Structural transformation in most currently developing countries takes the form of a rapid rise in services but limited industrialization. In this paper, we propose a new methodology to structurally estimate productivity growth in service industries that circumvents the notorious difficulties in measuring quality improvements. In our theory, the expansion of the service sector is both a consequence – due to income effects – and a cause – due to productivity growth – of the development process. We estimate the model using Indian household data. We find that productivity growth in non-tradable consumer services such as retail, restaurants, or residential real estate, was an important driver of structural transformation and rising living standards between 1987 and 2011. However, the welfare gains were heavily skewed toward high-income urban dwellers.
We examine international regulatory agreements that are negotiated under lobbying pressures from producer groups. The way in which lobbying influences the cooperative setting of regulatory policies, as well as the welfare impacts of international agreements, depend crucially on whether the interests of producers in different countries are aligned or in conflict. The former situation tends to occur for product standards, while the latter tends to occur for process standards. We find that, if producer lobbies are strong enough, agreements on product standards lead to excessive deregulation and decrease welfare, while agreements on process standards tighten regulations and enhance welfare.
We review theoretical and empirical work on the economic effects of the United States and China trade relations during the past 20 years. We first discuss the origins of the China shock and its measurement and present methods used to study its economic effects on different outcomes. We then focus on the recent US–China trade war. We review methods used to evaluate its effects, describe its economic effects, and analyze whether this increase in trade protectionism reverted the effects of the China shock. The main lessons learned in this review are that (a) the aggregate gains from US–China trade created winners and losers; (b) China's trade expansion seems not to be the main cause of the decline in US manufacturing employment during the same period; and (c) the recent trade war generated welfare losses, had small employment effects, and was ineffective in reversing the distributional effects due to the China shock.
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.
Millions of children are at risk for developmental deficits in low and-middle-income countries (LMICs). Reviews find that psychosocial interventions for children aged <3 years improve short-run child cognition and language (0.28–0.47 SD). Similarly, a meta-regression analysis of 54 preschool interventions for children aged ≥3 years found significant improvements in children’s cognitive skills (0.15 SD), executive functioning, social–emotional learning, and behavior (0.12 SD). Only 18 of these interventions were from LMICs, with 2 from India, which has the world’s largest population of children attending preschool (36 million children enrolled in Integrated Childhood Development Services [ICDS]). Interventions have had benefits in math and language. However, a survey of 298 Indian preschools found generally poor quality. Although short-run impacts of some interventions fade, some rigorous studies with long-term follow-ups found later benefits in educational attainment, reduced crime, and increased income.
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.
We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2 km and 2.4 km (where the average US county has dimension of 51.9 km), our model predictions achieve R2 values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3–4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
This paper analyzes earnings inequality and earnings dynamics in Sweden over 1985–2016. The deep recession in the early 1990s marks a historic turning point with a massive increase in earnings inequality and earnings volatility, and the impact of the recession and the recovery from it lasted for decades. In the aftermath of the recession, we find steady growth in real earnings across the entire distribution for men and women and decreasing inequality over more than 20 years. Despite the positive trend, large gender differences in earnings dynamics persist. While earnings growth for men is more closely tied to the business cycle, women face much higher volatility overall. Earnings volatility is also substantially higher among foreign-born workers, reflecting weaker labor market attachment and high risk of large negative shocks for low-income immigrants. We document an important role of social benefits usage for the overall trends and for differences across subpopulations. Higher benefits enrollment, especially for women and immigrants, is associated with higher earnings volatility. As the generosity and usage of benefit programs declined over time, we find stronger earnings growth among low-income workers, consistent with higher self-sufficiency.
A Universal Basic Income (UBI) is often seen as an attractive policy option to replace existing targeted transfer and subsidy programs. However, in a budget-neutral switch to a UBI there is a trade-off between the generosity of the universal transfer, and hence its poverty impact, and the implied increase in tax burden. We summarize our results for fourteen low- and middle-income countries. We find that, with the exception of Russia, a poverty reducing, budget-neutral UBI would entail a significant increase in the net tax burden of top deciles. The efficiency cost and political resistance for such a policy would likely be too high.
Background:India's abrupt nationwide Covid-19 lockdown internally displaced millions of migrant workers, who returned to distant rural homes. Documenting their labour market reintegration is a critical aspect of understanding the economic costs of the pandemic for India's poor. In a country marked by low and declining female labor force participation, identifying gender gaps in labor market reintegration – as a marker of both women's vulnerability at times of crisis and setbacks in women's agency – is especially important. Yet most studies of pandemic-displaced internal migrants in India are small, rely on highly selected convenience samples, and lack a gender focus.
