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.

Análise das relações de longo prazo entre a posição internacional de investimentos, o efeito Balassa-Samuelson e a taxa de câmbio real: testes de cointegração

Este trabalho tem a finalidade de analisar as evidências de relações de longo prazo entre a taxa de câmbio real (“RER”), a posição internacional de investimentos (“NFA”) e o efeito Balassa-Samuelson (“PREL”) em um grupo de 28 países, grupo este que inclui países em diferentes estágios de desenvolvimento. A metodologia utilizada foi a de testes de cointegração. Os testes aplicados foram desenvolvidos por Bierens (1997), teste não paramétrico, e por Saikkonen e Lütkepohl (2000a, b, c), teste que consiste em primeiro estimar um termo determinístico. Evidências de cointegração são constatadas, em ambos os testes, na maioria dos países estudados. Entretanto, houve diferenças relevantes entre os resultados encontrados através dos dois testes aplicados. Estas diferenças entre os resultados, bem como alguns casos especiais de países que não demonstraram evidências de cointegração, requerem análises mais aprofundadas sobre o comportamento de longo prazo das três variáveis estudadas.

Comparing two multivariate unit root tests

In this essay, a method for comparing the asymptotic power of the multivariate unit root tests proposed in Phillips & Durlauf (1986) and Flˆores, Preumont & Szafarz (1996) is proposed. In order to determine the asymptotic power of the tests the asymptotic distributions under the null hypothesis and under the set of alternative hypotheses described in Phillips (1988) are determined. In addition, a test which combines characteristics of both tests is proposed and its distributions under the null hypothesis and the same set of alternative hypotheses are determined. This allows us to determine what causes any difference in the asymptotic power of the two tests against the set of alternative hypotheses considered

Nonparametric entropy-based tests of independence between stochastic processes

This paper develops nonparametric tests of independence between two stationary stochastic processes. The testing strategy boils down to gauging the closeness between the joint and the product of the marginal stationary densities. For that purpose, I take advantage of a generalized entropic measure so as to build a class of nonparametric tests of independence. Asymptotic normality and local power are derived using the functional delta method for kernels, whereas finite sample properties are investigated through Monte Carlo simulations.

The forward and the equity-premium puzzles: a straightforward test of whether they are two symptoms of the same illness

We build a stochastic discount factor—SDF— using information on US domestic financial data only, and provide evidence that it accounts for foreign markets stylized facts that escape SDF’s generated by consumption based models. By interpreting our SDF as the projection of the pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. In our tests, we address predictability, a defining feature of the Forward Premium Puzzle—FPP— by using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations both in the equity and the foreign markets.

A note on the forward and the equity-premium puzzles: two symptoms of the same illness?

We build a stochastic discount factor—SDF— using information on US domestic financial data only, and provide evidence that it accounts for foreign markets stylized facts that escape SDF’s generated by consumption based models. By interpreting our SDF as the projection of the pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. In our tests, we address predictability, a defining feature of the Forward Premium Puzzle—FPP— by using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations both in the equity and the foreign markets.

Wald tests for IV regression with weak instruments

This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).

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.