Colombia's PACES program provided over 125,000 poor children with vouchers that covered the cost of private secondary school. The vouchers were renewable annually conditional on adequate academic progress. Since many vouchers were assigned by lottery, program effects can reliably be assessed by comparing lottery winners and losers. Estimates using administrative records suggest the PACES program increases secondary school completion rates by 15 to 20 percent. Correcting for the greater percentage of lottery winners taking college admissions tests, the program increased test scores by two-tenths of a standard deviation in the distribution of potential test scores.
Compensation of most US public school teachers is rigid and solely based on seniority. This paper studies the effects of a reform that gave school districts in Wisconsin full autonomy to redesign teacher pay schemes. Following the reform some districts switched to flexible compensation. Using the expiration of preexisting collective bargaining agreements as a source of exogenous variation in the timing of changes in pay, I show that the introduction of flexible pay raised salaries of high-quality teachers, increased teacher quality (due to the arrival of high-quality teachers from other districts and increased effort), and improved student achievement.
The public debate over disability insurance has centered on concerns about individuals without severe health conditions receiving benefits. We go beyond health risk alone to quantify the overall insurance value of U.S. disability programs, including value from insuring non-health risk. We find that disability recipients, especially those with less-severe health conditions, are much more likely to have experienced a wide variety of non-health shocks than non-recipients. Selection into disability receipt on the basis of non-health shocks is so strong among individuals with less-severe health conditions that by many measures less-severe recipients are worse off than more-severe recipients. As a result, under baseline assumptions, benefits to less-severe recipients have an annual surplus value (insurance benefit less efficiency cost) over cost-equivalent tax cuts of $7,700 per recipient, about three-fourths that of benefits to more-severe recipients ($9,900). Insurance against non-health risk accounts for about one-half of the value of U.S. disability programs.
How much are low-income individuals willing to pay for health insurance, and what are the implications for insurance markets? Using administrative data from Massachusetts’ subsidized insurance exchange, we exploit discontinuities in the subsidy schedule to estimate willingness to pay and costs of insurance among low-income adults. As subsidies decline, insurance take-up falls rapidly, dropping about 25 percent for each $40 increase in monthly enrollee premiums. Marginal enrollees tend to be lower-cost, indicating adverse selection into insurance. But across the entire distribution we can observe (approximately the bottom 70 percent of the willingness to pay distribution) enrollees’ willingness to pay is always less than half of their own expected costs that they impose on the insurer. As a result, we estimate that take-up will be highly incomplete even with generous subsidies. If enrollee premiums were 25 percent of insurers’ average costs, at most half of potential enrollees would buy insurance; even premiums subsidized to 10 percent of average costs would still leave at least 20 percent uninsured. We briefly consider potential explanations for these findings and their normative implications
We study the effects of conviction and incarceration on recidivism using quasi-random judge assignment. We extend the typical binary-treatment framework to a setting with multiple treatments, and outline a set of assumptions under which standard 2SLS regressions recover causal and margin-specific treatment effects. Under these assumptions, 2SLS regressions applied to data on felony cases in Virginia imply that conviction leads to a large and long-lasting increase in recidivism relative to dismissal, consistent with a criminogenic effect of a criminal record. In contrast, incarceration reduces recidivism, but only in the short run. The assumptions we outline could be considered restrictive in the random judge framework, ruling out some reasonable models of judge decision-making. Indeed, a key assumption is empirically rejected in our data. Nevertheless, after deriving an expression for the resulting asymptotic bias, we argue that the failure of this assumption is unlikely to overturn our qualitative conclusions. Finally, we propose and implement alternative identification strategies. Consistent with our characterization of the bias, these analyses yield estimates qualitatively similar to those based on the 2SLS estimates. Taken together, our results suggest that conviction is an important and potentially overlooked driver of recidivism, while incarceration mainly has shorter-term incapacitation effects.
