This paper presents a model of consumption behavior that explains the presence of “wealthy hand-to-mouth” consumers using a mechanism that differs from those analyzed previously. We show that a two-asset model with temptation preferences generates a demand for commitment and thus illiquidity, leading to hand-to-mouth behavior even when liquid assets deliver higher returns than illiquid assets. This preference for illiquidity has important implications for consumption behavior and for fiscal stimulus policies. Our model matches the recent empirical evidence that Marginal Propensity to Consume remain high even for large income shocks, suggesting a larger response to targeted fiscal stimulus than previously believed.
Wealth accumulation is critical for advancing women's and men's economic opportunities, and yet is understudied in developing countries. Leveraging new, nationally-representative, cross-country comparable surveys where men and women self-reported on their personal asset ownership, we show that individual-level wealth inequality is significantly higher vis-à-vis comparators based on per capita household consumption expenditure, and per capita household wealth. Intra-household wealth inequality explains about 12–30 percent of overall wealth inequality, depending on the country context. The analysis further demonstrates how survey design choices, in particular respondent selection, matter for individual wealth inequality estimates.
We study the welfare and human capital impacts of colleges’ (non)participation in Chile’s centralized higher-education platform, leveraging administrative data and two policy changes: the introduction of a large scholarship program and the inclusion of additional institutions, which raised the number of on-platform slots by approximately 40%. We first show that the expansion of the platform raised on-time graduation rates. We then develop and estimate a model of college applications, offers, wait lists, matriculation, and graduation. When the platform expands, welfare increases, and welfare, enrollment, and graduation rates are less sensitive to off-platform frictions. Gains are larger for students from lower-socioeconomic-status backgrounds.
We derive a small open economy (SOE) as the limit of an economy as the number or size of its trading partners goes to infinity and trade costs also go to infinity. We obtain this limit in the Armington, Eaton–Kortum, Krugman, and Melitz models. In all cases, the trade of the SOE with the foreign countries approaches a finite limit, and the domestic expenditure share for the SOE approaches a limit that is not zero or unity. The foreign countries can be either infinitely many SOEs, or alternatively, one or many large countries with domestic expenditure shares that approach unity. We illustrate the usefulness of this framework by obtaining a formula for the optimal tariff in the SOE – depending on the elasticity of domestic wages with respect to the tariff – that is consistent with all models.
Two years prior to elections, two-thirds of Delhi municipal councillors learned they had been randomly chosen for a preelection newspaper report card. Treated councillors in high-slum areas increased pro-poor spending, relative both to control counterparts and treated counterparts from low-slum areas. Treated incumbents ineligible to rerun in home wards because of randomly assigned gender quotas were substantially likelier to run elsewhere only if their report card showed a strong pro-poor spending record. Parties also benefited electorally from councillors' high pro-poor spending. In contrast, in a cross-cut experiment, councillors did not react to actionable information that was not publicly disclosed.
Globally, preschool enrollment has surged, but its quality is often poor. We evaluate strategies to improve quality of public preschools in Colombia. The first, designed by the government and rolled out nationwide, provided extra funding, mainly earmarked for hiring teaching assistants. The second also offered low-cost training for existing teachers. The first intervention had no effect on child development, while the second improved children’s cognitive development, especially for more disadvantaged children. This pattern can be explained by the interventions affecting teachers' behavior differently. The first led teachers to reduce their classroom time, including learning activities, while additional training offset the adverse effect on learning activities and improved teaching quality.
Most empirical work in economics has considered only a narrow set of measures as meaningful and useful to characterize individual behavior, a restriction justified by the difficulties in collecting a wider set. However, this approach often forces the use of strong assumptions to estimate the parameters that inform individual behavior and identify causal links. In this paper, we argue that a more flexible and broader approach to measurement could be extremely useful and allow the estimation of richer and more realistic models that rest on weaker identifying assumptions. We argue that the design of measurement tools should interact with, and depend on, the models economists use. Measurement is not a substitute for rigorous theory, it is an important complement to it, and should be developed in parallel to it. We illustrate these arguments with a model of parental behavior estimated on pilot data that combines conventional measures with novel ones.
On the basis of a randomized controlled trial, we evaluate a scholarship program in Mexico, Programa de Becas Educación Media Superior (PROBEMS), aimed at improving graduation rates and test scores among upper secondary school students from poor backgrounds. We find that, on average, the program has no effect on either graduation rates or math and Spanish test scores. We point to two possible reasons for this failure: (i) the program was badly targeted, with many of the recipients being from less disadvantaged families than intended; and (ii) the prior academic achievement of those eligible was often insufficient for successful completion of the academic requirements of upper secondary school. This points to accumulated achievement deficits that could be addressed by interventions targeting learning at an earlier stage.
