Topic
Statistical hypothesis testing
About: Statistical hypothesis testing is a research topic. Over the lifetime, 19580 publications have been published within this topic receiving 1037815 citations. The topic is also known as: statistical hypothesis testing & confirmatory data analysis.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, a unit root null hypothesis for the errors affecting a classical regression model against the non-stationary (including explosive) alternative hypothesis is developed, and the test statistic is simplified in order that it could be viewed as a von Neumann type ratio and exact significance points are tabulated.
Abstract: This paper provides a framework for testing for a unit root in an observed time series against some alternatives considered previously by Anderson (1948). Some new tests for the unit root null hypothesis for the errors affecting a classical regression model against the non-stationary (including explosive) alternative hypothesis are developed. The previous results of Sargan and Bhargava (1983) and the new test statistics are then applied to test the simple random walk and the random walk with a constant drift null hypotheses against stationary and non-stationary one-sided alternatives. In each case, the test statistic is simplified in order that it could be viewed as a von Neumann type ratio and the exact significance points are tabulated. Finally, the unit root null hypotheses are tested using U.S. data on the velocity of money and the Michigan PSID.
597 citations
TL;DR: In this article, a Lagrange multiplier (LM) test for the hypothesis of no error autocorrelation and LM-type tests for the hypotheses of no remaining nonlinearity and that of parameter constancy are proposed.
596 citations
Book•
24 Feb 2005
TL;DR: In this article, the Instrumental Variable Estimator in the Linear Regression Model is used to estimate the GMM in correctly specified models and GMM estimation in misspecified models.
Abstract: 1. Introduction 2. The Instrumental Variable Estimator in the Linear Regression Model 3. GMM Estimation in Correctly Specified Models 4. GMM Estimation in Misspecified Models 5. Hypothesis Testing 6. Asymptotic Theory and Finite Sample Behaviour 7. Moment Selection in Theory and in Practice 8. Alternative Approximations in Finite Sample Behaviour 9. Empirical Examples 10. Related Methods of Estimation Appendix: Mixing processes and Nonstationarity
596 citations
01 Dec 1992
TL;DR: In this article, the small sample properties of different tests for multivariate cointegration like Johansen's trace test, stock & Watson's common trend test, Phillips & Ouliaris' principal component test, as well as co-integration rank decisions based on order selection criteria are compared.
Abstract: This paper compares the small sample properties of different tests for multivariate cointegration like Johansen's trace test, stock & Watson's common trend test, Phillips & Ouliaris' principal component test, as well as cointegration rank decisions based on order selection criteria. Under the null hypothesis of non-cointegration we find a slow convergence rate of the test statistics. In bivariate models the Phillips & Ouliaris test is extremely dependent on the specification and is outperformed by the other procedures. For trivariate processes we find dependence of the power results on the dynamic specification. The lag order is successfully estimated by order selection criteria.
594 citations