Demand dynamics and peer effects in consumption : historic evidence from a non-parametric model
Part of : Αρχείον οικονομικής ιστορίας ; Vol.XXVI, No.1, 2014, pages 27-59
Issue:
Pages:
27-59
Abstract:
The aim of this paper is to establish probabilistic statements of how the post-opening consumption decisions of individuals depend on information they receive from their peers during the opening week by using box-office data for movies released in the US market in the 1990s and 1930s. In doing so, we quantify how the post-opening demand dynamics depend on the opening power that the market at these instances dictate by proposing a smooth and non-parametric model. An understanding of the demand dynamics and adaptive supply arrangements of the motion picture industry is presented. The movie market is particularly interesting due to its skewed and kurtotic macro-regularity, which resulted in the hypothesis, that ‘nobody knows what makes a hit or when it will happen’. This hypothesis is revised here. Finally, we also find evidence of strong interaction among consumers, as one would expect information to spread,because of the multiplicative error properties of the proposed semi-parametric model. This implies the existence of a ‘social multiplier’ when quality is ex-ante uncertain.
Subject (LC):
Keywords:
Box-office revenues, Non-parametric model, The Box-Cox Power Exponential distribution, Generalised Additive Models for Location Scale and Shape (GAMLSS), Demand dynamics
References (1):
- Akaike, H. (1983). Information measures and model selection. Bulletin of the International Statistical Institute, 50: 277–290.Arthur, W. B. (1988). The Economy as an Evolving Complex System, volume 5, chapter Self-Reinforcing Mechanisms in Economics. Addison Wesley, Redwood City California.Becker, G. S. (1991). A Note on Restaurant Pricing and Other Examples of Social Influences on Price. Journal of Political Economy, 99: 1109–1116.Bikhchandani, S., H. D. and Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. The Journal ofPolitical Economy., 100: 992–1026.Bikhchandani, S., H. D. and Welch, I. (1998). Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades. The Journal ofEconomic Perspectives, 12: 151–170.Black, F. (1976). Studies of stock price volatility changes. Proceedings of the 1976 Meetings of the American Statistical Association, Business and Economical Statistics Section, pp.177–181.Calvet, L. and Fisher, A. (2008). Multifractal volatility: Theory, forecasting and pricing. Academic Press, London.Cole, T. J. and Green, P. J. (1992). Smoothing reference centile curves: the LMS method and penalized likelihood. Statist. Med., 11: 1305–1319.De Vany, A. and Eckert, R. (1991). Motion picture antitrust: the Paramount cases revisited. Research in Law and Economics, 14: 51–112.De Vany, A. and Walls, W. D. (1996). Bose-Einstein dynamics and adaptive contracting in the motion picture industry. Economic Journal., 106: 1493–1514.De Vany, A. and Walls, W. D. (2004). Hollywood Economics: How Extreme Uncertainty Shames the Film Industry, chapter Quality evaluations andthe breakdown of statistical herding in the dynamics of box-office revenue. Routledge, London.De Vany, A. and Walls, W. D. (2004). Motion picture profit, the stable Paretian hypothesis, and the curse of the superstar. Journal of Economic Dynamics and Control.,28: 1035–1057.Eilers, P. H. C. and Marx, B. D. (1996). Flexible smoothing with B-splines and penalties (with comments and rejoinder). Statist. Sci, 11: 89–121.Fernandez, C., Osiewalski, J. and Steel, M. J. F. (1995). Modeling and inference with v-spherical distributions. J. Am. Statist. Ass., 90: 1331–1340.Fernholz, R. (2002). Stochastic Portfolio Theory. Springer, New York.Fernholz, R. and Shay, B. (1982). Stochastic portfolio theory and stock market equilibrium. Journal of Finance, 37: 615–624.Glaeser, E. Sacerdote, B. and Scheinkman, J. (2003). The Social Multiplier. Journal of The European Economic Association, 1: 345–353.Haavelmo, T. (1943). The statistical implications of a system of simultaneous equations. Econometrica, 11: 1–12.Haavelmo, T. (1944).The probability approach in econometrics. Supplement to Economertica, 12.Hanssen, F. (2000). The block booking of films re-examined. Journal of Law and Economics, 43: 395-426.Jones, M. and Pewsey, A. (2009). Sinh-Arcsinh distributions. Biometrika, 96: 761–780.Lee, Y. Nelder, J.A. and Pawitan, Y. (2006). Generalized Linear Models with Random Effects. Chapman and Hall, Boca Raton.Mandelbrot, B. (1963). New Methods in Statistical Economics. The Journal of Political Economy, 71: 421–440.Mandelbrot, B. (1997). Fractals and Scaling in Finance: Discontinuity, Concentration, Risk. Springer, New York.McDonald, J. B. and Xu, Y. J. (1995). A generalisation of the beta distribution with applications. Journal of Econometrics, 66: 133–152.Moretti, E. (2010). Social Learning and Peer Effects in Consumption: Evidence from Movie Sales. Review of Economic Studies.Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: a new approach. Econometrica, 59: 347–370.Rigby, R. A. and Stasinopoulos, D. M. (2004). Smooth centile curves for skew and kurtotic data modelled using the Box-Cox Power Exponential distribution. Statistics in Medicine, 23: 3053–3076.Rigby, R. A. and Stasinopoulos, D. M. (2005). Generalized additive models for location, scale and shape, (with discussion). Appl. Statist., 54: 507–554.Sedgwick, J. and Pokorny, M. (2005). The film business in the U.S. and Britain during the 1930s. Economic History Review, 58: 79–112.van Buuren, S. and Fredriks, M. (2001). Worm plot: a simple diagnostic device for modelling growth reference curves. Statistics in Medicine, 20: 1259–1277.Vogel, H. (2007). Entertainment Industry Economics. Cambridge University Press, Cambridge, UK, 7 edition.Walls, W. D. (1997). Increasing returns to information: Evidence from the Hong Kong movie market. Applied Economics Letters., 4: 187–190.Walls, W. D. (2005). Modelling heavy tails and skewness in film returns. Applied Financial Economics., 15: 1181–1188.