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Estimation of Quadratic Expenditure Systems Using German Household Budget Data / Schätzung Quadratischer Ausgabensysteme anhand der Daten der Einkommens- und Verbrauchsstichprobe

Author

Listed:
  • Kohn Karsten

    () (Department of Economics, University of Mannheim, D-68131 Mannheim)

  • Missong Martin

    () (Institute of Statistics and Econometrics, Christian-Albrechts-University at Kiel, Olshausenstraße 40, D-24118 Kiel)

Abstract

Drawing on household budget data from the German Income and Consumption Surveys of 1988 and 1993, we estimate demographicaily structured Quadratic Expenditure Systems. Both Full Information Maximum Likelihood methods and a Limited Information approach as proposed recently by Ding and Hadri (1996) are employed. The quadratic specification is found to significantly improve the model fit as compared to the linear one used in previous demand studies for Germany. Price elasticities of demand for different household types are analyzed at distinct income levels, and ratios of estimated subsistence expenditures are compared to both institutional and empirical equivalence scales.

Suggested Citation

  • Kohn Karsten & Missong Martin, 2003. "Estimation of Quadratic Expenditure Systems Using German Household Budget Data / Schätzung Quadratischer Ausgabensysteme anhand der Daten der Einkommens- und Verbrauchsstichprobe," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(4), pages 422-448, August.
  • Handle: RePEc:jns:jbstat:v:223:y:2003:i:4:p:422-448
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    References listed on IDEAS

    as
    1. Lluch, Constantino, 1973. "The extended linear expenditure system," European Economic Review, Elsevier, vol. 4(1), pages 21-32, April.
    2. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    3. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-371, July.
    4. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    5. Ding, Hua & Hadri, Kaddour, 1996. "Chinese emprical evidence on the linear and quadratic expenditure systems," Discussion Papers 9611, Exeter University, Department of Economics.
    6. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
    7. Krug Walter, 2000. "Zum Aufbau eines Systems von Haushaltsstichproben in der amtlichen Statistik / Problems of Coordination of Household Statistics in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 220(6), pages 731-741, December.
    8. Barnes, Roberta & Gillingham, Robert, 1984. "Demographic Effects in Demand Analysis: Estimation of the Quadratic Expenditure System Using Microdata," The Review of Economics and Statistics, MIT Press, vol. 66(4), pages 591-601, November.
    9. Arthur Lewbel, 1985. "A Unified Approach to Incorporating Demographic or Other Effects into Demand Systems," Review of Economic Studies, Oxford University Press, vol. 52(1), pages 1-18.
    10. Howe, Howard, 1975. "Development of the extended linear expenditure system from simple saving assumptions," European Economic Review, Elsevier, vol. 6(3), pages 305-310, July.
    11. Howe, Howard & Pollak, Robert A & Wales, Terence J, 1979. "Theory and Time Series Estimation of the Quadratic Expenditure System," Econometrica, Econometric Society, vol. 47(5), pages 1231-1247, September.
    12. Pollak, Robert A & Wales, Terence J, 1978. "Estimation of Complete Demand Systems from Household Budget Data: The Linear and Quadratic Expenditure Systems," American Economic Review, American Economic Association, vol. 68(3), pages 348-359, June.
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    Cited by:

    1. Christian Dudel & Notburga Ott & Martin Werding, 2016. "Maintaining one’s living standard at old age: What does that mean?," Empirical Economics, Springer, vol. 51(3), pages 1261-1279, November.
    2. Christian Dudel & Notburga Ott & Martin Werding, 2013. "Maintaining One's Living Standard at Old Age: What Does that Mean? Evidence Using Panel Data from Germany," CESifo Working Paper Series 4223, CESifo Group Munich.
    3. Heindl, Peter & Schuessler, Rudolf, 2015. "Dynamic properties of energy affordability measures," Energy Policy, Elsevier, vol. 86(C), pages 123-132.
    4. repec:bpj:pewipo:v:18:y:2017:i:4:p:348-367:n:1 is not listed on IDEAS
    5. Ralf A. Wilke, 2006. "Semi-parametric estimation of consumption-based equivalence scales: the case of Germany," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 781-802.
    6. Nikodinoska, Dragana & Schröder, Carsten, 2016. "On the emissions–inequality and emissions–welfare trade-offs in energy taxation: Evidence on the German car fuels tax," Resource and Energy Economics, Elsevier, vol. 44(C), pages 206-233.
    7. Shiyuan Chen & Sally Wallace, 2009. "Food Consumption in Jamaica: A Household and Social Behavior," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper0901, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
    8. Heindl Peter & Aigeltinger Gerd & Liessem Verena & Römer Daniel & Schwengers Clarita & Vogt Claire, 2017. "Zum Stromkonsum von Haushalten in Grundsicherung: Eine empirische Analyse für Deutschland," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 18(4), pages 348-367, November.

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