Developing country megacities suffer from severe road traffic congestion, yet the level of congestion is not a direct measure of equilibrium inefficiency. I study the peak‐hour traffic congestion equilibrium in Bangalore. To measure travel preferences, I use a model of departure time choice to design a field experiment with congestion pricing policies and implement it using precise GPS data. Commuter responses in the experiment reveal moderate schedule inflexibility and a high value of time. I then show that in Bangalore, traffic density has a moderate and linear impact on travel delay. My policy simulations with endogenous congestion indicate that optimal congestion charges would lead to a small reduction in travel times, and small commuter welfare gains. This result is driven primarily by the shape of the congestion externality. Overall, these results suggest limited commuter welfare benefits from peak‐spreading traffic policies in cities like Bangalore.
This paper investigates how tax rates and tax enforcement jointly impact fiscal capacity in low‐income countries. We study a policy experiment in the D.R. Congo that randomly assigned 38,028 property owners to the status quo tax rate or to a rate reduction. This variation in tax liabilities reveals that the status quo rate lies above the revenue‐maximizing tax rate (RMTR). Reducing rates by about one‐third would maximize government revenue by increasing tax compliance. We then exploit two sources of variation in enforcement—randomized enforcement letters and random assignment of tax collectors—to show that the RMTR increases with enforcement. Including an enforcement message on tax letters or replacing tax collectors in the bottom quartile of enforcement capacity with average collectors would raise the RMTR by about 40%. Tax rates and enforcement are thus complementary levers. Jointly optimizing tax rates and enforcement would lead to 10% higher revenue gains than optimizing them independently. These findings provide experimental evidence that low government enforcement capacity sets a binding ceiling on the revenue‐maximizing tax rate in some developing countries, thereby demonstrating the value of increasing tax rates in tandem with enforcement to expand fiscal capacity.
We show that Theorem 4 in Hansen (2022) applies to exactly the same class of estimators as does the classical Aitken theorem. We furthermore point out that Theorems 5–7 in Hansen (2022) contain extra assumptions not present in the classical Gauss–Markov or Aitken theorem, and thus the former theorems do not contain the latter ones as special cases.
Annually, work‐related mortality is responsible for 5–7% of all global deaths, and at least 1‐in‐9 workers experience nonfatal occupational accidents (ILO (2019a,b)). Occupational Safety and Health (OSH) committees are considered the key worker voice institution through which to improve workplace safety and health (ILO (1981)). I present evidence of OSH committees' causal effects on workers and on factories. To do so, I collaborated with 29 multinational apparel buyers that committed to enforce a local mandate for OSH committees on their suppliers in Bangladesh. With the buyers, I implemented a nearly year‐long field experiment with 84 supplier factories, randomly enforcing the mandate on half. The buyers' intervention increased compliance with the OSH committee law. Exploiting the experimental variation in OSH committees' strength, I find that stronger OSH committees had small, positive effects on objective measures of safety. These improvements did not come at a cost to workers in terms of wages or employment or to factories in terms of labor productivity. The effects on compliance, safety, and voice were largest for factories with better managerial practices. Factories with worse practices did not improve, and workers in these factories reported lower job satisfaction; this finding suggests complementarity between external enforcement and internal capacity in determining the efficacy of regulation.
Central banks wish to avoid self‐fulfilling fluctuations. Interest rate rules with a unit response to real rates achieve this under the weakest possible assumptions about the behavior of households and firms. They are robust to household heterogeneity, hand‐to‐mouth consumers, non‐rational household or firm expectations, active fiscal policy, and to any form of intertemporal or nominal‐real links. They are easy to employ in practice, using inflation‐protected bonds to infer real rates. With a time‐varying short‐term inflation target, they can implement an arbitrary inflation path, including optimal policy. This provides a way to translate policy makers' desired path for inflation into one for nominal rates. U.S. Federal Reserve behavior is remarkably close to that predicted by a real rate rule, given the desired inflation path of U.S. monetary policy makers. Real rate rules work thanks to the key role played by the Fisher equation in monetary transmission.