Criminal groups govern millions worldwide. Even in strong states, gangs resolve disputes and provide security. Why do these duopolies of coercion emerge? In many cases, gangs fill vacuums of official order. If so, increasing state presence should crowd out criminal governance. In this paper, however, we show that state and gang rule are sometimes complements. In particular, gangs can deter state predation by keeping neighborhoods orderly and loyal. If true, increasing state presence could increase gang rule. We investigate in Medellín, Colombia. Criminal leaders told us they rule mainly to protect drug rents. We test gang responses to state presence using a geographic discontinuity. Internal border changes in 1987 assigned some blocks to be exogenously closer to state security for three decades. Gangs responded to closer state presence by increasing governance services, but primarily in neighborhoods with the greatest potential drug rents. This suggests new strategies for countering criminal governance.
Does new media promote accountability in nondemocratic countries, where offline media is often suppressed? We show that blog posts, which exposed corruption in Russian state-controlled companies, had a negative causal impact on their market returns. For identification, we exploit the precise timing of blog posts by looking at within-day results with company-day fixed effects. Furthermore, we show that the posts are ultimately associated with higher management turnover and less minority shareholder conflicts. Taken together, our results suggest that social media can discipline corruption even in a country with limited political competition and heavily censored traditional media.
This paper provides evidence that exposure to illegal labor markets during childhood leads to the formation of industry-specific human capital at an early age, putting children on a criminal life path. Using the timing of U.S. antidrug policies, I show that when the return to illegal activities increases in coca suitable areas in Peru, parents increase the use of child labor for coca farming, putting children on a criminal life path. Using administrative records, I show that affected children are about 30% more likely to be incarcerated for violent and drug-related crimes as adults. No effect in criminality is found for individuals that grow up working in places where the coca produced goes primarily to the legal sector, suggesting that it is the accumulation of human capital specific to the illegal industry that fosters criminal careers. However, the rollout of a conditional cash transfer program that encourages schooling mitigates the effects of exposure to illegal industries, providing further evidence on the mechanisms.
When is it possible for one person to persuade another to change her action? We consider a symmetric information model where a sender chooses a signal to reveal to a receiver, who then takes a noncon- tractible action that affects the welfare of both players. We derive necessary and sufficient conditions for the existence of a signal that strictly benefits the sender. We characterize sender-optimal signals. We examine comparative statics with respect to the alignment of the sender’s and the receiver’s preferences. Finally, we apply our results to persuasion by litigators, lobbyists, and sales people.
Using a 1994 law change, we exploit quasi-experimental variation in the assignment of rent control in San Francisco to study its impacts on tenants and landlords. Leveraging new data tracking individuals' migration, we find rent control limits renters' mobility by 20 percent and lowers displacement from San Francisco. Landlords treated by rent control reduce rental housing supplies by 15 percent by selling to owner-occupants and redeveloping buildings. Thus, while rent control prevents displacement of incumbent renters in the short run, the lost rental housing supply likely drove up market rents in the long run, ultimately undermining the goals of the law.
Using data from the Current Population Survey, this paper describes the effect of the Marie1Boatlift of 1980on the Miami labor market. The Marie1 immigrants increased the Miami labor force by 7%, and the percentage increase in labor supply to less-skilled occupations and industries was even greater because most of the immigrants were relatively unskilled. Nevertheless, the Marie1 influx appears to have had virtually no effect on the wages or unemployment rates of less-skilled workers, even among Cubans who had immigrated earlier. The author suggests that the ability of Miami's labor market to rapidly absorb the Marie1 immigrants was largely owing to its adjustment to other large waves of immigrants in the two decades before the Marie1 Boatlift.
Abstract: We develop an algorithm for detecting teacher cheating that combines information on unexpected test score fluctuations and suspicious patterns of answers for students in a classroom. Using data from the Chicago public schools, we estimate that serious cases of teacher or administrator cheating on standardized tests occur in a minimum of 4–5 percent of elementary school classrooms annually. The observed frequency of cheating appears to respond strongly to relatively minor changes in incentives. Our results highlight the fact that high-powered incentive systems, especially those with bright line rules, may induce unexpected behavioral distortions such as cheating. Statistical analysis, however, may provide a means of detecting illicit acts, despite the best attempts of perpetrators to keep them clandestine.
