dln10incomepersistence1021textandtables1
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dln10incomepersistence1021textandtables1
Do Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1iversityAbstractThis paper estimates the persistence of transient income shocks to farm households in rural Indonesia. Persistence is defined as the elasticity of households’1997 per capita income with respect to its 1993 per capita income, controlling for time-invariant household characteristics. L dln10incomepersistence1021textandtables1ocal rainfall levels are employed as an exogenous indicator of transitory income shocks. On average, thirty percent of income shocks remain after fourdln10incomepersistence1021textandtables1
years. Negative shocks persist no longer than positive shocks, and neither negative nor positive shocks disproportionately affect poor households. ThDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1: Income dynamics, Income Shocks. Indonesia■ Corresponding author: Department of Economics, Cornell University. Ithaca, NY 14650. Tel.: +1-607-277 -7008. Email: dlnlOrjKoinell.edu. I thank John Abowd. Christopher Barrett. Gary Fields. George Jakubson. Ravi Kanbur, and Joseph Newhouse for their helpf dln10incomepersistence1021textandtables1ul comments.1How much do transient income shocks affect households’ future income? Do negative income shocks persist longer than positive shocks? Do edln10incomepersistence1021textandtables1
ither negative or positive shocks exhibit disproportionate persistence for poor households? How sensitive are empirical estimates of the persistence oDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1ral Indonesian farm households. Currently, little is known about the persistence of income shocks in the developing world, due to the lack of large scale panel surveys from developing countries.The efficacy of policies that seek to promote economic well being by stabilizing or redistributing income, dln10incomepersistence1021textandtables1 however, depends on how long negative and positive shocks persist. Assuming risk aversion, the greater the persistence, the greater the benefit fromdln10incomepersistence1021textandtables1
policies that reduce income volatility. The case for public intervention is stronger, however, if negative shocks persist longer than positive income Do Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1s are particularly persistent for the poor and if policymakers give particular attention to the poor, then the case for intervention is stronger still. Furthermore, if poor households are able to put income windfalls towards purchasing assets that substantially increase their expected future income, dln10incomepersistence1021textandtables1 then redistribution from rich to poor households can help families escape poverty. The hope that positive income shocks persist for the poor may partdln10incomepersistence1021textandtables1
ly explain the design of the Indonesian Left Behind Villages (IDT) program, a S564 million anti-poverty initiative undertaken by the Soeharto administDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1n poor villages. The persistence of positive income shocks for poor households affects the optimal mix2between investment in village infrastructure and direct grants to poor households as policy instruments to fight poverty.Although understanding income persistence is important for formulating anti- dln10incomepersistence1021textandtables1poverty policy, labor and development economists lend Io view this issue from different perspectives. Development economics has been influenced by moddln10incomepersistence1021textandtables1
els in which household income or well-being has al least one unstable equilibrium (e.g., Dasgupld and Ray, 1986, Bannerjee and Newman, 1991). Tn theseDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1ly germane to developing countries, which are characterized by a large number of household businesses, imperfect credit and insurance markets, a lack of public safety nets, and widespread malnutrition.Some empirical evidence from developing countries is consistent with models of multiple equilibria: dln10incomepersistence1021textandtables1 In rural China, data with relatively little measurement error indicate that one third of the mean poverty gap is due to year-to-year fluctuations indln10incomepersistence1021textandtables1
consumption (Jalan and Ravallion, 1998). High levels 0Í transient poverty would be predicted by models in which transient income shocks lead householdDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1ve income shocks (Jdlan and Ravallion, 1999); perhaps they arc least able to insure future income as well. Furthermore. in Ethiopia, the livestock holdings ol pastoralists appear Io be subject to two equilibria in herd sizes (T.ybberl, el al, 2001). These empirical findings, die popularity of theore dln10incomepersistence1021textandtables1tical models of multiple equilibria in household well-being, and underlying conditions in developing countries, all suggest to development economistsdln10incomepersistence1021textandtables1
that household income shocks persist far into the future.3Labor economists, on the other hand, have been profoundly influenced by the canonical model Do Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1957). Empirical tests of this model typically allow for an autoregressive component of unobserved earnings, using estimated covariances from standard earnings equations. These empirical studies, using data from developed countries, reject the permanent income model’s strong assumption of no serial d dln10incomepersistence1021textandtables1ependence, but autocorrelation between earnings and its lag tends to be low or even negative (See, for example, Lillard and Weiss, 1980.Bourguignon andln10incomepersistence1021textandtables1
d Morrisson. 1983, Abowd and Card,1989, Burkhauser et al, 1997). Given these empirical findings as well as the popularity of the permanent income framDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1s study contributes empirical evidence to this debate by analyzing the persistence of household income shocks among rural farm households in Indonesia. Persistence is defined as the elasticity of 1997 per capita income with respect to 1993 per capita income, controlling for time-invariant household dln10incomepersistence1021textandtables1characteristics. The empirical estimates of persistence, obtained by using local rainfall as an exogenous determinant of lagged transient income, yieldln10incomepersistence1021textandtables1
d four main conclusions. First, income shocks do persist; on average, approximately thirty percent of the income shock remains after four years. SeconDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1ive income shocks for poor households is low or moderate. Finally, unobserved heterogeneity and especially measurement error are significant sources of bias, and depending on the specification, can alter estimates of persistence by up to forty percentage points.https://khothuvien.cori!4This paper co dln10incomepersistence1021textandtables1nsists of seven sections: Section two reviews the empirical methods that have been used to estimate the persistence of earnings or income. Section thrdln10incomepersistence1021textandtables1
ee discusses the data used in this study. Section four presents a theoretical model that illustrates how income shocks can persist, and how persistencDo Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1underlying assumptions, that are used to estimate persistence. Section six presents the empirical results, and section seven concludes.Previous LiteratureExisting studies use four different econometric approaches to obtain estimates of income persistence. The most basic of these involves estimating dln10incomepersistence1021textandtables1persistence by regressing the logarithm of current per capita income on its lag, in the presence of other time-invariant characteristics (Grootaert andln10incomepersistence1021textandtables1
d Kanbur, 1997). Using this method, Fields et al (2001) estimate that in Indonesia, 50% of income shocks persist four years later?These OLS estimates Do Negative Income Shocks Last Longer, and Do They Hurt the Poor More? Evidencefrom Rural Indonesia.David Newhouse'Department of Economics Cornell Uni dln10incomepersistence1021textandtables1measurement error in lagged income leads its coefficient, which is estimated persistence, to be biased downward. On the other hand, OLS estimates of persistence are upwardly biased in the presence of unobserved household heterogeneity. Failure to control for unobserved fixed attributes, such as mana dln10incomepersistence1021textandtables1gerial ability or soil quality, leads estimates of the persistence of shocks to include the systematic effect of these unobserved characteristics on idln10incomepersistence1021textandtables1
ncome.1 Both Grootaert and Kanbur, and Fields et al, actually regress income change on a set of control variables, which includes lagged income. The pGọi ngay
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