Publication:
How Do the Poor Cope with Shocks in Bangladesh? Evidence from Survey Data

Loading...
Thumbnail Image
Files in English
English PDF (1011.13 KB)
450 downloads
English Text (57.14 KB)
352 downloads
Published
2011-09-01
ISSN
Date
2012-03-19
Author(s)
Sharif, Iffath
Rahman, Hossain Zillur
Zaman, Hassan
Editor(s)
Abstract
This paper uses household survey data collected in September-October 2009 on a nationally representative sample of 2,000 households in Bangladesh to examine the nature of shocks experienced by households over the preceding 12 months and the type of coping mechanisms that were adopted. The analysis finds that more than half the sample claimed to have faced a shock -- economic, health, climatic, or asset related -- over the previous year. Surprisingly, the non-poor face a larger share of these shocks compared with the poor. A closer look at this result shows that the non-poor report a significantly larger share of "asset-related" shocks, which is consistent with the fact that the poor have fewer assets to lose. Health-related shocks dominate and households appear to have coped with these shocks through savings and loans, help from friends, and depletion of assets. The results show that households, when faced with covariate shocks due to climatic reasons, are less able to cope. As would be expected, the poor are less able to cope with shocks compared with the non-poor; the poor are more likely to use coping mechanisms that could have negative welfare implications in the longer term, including the depletion of assets, reduction of essential consumption, and use of high-interest loans. Econometric analysis suggests that geographical location, socio-economic status, and access to microfinance all affect the ability to cope with shocks. Policy implications include the importance of developing safety nets that take into account the vulnerability to climate-related shocks and further developing the links between micro-finance and safety net programs.
Link to Data Set
Citation
Sharif, Iffath; Santos, Indhira; Rahman, Hossain Zillur; Zaman, Hassan. 2011. How Do the Poor Cope with Shocks in Bangladesh? Evidence from Survey Data. Policy Research working paper ; no. WPS 5810. © World Bank. http://hdl.handle.net/10986/3573 License: CC BY 3.0 IGO.
Associated URLs
Associated content
Report Series
Report Series
Other publications in this report series
  • Publication
    The Economic Value of Weather Forecasts: A Quantitative Systematic Literature Review
    (Washington, DC: World Bank, 2025-09-10) Farkas, Hannah; Linsenmeier, Manuel; Talevi, Marta; Avner, Paolo; Jafino, Bramka Arga; Sidibe, Moussa
    This study systematically reviews the literature that quantifies the economic benefits of weather observations and forecasts in four weather-dependent economic sectors: agriculture, energy, transport, and disaster-risk management. The review covers 175 peer-reviewed journal articles and 15 policy reports. Findings show that the literature is concentrated in high-income countries and most studies use theoretical models, followed by observational and then experimental research designs. Forecast horizons studied, meteorological variables and services, and monetization techniques vary markedly by sector. Estimated benefits even within specific subsectors span several orders of magnitude and broad uncertainty ranges. An econometric meta-analysis suggests that theoretical studies and studies in richer countries tend to report significantly larger values. Barriers that hinder value realization are identified on both the provider and user sides, with inadequate relevance, weak dissemination, and limited ability to act recurring across sectors. Policy reports rely heavily on back-of-the-envelope or recursive benefit-transfer estimates, rather than on the methods and results of the peer-reviewed literature, revealing a science-to-policy gap. These findings suggest substantial socioeconomic potential of hydrometeorological services around the world, but also knowledge gaps that require more valuation studies focusing on low- and middle-income countries, addressing provider- and user-side barriers and employing rigorous empirical valuation methods to complement and validate theoretical models.
  • Publication
    Direct and Indirect Impacts of Transport Mobility on Access to Jobs: Evidence from South Africa
    (Washington, DC: World Bank, 2025-11-12) Iimi, Atsushi
    Access to jobs is essential for economic growth. In Africa, unemployment rates are notably high. This paper reexamines the relationship between transport mobility and labor market outcomes, with a particular focus on the direct and indirect effects of transport connectivity. As predicted by theory, wages are influenced by the level of commuting deterrence. Generally, higher earnings are associated with longer commute times and/or higher commuting costs. Local accessibility is also important, especially for individuals with time constraints. Both direct and indirect impacts are found to be significant in South Africa, where job accessibility has been challenging since the end of apartheid. For the direct impact, the wage elasticity associated with commuting costs is significant. Returns on commute are particularly high for women. Local accessibility to socioeconomic facilities, such as shops and health services, is also found to have a significant impact, consistent with the concept of mobility of care. To enhance employment, therefore, it is crucial to connect people not only to job locations but also to various socioeconomic points of interest, such as markets and hospitals, in an integrated manner. This integration will enable individuals to spend more time working and commuting longer distances.
