This paper examines the extent to which government audits of public resources can reduce corruption by enhancing political and judiciary accountability. We do so in the context of Brazil’s anticorruption program, which randomly audits municipalities for their use of federal funds. We find that being audited in the past reduces future corruption by 8 percent, while also increasing the likelihood of experiencing a subsequent legal action by 20 percent. We interpret these reduced-form findings through a political agency model, which we structurally estimate. Our results suggest that the reduction in corruption comes mostly from the audits increasing the perceived nonelectoral costs of engaging in corruption.

We consider a new, flexible and easy-to-implement method to estimate thecausal effects of an intervention on a single treated unit when a control group is not available and which nests previous proposals in the literature. It is a two-step methodology where in the first stage, a counterfactual is estimated based on a large-dimensional set of variables from a pool of untreated units by means of shrinkage methods, such as the least absolute shrinkage and selection operator (LASSO). In the second stage, we estimate the average intervention effect on a vector of variables, which is consistent and asymptotically normal. Our results are valid uniformly over a wide class of probability laws. We show that these results hold even when the exact date of the intervention is unknown. Tests for multiple interventions and for contamination effects are derived. By a simple transformation of the variables, it is possible to test for multivariate intervention effects on several moments of the variables of interest. Existing methods in the literature usually test for intervention effects on a single variable and assume that the time of the intervention is known. In addition, high-dimensionality is frequently ignored and inference is either conducted under a set of more stringent hypotheses and/or by permutation tests. A Monte Carlo experiment evaluates the properties of the method in finite samples and compares it with other alternatives. As an application, we evaluate the effects on inflation, GDP growth, retail sales and credit of an anti tax-evasion program.

We study the revenue maximization problem of a seller who is partially informed about the distribution of buyer's valuations, only knowing its first N moments. The seller chooses the mechanism generating the best revenue guarantee based on the information available, that is, the optimal mechanism is chosen according to maxmin expected revenue. We show that the transfer function in the optimal mechanism is given by non-negative monotonic hull of a polynomial of degree N. This enables us to transform the seller's problem into a much simpler optimization problem over Nvariables. The optimal mechanism is found by choosing the coefficients of the polynomial subject to a resource constraint. We show that knowledge of the first moment does not guarantee strictly positive revenue for the seller, characterize the solution for the cases of two moments and derive some characteristics of the solution for the general case.

An English auction is studied in which bidders can acquire information during the bidding process, allowing for heterogeneity both in ex-ante private information and the cost of information acquisition. The best response has a simple characterization where the optimal information acquisition time is unaffected by the other bidders’ strategies. We prove the existence of an equilibrium in a novel way by characterizing it as a fixed point in the space of bid distributions rather than the space of bid functions. Furthermore, we show that when bidders have homogeneous ex-ante private information about valuations: (1) The English auction generates more revenue than the Vickrey auction when the number of bidders is sufficiently large; and (2) the English auction is more efficient than the Vickrey auction when the information acquisition cost are relatively small. We present numerical simulations that show that these effects can be large. Our findings provide an additional explanation for the popularity of the English auction, even in settings where the bidders’ valuations are independent.

A three-sector model with a suitably chosen distribution of price stickiness can closely approximate the response to aggregate shocks of New Keynesian models with a much larger number of sectors, allowing for their estimation at much reduced computational cost.

This article examines the effects of bank privatization on the number of bank branches operating in small isolated markets in Brazil. We estimate a dynamic game played between Brazilian public and private banks. We find private banks compete with each other as expected. We also find public banks generate positive spillovers for private banks. Our counterfactual study shows that privatization substantially reduces the number of banks. The government can mitigate the effects of privatization by providing subsidies to private banks. Our model predicts subsidy policies that reduce operating costs are more cost‐effective than entry costs for isolated markets in Brazil.

This paper considers the problem of a Principal who faces a privately informed Agent and only knows one moment of the type’s distribution. Preferences are nonlinear in the allocation, and the Principal maximizes her worst-case expected profits. The robustness property of the optimal mechanism imposes restrictions on the Principal’s ex-post payoff function: subject to the allocation being nonzero, ex-post payoffs are linear in the Agent’s type. The robust mechanism entails exclusion of low types, distortions at the intensive margin and efficiency at the top. We show that, under some conditions, distortions in the optimal mechanism are decreasing in types. This monotonicity has relevant consequences for several applications discussed. Our characterization uses an auxiliary zero-sum game played by the Principal and an adversarial Nature who seeks to minimize her expected payoffs which also gives us a characterization of the worst-case distribution from the Principal’s perspective. Applications of our framework to insurance provision, optimal taxation, nonlinear pricing and regulation are discussed

In a repeated unobserved endowment economy in which agents negotiate longterm contracts with a financial intermediary, we study the risk-sharing implications of the interaction between incentive compatibility constraints (due to private information) and participation constraints (due to one-sided commitment). In particular, we assume that after a default episode, agents consume their endowment and remain in autarky forever. We find that once they are away from autarky today, if the probability of drawing the highest possible endowment shock is sufficiently small, the optimal contract prevents agents from reaching autarky tomorrow and, thus, from being “impoverished”. Moreover, an invariant cross-sectional distribution of life-time utilities (or values) exists. A numerical example shows that the mass of agents living in autarky can be zero in the limit.

