Ein empirischer Test der Annahme der permanenten Einkommenshypothese von Milton Friedman

Summary We apply the Variate-Difference-Method to yearly Austrian data from 1956 to 1975 to test the permanent-income-hypothesis byM. Fiedman.First we determe the degree of the polynomial, which is sufficient to eliminate the trend (i.e. the permanent part) from time series of disposable income. Then the permanent income variable is constructed in two alternative ways: first, as a polynomial in time and second bySheppard's smoothing formulae. Transitory consumption is identified with the residuals of the consumption function. A correlation analysis shows that, transitory income and consumption are correlated, if permanent income is determined by a trend polynomial, while this is not the case ifSheppard's smoothing formulae is used to estimate permanent income.Consumption functions are specified for total consumption, durables and non-durables and eleven sub-groups of total private consumption. The results indicate that autocorrelation can considerably be reduced by usingSheppard's smoothing formulae.     

Proportional Odds Models with High‐Dimensional Data Structure

The proportional odds model is the most widely used model when the response has ordered categories. In the case of high‐dimensional predictor structure, the common maximum likelihood approach typically fails when all predictors are included. A boosting technique pomBoost is proposed to fit the model by implicitly selecting the influential predictors. The approach distinguishes between metric and categorical predictors. In the case of categorical predictors, where each predictor relates to a set of parameters, the objective is to select simultaneously all the associated parameters. In addition, the approach distinguishes between nominal and ordinal predictors. In the case of ordinal predictors, the proposed technique uses the ordering of the ordinal predictors by penalizing the difference between the parameters of adjacent categories. The technique has also a provision to consider some mandatory predictors (if any) that must be part of the final sparse model. The performance of the proposed boosting algorithm is evaluated in a simulation study and applications with respect to mean squared error and prediction error. Hit rates and false alarm rates are used to judge the performance of pomBoost for selection of the relevant predictors.     

Kommentar zu Beiers Beitrag

Ohne ZusammenfassungGerhard Scherhorn ist Professor für Konsumtheorie und Verbraucherpolitik an der Universität Hohenheim, Postfach 106, D-7000 Stuttgart 70.     

The goal of consumer advice: Transparency or autonomy?

To improve the transparency of consumer markets by means of information is an important task but it cannot be served efficiently by consumer advice. The genuine aim of consumer advice is described here as promoting consumer autonomy by, first, decision counselling and related means and, second, coordinating consumer interests. The paper is centred on two main issues: the responsibility of suppliers of consumer goods to meet the consumers' information needs, and the potential and chance for consumers to progress towards a higher degree of autonomy.     

Rezensionen

Ohne Zusammenfassung     

Box-Jenkins Methoden — Alternative Verfahren zur Prognose ökonomischer Zeitreihen

Summary In this paper we try to clarify whether the use ofBox-Jenkins methods would have improved the forecasting performance in Austria during the recession of 1975. For this purpose we estimate ARIMA models for gross national product, private consumption, investment in plant and equipment, and inventory investment. We then compare the forecasts derived from these models with the results of more convential forecasting techniques. It can not be expected that Box-Jenkins methods predict a business cycle turning point. But, as soon as the recession was under way Box-Jenkins methods were faster in adapting to the new situation than conventional forecasting techniques. We found that the accuracy of Box-Jenkins predictions depends to a large extent on the length of the forecasting horizon. Our results suggest that the forecasting horizon should not exceed one year. All in all, Box-Jenkins methods applied together with the forecasting techniques already in use could further improve the forecasting performance.     

I. Allgemeine wirstchaftslehre

Ohne Zusammenfassung     

Ein Beitrag zur nicht-statischen Werttheorie

Ohne Zusammenfassung