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.

International entry modes in Brazil and the CAGE distances effects

The international entry mode choices have a relevant importance for the impact they have on successful internationalization strategies. Many theories have been developed to describe which entry mode may be better than another according to the particular situation. The CAGE Distances Framework developed by Ghemawat to identify which dimensions companies should look when develop an internationalization strategy, may be useful to identify also how those dimensions impact on the international entry mode decision. The aim of this thesis is to study which kind of relationship exists between Cultural, Administrative, Geographic and Economic Distances and international entry mode choice. It analyzes a sample of companies that have been entered in Brazil through a logistic regression. According to this analysis, a negative and significant relation between Cultural Distance and need of control exists, a positive one exists between Administrative and Geographic, while no significant relationship has been found with the Economic dimension. Those findings are conceivably explainable through the theories found by scholars, but a deeper analysis that may take into account the specificity of every country is highly recommended, like the one developed with Brazil in this thesis.

Contributions to the Theory of Optimal Tests

This paper considers tests which maximize the weighted average power (WAP). The focus is on determining WAP tests subject to an uncountable number of equalities and/or inequalities. The unifying theory allows us to obtain tests with correct size, similar tests, and unbiased tests, among others. A WAP test may be randomized and its characterization is not always possible. We show how to approximate the power of the optimal test by sequences of nonrandomized tests. Two alternative approximations are considered. The rst approach considers a sequence of similar tests for an increasing number of boundary conditions. This discretization allows us to implement the WAP tests in practice. The second method nds a sequence of tests which approximate the WAP test uniformly. This approximation allows us to show that WAP similar tests are admissible. The theoretical framework is readily applicable to several econometric models, including the important class of the curved-exponential family. In this paper, we consider the instrumental variable model with heteroskedastic and autocorrelated errors (HAC-IV) and the nearly integrated regressor model. In both models, we nd WAP similar and (locally) unbiased tests which dominate other available tests.

Multiple structural change models:a simulation analysis

In a reccnt paper. Bai and Perron (1998) considcrccl theoretical issues relatec\ lo lhe limiting distriblltion of estimators and test. statist.ics in the linear model \\'ith multiplc struct ural changes. \Ve assess. via simulations, the adequacy of the \'arious I1Iethods suggested. These CO\'er the size and power of tests for structural changes. the cO\'erage rates of the confidence Íntervals for the break dates and the relat.Í\'e merits of methods to select the I1umber of breaks. The \'arious data generating processes considered alIo,,' for general conditions OIl the data and the errors including differellces across segmcll(s. Yarious practical recommendations are made.