Journal ArticleDOI
Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher
TLDR
In this paper, a simple, regenerative, optimal stopping model of bus-engine replacement is proposed to describe the behavior of Harold Zurcher, superintendent of maintenance at the Madison (Wisconsin) Metropolitan Bus Company.Abstract:
This paper formulates a simple, regenerative, optimal-stopping model of bus-engine replacement to describe the behavior of Harold Zurcher, superintendent of maintenance at the Madison (Wisconsin) Metropolitan Bus Company. Admittedly, few people are likely to take particular interest in Harold Zurcher and bus engine replacement per se. The author focuses on a specific individual and capital good because it provides a simple, concrete framework to illustrate two ideas: (1) a "bottom-up" approach for modeling replacement investment and (2) a "nested fixed point" algorithm for estimating dynamic programming models of discrete choice.read more
Citations
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Book
Discrete Choice Methods with Simulation
TL;DR: In this paper, the authors describe the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation, and compare simulation-assisted estimation procedures, including maximum simulated likelihood, method of simulated moments, and methods of simulated scores.
Journal ArticleDOI
Credit Market Constraints, Consumption Smoothing and the Accumulation of Durable Production Assets in Low-Income Countries: Investments in Bullocks in India
TL;DR: In this paper, the authors formulate and estimate a finite-horizon, structural dynamic model of agricultural investment behavior that incorporates the major features of low-income agricultural environments: income uncertainty, constraints on borrowing and rental markets, and the use of investment assets to generate income and smooth consumption.
Journal ArticleDOI
Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets
Tülin Erdem,Michael Keane +1 more
TL;DR: In this article, the authors derive from the Bayesian learning framework how brand choice probabilities depend on past usage experience and advertising exposure, and then form likelihood functions for the models and estimate them using simulated maximum likelihood.
Journal ArticleDOI
Conditional Choice Probabilities and the Estimation of Dynamic Models
V. Joseph Hotz,Robert A. Miller +1 more
TL;DR: In this article, a new method for estimating the structural parameters of (discrete choice) dynamic programming problems is proposed. But the method is limited to the case of discrete choice problems.
Journal ArticleDOI
How Social Security and Medicare affect retirement behavior in a world of incomplete markets
John Rust,Christopher Phelan +1 more
TL;DR: In this article, a detailed dynamic programming model of the joint labor supply and Social Security acceptance decision, focusing on a sample of males in the low to middle income brackets whose only pension is Social Security, is presented.
References
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Book
The theory of stochastic processes
David Cox,Hilton D. Miller +1 more
TL;DR: This book should be of interest to undergraduate and postgraduate students of probability theory.
Posted Content
Analysis of Covariance with Qualitative Data
TL;DR: In this paper, the joint maximum likelihood estimator of the structural parameters is not consistent as the number of groups increases, with a fixed number of observations per group, and a conditional likelihood function is maximized, conditional on sufficient statistics for the incidental parameters.
Posted Content
Estimation and Inference in Nonlinear Structural Models
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Conditional Choice Probabilities and the Estimation of Dynamic Models
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