We show that a simple "reputation-style" test can always identify which of two experts is informed about the true distribution. The test presumes no prior knowledge of the true distribution, achieves any desired degree of precision in some fixed finite time, and does not use "counterfactual" predictions. Our analysis capitalizes on a result of Fudenberg and Levine (1992) on the rate of convergence of supermartingales. Copyright
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While the literature on nonclassical measurement error traditionally relies on the availability of an auxiliary data set containing correctly measured observations, we establish that the availability of instruments enables the identification of a large class of nonclassical nonlinear errors-in-variables models with continuously distributed variables. Our main identifying assumption is that, conditional on the value of the true regressors, some “measure of location” of the distribution of the measurement error (e.g., its mean, mode, or median) is equal to zero. The proposed approach relies on the eigenvalue–eigenfunction decomposition of an integral operator associated with specific joint probability densities. The main identifying assumption is used to “index” the eigenfunctions so that the decomposition is unique. We propose a convenient sieve-based estimator, derive its asymptotic properties, and investigate its finite-sample behavior through Monte Carlo simulations.
We study the provision of dynamic incentives to self-interested politicians who control the allocation of resources in the context of the standard neoclassical growth model. Citizens discipline politicians using elections. We show that the need to provide incentives to the politician in power creates political economy distortions in the structure of production, which resemble aggregate tax distortions. We provide conditions under which the political economy distortions persist or disappear in the long run. If the politicians are as patient as the citizens, the best subgame perfect equilibrium leads to an asymptotic allocation where the aggregate distortions arising from political economy disappear. In contrast, when politicians are less patient than the citizens, political economy distortions remain asymptotically and lead to positive aggregate labor and capital taxes.
The difficulties in properly anticipating key economic variables may encourage decision makers to rely on experts' forecasts. Professional forecasters, however, may not be reliable and so their forecasts must be empirically tested. This may induce experts to forecast strategically in order to pass the test. A test can be ignorantly passed if a false expert, with no knowledge of the data-generating process, can pass the test. Many tests that are unlikely to reject correct forecasts can be ignorantly passed. Tests that cannot be ignorantly passed do exist, but these tests must make use of predictions contingent on data not yet observed at the time the forecasts are rejected. Such tests cannot be run if forecasters report only the probability of the next period's events on the basis of the actually observed data. This result shows that it is difficult to dismiss false, but strategic, experts who know how theories are tested. This result also shows an important role that can be played by predictions contingent on data not yet observed.
Much evidence suggests that people are heterogeneous with regard to their abilities to make rational, forward-looking decisions. This raises the question as to when the rational types are decisive for aggregate outcomes and when the boundedly rational types shape aggregate results. We examine this question in the context of a long-standing and important economic problem: the adjustment of nominal prices after an anticipated monetary shock. Our experiments suggest that two types of bounded rationality—money illusion and anchoring—are important behavioral forces behind nominal inertia. However, depending on the strategic environment, bounded rationality has vastly different effects on aggregate price adjustment. If agents' actions are strategic substitutes, adjustment to the new equilibrium is extremely quick, whereas under strategic complementarity, adjustment is both very slow and associated with relatively large real effects. This adjustment difference is driven by price expectations, which are very flexible and forward-looking under substitutability but adaptive and sticky under complementarity. Moreover, subjects' expectations are also considerably more rational under substitutability.
Productivity differences across firms are large and persistent, but the evidence for worker reallocation as an important source of aggregate productivity growth is mixed. The purpose of this paper is to estimate the structure of an equilibrium model of growth through innovation designed to identify and quantify the role of resource reallocation in the growth process. The model is a version of the Schumpeterian theory of firm evolution and growth developed by Klette and Kortum (2004) extended to allow for firm heterogeneity. The data set is a panel of Danish firms that includes information on value added, employment, and wages. The model's fit is good. The estimated model implies that more productive firms in each cohort grow faster and consequently crowd out less productive firms in steady state. This selection effect accounts for 53% of aggregate growth in the estimated version of the model.
Rabin (2000) proved that a low level of risk aversion with respect to small gambles leads to a high, and absurd, level of risk aversion with respect to large gambles. Rabin's arguments strongly depend on expected utility theory, but we show that similar arguments apply to general non-expected utility theories.
We study preferences over menus which can be represented as if the agent selects an alternative from a menu and experiences regret if her choice is ex post inferior. Since regret arises from comparisons between the alternative selected and the other available alternatives, our axioms reflect the agent's desire to limit her options. We prove that our representation is essentially unique. We also introduce two measures of comparative regret attitudes and relate them to our representation. Finally, we explore the formal connection between the present work and the literature on temptation.
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirical practice to use kernel-based robust standard errors that involve some smoothing function over the sample autocorrelations. The underlying smoothing parameter b, which can be defined as the ratio of the bandwidth (or truncation lag) to the sample size, is a tuning parameter that plays a key role in determining the asymptotic properties of the standard errors and associated semiparametric tests. Small-b asymptotics involve standard limit theory such as standard normal or chi-squared limits, whereas fixed-b asymptotics typically lead to nonstandard limit distributions involving Brownian bridge functionals. The present paper shows that the nonstandard fixed-b limit distributions of such nonparametrically studentized tests provide more accurate approximations to the finite sample distributions than the standard small-b limit distribution. In particular, using asymptotic expansions of both the finite sample distribution and the nonstandard limit distribution, we confirm that the second-order corrected critical value based on the expansion of the nonstandard limiting distribution is also second-order correct under the standard small-b asymptotics. We further show that, for typical economic time series, the optimal bandwidth that minimizes a weighted average of type I and type II errors is larger by an order of magnitude than the bandwidth that minimizes the asymptotic mean squared error of the corresponding long-run variance estimator. A plug-in procedure for implementing this optimal bandwidth is suggested and simulations confirm that the new plug-in procedure works well in finite samples.