We investigate the persistent impact of data misreporting from China’s Qing Dynasty (1644-1912) on contemporary data quality in the country. We examine historical grain price data, collected monthly by Qing prefectural officials and reported to the central government. Using the absence of seasonal price fluctuations over extended periods as an indicator, we assess data quality. Employing an instrumental variable approach, we establish a causal link between data quality in the Qing Dynasty and data misreporting in modern China. Our findings indicate that a one-standarddeviation increase in Qing data quality corresponds to a 0.16 standard deviation increase in modern data quality. This result holds under various alternative specifications, even when the analysis is limited to frequently traded major crop types from the Qing Dynasty and when different periods of modern data quality are used. Moreover, we find that the persistence of data misreporting remains evident even in prefectures that have undergone significant changes in geographical attributes. We further suggest that this persistent pattern of data misreporting is primarily influenced by cultural factors rather than geographical ones.
This article argues that the European Marriage Pattern (EMP) has played a fundamental role in western Europe’s economic development. The EMP emerged in north-western Europe in the late medieval period as a result of the preaching of the Catholic Church promoting marriage based on consensus, the rise of labour markets, and specific institutions concerning property transfers between generations that encouraged wage labour by women. It resulted in a demographic regime embedded in a highly commercial environment, in which households interacted frequently with labour, capital, and commodity markets.We also discuss possible long-term consequences for human capital formation and institution building.
In this essay, we review the basic economics of housing supply and the functioning of US housing markets to better understand the distribution of home prices, household wealth, and the spatial distribution of people across markets. We employ a cost-based approach to gauge whether a housing market is delivering appropriately priced units. Specifically, we investigate whether market prices (roughly) equal the costs of producing the housing unit. If so, the market is well-functioning in the sense that it efficiently delivers housing units at their production cost. The gap between price and production cost can be understood as a regulatory tax. The available evidence suggests, but does not definitively prove, that the implicit tax on development created by housing regulations is higher in many areas than any reasonable negative externalities associated with new construction. We discuss two main effects of developments in housing prices: on patterns of household wealth and on the incentives for relocation to high-wage, high-productivity areas. Finally, we turn to policy implications.
There is no doubt that physical activity improves health conditions; however, does it also affect the way people interact? Beyond the obvious effects related to team games, we wonder whether physical activity has in itself some effect on social behavior. Our research focuses on the potential effects of physical activity on trust and trustworthiness. Specifically, we compare the choices of subjects playing an investment game who were previously exposed to short-time physical activity to others who are not exposed to it, but involved in different simple tasks. On average, we find that subjects exposed to physical activity exhibit more trust and prosocial behaviors than those who are not exposed. These effects are not temporary.
Random assignment of treatment and concurrent data collection on treatment and control groups is the norm in medical evaluation research. In contrast, the use of random assignment to evaluate social programs remains controversial. Following criticism of parametric evaluation models (e.g., Lalonde (1986)), econometric research has been geared towards establishing conditions that guarantee nonparametric identification of treatment effects in observational studies, i.e. identification without relying on functional form restrictions or distributional assumptions. The focus has been on identification of average treatment effects in a population of interest, or on the average effect for the subpopulation that is treated. The conditions required to nonparametrically identify these parameters can be restrictive, however, and the derived identification results fragile. In particular, results in Chamberlain (19861, Manski (1990),Heckman (1990),and Angrist and Imbens (1991) require that there be some subpopulation for whom the probability of treatment is zero, at least in the limit. The purpose of this paper is to show that even when there is no subpopulation available for whom the probability of treatment is zero, we can still identify an average treatment effect of interest under mild restrictions satisfied in a wide range of models and circumstances. We call this a local average treatment effect (LATE). Examples of problems where the local average treatment effect is identified include latent index models and evaluations based on natural experiments such as those studied by Angrist (1990) and Angrist and Krueger (1991). LATE is the average treatment effect for individuals whose treatment status is influenced by changing an exogenous regressor that satisfies an exclusion restriction.
