Abstract
The demand structure for yogurt is assumed to be properly described by a one level nested logit model that is applied to aggregate market data. Given the presence of endogenous regressors, suitably lagged endogenous variables (Arellano and Bover in J Econom 68:29–51, 1995; Blundell and Bond in J Econom 87:115–143, 1998) are proposed as instrumental variables. The validity of this set of instruments is discussed and price elasticities and marginal costs are recovered from the demand estimates. Total welfare gains associated to the introduction of two new brands by the same manufacturer are finally computed. Prices and profits decreased and total welfare increased.
Similar content being viewed by others
References
Ackerberg D (2001) Empirically distinguishing informative and prestige effects of advertising. RAND J Econ 32:316–333
Ackerberg D, Rysman M (2005) Unobserved product differentiation in discrete choice models: estimating price elasticities and welfare effects. RAND J Econ 36:771–788
Ackerberg D, Benkard L, Berry S, Pakes A (2005) Econometric tools for analyzing market outcomes. In: Heckman JJ (ed) Handbook of econometrics. JAI Elsevier Science, Amsterdam (forthcoming)
Ahn SC, Schmidt P (1995) Efficient estimation of models for dynamic panel data. J Econom 68:5–27
Anderson S, De Palma A (1992) Multiproduct firms: a nested logit approach. J Ind Econ 40:261–276
Anderson S, De Palma A (2001) Product diversity in asymmetric oligopoly: is the quality of consumer goods too low?. J Ind Econ 49:113–135
Anderson S, De Palma A, Thisse JF (1992) Discrete choice theory of product differentiation. Cambridge, MIT
Arellano M, Bond S (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev Econ Stud 58:277–297
Arellano M, Bond S (1998) Dynamic panel data estimation using DPD98 for Gauss: a guide for users. Institute for Fiscal Studies. Available from http://www.ifs.org.uk
Arellano M, Bover O (1995) Another look at the instrumental variables estimation of error components models. J Econom 68:29–51
Arrow K (1962) Economic welfare and the allocation of resources for invention. In: Nelson R (eds.) The rate and direction on inventive activity. Princeton University Press, Princeton
Berry S (1994) Estimating discrete choice models of product differentiation. RAND J Econ 25:242–262
Berry S, Pakes A (2001) Additional information for: comments on alternative models of demand for automobiles by Charlotte Wojcik. Econ lett 74:43–51
Berry S, Pakes A (2005) The pure characteristics demand model. Int Econ Rev (forthcoming)
Berry S, Levinsohn J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63:841–890
Biørn E (2000) Panel data with measurement errors: instrumental variables and GMM procedures combining levels and differences. Econom Rev 19:391–424
Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econom 87:115–143
Blundell R, Bond S, Windmeijer F (2000) Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator. In: Baltagi B (ed) Advances in econometrics. Nonstationary panels, panel cointegration and dynamic panels, vol 15. JAI Elsevier Science, Amsterdam, pp 53–91
Bond S (2002) Dynamic panel data models: a guide to micro data methods and practice. Port Econ J 1:141–161
Bresnahan T (1989) Empirical studies of industries with market power. In: Schmalensee R, Willig R (eds.) Handbook of industrial organization. Elsevier, Amsterdam, pp. 1011–1057
Bresnahan T, Gordon R (1997) The economics of new goods. In: Studies in income and wealth, vol 58. NBER, Chicago
Bresnahan T, Schmalensee R (1987) The empirical renaissance in industrial economics: an overview. J Ind Econ 35:371–378
Bresnahan T, Stern S, Trajtenberg M (1997) Market segmentation and the sources of rents from innovation: personal computers in the late 1980’s. RAND J Econ 28:17–44
Caplin A, Nalebuff B (1991) Aggregation and imperfect competition: on the existence of equilibrium. Econometrica 59:25–59
Cardell N (1989) Variance components structures for the extreme value and logistic distributions with application to models of heterogeneity. Econom Theory 13:185–213
Chintagunta P, Kyriazidou E, Perktold J (2001) Panel data analysis of household brand choices. J Econom 103:111–153
Dubé JP (2005) Product differentiation and mergers in the carbonated soft drink industry. J Econ Manage Strategy 14:879–904
Hansen LP (1982) Large sample properties of generalized method of moments estimators. Econometrica 50:1029–1054
Hausman JA (1997) Valuation of new goods under perfect and imperfect competition. In: Gordon R (eds). The economics of new goods. Studies in income and wealth, vol 58. NBER, Chicago, pp 209–248
Hausman JA, Leonard GK (2002) The competitive effects of a new product introduction: a case study. J Ind Econ L3:237–263
Hausman JA, Leonard GK, Zona JD (1994) Competitive analysis with differentiated products. Ann Econ Stat 34:159–180
Hendel I (1999) Estimating multiple discrete choice models: an application to computerization returns. Rev Econ Stud 66:423–446
Ivaldi M, Verboven F (2005) Quantifying the effects from horizontal mergers in European competition policy. Int J Ind Organ 23:669–691
Lancaster K (1979) Variety, equity and efficiency: product variety in an industrial society. Columbia University Press, New York
Mas-Colell A, Whinston MD, Green JR (1995) Microeconomic theory. Oxford University Press, New York
McFadden D (1974) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (eds) Frontiers of econometrics. Academic, New York, pp. 105–142
McFadden D (1981) Econometric models of probabilistic choice. In: Manski C, McFadden D (eds). Structural analysis of discrete data with econometric applications. MIT, Cambridge, pp. 198–272
Nevo A (2000a) Mergers with differentiated products: the case of the ready-to-eat cereal industry. RAND J Econ 31:395–421
Nevo A (2000b) A Practitioner’s guide to estimation of random coefficients logit models of demand. J Econ Manage Strategy 9:513–548
Nevo A (2001) Measuring market power in the ready-to-eat cereal industry. Econometrica 69:307–342
Osservatorio del Mercato del Latte (2003) Annuario del latte. Università Cattolica Milano, Milano
Petrin A (2002) Quantifying the benefits of new products: the case of the Minivan. J Polit Econ 110:705–729
Pinkse J, Slade ME (2002) Mergers, brand competition and the price of a pint. Eur Econ Rev 48:617–643
Rodman D (2005) xtabond2: Stata module to extend xtabond dynamic panel data estimator. Center for Global Development, Washington. http://econpapers.repec.org/software/bocbocode/s435901.htm
Schmalensee R (1978) Entry deterrence in the ready to eat breakfast cereal industry. Bell J Econ 9:305–327
Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica 65:557–586
Stock JH, Yogo M (2002) Testing for weak instruments in linear IV regression. NBER, Technical working paper no. 284
Trajtenberg M (1989) The welfare analysis of product innovations, with an application to computed tomography scanners. J Polit Econ 97:444–479
Verboven F (1996) International price discrimination in the European car market. RAND J Econ 27:240–268
Villas-Boas JM, Winer RS (1999) Endogeneity in brand choice models. Manage Sci 45:1324–1338
Windmeijer F (2005) A finite sample correction for the variance of linear efficient two-step GMM estimators. J Econom 126:25–51
Wojcik C (2000) Alternative models of demand for automobiles. Econ Lett 68:113–118
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Giacomo, M.D. GMM estimation of a structural demand model for yogurt and the effects of the introduction of new brands. Empirical Economics 34, 537–565 (2008). https://doi.org/10.1007/s00181-007-0135-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00181-007-0135-4