Knowledge that Transforms

We consider the problem of repeatedly choosing policies to maximize social welfare. Welfare is a weighted sum of private utility and public revenue. Earlier outcomes inform later policies. Utility is not observed, but indirectly inferred. Response functions are learned through experimentation. We derive a lower bound on regret, and a matching adversarial upper bound for a variant of the Exp3 algorithm. Cumulative regret grows at a rate of T 2/3 . This implies that (i) welfare maximization is harder than the multiarmed bandit problem (with a rate of T 1/2 for finite policy sets), and (ii) our algorithm achieves the optimal rate. For the stochastic setting, if social welfare is concave, we can achieve a rate of T 1/2 (for continuous policy sets), using a dyadic search algorithm. We analyze an extension to nonlinear income taxation, and sketch an extension to commodity taxation. We compare our setting to monopoly pricing (which is easier), and price setting for bilateral trade (which is harder).

The Mussa (1986) puzzle is the observation of a sharp and simultaneous increase in the volatility of both nominal and real exchange rates following the end of the Bretton Woods System of pegged exchange rates in 1973. It is commonly viewed as a central piece of evidence in favor of monetary non‐neutrality because it is an instance in which a change in the monetary regime caused a dramatic change in the equilibrium behavior of a real variable—the real exchange rate—and is often further interpreted as direct evidence in favor of models with nominal rigidities in price setting. This paper shows that the data do not support this latter conclusion because there was no simultaneous change in the properties of the other macro variables, nominal or real; an extended set of Mussa facts falsifies both conventional flexible‐price RBC models and sticky‐price New Keynesian models. We present a resolution to the broader Mussa puzzle based on a model of segmented financial market, in which the bulk of the nominal exchange rate risk is held by financial intermediaries and is not shared smoothly throughout the economy, emphasizing the importance of monetary transmission via the risk premium channel.

Two opposed interested parties (IPs) compete to influence citizens with heterogeneous priors which receive news items produced by a variety of sources. The IPs fight to capture the coverage conveyed in these items. We characterize the equilibrium level of capture of item as well as the equilibrium level of information transmission. Capture increases the prevalence of the ex ante most informative messages and can explain the empirical distribution of slant at the news‐item level. Opposite capturing efforts do not cancel each other and instead undermine social learning as rational citizens discount informative messages. Citizen skepticism makes efforts to capture the news strategic substitutes. Because of strategic substitution, competition for influence is compatible with horizontal differentiation between successful media. In equilibrium, rational citizens choose to consume messages from aligned sources despite knowledge of the bias in a manner consistent with recent empirical evidence.

Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. We evaluate a Colombian program for 200 firms which aimed to increase exporting. Priors were elicited from academics, policymakers, and firms. Contrary to these priors, frequentist estimation cannot reject null effects in 2019, and finds some negative impacts in 2020. For binary outcomes like whether firms export, frequentist estimates are relatively precise, and Bayesian posterior intervals update to overlap almost completely with standard confidence intervals. For outcomes like increasing export variety, where the priors align with the data, the value of these priors is seen in posterior intervals that are considerably narrower than the confidence intervals. Finally, for noisy outcomes like export value, posterior intervals show almost no updating from priors, highlighting how uninformative the data are about such outcomes. Future policy experiments could use these posteriors as priors in a Bayesian or empirical Bayesian analysis.

India's Industrial Disputes Act (IDA) requires large manufacturing plants to pay substantial costs if they wish to shrink their workforce. Since the early 2000s, these large plants have dramatically increased their use of contract workers who are not subject to these regulatory constraints. Between 2000 and 2015, the contract labor share in non‐managerial employment nearly doubled at establishments with more than 100 workers (from 21 to 40 percentage points), while it only increased from 14 to 17 percentage points at establishments with less than 50 workers. Over the same period, the thickness of the right tail of the establishment size distribution in formal Indian manufacturing plants increased, the average product of labor at large plants declined, the job creation rate for large plants increased, and the probability that large plants introduced new products rose. We argue that these changes were caused by the increased adoption of contract labor. In a model of establishment growth subject to firing costs, we show that easing access to contract labor increased TFP in Indian manufacturing by 7.3% since the early 2000s, occurring all through a one‐time reduction in misallocation between large and small plants with negligible change in the long‐run growth rate.

