Executive summary

1.Assessing the Trends of Growth, Inequality, and Poverty in PanamA - 1997-2003

1.1This chapter examines changes in growth, inequality, and poverty in Panama. Over the years 1997-2003, the fraction of the population living below the moderate poverty line was essentially unchanged, while extreme poverty fell slightly, as did inequality. Considering the substantial growth in national income that took place during the period, the changes in poverty were puzzling. The difference reflects a divergence between GDP growth in the National Accounts and consumption growth as measured in household surveys. During 1997-2003, rural areas saw substantial drops in poverty, which may reflect recent gains in education levels. National extreme poverty fell as a consequence of rural growth and rural-to-urban migration. The situation for indigenous areas, by far the poorest regions of the country, grew worse during this period. In 2003, 42 percent of the extreme poor lived in indigenous areas, although they are home to just 8 percent of the overall population. The great concentration of extreme poor in indigenous zones suggests that anti-poverty efforts should focus on those areas.

1.2As in many countries, the GDP growth figures for Panama are at odds with estimates of growth in household consumption derived from survey data. Because these differences necessarily enter into the question of how growth and poverty reduction are related, the first part of this chapter explores the potential sources of these differences. The disconnect between GDP growth and poverty is due to the fact that changes of consumption levels in household surveys, on which poverty estimates are based, differ markedly from GDP growth rates based on National Accounts data. During 1997-2003, GDP per capita grew by an annual rate of 1.5 percent per person while consumption as measured in household surveys fell by 0.7 percent per year. The analysis finds that the differences are most likely due to measurement error and/or differences of coverage for specific sectors between the survey and National Accounts. The remainder of the chapter is based entirely on consumption data from the survey.

1.3The second section of the chapter presents several diagnostics to consider the relationship between poverty, growth, and inequality from various angles. These analyses include the following: (i) a decomposition of changes in poverty into growth and inequality, (ii) a decomposition of poverty changes by urban and rural sectors, (iii) growth incidence curves; and (iv) a poverty simulation analysis to assess the likely trajectory of poverty rates under different growth and redistribution scenarios. We also estimate the elasticity of poverty to growth.

1.4The overall pattern observed in Panama is one of convergence between the rural and urban sectors. Pro-poor growth in rural Panama reduced the ranks of the poor and particularly the extreme poor, while in urban areas the combination of stagnant growth and a small increase in inequality caused poverty rates to grow. Indigenous areas remained by far the poorest in the country, with the vast majority of their residents living well below the extreme poverty line. The poverty elasticity estimates imply that growth in Panama leads to substantial drops in poverty. The simulation exercise shows that under an optimistic scenario of sustained annual growth per capita of three percent, with no increase in inequality, the extreme poverty rate would drop from its 2003 level of 16.6 percent to 9.7 percent in 2015.

Annual Growth Rates: How Well Do the Survey and National Accounts Agree?

1.5The poverty and inequality analysis in this report is based primarily on consumption data from the 1997 and 2003 ENV surveys. For a variety of reasons, consumption is generally preferred to income for the analysis of household welfare in developing countries (see Box 1.1). Macroeconomic growth data comes from a different source: the National Accounts. Panama’s National Accounts (NAS) include estimates of GDP and private consumption for the nation as a whole. Table 1.1 shows estimates of annual growth rates of various consumption and income figures, calculated from the ENV surveys and the national accounts. Growth rates are shown both for national totals and for the measures calculated on a per capita basis.⁶

1.6The Table 1.1 illustrates two points. First, there are huge differences between growth rates shown in the survey and those in the NAS. NAS growth rates for private consumption and GDP are far higher than those for both consumption and income in the survey. The NAS show very rapid growth in private consumption, while the survey shows a decline in consumption, calculated on a per capita basis. Second, in the survey by itself, income and consumption show markedly different growth rates. On a per capita basis, survey-based consumption declined by 0.7 percent, while income grew slightly, by 0.3 percent.

Table 1.1: Annual Growth Rate, 1997-2003

Source: National Accounts, Contraloria General de la Republica de Panama. Note: Own estimate based on ENV 1997 and 2003 data.

1.7NAS and survey-based measures may differ for a variety of reasons. Across countries, it is often the case that household survey-based measures of consumption and income differ greatly from measures based on the National Accounts (see Figure A1.1.2 in Annex 1.1).⁷ Reasons for differences include underestimation of consumption/income in the household survey, measurement error in the National Accounts, and differences in coverage and accounting practices between the two sources. On the whole, these factors are likely to result in downward biases in survey measures and upwards biases in national accounts. Deaton (2005) found that consumption measured from household surveys grows less rapidly than consumption measured in national accounts, both in the world as a whole and in large countries.

