Ron C. Mittelhammer

Are Stated Preferences Good Predictors of Market Behavior

Using an economic experiment in conjunction with a survey, we analyze whether consumers’ hypothetical willingness-to-pay responses are effective predictors of actual market behavior. We model revealed preferences as a function of socio-demographic characteristics and instrumental variables that represent the intensity of stated preferences. Our findings show that consumers who state that they are willing to pay a premium, which is equal to or greater than a positive lower bound, have a higher likelihood of actually buying the product in question. This implies that consumers’ actions in the economic experiment validate their survey responses. (JEL Q13, Q26)

Location and attendance in major league baseball

This study uses a travel-cost model to analyse the attendance impacts on Major League Baseball (MLB) of the closest substitute MLB team. It is found that the closer two teams are, the lower attendance is at each team relative to two teams that are farther apart. In addition, when a new team moves into the area of an existing team, there is an additional initial reduction in attendance for the incumbent team. This has implications for actions aimed at changing the number of teams in MLB either by contraction or by possible antitrust approaches that would increase the number of teams, especially in megalopolis markets. Further, and consistent with past demand studies, pricing is in the inelastic portion of gate demand and fan loyalty is a significant contributor to the estimation of gate attendance.

An Information Theoretic Approach to Econometrics

This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic econometric models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of power divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-model problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family.

Restricted least squares, pre-test, ols and stein rule estimators: Risk comparisons under model misspecification

Abstract The predictive squared error risk behavior of a restricted least squares estimator (RLS), pre-test estimator (PT), and Stein rule (SR) estimator are each compared to the behavior of the OLS estimator when relevant variables are omitted. Risk superiority conditions dependent on prior constraint error and this model specification error in a two-dimensional parameter space are exhibited. Among the consequences of this model misspecification, it is found that (i) perfectly correct prior constraints do not ensure risk superiority of any of the alternatives to OLS, (ii) the risk difference between OLS and PT is no longer bounded, and (iii) the SR no longer dominates OLS. The usefulness of risk superiority hypothesis tests based on the doubly non-centralF distribution is examined.

A hedonic price analysis of quality characteristics of Japanese Wagyu beef.

Understanding the implicit valuations of beef characteristics in the Japanese market has important policy implications for the U.S. beef industry. Hedonic price analysis was used to estimate beef characteristics values in Japan. Japanese Wagyu beef auction data were used in the analysis.

Retail-Level Hedonics and the Valuation of Milk Components

A retail-level hedonic model for analyzing the value of milk components contained in aggregate dairy product commodities is developed and applied to household food consumption survey data. The findings support Perrins conjecture that a hedonic approach applied at the retail level can be used to value milk components. Milk component values are found to be a function of household sociodemographic variables. The sample-weighted average implicit fat value estimate was very similar to values published in two of three previous component value analyses in the Journal, but protein values were significantly different.

GENERALIZED MAXIMUM ENTROPY ESTIMATION OF A FIRST ORDER SPATIAL AUTOREGRESSIVE MODEL

We formulate generalized maximum entropy estimators for the general linear model and the censored regression model when there is first order spatial autoregression in the dependent variable. Monte Carlo experiments are provided to compare the performance of spatial entropy estimators relative to classical estimators. Finally, the estimators are applied to an illustrative model allocating agricultural disaster payments.

Probit With Spatial Correlation by Field Plot: Potato Leafroll Virus Net Necrosis in Potatoes

A probit model with spatial correlation is applied to data from a field experiment, which characterizes the impact of management variables on potato leafroll virus net necrosis in potato tubers. In the estimation, each field plot is assigned distinct spatial autoregressive coefficients for the dependent variable and the residual to be estimated simultaneously with coefficients of the management variables. Statistical findings demonstrate that spatial correlation exists and varies across field plots. We also find that ignoring spatial correlation by plot results in inconsistent parameter estimates and leads to management strategies promoting overuse of insecticides. In contrast, incorporating spatial correlation by plot into the probit model yields empirical estimates that are consistent with past research and promotes more efficient insecticide use from both an individual and environmental perspective.

Mitigating the Effects of Multicollinearity Using Exact and Stochastic Restrictions: The Case of an Aggregate Agricultural Production Function in Thailand

Ordinary least squares, exactly restricted OLS, stochastically restricted OLS (mixed estimation), and principal components regression each were used to estimate an aggregate agricultural production function for Thailand for which data were highly multicollinear. Pretest considerations, incorporating alternative risk measures, were addressed in detail for purposes of model evaluation. The final mixed and principal components models generally outperformed OLS in terms of risk and overall reasonableness, mitigating a serious multicollinearity problem and permitting a direct examination of the rate and composition of Thai agricultural output growth.

Applying Mixed Estimation in Econometric Research

The validity of the Theil-Goldberger mixed estimation procedure for incorporating prior information into the estimation of econometric models has recently been questioned in the literature. In this article, a set of accepted statistical principles are used both to rationalize past and future applications of mixed estimation through the introduction of a modified mixed estimator and to provide an explicit rationale for the abandonment of the Theil-Goldberger procedure. A previous application of mixed estimation in this Journal is reexamined to illustrate the issues involved.