We explore the deliberate infusion of ambiguity into the design of contracts. We show that when the agent is ambiguity‐averse and hence chooses an action that maximizes their minimum utility, the principal can strictly gain from using an ambiguous contract, and this gain can be arbitrarily high. We characterize the structure of optimal ambiguous contracts, showing that ambiguity drives optimal contracts toward simplicity. We also provide a characterization of ambiguity‐proof classes of contracts, where the principal cannot gain by infusing ambiguity. Finally, we show that when the agent can engage in mixed actions, the advantages of ambiguous contracts disappear.
We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market‐level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market‐level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which nonprice product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work.
The allocation of decision‐making power is a critical choice that organizations make to mitigate agency problems and information frictions. This paper investigates the role of delegation for organizations where the agency problem is both pervasive and has potentially high welfare consequences: state‐owned enterprises (SOEs). I use a natural experiment in India to uncover the causal effects of granting SOE managers more autonomy over strategic decisions. Managers meaningfully exercise this autonomy, which results in greater value added, but also a reduced emphasis on outcomes valued by the government, such as a reduction in worker amenities (employee housing), and an increase in markups. Returns to autonomy are higher for firms with higher baseline incentive conflict.
The expectation is an example of a descriptive statistic that is monotone with respect to stochastic dominance, and additive for sums of independent random variables. We provide a complete characterization of such statistics, and explore a number of applications to models of individual and group decision‐making. These include a representation of stationary monotone time preferences, extending the work of Fishburn and Rubinstein (1982) to time lotteries. This extension offers a new perspective on risk attitudes toward time, as well as on the aggregation of multiple discount factors. We also offer a novel class of non‐expected utility preferences over gambles which satisfy invariance to background risk as well as betweenness, but are versatile enough to capture mixed risk attitudes.
Consider a bipartite network where N consumers choose to buy or not to buy M different products. This paper considers the properties of the logit fit of the N × M array of “ i ‐buys‐ j ” purchase decisions, <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi mathvariant="bold">Y</a:mi> <a:mo>=</a:mo> <a:msub> <a:mrow> <a:mo stretchy="false">[</a:mo> <a:msub> <a:mrow> <a:mi>Y</a:mi> </a:mrow> <a:mrow> <a:mi>i</a:mi> <a:mi>j</a:mi> </a:mrow> </a:msub> <a:mo stretchy="false">]</a:mo> </a:mrow> <a:mrow> <a:mn>1</a:mn> <a:mo>≤</a:mo> <a:mi>i</a:mi> <a:mo>≤</a:mo> <a:mi>N</a:mi> <a:mo>,</a:mo> <a:mn>1</a:mn> <a:mo>≤</a:mo> <a:mi>j</a:mi> <a:mo>≤</a:mo> <a:mi>M</a:mi> </a:mrow> </a:msub> </a:math>, onto a vector of known functions of consumer and product attributes under asymptotic sequences where (i) both N and M grow large, (ii) the average number of products purchased per consumer is finite in the limit, (iii) there exists dependence across elements in the same row or same column of Y (i.e., dyadic dependence), and (iv) the true conditional probability of making a purchase may, or may not, take the assumed logit form. Condition (ii) implies that the limiting network of purchases is sparse : only a vanishing fraction of all possible purchases are actually made. Under sparse network asymptotics, I show that the parameter indexing the logit approximation solves a particular Kullback–Leibler Information Criterion (KLIC) minimization problem (defined with respect to a certain Poisson population). This finding provides a simple characterization of the logit pseudo‐true parameter under general misspecification (analogous to a (mean squared error (MSE) minimizing) linear predictor approximation of a general conditional expectation function (CEF)). With respect to sampling theory, sparseness implies that the first and last terms in an extended Hoeffding‐type variance decomposition of the score of the logit pseudo composite log‐likelihood are of equal order. In contrast, under dense network asymptotics, the last term is asymptotically negligible. Asymptotic normality of the logistic regression coefficients is shown using a martingale central limit theorem (CLT) for triangular arrays. Unlike in the dense case, the normality result derived here also holds under degeneracy of the network graphon. Relatedly, when there “happens to be” no dyadic dependence in the data set in hand, it specializes to recently derived results on the behavior of logistic regression with rare events and i.i.d. data. Simulation results suggest that sparse network asymptotics better approximate the finite network distribution of the logit estimator. A short empirical illustration, and additional calibrated Monte Carlo experiments, further illustrate the main theoretical ideas.