Methods: Beginning in April 2020 we enrolled roughly 4,600 displaced migrants who had, during the lockdown, returned to two of India's poorest states into a cohort observational study which tracked enrolees through July 2021. Survey respondents were randomly selected from the states’ official databases of return migrants, with sampling stratified by state and gender. 85% of enrollees (3950) were working prior to the pandemic. Our difference-in-means analysis uses three survey waves conducted in July to August 2020, January to March 2021, and June to July 2021. Our analysis focuses on a balanced panel of 1780 previously working enrollees (the 45% of respondents present in the first wave that also participated in the subsequent two survey rounds). Primary outcomes of interest include labor market re-entry, earnings, and measures of vulnerability by gender.
Findings: Before the March 2020 national lockdown, 98% (95% CI [97,99]) of workers were employed in the non-agricultural sector. In July 2020, one month after the end of the lockdown, incomes plummet, with both genders earning roughly 17% of their pre-pandemic incomes. 47% (95% CI [45,49]) were employed in agriculture and 37% (95% CI [35,39]) were unemployed. Remigration is critical to regaining income – by January 2021, male re-migrants report earnings on par with their pre-pandemic incomes, while men remaining in rural areas earn only 23% (95% CI [19,27]) of their pre-pandemic income. Remigration benefits women to a lesser extent – female re-migrants regain no more than 65% (95% CI [57,73]) of their pre-pandemic income at any point. Yet men and women struggle to remigrate throughout – by July 2021, no more than 63% (95% CI [60,66]) of men and 55% (95% CI [51,59]) of women had left their home villages since returning. Gender gaps in income recovery largely reflect higher rates of unemployment among women, both among those remaining in rural areas (9 percentage points (95% CI [6,13]) higher than men across waves) and among those who remigrate (13 percentage points (95% CI [9,17]) higher than men across waves). As a result, we observe gender gaps in well-being: relative to male counterparts, women across waves were 7 percentage points (95% CI [4,10]) more likely to report reduced consumption of essential goods and fared 6 percentage points (95% CI [4,7]) worse on a food insecurity index.
Interpretation: Displaced migrants of both genders experienced persistent hardships for over a year after the initial pandemic lockdown. Women fare worse, driven by both lower rates of remigration and lower rates of labor market re-entry both inside and outside home villages. Some women drop out of the labor force entirely, but most unemployed report seeking or being available to work. In short, pandemic-induced labor market displacement has far-reaching, long-term consequences for migrant workers, especially women.
Funding: Survey costs were funded by research grants from IZA/FCDO Gender, Growth, and Labour Markets in Low Income Countries Programme, J-PAL Jobs and Opportunity Initiative, and the Evidence-based Measures of Empowerment for Research on Gender Equality (EMERGE) program at University of California San Diego.
We examine the employment effects of 3G mobile internet expansion in developing countries. We find that 3G significantly increases the labor force participation rate of women and the employment rates of both men and women. Our results suggest that 3G affects the type of jobs and there is a distinct gender dimension to these effects. Men transition away from unpaid agricultural work into operating small agricultural enterprises, while women take more unpaid jobs, especially in agriculture, and operate more small businesses in all sectors. Both men and women are more likely to work in wage jobs in the service sector.
Each year in the US, hundreds of billions of dollars are spent on transportation infrastructure and billions of hours are lost in traffic. We develop a quantitative general equilibrium spatial framework featuring endogenous transportation costs and traffic congestion and apply it to evaluate the welfare impact of transportation infrastructure improvements. Our approach yields analytical expressions for transportation costs between any two locations, the traffic along each link of the transportation network, and the equilibrium distribution of economic activity across the economy, each as a function of the underlying quality of infrastructure and the strength of traffic congestion. We characterize the properties of such an equilibrium and show how the framework can be combined with traffic data to evaluate the impact of improving any segment of the infrastructure network. Applying our framework to both the US highway network and the Seattle road network, we find highly variable returns to investment across different links in the respective transportation networks, highlighting the importance of well-targeted infrastructure investment.
This paper studies the role of private sector companies in the development of local amenities. We use evidence from one of the largest multinationals of the 20th century: the United Fruit Company (UFCo). The firm was given a large land concession in Costa Rica—one of the so‐called “Banana Republics”—from 1899 to 1984. Using administrative census data with census‐block geo‐references from 1973 to 2011, we implement a geographic regression discontinuity design that exploits a land assignment that is orthogonal to our outcomes of interest. We find that the firm had a positive and persistent effect on living standards. Company documents explain that a key concern at the time was to attract and maintain a sizable workforce, which induced the firm to invest heavily in local amenities—like the development of education and health infrastructure—that can account for our result. Consistent with this mechanism, we show, empirically and through a proposed model, that the firm's investment efforts increase with worker mobility.
We examine election voting and legislators’ roll-call votes in the United States over a twenty-five year period. Voters in areas more exposed to trade liberalization with China in 2000 subsequently shift their support toward Democrats, relative to the 1990s, though this boost for Democrats wanes after the rise of the Tea Party in 2010. House members’ votes in Congress rationalize these trends, with Democratic representatives disproportionately supporting protection during the early 2000s. Together, these results imply that voters in areas subject to higher import competition shifted votes toward the party more likely to restrict trade.