Testing the null hypothesis of no regime switching with an application to GDP growth rates

This paper presents tests for the null hypothesis of no regime switching in Hamilton's (1989) regime switching model. The test procedures exploit similarities between regime switching models, autoregressions with measurement errors, and finite mixture models. The proposed tests are computationally simple and, contrary to likelihood based tests, have a standard distribution under the null. When the methodology is applied to US GDP growth rates, no strong evidence of regime switching is found.regime switching, LM tests, GMM, matching methods, GDP growth rates

Instrumental Variables Estimation and Weak-Identification-Robust Inference Based on a Conditional Quantile Restriction

Extending the L1-IV approach proposed by Sakata (1997, 2007), we develop a new method, named the $rho_{tau}$-IV estimation, to estimate structural equations based on the conditional quantile restriction imposed on the error terms. We study the asymptotic behavior of the proposed estimator and show how to make statistical inferences on the regression parameters. Given practical importance of weak identification, a highlight of the paper is a proposal of a test robust to the weak identification. The statistics used in our method can be viewed as a natural counterpart of the Anderson and Rubin's (1949) statistic in the $rho_{tau}$-IV estimation.quantile regression; instrumental variables; weak identification

Quantile-Based Nonparametric Inference for First-Price Auctions

We propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre, Perrigne, and Vuong (2000), and is also asymptotically normal with the appropriate choice of the bandwidth. As an application, we consider the problem of inference on the optimal reserve price.First-price auctions; independent private values; nonparametric estimation; kernel estimation; quantiles; optimal reserve price

Limit Theorems for Network Dependent Random Variables

This paper is concerned with cross-sectional dependence arising because observations are interconnected through an observed network. Following Doukhan and Louhichi (1999), we measure the strength of dependence by covariances of nonlinearly transformed variables. We provide a law of large numbers and central limit theorem for network dependent variables. We also provide a method of calculating standard errors robust to general forms of network dependence. For that purpose, we rely on a network heteroskedasticity and autocorrelation consistent (HAC) variance estimator, and show its consistency. The results rely on conditions characterized by tradeoffs between the rate of decay of dependence across a network and network's denseness. Our approach can accommodate data generated by network formation models, random fields on graphs, conditional dependency graphs, and large functional-causal systems of equations

Comparison of Misspecified Calibrated Models: The Minimum Distance Approach

This paper proposes several testing procedures for comparison of misspecified calibrated models. The proposed tests are of the Vuong-type (Vuong, 1989; Rivers and Vuong, 2002). In our framework, the econometrician selects values for model's parameters in order to match some characteristics of data with those implied by the theoretical model. We assume that all competing models are misspecified, and suggest a test for the null hypothesis that they provide equivalent fit to data characteristics, against the alternative that one of the models is a better approximation. We consider both nested and non-nested cases. We also relax the dependence of models' ranking on the choice of a weight matrix by suggesting averaged and sup-norm procedures. The methods are illustrated by comparing the cash-in-advance and portfolio adjustment cost models in their ability to match the impulse responses of output and inflation to money growth shocks.misspecified models; calibration; matching; minimum distance estimation

Weak Identification in Fuzzy Regression Discontinuity Designs

In fuzzy regression discontinuity (FRD) designs, the treatment effect is identified through a discontinuity in the conditional probability of treatment assignment. We show that when identification is weak (i.e. when the discontinuity is of a small magnitude) the usual t-test based on the FRD estimator and its standard error suffers from asymptotic size distortions as in a standard instrumental variables setting. This problem can be especially severe in the FRD setting since only observations close to the discontinuity are useful for estimating the treatment effect. To eliminate those size distortions, we propose a modified t-statistic that uses a null-restricted version of the standard error of the FRD estimator. Simple and asymptotically valid confidence sets for the treatment effect can be also constructed using this null-restricted standard error. An extension to testing for constancy of the regression discontinuity effect across covariates is also discussed.Nonparametric inference; treatment effect; size distortions; Anderson-Rubin test; robust confidence set; class size effect

Rassismus in deutschen Schulbüchern am Beispiel von Afrikabildern

Unterrichtsmaterialien reproduzieren koloniale Afrikabilder und transportieren rassistisches Gedankengut. Der koloniale Diskurs bleibt von den Lehrenden oft unerkannt. Dieser Aufsatz untersucht die historische Genese rassistischer Ideologie und analysiert ihr Fortwirken in Schulbüchern. Anhand von Beispielen werden typische Repräsentationsmodi aufgezeigt und rassistische Botschaften sichtbar gemacht. (DIPF/Orig.)Teaching materials reproduce colonial pictures of Africa and feed racist ideas. The colonial discourse often remains undetected by teachers. This article investigates the historical genesis of racist ideology and analyzes its persistence in class books. With the help of examples typical modes of representation will be depicted and racist messages will be illustrated. (DIPF/Orig.

Supplement to "Comparison of Misspecified Calibrated Models"

This paper contains supplemental material to Hnatkovska, Marmer, and Tang (2009) "Comparison of Misspecified Calibrated Models: The Minimum Distance Approach".misspecified models; calibration; minimum distance estimation

Supplement to "Quantile-Based Nonparametric Inference for First-Price Auctions"

This paper contains supplemental materials for Marmer and Shneyerov (2010). We discuss here how the approach developed in the aforementioned paper can be applied to conducting inference on the optimal reserve price in first-price auctions, report additional simulations results, and provide a detailed proof of the bootstrap result in Marmer and Shneyerov (2010).First-price auctions, independent private values, nonparametric estimation, kernel estimation, quantiles, optimal reserve price, bootstrap

Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit

Suppose that the econometrician is interested in comparing two misspecified moment restriction models, where the comparison is performed in terms of some chosen measure of fit. This paper is concerned with describing an optimal test of the Vuong (1989) and Rivers and Vuong (2002) type null hypothesis that the two models are equivalent under the given measure of fit (the ranking may vary for different measures). We adopt the generalized Neyman-Pearson optimality criterion, which focuses on the decay rates of the type I and II error probabilities under fixed non-local alternatives, and derive an optimal but practically infeasible test. Then, as an illustration, by considering the model comparison hypothesis defined by the weighted Euclidean norm of moment restrictions, we propose a feasible approximate test statistic to the optimal one and study its asymptotic properties. Local power properties, one-sided test, and comparison under the generalized empirical likelihood-based measure of fit are also investigated. A simulation study illustrates that our approximate test is more powerful than the Rivers-Vuong test.Moment restriction, Model comparison, Misspecification, Generalized Neyman-Pearson optimality, Generalized method of moments