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A Spatial Cost of Living Index for Colombia using a Microeconomic Approach and Censored Data

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  • Atuesta, Laura
  • Paredes, Araya
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    Abstract

    This paper describes a methodology to calculate a spatial cost of living index using Colombian data for 2006 that takes into consideration the microeconomic behavior of households. Using the Almost Ideal Demand System and recovering the expenditure functions for the 23 main Colombian cities, the index proposed is compared to the traditional methodologies used to calculate the regional basket of goods in the country and to an alternative methodology proposed by Romero (2005). This comparison suggests that when the substitution effects are not considered, and the same basket of goods is evaluated in every city, the index is biased, and this bias increases when the diference between cities increases. For reducing the bias, we use a microeconomic approach that keeps the households' level of utility constant and allows substitution among diferent baskets of goods. According to our calculations, Bogota is still the most expensive city in the country followed by Armenia, Cali, Bucaramanga and Ibague.

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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 30580.

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    Date of creation: 29 Apr 2011
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    Handle: RePEc:pra:mprapa:30580

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    Keywords: Spatial Price Index; Almost Ideal Demand System;

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    1. Ray, Ranjan, 1983. "Measuring the costs of children : An alternative approach," Journal of Public Economics, Elsevier, vol. 22(1), pages 89-102, October.
    2. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
    3. Keen, Michael, 1986. "Zero Expenditures and the Estimation of Engel Curves," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(3), pages 277-86, July.
    4. Federico Perali & Jean-Paul Chavas, 2000. "Estimation of Censored Demand Equations from Large Cross-Section Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 1022-1037.
    5. Deaton, Angus, 1987. "Estimation of own- and cross-price elasticities from household survey data," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 7-30.
    6. Russel J. Cooper & Keith R. McLaren, 1992. "An Empirically Oriented Demand System with Improved Regularity Properties," Canadian Journal of Economics, Canadian Economics Association, vol. 25(3), pages 652-68, August.
    7. 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 365-71, July.
    8. Timmins, Christopher, 2006. "Estimating spatial differences in the Brazilian cost of living with household location choices," Journal of Development Economics, Elsevier, vol. 80(1), pages 59-83, June.
    9. Jahyeong Koo & Keith Phillips & Fiona Sigalla, 1997. "Measuring regional cost of living," Working Papers 9713, Federal Reserve Bank of Dallas.
    10. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
    11. Braithwait, Steven D, 1980. "The Substitution Bias of the Laspeyres Price Index: An Analysis Using Estimated Cost-of-Living Indexes," American Economic Review, American Economic Association, vol. 70(1), pages 64-77, March.
    12. Robert A. Pollak, 1998. "The Consumer Price Index: A Research Agenda and Three Proposals," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 69-78, Winter.
    13. Jorge Barrientos Marín, 2009. "On the Consumer Behavior in Urban Colombia: The Case of Bogotá," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE.
    14. Dusan Paredes, 2011. "A methodology to compute regional housing price index using matching estimator methods," The Annals of Regional Science, Springer, vol. 46(1), pages 139-157, February.
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