A Practitioner's Guide to Estimation of Random‐Coefficients Logit Models of Demand

By Aviv Nevo. 2000

1,050 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/dcb72c691a42ded7b896c08f4c74c7812eca8709

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Citations in the corpus

Merger Simulation in Competition Policy: A Survey (2010, methodology): “In some industries, especially for day-to-day products, this does not represent actual consumer behaviour (Nevo 2000a: 401).”
Product‐Line Length as a Competitive Tool (2005, methodology): “We therefore employ a contraction mapping procedure similar to the one suggested by Berry (1994) and choose ξt = (ξ1t, . . . , ξJt) so that the actual market shares equal the theoretical ones (see also Berry, Levinsohn and Pakes 1995, Nevo 2000).”
Empirical Evidence on the Role of Nonlinear Wholesale Pricing and Vertical Restraints on Cost Pass-Through (2009, background): “As in Nevo (2000), we rewrite the utility of consumer i for product j as”
Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective (2014, methodology): “…to a variety of important questions in numerous empirical studies.1 Measuring market power (Nevo, 2001), analyzing horizontal merger effects (Nevo, 2000a), evaluating international trade policies (Berry, Levinsohn, & Pakes 1999), welfare gains due to new products (Petrin, 2002), and…”
Do private labels increase retailer bargaining power? (2010, positive): “In practice, to reduce computing logarithms, we follow Nevo (2000) by solving for wjt ¼ exp djt �� with the following contraction mapping”
Willingness to Pay for Clean Air: Evidence from Air Purifier Markets in China (2020, positive): “An attractive feature of this approach is that the conventional random-coefﬁcient logit estimation (Berry, Levinsohn, and Pakes 1995; Nevo 2000) can be applied to investigate heterogeneity in WTP for environmental quality.”
The Impact of Bestseller Rank on Demand: Evidence from the App Market (2012, neutral): “Other models like the nested logit (McFadden 1978; Cardell 1991) and the random coefficients logit (Nevo 2000) avoid this issue, but impose data requirements that are considerably more demanding than the rank data available for the present study.”
Got Organic Milk? Consumer Valuations of Milk Labels after the Implementation of the USDA Organic Seal (2007, methodology): “The utilized discrete choice model (e.g. Berry, Levinsohn, and Pakes 1995, McFadden and Train 2000, Nevo 2000 and Nevo, 2001, Swait et al 2004) also offers flexibility in incorporating consumer heterogeneity with regard to organic production.”
An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty (2006, methodology): “The GMM estimation approach mostly follows Nevo (2001); hence, the presentation here is intentionally brief.”
The impact of car specifications, prices and incentives for battery electric vehicles in Norway: Choices of heterogeneous consumers ☆ (2016, methodology): “We apply the Nelder-Mead simplex search algorithm, widely used in previous studies (Li et al., 2011; Nevo, 2000).”
Improving the Numerical Performance of Static and Dynamic Aggregate Discrete Choice Random Coefficients Demand Estimation by Jean-pierre Dubé, (2012, methodology): “Parameter Errors With Nevo’s Data and Closed-Form Derivatives In this section, we apply the three implementations of NFP from the last section to the pseudo-real cereal dataset from Nevo (2000).”
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content (2012, neutral): “This can be achieved in a similar fashion as in Nevo (2001), by enabling interactions between travel categories and product characteristics.”
Monitoring the Dynamics of Brand Equity Using Store-Level Data (2007, methodology): “The integral in Equation 3 is evaluated numerically (Nevo 2000).”
High Performance Quadrature Rules: How Numerical Integration Affects a Popular Model of Product Differentiation (2011, methodology): “The original implementation (Berry, Levinsohn, and Pakes, 1995; Nevo, 2000a) uses a contraction mapping to perform this inversion.”