We develop a stylized model that allows us to estimate a value-added measure for nursing homes ("SNFs") which accounts for patient selection both into and out of a SNF. We use the model, together with detailed data on the physical and mental health of about 6 million Medicare SNF patients between 2011 and 2016, to estimate the value added for about 14,000 distinct SNFs. We document substantial heterogeneity in value added. Nationwide, compared to a 10th percentile SNF, a 90th percentile SNF is able to discharge a patient at the same health level almost a week sooner, or one quarter of the median length of stay. Heterogeneity in value added within a market is almost as large as it is nationwide. Our results point to the potential for substantial gains through policies that encourage reallocation of patients to higher-quality SNFs within their market.

We study the effect of incarceration on wages, self-employment, and taxes and transfers in North Carolina and Ohio using two quasi-experimental research designs: discontinuities in sentencing guidelines and random assignment to judges. Across both states, incarceration generates short-term drops in economic activity while individuals remain in prison. As a result, a year-long sentence decreases cumulative earnings over five years by 13%. Beyond five years, however, there is no evidence of lower employment, wage earnings, or self-employment in either state, as well as among defendants with no prior incarceration history. These results suggest that upstream factors, such as other types of criminal justice interactions or pre-existing labor market detachment, are more likely to be the cause of low earnings among the previously incarcerated, who we estimate would earn just $5,000 per year on average if spared a prison sentence.

Based on the GARCH literature, Engle and Russell (1998) established consistency and asymptotic normality of the QMLE for the autoregressive conditional duration (ACD) model, assuming strict stationarity and ergodicity of the durations. Using novel arguments based on renewal process theory, we show that their results hold under the stronger requirement that durations have finite expectation. However, we demonstrate that this is not always the case under the assumption of stationary and ergodic durations. Specifically, we provide a counterexample where the MLE is asymptotically mixed normal and converges at a rate significantly slower than usual. The main difference between ACD and GARCH asymptotics is that the former must account for the number of durations in a given time span being random. As a by‐product, we present a new lemma which can be applied to analyze asymptotic properties of extremum estimators when the number of observations is random.

How do collateral requirements impact consumer borrowing behavior? Using administrative loan application and performance data from the U.S. Federal Disaster Loan Program, we exploit a loan amount threshold above which households must post their residence as collateral. Our bunching estimates suggest that the median borrower is willing to give up 40% of their loan amount to avoid posting collateral. Exploiting time variation in the threshold, we estimate collateral causally reduces default rates by 36%. Finally, we structurally estimate households' attachment to their homes, net of any equity, and find a median value of $11,000. Attachment creates a wedge between lender and borrower valuation of collateral of 15%. Our results explain high perceived default costs in the mortgage market, and document the importance of collateral for reducing moral hazard in consumer credit markets.

Milgrom and Shannon (1994) provide necessary and sufficient conditions on parameterized optimization problems for their solution sets to be globally monotone in the parameter. We establish that their conditions may be significantly relaxed when focusing on discrete, binary comparisons between solution sets. Such binary comparisons are ubiquitous in economics and may involve comparing the same decision maker across two distinct regimes or two distinct decision makers with related objectives (e.g., a monopolist firm versus a social planner). While the single‐crossing property remains prominent in the theory, quasisupermodularity of the objective functions of interest is not needed. Our approach relies upon a novel method of embedding a new optimization problem with a quasisupermodular objective function “between” the two original problems of interest. In smooth problems, sufficient conditions for our new assumptions may be verified by elementary differential comparisons, making them well suited for applied work. We illustrate the relevance of this novel approach with several economic applications.