Este trabalho investiga os efeitos da incerteza sobre a atividade econômica no Brasil. Para isso, são construídas diversas proxies que buscam capturar o nível de incerteza vigente na economia brasileira (incerteza doméstica) e em vários de seus principais parceiros comerciais (incerteza externa). Em seguida, são estimados diversos modelos de vetores autorregressivos (VAR) estruturais, tal como proposto por ^{Baker, Bloom & Davis (2016)}. As funções de resposta ao impulso sugerem efeitos contracionistas significativos da incerteza sobre a atividade, em particular sobre o investimento. Além disso, as estimativas indicam que os efeitos da incerteza doméstica são mais acentuados do que os da incerteza externa. Pode-se afirmar, portanto, que os níveis de incerteza vigentes no Brasil desde as eleições presidenciais de 2014 representam importante fator por trás da recessão subsequente. Estima-se que caso não houvesse a expansão de incerteza doméstica observada a partir do segundo semestre de 2014, a produção industrial em 2015 teria sido, em média, entre 0,9% e 3,9% maior, dependendo da variável proxy de incerteza utilizada. No caso do IBC-Br, este teria sido entre 0,4% e 1,3% maior. Os resultados encontrados são robustos para diversas alterações no modelo.

We develop a model where, in the first stage, minority individuals have to decide whether or not they want to assimilate to the majority culture while, in the second stage, all individuals (both from the majority and the minority group) embedded in a network have to decide how much effort they exert in some activity (say education). We show that the more central minority agents are located in the social network, the more they assimilate to the majority culture. We also show that denser networks tend to favor assimilation so that, for example, it is easier to assimilate in a complete network than in a star-shaped network. We show that the subgame-perfect equilibrium is not optimal because there is not enough activity and assimilation. We then endogeneize the network and show under which condition the ethnic minorities either assimilate to or separated themselves from the majority group.

This paper suggests an identification and estimation approach based on quantile regression to recover the underlying distribution of bidders' private values in ascending auctions under the IPV paradigm. The quantile regression approach provides a flexible and convenient parametrization of the private values distribution, with an estimation methodology easy to implement and with several specification tests. The quantile framework provides a new focus on the quantile level of the private values distribution, in particular the seller's optimal screening level, which can be very useful for bidders and seller. An empirical application using data from the USFS timber auctions illustrates the methodology.

The literature that emerged from Mankiw and Reis' (2002) proposal of sticky information as an alternative to sticky-price models has focused on economies populated with (ex-ante) identical firms. This paper analyzes the implications of heterogeneity in the degree of information stickiness among price-setting firms in different sectors for the dynamic response of the economy to various shocks. I compare multisector sticky-information models with otherwise identical one-sector economies that feature the same frequency of information updating. I find that the effects of such shocks on the output gap -- the difference between actual output and the output level that would prevail in the absence of information frictions -- are larger in heterogeneous economies.

This paper documents the persistence of human capital over time and its association with long-term development. We exploit variation induced by a state-sponsored settlement policy that attracted immigrants with higher levels of schooling to particular regions of Brazil in the late nineteenth and early twentieth century. We show that one century after the policy, municipalities that received settlements had higher levels of schooling and higher income per capita. We provide evidence that long-run effects worked through higher supply of educational inputs and shifts in the structure of occupations toward skill-intensive sectors

We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso‐type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast realized covariance matrices almost as precisely as if we had known the true driving dynamics of these in advance. We next investigate the sources of these driving dynamics as well as the performance of the proposed models for forecasting the realized covariance matrices of the 30 Dow Jones stocks. We find that the dynamics are not stable as the data are aggregated from the daily to lower frequencies. Furthermore, we are able beat our benchmark by a wide margin. Finally, we investigate the economic value of our forecasts in a portfolio selection exercise and find that in certain cases an investor is willing to pay a considerable amount in order get access to our forecasts. Copyright © 2016 John Wiley & Sons, Ltd.

In the aftermath of the Taper Tantrum, the Central Bank of Brazil announced a major program of sterilized foreign exchange intervention. We use a synthetic control approach to estimate its impact on the level and volatility of the exchange rate. Our counterfactual results, based on the experience of other emerging markets, indicate the program led to an appreciation of the Brazilian real in excess of 10 percent. Some of our estimates also point to a decline in the option-implied volatility. A second announcement extending the program had more muted effects, and subsequent extensions had little or no impact.

In this paper, we show the validity of the adaptive least absolute shrinkage and selection operator (LASSO) procedure in estimating stationary autoregressive distributed lag(p,q) models with innovations in a broad class of conditionally heteroskedastic models. We show that the adaptive LASSO selects the relevant variables with probability converging to one and that the estimator is oracle efficient, meaning that its distribution converges to the same distribution of the oracle-assisted least squares, i.e., the least square estimator calculated as if we knew the set of relevant variables beforehand. Finally, we show that the LASSO estimator can be used to construct the initial weights. The performance of the method in finite samples is illustrated using Monte Carlo simulation.