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[Rezension von: Engle, Robert F., ...,, Cointegration, causality, and forecasting]

Bewley, Ronald A. - In: Journal of economic literature 40 (2002) 3, pp. 931-933

Persistent link: https://www.econbiz.de/10001735218

Alternative methods for estimating long-run responses with application to Australian import demand

Bewley, Ronald A.; Orden, David R. - 1991

Persistent link: https://www.econbiz.de/10000819665

Alternative methods for estimating long-run responses with applications to Australian import demand

Bewley, Ronald A. - In: Econometric reviews 13 (1994) 2, pp. 179-204

Persistent link: https://www.econbiz.de/10001163116

Bayesian estimation of a random effects heteroscedastic probit model

Gu, Yuanyuan; Fiebig, Denzil G.; Cripps, Edward; Kohn, … - In: The econometrics journal 12 (2009) 2, pp. 324-339

Persistent link: https://www.econbiz.de/10003875768

Parsimonious estimation of the covariance matrix in multinomial probit models

Cripps, Edward; Fiebig, Denzil G.; Kohn, Robert - In: Econometric reviews 29 (2010) 2, pp. 146-157

Persistent link: https://www.econbiz.de/10003960494

Well-being losses due to care-giving

Berg, Bernard van den; Fiebig, Denzil G.; Hall, Jane - In: Journal of health economics 35 (2014), pp. 123-131

Persistent link: https://www.econbiz.de/10010469422

Estimating end-use demand : a Bayesian approach

Bauwens, Luc - In: Journal of business & economic statistics : JBES ; a … 12 (1994) 2, pp. 221-231

Persistent link: https://www.econbiz.de/10001167109

Estimating end-use demand : a Bayesian approach

Bauwens, Luc - 1992

Persistent link: https://www.econbiz.de/10000852951

Forecasting with micro panels : the case of health care costs

Fiebig, Denzil G.; Johar, Meliyanni - In: Journal of forecasting 36 (2017) 1, pp. 1-15

Persistent link: https://www.econbiz.de/10011725711

Bayesian Estimation of a Random Effects Heteroscedastic Probit Model

Gu, Yuanyuan; Fiebig, Denzil G.; Cripps, Edward Jerrold; … - 2008

A Bayesian analysis is given of a random effects probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an...

Persistent link: https://www.econbiz.de/10014215204