Multinomial Logit Model ile Amerika Birleşik Devletleri'nde Marka Düzeyinde Cips Talebi Analizi

Yıl 2024, , 155 - 180, 01.04.2024

Merve Özbağ Keçeci

https://doi.org/10.17153/oguiibf.1347020

Öz

Bu çalışma, IRI verilerini kullanarak 52 cips markasının talebini tahmin etmektedir. Multinomial logit modeli, talep tahmininde karşılaşılan çok sayıda parametre sorunu ve içsellik problemlerine çözüm getirmektedir. Tüm markaların fiyat esneklikleri -5.0412 ile -1.4251 aralığında değişmektedir; bu da tüketicilerin cips fiyatlarına son derece duyarlı olduklarını göstermektedir. Tortilla cips markaları, patates cipsi markalarına göre daha az esnek bulunmuştur. Ayrıca fırınlanmış cips markaları en esnek talebe sahip ürünler arasındadır. Funyuns en yüksek, Calidad Triangle ise en düşük talep esnekliğine sahip markalardır. Çapraz fiyat esneklikleri, IIA (ilişkisiz-alternatiflerin-bağımsızlığı) özelliğini sergilemektedir ve büyüklükleri (0.0010 ile 0.0263 arasında), fiyat esnekliklerinin büyüklükleriyle kıyaslandığında tüketicilerin marka sadakatine sahip olduğunu göstermektedir.

Anahtar Kelimeler

Farklılaştırılmış Ürün Talebi, Cips Talebi, Multinomial Logit Model

Analyzing Brand-Level Chips Demand in the United States Using the Multinomial Logit Model

Öz

This study estimates demand for 52 chip brands using IRI scanner data. The multinomial logit model addresses dimensionality and endogeneity issues in demand estimation. All brands exhibit elastic demand, with own-price elasticities between -5.0412 and -1.4251, indicating high consumer responsiveness to price changes. Notably, tortilla chip brands are less elastic than potato chip brands. Baked chip brands fall under the category of highly elastic brands. Funyuns has the most elastic demand, while Calidad Triangle has the least elastic demand. Cross-price elasticities (0.0010 to 0.0263), exhibiting the IIA property, indicate that consumers have brand loyalty, as seen by comparisons with own-price elasticities' magnitudes.