Over the past decade, national statistical offices in low- and middle-income countries have increasingly transitioned to computer-assisted personal interviewing and computer-assisted telephone interviewing for the implementation of household surveys. The byproducts of these types of data collection are survey paradata, which can unlock objective, module- and question-specific, actionable insights on survey respondent burden, survey costs, and interviewer effects – all of which have been understudied in low- and middle-income contexts. This study uses paradata generated by Survey Solutions, a computer-assisted personal interviewing platform used in recent national household surveys implemented by the national statistical offices of Cambodia, Ethiopia, and Tanzania. Across countries, the average household interview, based on a socioeconomic household questionnaire, ranges from 82 to 120 minutes, while the average interview with an adult household member, based on a multi-topic individual questionnaire, takes between 13 to 25 minutes. The paper further provides guidelines on the use of paradata for module-level analysis to aid in operational survey decisions, such as using interview length to estimate unit cost for budgeting purposes as well as understanding interviewer effects using a multilevel model. Our findings, particularly by module, point to where additional interviewer training, fieldwork supervision, and data quality monitoring may be needed in future surveys.
We study noisy aggregation of dispersed information in financial markets without imposing parametric restrictions on preferences, information, and return distributions. We provide a general characterization of asset returns by means of a risk-neutral probability measure that features excess weight on tail risks. Moreover, we link excess weight on tail risks to observable moments such as forecast dispersion and accuracy, and argue that it provides a unified explanation for several prominent cross-sectional return anomalies. Simple calibrations suggest the model can account for a significant fraction of empirical returns to skewness, returns to disagreement, and interaction effects between the two.
The US-China trade war created net export opportunities rather than simply shifting trade across destinations. Many "bystander" countries grew their exports of taxed products into the rest of the world (excluding the United States and China). Country-specific components of tariff elasticities, rather than specialization patterns, drove large cross-country variation in export growth of tariff-exposed products. The elasticities of exports to US-Chinese tariffs identify whether a country's exports complement or substitute the United States or China and its supply curve's slope. Countries that operate along downward-sloping supplies whose exports substitute (complement) the United States and China are among the larger (smaller) beneficiaries of the trade war.
Does economic growth close labor market-linked gender gaps that disadvantage women? Conversely, do gender inequalities in the labor market impede growth? To inform these questions, we conduct two analyses. First, we estimate regressions using data on gender gaps in a range of labor market outcomes from 153 countries spanning two decades (1998-2018). Second, we conduct a systematic review of the recent economics literature on gender gaps in labor markets, examining 16 journals over 21 years. Our empirical analysis demonstrates that growth is not a panacea. While economic gender gaps have narrowed and growth is associated with gender gap closures specifically in incidence of paid work, the relationship between growth and labor market gaps is otherwise mixed, and results vary by specification. This result reflects, in part, the gendered nature of structural transformation, in which growth leads men to transition from agriculture to industry and services while many women exit the labor force. Disparities in hours worked and wages persist despite growth, and heterogeneity in trends and levels between regions highlight the importance of local institutions. To better understand whether gender inequalities impeded growth, we explore a nascent literature that shows that reducing gender gaps in labor markets increases aggregate productivity. Our broader review highlights how traditional explanations for gender differences do not adequately explain existing gaps and how policy responses need to be sensitive to the changing nature of economic growth. We conclude by posing open questions for future research.
Low- and middle-income nations host 76 percent of the world's refugees. This study uses original data to explore within-country spatial variability in refugee-hosting responsibilities. We find that hosting responsibilities for the displaced Rohingya people in Bangladesh are allocated in similarly unequal fashion when analyzed at the national, regional, and microregional levels. Refugee camps are placed in socioeconomically disadvantaged communities relative to both Bangladesh as a whole and surrounding areas. Our findings underscore the importance of considering host communities in the coordination of humanitarian responses to refugee crises to prevent economic hardship and political backlash.
Does a woman’s take-up of government benefits vary with her perception of how they will be shared within the household? Using randomized assignment to alternative information treatments, we examine this question in the context of Saudi women’s willingness to apply for unemployment assistance (Hafiz). We compare the take-up among women who receive no program information to three groups: those who receive information on program eligibility conditions (Eligibility group) and those who receive additional information that their registration status is broadly confidential (Privacy group) or that they fully control registering and accessing benefits (Agency group). Three months later, the treatments, on average, doubled Hafiz applications, with the treatment impacts largest for the Agency group. Women from poorer households and married women are most responsive to the Agency and Privacy interventions respectively. These findings are consistent with collective household bargaining models where family members’ spending preferences differ; we predict larger treatment impacts when there is more competition for resources.