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Testing the Specification of Econometric Models in Regression and Non-Regression Directions

Davidson, Russell; MacKinnon, James G. - Economics Department, Queen's University - 1986

The asymptotic power of a statistical test depends on the model being tested, the (implicit) alternative against which … for several classes of models and tests. First, we analyze the power of tests of nonlinear regression models in regression … directions. Next, we consider the power of heteroskedasticity-robust variants of these tests. Finally, we examine the power of …

Persistent link: https://www.econbiz.de/10005688503

Heteroskedasticity-Robust Tests in Regression Directions

Davidson, Russell; MacKinnon, James G. - 1985

We develop simple procedures to test for omitted variables and perform other tests in regression directions, which are asymptotically valid in the presence of heteroskedasticity of unknown form. We examine the asymptotic behaviour of these tests, and use Edgeworth approximations to study their...

Persistent link: https://www.econbiz.de/10011940424

Heteroskedasticity-Robust Tests in Regression Directions

Davidson, Russell; MacKinnon, James G. - Economics Department, Queen's University - 1985

Persistent link: https://www.econbiz.de/10005653228

More Efficient Tests Robust to Heteroskedasticity of Unknown Form

Flachaire, Emmanuel - In: Econometric Reviews 24 (2005) 2, pp. 219-241

In the presence of heteroskedasticity of unknown form, the Ordinary Least Squares parameter estimator becomes inefficient, and its covariance matrix estimator inconsistent. Eicker (1963) and White (1980) were the first to propose a robust consistent covariance matrix estimator, that permits...

Persistent link: https://www.econbiz.de/10009228481

Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap

Flachaire, Emmanuel - HAL - 2005

In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments. The simulation results...

Persistent link: https://www.econbiz.de/10010750557

More efficient tests robust to heteroskedasticity of unknown form

Flachaire, Emmanuel - HAL - 2005

In the presence of heteroskedasticity of unknown form, the Ordinary Least Squares parameter estimator becomes inefficient and its covariance matrix estimator inconsistent. Eicker (1963) and White (1980) were the first to propose a robust consistent covariance matrix estimator, that permits...

Persistent link: https://www.econbiz.de/10010750564

Specification tests indexed by bandwidths

Dette, Holger; Hetzler, Benjamin - 2004

In this note we consider several goodness-of-fit tests for model specification in non- parametric regression models which are based on kernel methods. In order to circumvent the problem of choosing a bandwidth for the corresponding test statistic we propose to consider the statistics as...

Persistent link: https://www.econbiz.de/10010296632

Economic Development and CO2 Emissions: A Nonparametric Panel Approach

Azomahou, Théophile; Laisney, François; van Phu, Nguyen - 2005

We examine the empirical relation between CO2 emissions per capita and GDP per capita during the period 1960-1996, using a panel of 100 countries. Relying on the nonparametric poolability test of Baltagi et al. (1996), we find evidence of structural stability of the relationship. We then specify...

Persistent link: https://www.econbiz.de/10010297464

Nonparametric Regression on Latent Covariates with an Application to Semiparametric GARCH-in-Mean Models

Conrad, Christian; Mammen, Enno - 2008

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...

Persistent link: https://www.econbiz.de/10011422182

The Maximum Number of Parameters for the Hausman Test When the Estimators are from Different Sets of Equations

Nawata, Kazumitsu; McAleer, Michael - 2013

Hausman (1978) developed a widely-used model specification test that has passed the test of time. The test is based on two estimators, one being consistent under the null hypothesis but inconsistent under the alternative, and the other being consistent under both the null and alternative...

Persistent link: https://www.econbiz.de/10010328351

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