  • Publication
    The Macroeconomic Implications of Climate Change Impacts and Adaptation Options
    (Washington, DC: World Bank, 2025-05-29) Abalo, Kodzovi; Boehlert, Brent; Bui, Thanh; Burns, Andrew; Castillo, Diego; Chewpreecha, Unnada; Haider, Alexander; Hallegatte, Stephane; Jooste, Charl; McIsaac, Florent; Ruberl, Heather; Smet, Kim; Strzepek, Ken
    Estimating the macroeconomic implications of climate change impacts and adaptation options is a topic of intense research. This paper presents a framework in the World Bank's macrostructural model to assess climate-related damages. This approach has been used in many Country Climate and Development Reports, a World Bank diagnostic that identifies priorities to ensure continued development in spite of climate change and climate policy objectives. The methodology captures a set of impact channels through which climate change affects the economy by (1) connecting a set of biophysical models to the macroeconomic model and (2) exploring a set of development and climate scenarios. The paper summarizes the results for five countries, highlighting the sources and magnitudes of their vulnerability --- with estimated gross domestic product losses in 2050 exceeding 10 percent of gross domestic product in some countries and scenarios, although only a small set of impact channels is included. The paper also presents estimates of the macroeconomic gains from sector-level adaptation interventions, considering their upfront costs and avoided climate impacts and finding significant net gross domestic product gains from adaptation opportunities identified in the Country Climate and Development Reports. Finally, the paper discusses the limits of current modeling approaches, and their complementarity with empirical approaches based on historical data series. The integrated modeling approach proposed in this paper can inform policymakers as they make proactive decisions on climate change adaptation and resilience.
  • Publication
    From Policy to Practice: Lessons from the Implementation of the Refugee Work Rights Policy in Ethiopia
    (Washington, DC: World Bank, 2025-11-10) Perez, Ana Maria; Rozo, Sandra V.
    This paper examines the early implementation of Ethiopia’s refugee work rights policy, with a focus on the issuance of permits that enable refugees to engage in economic activities. Building on significant legal and institutional advances under the 2019 Refugee Proclamation and subsequent directives, the analysis explores how these reforms are being operationalized in practice. Using a mixed-methods approach, combining document review, administrative data analysis, and semi-structured interviews, the paper identifies both progress and remaining challenges. Permit issuance has increased since the adoption of detailed operational guidance in 2024, reflecting the Government of Ethiopia’s commitment to operationalizing its progressive legal framework and ensuring that refugees can exercise their right to work. However, take-up remains modest, with about 5.2 percent of the working-age population holding a permit. Preliminary evidence suggests that coordination gaps, limited subnational capacity, low awareness among refugees and employers, and disincentives to formalize in a largely informal labor market are contributing to the low take-up. The paper offers policy suggestions, grounded in the Ethiopian context and emerging evidence, to help translate legal commitments into improved labor market outcomes for refugees.
  • Publication
    Monitoring Global Aid Flows: A Novel Approach Using Large Language Models
    (Washington, DC: World Bank, 2025-11-04) Luo, Xubei; Rajasekaran, Arvind Balaji; Scruggs, Andrew Conner
    Effective monitoring of development aid is the foundation for assessing the alignment of flows with their intended development objectives. Existing reporting systems, such as the Organisation for Economic Co-operation and Development’s Creditor Reporting System, provide standardized classification of aid activities but have limitations when it comes to capturing new areas like climate change, digitalization, and other cross-cutting themes. This paper proposes a bottom-up, unsupervised machine learning framework that leverages textual descriptions of aid projects to generate highly granular activity clusters. Using the 2021 Creditor Reporting System data set of nearly 400,000 records, the model produces 841 clusters, which are then grouped into 80 subsectors. These clusters reveal 36 emerging aid areas not tracked in the current Creditor Reporting System taxonomy, allow unpacking of “multi-sectoral” and “sector not specified” classifications, and enable estimation of flows to new themes, including World Bank Global Challenge Programs, International Development Association–20 Special Themes, and Cross-Cutting Issues. Validation against both Creditor Reporting System benchmarks and International Development Association commitment data demonstrates robustness. This approach illustrates how machine learning and the new advances in large language models can enhance the monitoring of global aid flows and inform future improvements in aid classification and reporting. It offers a useful tool that can support more responsive and evidence-based decision-making, helping to better align resources with evolving development priorities.
Journal
Journal Volume
Journal Issue