A modified logit model for time series with an application to the pricing behaviour of manufacturing firms in Australia

被引：0
作者：
Chris M. Alaouze
机构：
[1] School of Economics, University of New South Wales, Sydney
来源：
Empirical Economics | 2003年 / 28卷 / 3期
关键词：
Logit model; Pricing behaviour; Time series;
D O I：
10.1007/s001810200148
中图分类号：
学科分类号：
摘要：
The modified logit model (Amemiya and Nold, 1975) is generalised to the case where the error term is autocorrelated. The asymptotic distribution (as n → ∞ and T → ∞) of a feasible GLS estimator of β is derived. Tests of linear restrictions on β and the significance of ρ are presented. The results of the applied work suggest that the factors which explain the pricing behaviour of manufacturing firms, as reported in the tendency survey conducted by the Australian Chamber of Commerce and Industry and the Westpac Banking Corporation, include historical inflation rates of up to 7 quarters and capacity utilisation.
引用
收藏
页码：599 / 613
页数：14
相关论文
共 35 条
[1]  
Alaouze C.M., Some Monte Carlo Results for the Modified Logit Model, (1998)
[2]  
Alaouze C.M., A Disaggregated Measure of Pressure of Demand: Its Use in Import Demand Estimation, (1977)
[3]  
Amemiya T., Advanced Econometrics, (1985)
[4]  
Amemiya T., Qualitative response models: A survey, Journal of Economic Literature, 19, pp. 1483-1536, (1981)
[5]  
Amemiya T., Nold F.C., A modified logit model, Review of Economics and Statistics, 57, pp. 255-257, (1975)
[6]  
Anderson T.W., The Statistical Analysis of Time Series, (1971)
[7]  
Anscombe F.J., On estimating binomial response relationships, Biometrika, 43, pp. 461-464, (1956)
[8]  
Barry P.F., Guille C.W., The Australian business cycle and industrial cyclical linkages, 1959-1974, Economic Record, 52, pp. 127-165, (1976)
[9]  
Batchelor R.A., Expectations, output and inflation, the European experience, European Economic Review, 17, pp. 1-25, (1982)
[10]  
Berkson J., Maximum likelihood and minimum chi-square estimates of the logistic function, Journal of the American Statistical Association, 50, pp. 130-162, (1955)
1234