Suchergebnisse

"The widely-used estimator of Berry, Levinsohn and Pakes (1995) produces estimates of consumer preferences from a discrete-choice demand model with random coefficients, market-level demand shocks and endogenous prices. We derive numerical theory results characterizing the properties of the nested fixed point algorithm used to evaluate the objective function of BLP's estimator. We discuss problems with typical implementations, including cases that can lead to incorrect parameter estimates. As a solution, we recast estimation as a mathematical program with equilibrium constraints, which can be faster and which avoids the numerical issues associated with nested inner loops. The advantages are even more pronounced for forward-looking demand models where Bellman's equation must also be solved repeatedly. Several Monte Carlo and real-data experiments support our numerical concerns about the nested fixed point approach and the advantages of constrained optimization"--National Bureau of Economic Research web site

We study the long-run evolution of brand preferences, using new data on consumers' life histories and purchases of consumer packaged goods. Variation in where consumers have lived in the past allows us to isolate the causal effect of past experiences on current purchases, holding constant contemporaneous supply-side factors. We show that brand preferences form endogenously, are highly persistent, and explain 40 percent of geographic variation in market shares. Counterfactuals suggest that brand preferences create large entry barriers and durable advantages for incumbent firms and can explain the persistence of early-mover advantage over long periods. (JEL D12, L11, M31, M37)