Given Asia’s record of rapid economic growth and the conceptual and empirical problems of the current international income poverty line (‘dollar-a-day’), this chapter discusses whether there is merit in developing an Asia-specific poverty line that addresses some of the shortcomings of the dollar-a-day line and additionally considers Asia’s particular economic situation. We consider various ways of creating an Asia-specific poverty line, including an Asia-specific international income poverty line (using purchasing-power parity, PPP, adjusted dollars) that is derived from Asian national poverty lines. We argue that there can be some merit in developing an Asian poverty line and that, in the case of income poverty, it would be best to ground such an Asia-specific poverty line in a consistent method of generating national poverty lines using national currencies rather than generating a PPP-adjusted poverty line in international dollars that is specific for Asia. It is important that such a poverty line also considers relative poverty in its assessment to reflect the rising aspirations of Asian societies, in line with suggestions made by Chen and Ravallion (2013) on weakly relative poverty lines. In terms of multidimensional poverty lines, there is also some merit in developing an Asia-specific multidimensional poverty index that takes into account the specific living conditions of Asian societies.
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Impressive Accomplishments or Incomplete Achievements?
Edited by Jacques Silber and Guanghua Wan
Scientists estimate that anthropogenic climate change leads to increased surface temperature, sea-level rise, more frequent and significant extreme weather and climate events, among others. In this study, we investigate how climate change can potentially change the vulnerability to poverty using a panel data set in Indonesia. We focus on the effect of drought and flood, two of the commonly observed disasters there. Our simulation results indicate that vulnerability to poverty may increase substantially as a result of climate change in Indonesia.
This chapter reviews the growing body of literature on vulnerability. We first provide a survey of existing studies on the concepts and measurements of vulnerability to poverty by classifying them into welfarist, expected poverty, and axiomatic approaches. We then review a number of empirical studies on vulnerability to poverty in Asia and elsewhere. This review shows that poverty and vulnerability are related, but different, and that key determinants of vulnerability often include education and location. We also briefly review other areas of vulnerability analysis such as vulnerability to climate change and offer various policy implications arising from vulnerability analysis.
Jacques Silber and Guanghua Wan
The primary objective of this chapter is to highlight the contribution of the recent methodological refinements of poverty measures based on counting approaches using ordinal variables to the understanding of the evolution of poverty in Cambodia, Indonesia and the Philippines. Using the general framework proposed by Silber and Yalonetzky (2013), this chapter compares multidimensional poverty measures such as the Multidimensional Poverty Index used by the UNDP (an index based on the approach of Alkire and Foster (2011)) with others which are sensitive to the distribution of deprivation counts across individuals. To the latter family belong the poverty measures introduced by Chakravarty and D’Ambrosio (2006) and Rippin (2010) and those based on the extension of the approach of Aaberge and Peluso (2012), as suggested by Silber and Yalonetzky (2013). Poverty is estimated using Demographic and Health Surveys for three different years for Cambodia (2000, 2005 and 2010), for Indonesia (1997, 2003 and 2007), and for the Philippines (1997, 2003 and 2008) by considering the deprivations in education, health and standard of living. Our findings indicate that Cambodia shows the highest level of poverty, followed by Indonesia and the Philippines, irrespective of the poverty measures used. At the national level, all countries reduced their multidimensional poverty over time using poverty measures as the one based on the approach of Alkire and Foster (2011) and those that are sensitive to the concentration of deprivations across individuals. As in most of Asian developing countries, poverty is largely a rural phenomenon. However, when examining the evolution of poverty over time for each country, conclusions drawn from the use of various poverty measures may differ regarding trends in poverty over time by area of residence as well as by region of residence.
Satya R. Chakravarty, Nachiketa Chattopadhyay, Jacques Silber and Guanghua Wan
Given a poverty line, a person who is non-poor (poor) currently may not be treated as non-poor (poor) in a vulnerable situation. This chapter looks at the impact of vulnerability on the poverty line. The poverty line is adjusted in the presence of vulnerability such that the utility of a person at the current poverty line and that at the adjusted poverty line become identical. Using an additive model of vulnerability, it is shown that if the utility function obeys constant Arrow–Pratt absolute risk aversion, then the harmonized poverty line is a simple absolute augmentation of the current poverty line. On the other hand, under a multiplicative model of vulnerability with constant Arrow–Pratt relative risk aversion, the revised poverty line is a simple relative augmentation of the current poverty line. The chapter contains empirical illustrations which assume that constant relative risk aversion applies to countries involved in the Asia-Pacific region. Upward adjustment of the poverty line under increased vulnerability, as captured through the value of the risk aversion parameter, is also observed.
This chapter compares the extent and the nature of the higher prevalence of poverty among disadvantaged ethnic groups in six Asian countries using demographic surveys. We first estimate a composite wealth index as a proxy for economic status, and analyze the magnitude of the ethnic gap in absolute and relative poverty levels across six countries and different ethnicities in those countries. Then, we use regression-based counterfactual analysis for explaining these ethnic differentials in poverty. We compare the actual differential in poverty with the gap that remains after disadvantaged ethnic groups are given the distribution of characteristics of the advantaged ethnic groups (by reweighting their densities using propensity scores). Our results show that there is a substantial cross-country variability in the extension, evolution, and nature of the ethnic poverty gap, which is as high as 50 percentage points or more in some specific cases in Nepal, Pakistan, or India. The gap in the latter country increased over the analyzed period, while it was reduced in the Philippines. Our analyses indicate that factors that contribute to ethnic disadvantaged groups being poorer are the strongly persistent high inequalities in education (for example, India, Nepal, and Pakistan), in regional development (for example, the Philippines) and the large urban–rural gap (for example, Pakistan).
Hermann Waibel and Lena Hohfeld
In this chapter, we analyze the link between nutrition and poverty in two Asian countries where monetary-based poverty reduction was especially successful. Thailand and Viet Nam are two emerging market economies where poverty rates are now below 10 percent and are declining further. Despite this success, it is not clear to what extent this success has translated into similar improvements in the nutritional situation of the people and especially of children. We find that undernutrition continues to be a problem in Viet Nam with child underweight rates of 27 percent and therefore higher than headcount rates of the $1.25 poverty line. Also, Thailand, after the economic crisis, with 19 percent of children underweight, is still above the World Health Organization’s threshold. We investigate the factors that influence nutrition outcomes, measured as Z-scores of the weight-for-age indicator, by using Tobit regressions for four different groups of children, based on income (poor versus non-poor) and nutrition (underweight versus non-underweight). We find that poverty and income influence nutrition outcomes, but other factors such as mother’s height, education, migration and sanitation also affect nutrition. Coefficients of respective variables differ by poverty status. Our conclusion that non-monetary factors matter to reduce undernutrition, and, therefore, monetary poverty reduction is not a sufficient condition, is further underlined by a prediction of future undernutrition rates based on regressions. Also, we find that, even under the assumption of high growth, income growth alone will not be able to reduce undernutrition to a level of low severity until the year 2030.
Satya R. Chakravarty, Nachiketa Chattopadhyay and Jacques Silber
This chapter estimates the number of poor in various countries in Asia by applying an ‘amalgam poverty line’, which is a weighted average of an absolute poverty line (such as $1.25 per day or $1.45 per day) and a reference income (such as the mean or the median income). The number of poor is computed under various values of the weight applied to the absolute poverty line, namely 100 percent, 90 percent, 66 percent and 50 percent. The chapter provides estimates of the headcount ratio and poverty gap ratio under the various scenarios for 25 different countries or regions examined.