Unemployed	0.149	0.342	0.156	0.158	0.172
Inactive	0.908	0.985	0.760	0.838	0.865
Primary education or less	1.243	0.551	0.781	0.248	0.876
Incomplete secondary educ.	0.464	0.969	0.706	0.649	0.611
Complete secondary educ.	0.151	0.582	0.457	0.822	0.393
Incomplete tertiary educ.	0.043	0.152	0.280	0.659	0.225
Complete tertiary educ.	0.000	0.021	0.046	0.414	0.088
Rural (share)	0.676	0.112	0.391	0.077	0.438

Country Profiles—Paraguay.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	30.6	14.7	33.3	19.8	1.6	100.0
Urban	11.2	12.5	42.6	31.0	2.7	100.0
Rural	54.2	17.4	22.0	6.2	0.3	100.0
Incidence in 2013—total	15.9	14.0	38.5	30.1	1.5	100.0
Urban	6.6	10.5	40.5	40.3	2.0	100.0
Rural	30.1	19.4	35.4	14.5	0.6	100.0
Share rural in 2000	79.8	53.3	29.7	14.0	7.2	45.0
Share rural in 2013	74.9	54.7	36.4	19.1	17.5	39.6
Transition probabilities—total
Extreme poverty	31.9	34.3	32.1	1.5	0.2	100.0
Moderate poverty	4.5	15.2	67.8	12.3	0.2	100.0
Vulnerable class	1.1	4.1	62.0	32.6	0.3	100.0
Middle class	0.0	0.6	14.5	83.2	1.7	100.0
High income	0.0	0.0	2.1	47.9	50.0	100.0
Transition probabilities—urban
Extreme poverty	15.5	30.2	51.1	3.0	0.2	100.0
Moderate poverty	1.7	7.9	72.2	18.1	0.1	100.0
Vulnerable class	0.9	2.1	56.7	39.8	0.4	100.0
Middle class	0.0	0.2	10.2	87.5	2.0	100.0
High income	0.0	0.0	0.0	48.9	51.1	100.0
Transition probabilities—rural
Extreme poverty	39.8	36.2	22.9	0.8	0.2	100.0
Moderate poverty	8.4	25.2	61.8	4.3	0.3	100.0
Vulnerable class	1.3	8.1	72.7	17.7	0.1	100.0
Middle class	0.0	1.9	30.4	67.3	0.4	100.0
High income	0.0	0.0	8.7	44.9	46.4	100.0
% of chronic poverty—total	96.4	61.0				83.2
Urban	90.6	39.7				64.4
Rural	99.2	90.1				96.7
% future poor—total			84.3	40.6	13.8	67.6
Urban			77.8	29.8	9.9	58.1
Rural			97.8	80.1	26.0	91.3

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	43.1	8.7	32.6	15.6	100.0
Male household head	0.482	0.384	0.468	0.466	0.466
Household size	6.021	5.289	4.898	4.206	5.308
Number of children (aged 0–5)	1.014	0.826	0.613	0.496	0.786
Adult members
Self-employed	0.522	0.426	0.544	0.400	0.502
Salaried	0.832	1.021	1.199	1.292	1.040
Unemployed	0.091	0.078	0.068	0.054	0.076
Inactive	1.245	1.109	0.949	0.816	1.069
Primary education or less	0.987	0.503	0.678	0.293	0.736
Incomplete secondary educ.	0.506	0.744	0.703	0.532	0.595
Complete secondary educ.	0.184	0.594	0.496	0.680	0.399
Incomplete tertiary educ.	0.049	0.193	0.218	0.543	0.194
Complete tertiary educ.	0.010	0.077	0.066	0.367	0.090
Rural (share)	0.633	0.076	0.303	0.065	0.388

