Walter J. Mayer

Genetic Algorithms for Estimation Problems With Multiple Optima, Nondifferentiability, and Other Irregular Features

The genetic algorithm is examined as a method for solving optimization problems in econometric estimation. It does not restrict either the form or regularity of the objective function, allows a reasonably large parameter space, and does not rely on a point-to-point search. The performance is evaluated through two sets of experiments on standard test problems as well as econometric problems from the literature. First, alternative genetic algorithms that vary over mutation and crossover rates, population sizes, and other features are contrasted. Second, the genetic algorithm is compared to Nelder–Mead simplex, simulated annealing, adaptive random search, and MSCORE.

A Poisson Probability Model of Entry and Market Structure with an Application to U. S. Industries during 1972-77

The performance characteristics of an industry are closely linked to the nature of entry and exit in the industry. If entry barriers are low, the threat of potential entry can effectively constrain the ability of incumbent firms to raise price above the competitive level. On the other hand, as entry barriers rise and the probability of entry diminishes, the potential for monopolistic practices increases. Prior empirical studies of entry have focused mainly on its determinants, emphasizing industry characteristics as entry barriers. Examples include McGuckin [19], Orr [21], McDonald [17], and Duetsch [7], which analyze the number of new entrants, and Berry [4], McDonald [17; 18], and Masson and Shannon [15; 16] which focus on the market share of entering firms. Our study uses the model of Orr, and its later extension by Duetsch, as its initial reference point. Like the Orr-Duetsch studies we estimate a model for entry determinants across industries based on the number of new firms. Our contribution is two-fold. First, we analyze a new sample period, 1972-77. Second, we provide a methodological improvement over the logarithmic regression approaches of Orr and Duestch. Because the observations on entry are count data (non-negative integers), our model is developed from the premise that entry requires a statistical framework based on a discrete probability distribution. To meet this requirement, we specify and estimate an econometric model of entry based on the Poisson distribution. Our methodology is in the spirit of Hausman, Hall, and Griliches [11] who apply the Poisson distribution to count data on patent application across firms. Hausman, Hall and Griliches point out that the Poisson model offers an improved methodology for a wide range of economic applications that feature data in the form of repeated counts. This observation motivated our application of the Poisson distribution to the entry problem. The Poisson approach admits a richer analysis of the entry data than the logarithmic regression approach in two ways. First, the logarithmic specification, while computationally convenient, provides a rather incomplete description of the entry data. The log of entry is only well defined

The Impact of Revenue Diversification on Expected Revenue and Volatility for Nonprofit Organizations

We investigate the relationship between revenue diversification and volatility for nonprofits. Modern portfolio theory suggests that more diversification reduces volatility at the expense of reduced expected revenue. We find that this relationship should not be taken for granted. We use a new empirical measure of volatility that addresses estimation issues of expected revenue, including heteroskedasticity and the omission of the effect of diversification on expected revenue. We also examine the impact on nonprofits of different types of diversification. We find that the effects of diversification on volatility and expected revenue depend on the compositional change in the portfolio. For example, a more diversified portfolio achieved by replacing earned income with donations reduces both volatility and expected revenue, while replacing investment income with donations to achieve an increase in diversification of the same magnitude reduces volatility and increases expected revenue. This suggests other motives for nonprofit organizations to hold investments.

The impact of unionization on the entry of firms: Evidence from U.S. industries

Traditional models of entry-deterrence typically emphasize sunk costs or predatory pricing, but unionization might also discourage potential entrants. This paper explores this possibility through an empirical model of entry that includes unionization as an explanatory variable. We find that unionization has a statistically significant entry-deterring effect.

Estimating disequilibrium models with limited a priori price-adjustment information

Abstract Economic theory imposes few a priori conditions on price adjustment and thus requires econometric disequilibrium models to be both sufficiently general and computationally tractable. The switching regression model of Lee and Porter (1984) meets these requirements. Unlike previous models, price adjustment enters without an explicit adjustment equation or the restriction that price changes reveal the sign of excess demand. I apply the model to the U.S. commercial loan market from 1979–1984. The estimates suggest a pattern of excess demand consistent with the financial developments of the period.

Union rents and market structure revisited

Several recent studies give conflicting evidence on whether market power associated with industry concentration is an important source of union rents. Using a 1977 sample of 327 four-digit manufacturing industries, we re-examine the issue with a regression analysis that allows for differential union effects on price-cost margins across three levels of concentration. Large and small firm as well as industry average price-cost margins are analyzed. The results reaffirm those of Hirsch and Connolly (1987), who conclude that the effect of unions on profits is independent of market structure, and thus market power is not an important source of union rents. We find that unionization: (1) reduces industry profits in all three concentration groups with statistically insignificant differential effects, and (2) has a greater negative effect on the profits of large firms than it does on the profits of small firms, regardless of the concentration category.

Maximum score estimation of disequilibrium models and the role of anticipatory price-setting

Abstract In this paper, a general model of disequilibrium quantity determination under median regression assumptions is combined with weak assumptions on the price adjustment to yield a consistent maximum score estimator. In contrast to Sapra (1986) , the supply and demand parameters are separately identifiable and the estimator employs all of the observed data. The price adjustment assumptions can be motivated by the anticipatory pricing model of Green and Laffont (1981) . In contrast to the Green–Laffont model, however, our assumptions only require that long-run Walrasian prices have positive probability. As an illustrative application, maximum score estimates of a model of the US commercial loan market are computed and compared to maximum likelihood estimates. Monte Carlo results are also reported.

Detection of Spurious Maxima through Random Draw Tests and Specification Tests

Consistent estimation requires finding the global maximum of some specifiedobjective function. Local maxima are often easy to find, but do notnecessarily yield consistent estimates. In many nonlinear applications, theresearcher can rarely be certain that a found local maximum is global. Thispaper examines the ability of random draw tests and specification tests todetect spurious maxima. For random draw tests we analyze Veall (1990) and atest introduced here based on a generalized beta distribution. Specificationtests routinely used by researchers are also examined as methods for detectingspurious maxima. Monte Carlo results are reported on various test functions.The results suggest that specification testa are more useful than the randomdraw tests for detecting spurious maxima.

An extension of the maximum score estimator for disequilibrium models

Abstract Mayer and Dorsey (1998) [Mayer, W.J., Dorsey, R.E., 1998. Maximum score estimation of disequilibrium models and the role of anticipatory price-setting. Journal of Econometrics, 87, 1–4] propose a maximum score estimator for disequilibrium models with anticipatory pricing models. Here I prove consistency under assumptions that allow for more general price adjustment processes. I also show that the smoothing function used in Mayer and Dorsey (1998) can be replaced with a simpler function that requires fewer arbitrary choices by the researcher.

THE EFFECT OF LEGALIZING RETAIL MARIJUANA ON HOUSING VALUES: EVIDENCE FROM COLORADO

Does legalizing retail marijuana generate more benefits than costs? This paper provides a first step toward addressing that question by measuring the benefits and costs that are capitalized into housing values. We exploit the time‐series and cross‐sectional variations in the adoption of Colorados municipality retail marijuana laws (RMLs) and examine the effect on housing values with a difference‐in‐differences strategy. Our estimates show that the legalization leads to an average 6% increase in housing values, indicating that the capitalized benefits outweigh the costs. In addition, we find suggestive evidence that this relatively large housing value appreciation is likely due to RMLs inducing strong housing demand while having no discernible effect on housing supply. Finally, we show that the effect of RMLs is heterogeneous across locations and property types. (JEL K20, R28)