Hypothesis Testing in Econometrics

Hypothesis Testing in Econometrics

This paper reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including finite-sample and large-sample optimality. Then, some of the most important methods are summarized, as well as resampling methodology which is useful to set critical values. Finally, we consider the pr...

HYPOTHESIS TESTING FOR AN EXCHANGEABLE NORMAL DISTRIBUTION

Consider an exchangeable normal vector with parameters ????2, and ?. On the basis of a vector observation some tests about these parameters are found and their properties are discussed. A simulation study for these tests and a few nonparametric tests are presented. Some advantages and disadvantages of these tests are discussed and a few applications are given.

LINEAR HYPOTHESIS TESTING USING DLR METRIC

Several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. In analysis of variance, when the response random variable Y , has linear relationship with several random variables X, another important model as analysis of covariance can be used. In this paper, assuming that Y is fuzzy and using DLR metric, a method for testing ...

The Bootstrap and Hypothesis Tests in Econometrics

Multiple Testing in Growth Econometrics∗

This paper discusses two longstanding questions in growth econometrics which involve multiple hypothesis testing. In cross sectional GDP growth regressions many variables are simultaneously tested for significance. Similarly, when investigating pairwise convergence of output for n countries, n(n − 1)/2 tests are performed. We propose to control the false discovery rate (FDR) so as not to errone...