Country Profiles—El Salvador.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	30.1	18.2	33.9	17.3	0.6	100.0
Urban	14.1	16.2	42.0	26.8	0.9	100.0
Rural	53.9	21.1	21.8	3.1	0.0	100.0
Incidence in 2013—total	21.6	21.2	41.4	15.4	0.3	100.0
Urban	10.6	18.5	48.4	22.1	0.5	100.0
Rural	40.5	25.9	29.5	4.0	0.1	100.0
Share rural in 2000	72.0	46.8	25.9	7.3	2.6	40.3
Share rural in 2013	69.2	45.1	26.3	9.6	6.8	36.9
Transition probabilities—total
Extreme poverty	61.8	30.0	8.0	0.1	0.1	100.0
Moderate poverty	19.9	42.3	37.1	0.6	0.0	100.0
Vulnerable class	4.4	19.6	69.2	6.9	0.0	100.0
Middle class	0.6	3.1	47.3	48.7	0.3	100.0
High income	0.0	0.9	3.3	90.7	5.0	100.0
Transition probabilities—urban
Extreme poverty	40.2	44.1	15.6	0.1	0.0	100.0
Moderate poverty	12.7	39.8	46.4	1.0	0.0	100.0
Vulnerable class	2.9	14.4	73.7	9.0	0.0	100.0
Middle class	0.5	2.5	45.1	51.6	0.4	100.0
High income	0.0	1.0	1.0	92.4	5.6	100.0
Transition probabilities—rural
Extreme poverty	72.4	23.1	4.3	0.1	0.1	100.0
Moderate poverty	27.8	45.1	26.9	0.3	0.0	100.0
Vulnerable class	8.2	33.5	57.0	1.3	0.0	100.0
Middle class	1.7	7.7	62.6	27.9	0.1	100.0
High income	0.0	0.0	23.7	76.3	0.0	100.0
% of chronic poverty—total	98.9	83.5				92.6
Urban	96.7	70.9				83.3
Rural	99.9	97.3				99.1
% future poor—total			84.7	29.5	6.5	66.7
Urban			79.9	25.5	5.1	59.9
Rural			97.6	57.4	18.6	90.3

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	43.4	3.5	35.5	17.7	100.0
Male household head	0.797	0.730	0.725	0.718	0.755
Household size	6.570	5.940	5.095	4.594	5.676
Number of children (aged 0–5)	1.200	1.024	0.680	0.494	0.884
Adult members
Self-employed	0.775	0.589	0.536	0.305	0.600
Salaried	0.720	1.152	1.274	1.444	1.059
Unemployed	0.079	0.214	0.103	0.157	0.106
Inactive	1.139	1.063	0.900	0.979	1.023
Primary education or less	1.128	0.603	0.666	0.262	0.793
Incomplete secondary educ.	0.239	0.934	0.967	1.098	0.673
Complete secondary educ.	0.005	0.032	0.059	0.120	0.046
Incomplete tertiary educ.	0.010	0.099	0.167	0.602	0.173
Complete tertiary educ.	0.003	0.016	0.036	0.383	0.083
Rural (share)	0.737	0.138	0.283	0.058	0.435

Country Profiles—Uruguay.

	Extreme poverty	Moderate poverty	Vulnerable class	Middle class	High income	Total
Incidence in 2000—total	–	–	–	–	–	–
Urban	4.8	9.1	37.4	45.8	2.9	100.0
Rural	–	–	–	–	–	–
Incidence in 2013—total	–	–	–	–	–	–
Urban	3.9	6.0	30.2	56.6	3.3	100.0
Rural	–	–	–	–	–	–
Share rural in 2000	–	–	–	–	–	–
Share rural in 2013	–	–	–	–	–	–
Transition probabilities—total
Extreme poverty	–	–	–	–	–	–
Moderate poverty	–	–	–	–	–	–
Vulnerable class	–	–	–	–	–	–
Middle class	–	–	–	–	–	–
High income	–	–	–	–	–	–
Transition probabilities—urban
Extreme poverty	5.9	26.9	65.3	1.8	0.1	100.0
Moderate poverty	1.0	7.1	79.6	12.3	0.0	100.0
Vulnerable class	0.0	1.2	49.6	49.1	0.1	100.0
Middle class	0.0	0.0	7.6	89.5	2.9	100.0
High income	0.0	0.0	0.0	44.7	55.3	100.0
Transition probabilities—rural
Extreme poverty	–	–	–	–	–	–
Moderate poverty	–	–	–	–	–	–
Vulnerable class	–	–	–	–	–	–
Middle class	–	–	–	–	–	–
High income	–	–	–	–	–	–
% of chronic poverty—total						–
Urban	51.9	6.4				25.2
Rural	–	–				–
% future poor—total			–	–	–	–
Urban			31.4	2.3	–	19.2
Rural			–	–	–	–

	Chronic poor	Transient poor	Future poor	Never poor	Total
% of population	7.3	21.7	13.6	57.3	100.0
Male household head	0.718	0.782	0.727	0.735	0.743
Household size	5.527	5.216	3.985	3.344	3.998
Number of children (aged 0–5)	1.045	0.776	0.339	0.211	0.412
Adult members
Self-employed	0.535	0.436	0.385	0.291	0.353
Salaried	0.685	0.971	1.099	1.057	1.017
Unemployed	0.492	0.487	0.334	0.208	0.307
Inactive	0.756	0.897	0.816	0.910	0.883
Primary education or less	0.535	0.361	0.380	0.209	0.289
Incomplete secondary educ.	0.701	1.093	0.985	0.786	0.873
Complete secondary educ.	0.045	0.143	0.188	0.373	0.274
Incomplete tertiary educ.	0.015	0.058	0.066	0.250	0.166
Complete tertiary educ.	0.004	0.017	0.037	0.308	0.186
Rural (share)	–	–	–	–	–