Atuesta, Laura and Paredes, Araya (2011): A Spatial Cost of Living Index for Colombia using a Microeconomic Approach and Censored Data.
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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.
Item Type: | MPRA Paper |
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Original Title: | A Spatial Cost of Living Index for Colombia using a Microeconomic Approach and Censored Data |
Language: | English |
Keywords: | Spatial Price Index, Almost Ideal Demand System |
Subjects: | D - Microeconomics > D1 - Household Behavior and Family Economics > D12 - Consumer Economics: Empirical Analysis C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C34 - Truncated and Censored Models ; Switching Regression Models C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C24 - Truncated and Censored Models ; Switching Regression Models ; Threshold Regression Models |
Item ID: | 30580 |
Depositing User: | Dusan Paredes |
Date Deposited: | 03 May 2011 12:53 |
Last Modified: | 26 Sep 2019 08:32 |
References: | Baron J. 2005. La inflacion en las ciudades de Colombia: Una evaluacion de la paridad del poder adquisitivo. Centro de Estudios economicos regionales, Banco de la Republica de Colombia.: Documento de Trabajo No. 31. Barrientos J. 2009. On the consumer behavior in urban Colombia: the case of Bogota. Ensayos sobre politica economia 27: 46{82. Boskin M, Dulberger E, Gordon R, Griliches Z, Jorgenson D. 1998. Consumer prices, the consumer price index, and the cost of living. Journal of Economic Perspectives 1: 3{26. Braithwait S. 1980. The substitution bias of the Laspeyres price index: an analysis using estimated cost-of-living indexes. The American Economic Review 70: 64{77. Cooper R, McLaren K. 1992. An empirically oriented demand system with improved regularity properties. Canadian Journal of Economics 25: 652{668. Cortes D, Perez J. 2010. El consumo de los hogares colombianos, 2006-2007: estimacion de sistemas de demanda. Universidad del Rosario.: Documento de Trabajo No. 86. Deaton A. 1987. Estimation of own- and cross-price elasticities from household survey data. Journal of Econometrics 36: 7{30. Deaton A, Muellbauer J. 1980. An almost ideal demand system. American Economic Association 70: 312{326. Heien D, Wessels C. 1990. Demand systems estimation with microdata: A censored regression approach. Journal of Business & Economic Statistics 8: 365{371. Keen M. 1986. Zero expenditures and the estimation of engel curves. Journal of Applied Econometrics 1: 277{286. Kokoski M. 1987. Problems in the measurement of consumer cost-of-living indexes. Journal of Business and Economic Statistics 5: 39{46. Koo J, Phillips K, Sigalla F. 2000. Measuring regional cost of living. Journal of Business and Economic Statistics 18: 127{136. Kosfeld R, Eckey H, Turck M. 2008. New economic geography and regional price level. Annals of Regional Science 28: 43{60. Paredes D. 2011. A methodology to compute regional housing price index using matching estimator methods. Annals of Regional Science 46: 139{157. Paredes D, Aroca P. 2008. Metodologa para estimar un indice regional de costo de vivienda en Chile. Latin American Journal of Economics 45: 129{143. Perales F, Chavas J. 2000. Estimation of censored demand equations from large cross- section data. American Journal of Agricultural Economics 82: 1022{1037. Polak R. 1971. The Theory of the Cost of Living Index. Research Division, Oce of Prices and Living Conditions, U.S. Bureau of Labor Statistics: Research Discussion Paper No. Polak R. 1998. The consumer price index: A research agenda and three proposals. The Journal of Economic Perspectives 12: 69{78. Ray R. 1983. Measuring the costs of children: An alternative approach. The Journal of Public Economics 22: 89{102. Romero J. 2005. >Cuanto cuesta vivir en las principales ciudades colombianas? Indice de Costo de Vida Comparativo. Centro de estudios economicos regionales, Banco de la Republica de Colombia.: Documento de Trabajo No. 57. Shonkwiler J, Yen S. 1999. Two-step estimation of a censored system of equations. Amer- ican Journal of Agricultural Economics 81: 972{982. Sudekum J. 2009. Regional costs-of-living wih congestion and amenity dierences: an economic geography perspective. Annals of Regional Science 43: 49{69. Timmins C. 2006. Estimating spatial dierences in the Brazilian cost of living with house- hold location choices. Journal of Development Economics 80: 59{83. Urzua C. 2010. Notes on the estimation of demand systems. URL http://economiccluster-lac.org/images/pdf/eventos/Fiscalidad/ Mexico23y240310/Notes_on_Demand_Systems.pdf |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/30580 |