A monopolist platform uses data to match heterogeneous consumers with multiproduct sellers. The consumers can purchase the products on the platform or search off the platform. The platform sells targeted ads to sellers that recommend their products to consumers and reveals information to consumers about their match values. The revenue- optimal mechanism is a managed advertising campaign that matches products and preferences efficiently. In equilibrium, sellers offer higher qualities at lower unit prices on than off platform. The platform exploits its information advantage to increase its bargaining power vis-à-vis the sellers. Finally, privacy-respecting data-governance rules can lead to welfare gains for consumers.
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.
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.
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.
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.
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.
Conditional cash transfer (CCT) programs aim to reduce poverty or advance social goals by encouraging desirable behavior that recipients under-invest in. An unintended consequence of conditionality may be the distortion of recipients’ behavior in ways that lower welfare. We first illustrate a range of potential distortions arising from CCT programs around the world. We then show that in the simple case where a CCT causes low return participants to select into a behavior, and social returns and private perceived returns are aligned, transfer size plays an important role: the larger the transfer, the stronger the distortion becomes, implying that (i) there is an optimal transfer size for such CCTs, and (ii) unconditional cash transfers (UCTs) may be better than CCTs when the transfer amount is large. We provide empirical evidence consistent with these claims by studying a cash transfer program conditional on seasonal labor migration in rural Indonesia. In line with theory, we show that when the transfer size exceeds the amount required for travel expenses, distortionary effects dominate and migration earnings decrease.
We study equilibria in static entry games with single-dimensional private information. Our framework embeds many models commonly used in applied work, allowing for firm heterogeneity and selective entry. We introduce the notion of strength, which summarizes a firm's ability to endure competition. In environments of applied interest, an equilibrium in which entry strategies are ordered according to the firms' strengths always exists. We call this equilibrium herculean. We derive simple and testable sufficient conditions guaranteeing equilibrium uniqueness and, consequently, a unique counterfactual prediction.
Reliable testing data for new infectious diseases like COVID-19 is scarce in developing countries making it difficult to rapidly diagnose spatial disease transmission and identify at-risk areas. We propose a method that uses readily available data on bi-lateral migration channels combined with COVID-19 cases at respective migrant destinations to construct a spatially oriented risk index. We find significant and consistent association between our measure and various types of outcomes including actual COVID-19 cases and deaths, indices of government policy responses, and community mobility patterns. Results suggest that future pandemic models should incorporate migration-linkages to predict regional socio-economic and health risk exposure.
This paper studies the welfare effects of encouraging rural–urban migration in the developing world. To do so, we build and analyze a dynamic general-equilibrium model of migration that features a rich set of migration motives. We estimate the model to replicate the results of a field experiment that subsidized seasonal migration in rural Bangladesh, leading to significant increases in migration and consumption. We show that the welfare gains from migration subsidies come from providing better insurance for vulnerable rural households rather than from correcting spatial misallocation by relaxing credit constraints for those with high productivity in urban areas that are stuck in rural areas.
Addressing public health externalities often requires community-level collective action. Due to social norms, each person’s sanitation investment decisions may depend on the decisions of neighbors. We report on a cluster randomized controlled trial conducted with 19,000 households in rural Bangladesh where we grouped neighboring households and introduced (either financial or social recognition) rewards with a joint liability component for the group, or asked each group member to make a private or public pledge to maintain a hygienic latrine. The group financial reward has the strongest impact in the short term (3 months), inducing a 7.5–12.5 percentage point increase in hygienic latrine ownership, but this effect dissipates in the medium term (15 months). In contrast, the public commitment induced a 4.2–6.3 percentage point increase in hygienic latrine ownership in the short term, but this effect persists in the medium term. Non-financial social recognition or a private pledge has no detectable effect on sanitation investments.
We track the effects of the COVID-19 pandemic on mental health in eight Low and Middle Income Countries (LMICs) in Asia, Africa, and South America utilizing repeated surveys of 21,162 individuals. Many respondents were interviewed over multiple rounds pre- and post-pandemic, allowing us to control for time trends and within-year seasonal variation in mental health. We demonstrate how mental health fluctuates with agricultural crop cycles, deteriorating during pre-harvest “lean” periods. Ignoring this seasonal variation leads to unreliable inferences about the effects of the pandemic. Controlling for seasonality, we document a large, significant, negative impact of the pandemic on mental health, especially during the early months of lockdown. In a random effects aggregation across samples, depression symptoms increased by around 0.3 standard deviations in the four months following the onset of the pandemic. The pandemic could leave a lasting legacy of depression. Absent policy interventions, this could have adverse long-term consequences, particularly in settings with limited mental health support services, which is characteristic of many LMICs.
What do recent advances in economic geography teach us about the spatial distribution of economic activity? We show that the equilibrium distribution of economic activity can be determined simply by the intersection of labor supply and demand curves. We discuss how to estimate these curves and highlight the importance of global geography—the connections between locations through the trading network—in determining how various policy relevant changes to geography shape the spatial economy.