We analyze a sequential decision model in which each decision maker looks at the decisions made by previous decision makers in taking her own decision. This is rational for her because these other decision makers may have some information that is important for her. We then show that the decision rules that are chosen by optimizing individuals will be characterized by herd behavior; i.e., people will be doing what others are doing rather than using their information. We then show that the resulting equilibrium is inefficient.
This paper shows how deportation policies can backfire by disseminating not only ideas between countries but also criminal networks, spreading gangs, in this case, across El Salvador, and spurring migration back to the United States. In 1996, the US Illegal Immigration Responsibility Act increased the number of criminal deportations. In particular, the members of large Salvadoran gangs developed in Los Angeles were sent back to El Salvador. Using variation in criminal deportations over time and across cohorts, combined with geographical variation in US gangs' location, I find that these deportations led to an increase in homicide rates and gang activity, as well as an increase in gang recruitment and migration of children.
Two people, 1 and 2, are said to have common knowledge of an event E if both know it, 1 knows that 2 knows it, 2 knows that 1 knows is, 1 knows that 2 knows that 1 knows it, and so on. THEOREM. If two people have the same priors, and their posteriors for an event A are common knowledge, then these posteriors are equal.
Does new media promote accountability in nondemocratic countries, where offline media is often suppressed? We show that blog posts, which exposed corruption in Russian state-controlled companies, had a negative causal impact on their market returns. For identification, we exploit the precise timing of blog posts by looking at within-day results with company-day fixed effects. Furthermore, we show that the posts are ultimately associated with higher management turnover and less minority shareholder conflicts. Taken together, our results suggest that social media can discipline corruption even in a country with limited political competition and heavily censored traditional media.
Which mechanisms are simple to play? When is it easy for participants to see that a mechanism is incentive-compatible? I will start by explaining how and why economists came to ask these questions. Then I will discuss three recent answers, that capture different aspects of what makes a mechanism simple.
Drug trade-related violence has escalated dramatically in Mexico since 2007, and recent years have also witnessed large-scale efforts to combat trafficking, spearheaded by Mexico's conservative PAN party. This study examines the direct and spillover effects of Mexican policy toward the drug trade. Regression discontinuity estimates show that drug-related violence increases substantially after close elections of PAN mayors. Empirical evidence suggests that the violence reflects rival traffickers' attempts to usurp territories after crackdowns have weakened incumbent criminals. Moreover, the study uses a network model of trafficking routes to show that PAN victories divert drug traffic, increasing violence along alternative drug routes.
This paper considers the problem faced by a seller who has a single object to sell to one of several possible buyers, when the seller has imperfect information about how much the buyers might be willing to pay for the object. The seller's problem is to design an auction game which has a Nash equilibrium giving him the highest possible expected utility. Optimal auctions are derived in this paper for a wide class of auction design problems.
We consider bargaining problems between one buyer and one seller for a single object. The seller’s valuation and the buyer’s valuation for the object are assumed to be independent random variables, and each individual’s valuation is unknown to the other. We characterize the set of allocation mechanisms that are Bayesian incentive compatible and individually rational, and show the general impossibility of ex post efficient mechanisms without outside subsidies. For a wide class of problems we show how to compute mechanisms that maximize expected total gains from trade, and mechanisms that can maximize a broker’s expected profit.
This paper develops a model of strategic communication, in which a better-informed Sender (S) sends a possibly noisy signal to a Receiver (R), who then takes an action that determines the welfare of both. We characterize the set of Bayesian Nash equilibria under standard assumptions, and show that equilibrium signaling always takes a strikingly simple form, in which S partitions the support of the (scalar) variable that represents his private information and introduces noise into his signal by reporting, in effect, only which element of the partition his observation actually lies in. We show under further assumptions that before S observes his private information, the equilibrium whose partition has the greatest number of elements is Pareto-superior to all other equilibria, and that if agents coordinate on this equilibrium, R's equilibrium expected utility rises when agents' preferences become more similar. Since R bases his choice of action on rational expectations, this establishes a sense in which equilibrium signaling is more informative when agents' preferences are more similar.
