Titlebook: Contributions to Consumer Demand and Econometrics; Essays in Honour of Ronald Bewley (Associate Professor of Economics),T Book 1992 Ronald

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书目名称Contributions to Consumer Demand and Econometrics影响因子(影响力)




书目名称Contributions to Consumer Demand and Econometrics影响因子(影响力)学科排名




书目名称Contributions to Consumer Demand and Econometrics网络公开度




书目名称Contributions to Consumer Demand and Econometrics网络公开度学科排名




书目名称Contributions to Consumer Demand and Econometrics被引频次




书目名称Contributions to Consumer Demand and Econometrics被引频次学科排名




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书目名称Contributions to Consumer Demand and Econometrics年度引用学科排名




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书目名称Contributions to Consumer Demand and Econometrics读者反馈学科排名

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甜瓜

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Accounting for Non-stationarity in Demand Systemstly general to permit the testing of homogeneity and symmetry. Later that decade, Theil (1969) introduced ‘The Multinomial Extension of the Linear Logit Model’ and manipulated it to show its connection with the Rotterdam model.

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Henri Theil’s Contributions to Demand Analysisy, forecasting, econometric methodology and demand analysis, to name just a few areas of major contributions. There is no question that Theil’s work has a style all of its own: it is characterized by insight, ingenuity, elegance and an almost unique combination of theory and measurement. Most (if no

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Economic Inequality and Consumer Behaviour: Theory and Applications1975) and is causally related to (a) the allocation of earned incomes, (b) the concentration of wealth, and (c) the relative importance of income from earnings and capital (Atkinson, 1983), an integration of economic inequality and consumer behaviour in empirical studies has not been widely reported

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Decomposition of Least-Squares Estimators and Covariance Matrices his full-time appointment in 1956. His first set of lecture notes carried the title ‘Elementary regression and time series analysis’. It had the level and indeed much of the style and the material of his . (Theil, 1978). Among other things, it already contained the ‘textile example’, dealing with t

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Mixing Forecasts in Linear Simultaneous Equations Under Quadratic Losstimators. Minimum risk (MELO) Bayesian estimators, Steinlike and pre-test estimators, mixed regression and Minimum Mean Squared Error (MMSE) are examples of such estimators. See Zellner and Vandaele (1975) and Maasoumi (1978, 1984). Zellner and Vandaele (1975) consider the Bayesian interpretations o

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Edgeworth Approximations to the Distributions of the Likelihood Ratio and F Statistics in the Null aistribution. In Neyman-Pearson theory of testing of statistical hypotheses, the efficiency of a statistical test is to be judged by its power of detecting the departure from the null hypothesis (.). Hence it is imperative that the distribution of any statistic be known both under the null and the al

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