Elasticidades de Demanda de Servicio Telefónico Básico en Argentina

Manuel Angel Abdala (), José Luis Arrufat and Rinaldo Colome

Cuadernos de Economía (Latin American Journal of Economics), 1996, vol. 33, issue 100, pages 397-424

Abstract: The accurate estimation of elasticities of demand for basic telephone services is extremely useful not only for the private firms in the industry but also for the regulatory agency. In this latter case, the regulators may carry out simulations in order to assess the likely effects of tariff rebalancing, especially when a price cap regulatory framework has been adopted. The elasticities reported in this paper arise from the estimation of econometric models based on the theory of demand for telephone services. Due to data limitations only the demand of use is addressed. Two general features of the equations reported are the use of a partial adjustment framework and the use of five cities in order to account for geographical dispersion across Argentina. We use monthly data for traffic, measured in minutes for both urban and long distance phone calls, for the period January 1991 - November 1993. While every conceivable effort was made in order to lengthen the period under study, severe data limitations made it impossible. The main conclusions obtained in the paper are: a) Almost 95% of the best equations estimated displayed the signs predicted by economic theory for price, fixed fee and network size for the cities of Córdoba, Corrientes, Posadas, Resistencia and Rosario. b) Price elasticities for both urban and long distance calls for distances of up to 170 Km. are negative and significantly different from zero. The magnitudes of these elasticities are fairly high when compared to the estimated reported in the literature for countries with a more mature network. A rather surprising finding is that there are instances in which price elasticities were smaller the longer the distance. Beside from one estimation which produced the wrong sign, the remaining estimations are not significant. c) With regards to size of the network elasticities, almost 90% of the estimations proved significant, displaying short-run values between 0.30 and 2.50. However, more than 50% of these are greater than 1, presumably due to the high growth rate of lines during the period analyzed in this paper. d) The elasticities of traffic with respect to the fixed fee are between -0.06 and -0.14. e) Long-run elasticities are greater than their short-run counterparts, suggesting the existence of significant lags in response to changes in prices and network size. f) The regulators should be very cautious when using the elasticities estimated in this paper for the various reasons explained in the text.

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