We posit that autocrats introduce local elections when their bureaucratic capacity is low. Local elections exploit citizens' informational advantage in keeping local officials accountable, but they also weaken vertical control. As bureaucratic capacity increases, the autocrat limits the role of elected bodies to regain vertical control. We argue that these insights can explain the introduction of village elections in rural China and the subsequent erosion of village autonomy years later. We construct a novel dataset to document political reforms, policy outcomes, and de facto power for almost four decades. We find that the introduction of elections improves popular policies and weakens unpopular ones. Increases in regional government resources lead to loss of village autonomy, but less so in remote villages. These patterns are consistent with an organizational view of local elections within autocracies.
Virtually all theories of economic growth predict a positive relationship between population size and productivity. In this paper, I study a particular historical episode to provide direct evidence for the empirical relevance of such scale effects. In the aftermath of the Second World War, 8 million ethnic Germans were expelled from their domiciles in Eastern Europe and transferred to West Germany. This inflow increased the German population by almost 20%. Using variation across counties, I show that the settlement of refugees had large and persistent effects on the size of the local population, manufacturing employment, and income per capita. These findings are quantitatively consistent with an idea‐based model of spatial growth if population mobility is subject to frictions and productivity spillovers occur locally. The estimated model implies that the refugee settlement increased aggregate income per capita by about 12% after 25 years and triggered a process of industrialization in rural areas.
The economic impacts of climate change are highly uncertain. Two of the most important uncertainties are the sensitivity of the climate system and the so-called damage functions, which relate climate change to economic costs and benefits. Despite broad awareness of these uncertainties, it is unclear which of them is most important, especially at the regional level. Here we construct regional damage functions, based on two different global damage functions, and apply them to two climate models with vastly different climate sensitivities. We find that uncertainty in both climate sensitivity and aggregate economic damages per degree of warming are of similar importance for the global economic impact of climate change, with the decrease in global economic productivity ranging between 4% and 24% by the end of the century under a high-emission scenario. At the regional level, however, the effects of climate change can vary even more substantially, depending both on a region's initial temperature and the amount of warming it experiences, with some regions gaining in productivity and others losing. The ranges of uncertainty are therefore potentially much larger at a regional level. For example, at the end of the century, under a high-emission scenario, we find that India's productivity decreases between 13% and 57% and Russia's increases between 24% and 74%, while Germany's change in productivity ranges from an increase of 8% to a decrease of 4%. Our findings emphasize the importance of including these uncertainties in estimates of future economic impacts, as they are vital for the resulting impacts and thus policy implications.
The COVID-19 pandemic has upended health and living standards around the world. This article provides an interim overview of these effects, with a particular focus on low- and middle-income countries (LMICs). Economists have explained how the pandemic is likely to have different consequences for LMICs and demands distinct policy responses compared to those of rich countries. We survey the rapidly expanding body of empirical research that documents the pandemic's many adverse economic and noneconomic effects in terms of living standards, education, health, and gender equality, which appear to be unprecedented in scope and scale. We also review research on successful and failed policy responses, including the failure to ensure widespread vaccine coverage in many LMICs, which is needed to end the pandemic. We close with a discussion of implications for public policy in LMICs and for the institutions of international governance, given the likelihood of future pandemics and other major shocks (e.g., climate).
In 2018, the United States launched a trade war with China, marking an abrupt departure from its historical leadership in integrating global markets. By late 2019, the United States had imposed tariffs on roughly $350 billion of Chinese imports, and China had retaliated on $100 billion of US exports. Economists have used a diversity of data and methods to assess the impacts of the trade war on the United States, China, and other countries. This article reviews what we have learned to date from this work.
Children's experiences during early childhood are critical for their cognitive and socioemotional development, two key dimensions of human capital. However, children from low-income backgrounds often grow up lacking stimulation and basic investments, which leads to developmental deficits that are difficult, if not impossible, to reverse later in life without intervention. The existence of these deficits is a key driver of inequality and contributes to the intergenerational transmission of poverty. In this article, we discuss the framework used in economics to model parental investments and early childhood development and use it as an organizing tool to review some of the empirical evidence on early childhood research. We then present results from various important early childhoods interventions, with an emphasis on developing countries. Bringing these elements together, we draw conclusions on what we have learned and provide some directions for future research.
Early childhood development is becoming the focus of policy worldwide. However, the evidence on the effectiveness of scalable models is scant, particularly when it comes to infants in developing countries. In this paper, we describe and evaluate with a cluster-Randomized Controlled Trial an intervention designed to improve the quality of child stimulation within the context of an existing parenting program in Colombia, known as FAMI. The intervention improved children’s development by 0.16 of a standard deviation (SD) and children’s nutritional status, as reflected in a reduction of 5.8 percentage points of children whose height-for-age is below -1 SD.