Identical agents gather costly information, and then aggregate it through voting. Because information is a public good, information is underprovided relative to the social optimum. A “good” voting rule must give incentives to acquire information, as well as aggregate information efficiently. A voting rule that requires a large plurality (in the extreme, unanimity) to upset the status quo can be optimal only if the information available to each agent is sufficiently accurate. This result is independent of the preferences of voters and of the cost of information.
This paper considers a buyer-seller relationship with observable but unverifiable investments and/or random utility parameters. In such situations, it is known that contract renegotiation may prevent the implementation of first-best outcomes. In this paper, we show however that efficient investments and optimal risk-sharing can typically be achieved provided the initial contract is able to monitor the ex post renegotiation process. Specifically, we focus on the following two features of renegotiation design. First, default options in case renegotiation breaks down; second, the allocation of all bargaining power to either contracting party. Moreover, we show that these two features can be obtained in standard Rubinstein bargaining games through contractual provisions, such as specific-performance clauses and penalties for delay (or, equivalently, financial "hostages" refundable without interest).
In this article, we analyze the canonical hold-up model of Hart and Moore under the assumption that the courts can verify delivery of the good by the seller. It is shown that no further renegotiation design is necessary to achieve the first best: simple option contracts, which give the seller the right to take the delivery decision and specify payments depending on whether delivery takes place, allow implementation of efficient investment decisions and efficient trade.
We develop a tool akin to the revelation principle for dynamic mechanism-selection games in which the designer can only commit to short-term mechanisms. We identify a canonical class of mechanisms rich enough to replicate the outcomes of any equilibrium in a mechanism-selection game between an uninformed designer and a privately informed agent. A cornerstone of our methodology is the idea that a mechanism should encode not only the rules that determine the allocation, but also the information the designer obtains from the interaction with the agent. Therefore, how much the designer learns, which is the key tension in design with limited commitment, becomes an explicit part of the design. Our result simplifies the search for the designer-optimal outcome by reducing the agent’s behavior to a series of participation, truthtelling, and Bayes’ plausibility constraints the mechanisms must satisfy.
We present a qualitative and quantitative analysis of the standard growth model modified to include precautionary saving motives and liquidity constraints. We address the impact on the aggregate saving rate, the importance of asset trading to individuals, and the relative inequality of wealth and income distributions.
This paper proposes that idiosyncratic firm-level shocks can explain an important part of aggregate movements and provide a microfoundation for aggregate shocks. Existing research has focused on using aggregate shocks to explain business cycles, arguing that individual firm shocks average out in the aggregate. I show that this argument breaks down if the distribution of firm sizes is fat-tailed, as documented empirically. The idiosyncratic movements of the largest 100 firms in the United States appear to explain about one-third of variations in output growth. This “granular” hypothesis suggests new directions for macroeconomic research, in particular that macroeconomic questions can be clarified by looking at the behavior of large firms. This paper’s ideas and analytical results may also be useful for thinking about the fluctuations of other economic aggregates, such as exports or the trade balance.
We construct a model of a dynamic economy in which lenders cannot force borrowers to repay their debts unless the debts are secured. In such an economy, durable assets play a dual role: not only are they factors of production, but they also serve as collateral for loans. The dynamic interaction between credit limits and asset prices turns out to be a powerful transmission mechanism by which the effects of shocks persist, amplify, and spill over to other sectors. We show that small, temporary shocks to technology or income distribution can generate large, persistent fluctuations in output and asset prices.
We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments. These key features include best linear predictors of the effects using machine learning proxies, average effects sorted by impact groups, and average characteristics of most and least impacted units. The approach is valid in high dimensional settings, including those with small samples. In an application to an Indian immunization project, we show that most of the units in our sample exhibit no impacts, while those in the top percentile of the treatment distribution experience large positive effects. We also provide a strategy to improve power by balancing treatment assignments.