Box 1.1 Measuring Welfare in Panama The welfare measure used in Panama and throughout this study is per capita consumption. Consumption is preferred over income as a measure of household welfare for several reasons. First, consumption tends to be less variable than income over the course of time (due to consumption smoothing) and thus provides a better measure of long-term welfare. Second, household surveys in developing countries typically measure consumption more accurately than income. Third, consumption of the household’s own production, which is often a large portion of consumption for agricultural households, is usually not captured well (if at all) in income data. Ignoring home-produced food would greatly understate the consumption levels of rural households. In this report, consumption includes; (i) the value of all food consumption, whether the food is purchased, home produced or received as a gift or donation; (ii) the use value of durable goods, (iii) the use value of housing, (iv) expenditures on utilities, (v) expenditures for education, (vi) health expenditures, and (vii) expenditures on other consumption items and services. Total household consumption is divided by the number of household members to provide the per capita consumption measure of welfare. This measure is then adjusted for spatial cost of living differences by region to ensure comparability of the measure across the country. Poverty is defined as having per capita consumption below the poverty line, while extreme poverty or food poverty is defined as having per capital consumption below the level of the extreme poverty line. For 1997 the extreme poverty line was set to B.\519 per capita per year, while the poverty line was set to B.\905 per capita. For 2003, these values were set to B.\534 and B.\953, respectively. The extreme poverty line is set at the cost of obtaining the minimum requirement of calories in a form that is acceptable to local tastes and preferences. To calculate this poverty line, the first step was to determine the food consumption patterns of the population, specifically those in the 11-39^th percentile who are expected to seek out a relatively inexpensive diet (compared to those in higher percentiles) but who are also not so constrained that their diet does not reflect preferences (as the diet of those in the bottom decile might). This ‘food basket’ is then analyzed for caloric content and adjusted to ensure that the minimum daily requirements of calories are obtained. Finally, the resulting basket is costed using price data from the household survey. The general poverty line is simply the extreme line plus an allowance for non-food consumption. This allowance is calculated by, first, determining the share of total consumption devoted to non-food consumption among those whose total consumption is at or near the extreme poverty line. This percentage is added to the value of the food poverty line. Several efforts were made to ensure the comparability of the poverty estimates between 1997 and 2003. First, the questions on consumption were kept the same in the two rounds of the survey. The consumption aggregate was also constructed in the same way, with only minor changes that reflected new items having come on the market in Panama since 1997. The same poverty lines from 1997 were used in 2003 updated for changes in prices. For the extreme poverty line, the same basket of food items was used, but costed using 2003, not 1997, prices. For the general poverty line, the non-food component was inflated using the regional consumer prices indices of the country given the difficulty of calculating this from the household survey data itself. In short, the comparison of poverty rates between the two surveys can be correctly done given the way in which both the welfare measure was constructed and the poverty lines were updated. For a much more detailed description of the methods used to construct the welfare measure and the poverty lines, see Pobreza y Desigualdad en Panamá: La equidad-Un reto impostergable, Ministerio de Economía y Finanzaz, Dirección de Políticas Sociales, Ciudad de Panamá, 2005 and Panama: Poverty Assessment: Priorities and Strategies for Poverty Reduction, World Bank, Human Development Department, Latin America and the Caribbean Region, Washington D.C. 1999.

1.8The survey-NAS differences in Panama are in line with the general pattern internationally: the growth rates of the NAS measures are higher than those of survey-based measures. Furthermore, as Figure A1.1.2 in the Annex shows the differences in growth rates between the NAS and household survey measures are typically greater for other countries in the LAC region. Detailed analysis of the possible factors behind these differences (shown in Annex 1.2) suggests that changes in non-response by rich households probably do not explain the divergence between the survey and the NAS. A comparison of growth rates by sector suggests that differences between GDP growth rates and survey income growth may be attributable to differences in particular sectors. Unfortunately, as with similar cases in other countries, we are left with an incomplete understanding of NAS-survey differences. As Ravallion (2003) notes, “When the levels or growth rates from these two data sources differ, there can be no presumption that the NAS is right and the surveys are wrong, or vice versa, since they are not really measuring the same thing and both are prone to errors.”

1.9We also consider the difference between the growth rates of consumption and income within the survey (see Annex 1.2 for detailed analysis.) Our analysis shows that the divergence between income and consumption in the survey is not explained by changes among households in any particular sector nor those with particular characteristics. Rather, the decline in consumption relative to income was a generalized phenomenon and not specific to any particular sector. This may either reflect an overall increase in savings or general errors in either the income or the consumption term.