不丹的贫困动态，2017-2022

Poverty Dynamics in Bhutan, 2017–2022 Evidence from Synthetic Panels Nicola AmendolaFederico BelottiAlvin EtangGiulia ManciniGiovanni Vecchi Poverty and Equity Global DepartmentJanuary 2025 Policy Research Working Paper11031 Abstract This paper examines the dynamics of poverty in Bhutanbetween 2017 and 2022, utilizing cross-sectional data fromthe Bhutan Living Standards Surveys. The paper constructssynthetic panels and estimates poverty transition probabil-ities. Three main findings emerge. First, poverty turnoverin Bhutan is low overall (not many people, as a share ofthe population, moved in and out of poverty during theperiod considered). Second, chronic poverty, defined asthe probability of remaining poor in both years (2017 and 2022), was also low, both in absolute terms and comparedto other countries for which similar estimates are available.The probability of being poor in both years is 6 percentof households in Bhutan, compared to over 15 percent inIndia and 17.5 percent in Pakistan. Third, upward pov-erty mobility (the probability of escaping poverty between2017 and 2022) is 20 times higher than downward povertymobility. This paper is a product of the Poverty and Equity Global Department. It is part of a larger effort by the World Bank toprovide open access to its research and make a contribution to development policy discussions around the world. PolicyResearch Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contactedat aetangndip@worldbank.org; nicola.amendola@uniroma2.it; federico.belotti@uniroma2.it; giulia.mancini@uniroma2.it;and giovanni.vecchi@uniroma2.it. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about developmentissues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry thenames of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely thoseof the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank andits affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Poverty Dynamics in Bhutan, 2017–2022:Evidence from Synthetic Panels Nicola Amendola*Federico Belotti*Alvin Etang**Giulia Mancini***Giovanni Vecchi* Keywords:poverty dynamics, economic mobility, synthetic panel methods. JEL:I30, I32, C10, C23 1Introduction Traditionally, the study of poverty dynamics requires tracking the same individuals orhouseholds over time. However, in many developing countries, panel data is scarce, whichprevents analysts from observing the economic trajectories of individuals or householdsover an extended period of time. Following the path opened by Deaton (1985), papers by Bourguignon, Goh, and Kim(2004), and Guell and Hu (2006) explored the use of synthetic panels at the householdlevel. However, these two approaches require certain assumptions that may not be easilysatisfied in available cross-sectional data. The former method requires at least three roundsof cross-sectional data, and assumes a first-order auto-regression process where pasthousehold or individual incomes (earnings) can affect present outcomes; the latter isexclusively restricted to duration analysis. To overcome these limitations, Dang et al.(2014) constructed synthetic panels from as few as two rounds of household-level cross-sectional data, providing lower-bound and upper-bound estimates of poverty transitions.More recently, Dang and Lanjouw (2023) proposed a method that delivers point estimatesof poverty transition probabilities (households shifting in and out of poverty, or preservingtheir status) in the absence of longitudinal data. This paper takes advantage of these new developments, as well as some critiques that haverecently been raised regarding some aspects of the methodology (e.g., Herault and Jenkins,2019; Garcés‐Urzainqui, Lanjouw, and Rongen. 2021, Colgan, 2023), to delve deeper intothe characteristics of poverty dynamics in Bhutan during the five-year period from 2017 to2022. According to Amendola et al. (2023), during this time the stark decrease of povertyin Bhutan at the national and sub-national levels seems to be linked mainly to redistributiveprocesses in the monetary metric of expenses, rather than to economic growth. The factthat the key driver of poverty reduction is a reshuffling of households along the distributioncurve, rather than a movement of the curve itself, justifies the need for tools capable ofidentifying who changes their position within the income (or expenditure) scale during theperiod considered. Methods based on pseudo-panels allow for precisely this kind ofanalysis, and significantly contribute to our understanding of the relative importance of theunderlying drivers of pover