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Robust Non‐nested Testing for Ordinary Least Squares Regression when Some of the Regressors are Lagged Dependent Variables

Godfrey, Leslie G. - In: Oxford Bulletin of Economics and Statistics 73 (2011) 5, pp. 651-668

Persistent link: https://www.econbiz.de/10011031976

A Note on the Treatment of Serial Correlation.

Godfrey, Leslie G. - In: Canadian Journal of Economics 6 (1973) 4, pp. 567-73

Persistent link: https://www.econbiz.de/10005770375

Some results on the Glejser and Koenker tests for heteroskedasticity

Godfrey, Leslie G. - In: Journal of Econometrics 72 (1996) 1-2, pp. 275-299

Persistent link: https://www.econbiz.de/10005228656

On the asymptotic validity of a bootstrap method for testing nonnested hypotheses

Godfrey, Leslie G. - In: Economics Letters 94 (2007) 3, pp. 408-413

Persistent link: https://www.econbiz.de/10005158833

Testing for multiplicative heteroskedasticity

Godfrey, Leslie G. - In: Journal of Econometrics 8 (1978) 2, pp. 227-236

Persistent link: https://www.econbiz.de/10005285485

Hausman tests for autocorrelation in the presence of lagged dependent variables Some further results

Godfrey, Leslie G. - In: Journal of Econometrics 82 (1998) 2, pp. 197-207

Persistent link: https://www.econbiz.de/10005285540

Controlling the finite sample significance levels of heteroskedasticity-robust tests of several linear restrictions on regression coefficients

Godfrey, Leslie G.; Orme, Chris D. - In: Economics Letters 82 (2004) 2, pp. 281-287

Persistent link: https://www.econbiz.de/10005297216

Using bootstrap methods to obtain nonnormality robust Chow prediction tests

Godfrey, Leslie G.; Orme, Chris D. - In: Economics Letters 76 (2002) 3, pp. 429-436

Persistent link: https://www.econbiz.de/10005275498

Bootstrap HAC Tests for Ordinary Least Squares Regression

Bravo, Francesco; Godfrey, Leslie G. - In: Oxford Bulletin of Economics and Statistics 74 (2012) 6, pp. 903-922

Persistent link: https://www.econbiz.de/10010596337

Instrument Relevance in Multivariate Linear Models

Godfrey, Leslie G. - In: The Review of Economics and Statistics 81 (1999) 3, pp. 550-552

A measure of the relevancy of instruments used to estimate the coefficients of a linear multiple regression model is discussed. A method for computing the measure using only standard results from ordinary least squares and two-stage least squares estimation is described. The method is...

Persistent link: https://www.econbiz.de/10010559912