The finite-sample size of the BDS test for GARCH standardized residuals

This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation, even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. Nonethe-less, the estimated response surfaces can provide not only a measure of the size distortion, but also more adequate critical values for the BDS test in small samples.

Monopoly power, trade protection and growth: cross industry evidence

This paper investigates the impact of monopoly power on trade policy. Annual panel-databases of Brazilian industries for the years 1988 through 1994 were used. The regressions reported here are robust to openness indicator, concentration index, control variables and sample size, and suggest that industries with higher monopoly power are more protected than competitive sectors. In the period of study the country experienced a major trade liberalization, but the results in the paper show that the reduction in protection was smaller in sectors with higher monopoly power. We thus have evidence favoring recent growth literature which stresses that interest groups with control over creasing productivity. The results here confirm the first part of this argument and show that organized groups in fact are able to obtain policy advantages that reduce competition.

Monopoly power and trade protection: cross- industry evidence

This paper investigates the impact of industry concentration on trade policy. Annual panel-databases of Brazilian industries for the years 1988 through 1994 were used. The regressions reported here are robust to openness indicator. concentration index, control variables and sample size, and suggest that the higher the concentration of a given industry the higher its leveI of trade protection. In the period of study the country experienced a major trade liberalization, but the results in the paper show that the reduction in protection was smaller in more concentrated sectors. Assuming that concentration is ;1 gCl()d proX\' for mOllopoh' po\\'er as it reduces the free-rider problem in coordinating a lobby the results in this paper indicates that interest groups with control over specific markets in fact are able to obtain policy advantages that reduce (international) competition.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.