This article examines the role that implementation science can play in evidence-based parenting programs. Although parenting programs can support parents in their caregiving roles, adapting and taking an evidence-based approach from one place to another without attending to implementation factors may contribute to poor impact in a new setting. Implementation science enables researchers to move beyond monitoring and evaluation of outcomes of a parenting program to understanding the process of putting the program into practice. Factors such as whether the program meets the needs of families and communities, how to secure buy-in from key stakeholders, what training and supervision are needed for the workforce, and ways that parenting programs can be integrated in existing infrastructure are all critical to successful implementation. Quality improvement can be built into the implementation process through feedback loops that inform rapid changes and testing cycles over time as a program is implemented. If researchers lead initial implementation of parenting programs, they must determine how the program can continue to work when using community workers and local systems rather than researchers. Open access components are especially important for the implementation of parenting programs in low- and middle-income countries to avoid prohibitive costs of proprietary programs and to benefit from flexibility in adapting components to meet the needs of particular local populations. Parenting programs benefit when policy makers, program leaders, and researchers attend not only to the what but also to the how of implementation.
We deliver one month's average profit to a randomly selected group of female microenterprise owners in Dandora, Kenya, arriving just in advance of an exponential growth in COVID-19 cases. Relative to a control group, firms recoup about one third of their initial decline in profit, and food expenditures increase. Control profit responds to economic conditions and government announcements during our study period, and treatment effects are largest when control profit is at its lowest. PPE spending and precautionary management practices increase to mitigate the health risks of more intensive firm operation, but only among those who perceive COVID-19 as a major risk.
We construct an endogenous growth model with random interactions where firms are subject to distortions. The TFP distribution evolves endogenously as firms seek to upgrade their technology over time either by innovating or by imitating other firms. We use the model to quantify the effects of misallocation on TFP growth in emerging economies. We structurally estimate the stationary state of the dynamic model targeting moments of the empirical distribution of R&D and TFP growth in China during the period 2007–2012. The estimated model fits the Chinese data well. We compare the estimates with those obtained using data for Taiwan and perform counterfactuals to study the effect of alternative policies. R&D misallocation has a large effect on TFP growth.
Hasan Mahmud Reza and colleagues argue that access to vaccines enabled by predictable supply of vaccine doses and delivery to remote areas are critical for vaccine uptake in low and middle income countries.
We start by considering the implications of unequal parenting for children’s outcomes later in life. The literature on child development has established that the development process is cumulative and that early achievements foster additional learning later on. To highlight this issue, we document how parenting decisions and the family environment correlate with long-run outcomes such as graduating from college. In our analysis, we touch upon a dimension that is less salient in the two chapters: parenting style. We show that parenting style is not a mere by-product of families’ socio-economic status. Rather, it is associated with children’s outcomes in a way that is distinct from the influence of socio-economic factors such as parents’ education and race. We also argue that the choice of parenting styles is responsive to changes in the environment where children grow up. We show that parenting styles vary systematically across countries with different policies and institutions. This evidence suggests that understanding how parents adjust their behaviour to policy changes is important for drawing useful policy implications. These insights could be especially important for policies aiming to alleviate inequality in early childhood outcomes as parents’ endogenous responses could potentially either magnify or dampen the direct effect of policy interventions.
The recent economic history of global integration has been characterized by a dismantling of capital controls and increased foreign direct investment (FDI). This paper explores the role of impediments to international capital mobility, foreign direct investment, and technology diffusion in shaping Latin American economic growth. First, the paper summarizes and quantifies the effects of the Bretton Woods international financial system in Latin America. Then, I study the consequences of capital controls—and their dismantling—on FDI and trade-induced technological advancements and their role in shaping local development, especially in the 1990s after the implementation of several trade liberalization policies.
Financial, informational and other constraints lower the adoption of welfare-improving technologies amongst people living in poverty. Field trials have identified effective strategies to facilitate behaviour change. Researchers and policymakers need to apply this knowledge, and form institutional partnerships to implement solutions at scale.
Many school districts with centralized school choice adopt strategy-proof assignment mechanisms to relieve applicants from needing to strategize based on beliefs about their own admissions chances. This article shows that beliefs about admissions chances shape choice outcomes even when the assignment mechanism is strategy-proof by influencing how applicants search for schools and that “smart matching platforms” that provide live feedback on admissions chances help applicants search more effectively. Motivated by a model in which applicants engage in costly search for schools and overoptimism can lead to undersearch, we use data from a large-scale survey of choice participants in Chile to show that learning about schools is hard, beliefs about admissions chances guide the decision to stop searching, and applicants systematically underestimate nonplacement risk. We use RCT and RD research designs to evaluate scaled live feedback policies in the Chilean and New Haven choice systems. Twenty-two percent of applicants submitting applications where risks of nonplacement are high respond to warnings by adding schools to their lists, reducing nonplacement risk by 58% and increasing test score value added at the schools where they enroll by 0.10 standard deviations. Reducing the burden of school choice requires not just strategy-proofness inside the centralized system but also choice supports for the strategic decisions that inevitably remain outside of it.
We show that labor market transaction costs explain why the smallest farms are more efficient than slightly larger farms in most low-income countries and that increases in machine capacity with operational scale result in the globally observed rising upper tail of productivity. We find evidence consistent with these mechanisms using Indian data, and we show that if all Indian farms were at the minimum scale required to maximize the return on land, the number of farms would be reduced by 82% and income per farm worker would rise by 68%.