Anahtar Kelimeler

Differentiated Goods Demand, Chip Demand, Multinomial Logit Model

Kaynakça

• Arnade, C., Gopinath, M., & Pick, D. (2011). How Much Do Consumers Benefit from New Brand Introductions? The Case of Potato Chips. Journal of Agricultural and Resource Economics, 36(1), 78-94.
• Barten, A.P., (1966). Theorie en empirie van een volledig stelsel van vraagvergelijkingen (Theory and empirics of a complete system of demand equations). Doctoral dissertation (Netherlands School of Economics, Rotterdam).
• Berry, S. (1994). Estimating Discrete-Choice Models of Product Differentiation. The RAND Journal of Economics, 25(2), 242-262.
• Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile Prices in Market Equilibrium. Econometrica, 63(4), 841-890. Besanko, D., Dranove, D., Shanley, M, & Schaefer, S. (2004). Economics of Strategy.
• Bresnahan, T. F. (1989). Chapter 17 Empirical studies of industries with market power. In Handbook of Industrial Organization (Vol. 2, pp. 1011–1057). Elsevier.
• Cameron, A., & Trivedi, P. (2005). Microeconometrics: Methods and applications. Cambridge University Press. Carlton, D.W. & Perloff, J.M. (2005). Modern Industrial Organization, 4th ed. New Jersey: Prentice-Hall.
• Chidmi, B., & Lopez, R. (2007). Brand-Supermarket Demand for Breakfast Cereals and Retail Competition. American Journal of Agricultural Economics, 89(2), 324-337.
• Cotterill, R. W., & Haller, L. E. (1997). An Econometric Analysis of the Demand for RTE Cereal: Product Market Definition and Unilateral Market Power Effects. University of Connecticut, Food Marketing Policy Center, Research Report 35.
• Deaton, A., & Muellbauer, J. (1980). An almost ideal demand system. American Economic Review, 70, 312.
• Drug Store News. (April 23, 2017). Consumer packaged goods (CPG) sales in the United States from 2011 to 2016 (in billion U.S. dollars) [Graph]. In Statista. Retrieved May 20, 2023, from https://www.statista.com/statistics /729659/cpg-sales-value/
• Dubé, J.-P. (2004). Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks. Marketing Science, 23(1), 66–81.
• Dubois, P., Griffith, R., & O'connell, M. (2018). The Effects of Banning Advertising in Junk Food Markets. The Review of Economic Studies, 85(1 (302)), 396-436.
• Eaton, B.C., & Lipsey, R.G. (1989). Product Differentiation. In R. Schmalensee and R.D. Willig, eds. Handbook of Industrial Organization Volume 1. Elsevier Science, pp. 723–768.
• Guadagni, P. M., & Little, J. D. (1983). A logit model of brand choice calibrated on scanner data. Marketing Science, 2(3), 203-238.
• Guadagni, P. M., & Little, J. D. (1998). When and what to buy: A nested logit model of coffee purchase. Journal of Forecasting, 17(3‐4), 303-326.
• Hausman, J., Leonard, G., & Zona, J. D. (1994). Competitive Analysis with Differenciated Products. Annales d'Économie et de Statistique, 34, 159–180.
• Hausman, J. A. (1996). Valuation of new goods under perfect and imperfect competition. The economics of new goods. University of Chicago Press, pp. 207–248.
• Hiller, R. S., Savage, S. J., & Waldman, D. M. (2018). Using aggregate market data to estimate patent value: An application to United States smartphones 2010 to 2015. International Journal of Industrial Organization, 60, 1–31.
• Kuchler, F., Tegene, A., & Harris, J. (2005). Taxing snack foods: Manipulating diet quality or financing information programs. Review of Agricultural Economics, 27(1), 4-20.
• Kumar, P., & Divakar, S. (1999). Size does matter: Analyzing brand-size competition using store level scanner data. Journal of Retailing, 75(1), 59-76.
• Lopez, R., & Fantuzzi, K. (2012). Demand for carbonated soft drinks: Implications for obesity policy. Applied Economics, 44(22), 2859-2865.
• McFadden, D. (1974). The measurement of urban travel demand. Journal of public economics, 3(4), 303-328.
• McFadden, D. (1978). Modeling the choice of residential location. Transportation Research Record, (673).
• McFadden, D. (1981). Econometric Models of Probabilistic Choice, in C. Manski and D. McFadden (eds) Structural Analysis of Discrete Data, Cambridge: MIT Press, 198-272.
• McFadden, D. (1984). Econometric analysis of qualitative response models, in Z. Griliches and M. Intriligator (ed) Handbook of Econometrics, Vol. '2, Amsterdam: North-Holland.
• Mojduszka, E.M., Caswell, J.A. and Harris, J.M. (2001), Consumer choice of food products and the implications for price competition and government policy. Agribusiness, 17: 81-104.
• Nevo, A. (2000a). A Practitioner's Guide to Estimation of Random‐Coefficients Logit Models of Demand. Journal of Economics & Management Strategy, 9(4), 513-548.
• Nevo, A. (2001). Measuring Market Power in the Ready‐to‐Eat Cereal Industry. Econometrica, 69(2), 307-342.
• Nevo, A. (2010). Empirical Models of Consumer Behavior. NBER Working Paper Series, 16511.
• Nielsen. (September 30, 2015). Retail snack dollar sales share in the United States in 2015, by type* [Graph]. In Statista. Retrieved May 20, 2023, from https://www.statista.com/statistics /475110/us-retail-snack-dollar-sales-share-by-type/
• Orion Market Research. (January 7, 2021). Value of the savory snacks market in the United States from 2019 to 2026 (in million U.S. dollars) [Graph]. In Statista. Retrieved May 20, 2023, from https://www.statista.com/statistics /1199704/savory-snack-market-size-in-the-united-states/
• Staudigel, M. & Anders, S. (2016). Does taste trump health? Effects of nutritional characteristics on brand-level demand for chips in the U.S. 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235755. Agricultural and Applied Economics Association.
• Staudigel, M., & Anders, S. (2018). Effects of nutrients, Brand, and flavor type on demand for differentiated chips products in the U.S. Food-Health-Economics-Workshop, Manufacture des tabacs, Toulouse, June 7–8, 2018, room MS 001.
• Staudigel, M., & Anders, S. (2020). Effects of the FDA's sodium reduction strategy in the U.S. market for chip products. Journal of Economic Behavior & Organization, 173, 216-238.
• Statista. (February 15, 2022). Most popular brands of salty snacks in the United States in 2021 [Graph]. In Statista. Retrieved May 29, 2023, from https://www.statista.com/forecasts /1093603/most-popular-brands-of-chips-or-crisps-in-the-us
• Stone, R. (1954). Linear Expenditure Systems and Demand Analysis: An Application to the Pattern of British Demand. The Economic Journal, 64(255), 511-527.
• Theil, H. (1965). The Information Approach to Demand Analysis. Econometrica (pre-1986), 32(1), 67.
• Train, K., McFadden, D., & Ben-Akiva, M. (1987). The Demand for Local Telephone Service: A Fully Discrete Model of Residential Calling Patterns and Service Choices. The Rand Journal of Economics, 18(1), 109-123.
• Verboven, F. (1996). International price discrimination in the European car market. The RAND Journal of Economics, 240-268.
• Villas-Boas, J. M., & Winer, R. S. (1999). Endogeneity in Brand Choice Models. Management Science, 45(10), 1324–1338.
• Villas-Boas, S. (2007a). Using Retail Data for Upstream Merger Analysis. Journal of Competition Law & Economics, 3(4), 689-715.
• Villas-Boas, S.B. (2007b). Vertical Relationships between Manufacturers and Retailers: Inference with Limited Data. The Review of Economic Studies, 74, 625-652.