Convenient estimators for the panel probit model: Further results

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likelihood estimation is actually straightforward, and resort to GMM estimation for convenience is unnecessary. In this note, we reconsider maximum likelihood based estimation of their panel probit model then examine some extensions which can exploit the heterogeneity contained in their panel data set. Empirical results are obtained using the data set employed in the earlier study. Helpful comments and suggestions by Irene Bertschek and Michael Lechner are gratefully acknowledged. This paper has also benefited from comments by two anonymous referees and from seminar participants at the Center for Health Economics at the University of York. Any remaining errors are the responsibility of the author.     

Electricity Market Restructuring: Reforms of Reforms

Electricity systems present complicated challenges for public policy. In many respects these challenges are similar to those in other network industries in providing a balance between regulation and markets, public investment and private risk taking, coordination and competition. As with other such industries, naturally monopoly elements interact with potentially competitive services, but electricity has some unusual features that defy simple analogy to other network industries. Following a reversal of a long-term decline in real electricity prices, the last two decades of the twentieth century were for the United States a time of reform, reaction, and reforms of reforms in electricity systems, moving slowly towards greater reliance on competition and markets. Changing technology, new entrants in the generation market, and a legislative mandate to provide access to the essential transmission facility accelerated a process that required major innovations in institutions and operations. Complete laissez faire competition is not possible, and the details of an efficient competitive electricity market are neither obvious nor easy to put in place. The benefits of reform may be substantial, but they require careful attention to market design. A review of the past identifies some choices on the road ahead.     

Provision Point Mechanisms and Field Validity Tests of Contingent Valuation

Past field validity tests of contingent valuation have relied on voluntary contribution mechanisms to elicit actual willingness to pay, and may overestimate hypothetical bias because of free riding in the actual contributions. This paper argues that provision point mechanisms are a preferred alternative for field validity tests of contingent valuation because they increase the proportion of demand revealed in cases in which public goods can be provided in a step function. The results of a contingent valuation validity study of participation in a green electricity pricing program that uses a provision point mechanism are reported, and hypothetical open-ended and dichotomous choice responses are compared to actual participation. Calibration of hypothetical responses is also explored.     

Estimation of a non-invertible moving average process: The case of overdifferencing

The effect of differencing all of the variables in a properly specified regression equation is examined. Excessive use of the difference transformation induces a non-invertible moving average (MA) process in the disturbances of the transformed regression. Monte Carlo techniques are used to examine the effects of overdifferencing on the efficiency of regression parameter estimates, inferences based on these estimates, and tests for overdifferenccing based on the estimator of the MA parameter for the disturbances of the differences regression. Overall, the problem of overdifferencing is not serious if careful attention is paid to the properties of the disturbances of regression equations.     

Variables sampling plans for the Poisson and the binomial

Variables sampling plans based upon continuous distributions are well known. The usual assumption is that a measurable characteristic associated with a product has a normal distribution, a case which has been treated extensively in the literature. Other continuous distributions, particularly the exponential, have also been used as models. In this paper we discuss variables sampling plans for situations in which the measurable characteristic has either a Poisson or a binomial distribution.     

Deriving benefits from conflict resolution: A macrojustice assessment

Effective conflict resolution procedures serve to minimize dysfunctional effects of conflict and maximize functional effects. In the literature on conflict resolution procedures, the effectiveness of procedures has been evaluated primarily from the perspective of the individual. This article suggests that a system-level analysis of the pattern of outcomes resulting from different conflict resolution procedures is a necessary component in formulating a comprehensive framework for the design and evaluation of conflict resolution systems in organizations. The analytic questions addressed by this study concern associations between resolution procedures and outcome patterns in a system created specifically for conflict resolution within organizations: the grievance system. The pattern of outcomes was found to vary with the conflict resolution procedure. It is suggested that this has important implications for effective conflict resolution systems.     

Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA

Pareto-Koopmans efficiency in Data Envelopment Analysis (DEA) is extended to stochastic inputs and outputs via probabilistic input-output vector comparisons in a given empirical production (possibility) set. In contrast to other approaches which have used Chance Constrained Programming formulations in DEA, the emphasis here is on joint chance constraints. An assumption of arbitrary but known probability distributions leads to the P-Model of chance constrained programming. A necessary condition for a DMU to be stochastically efficient and a sufficient condition for a DMU to be non-stochastically efficient are provided. Deterministic equivalents using the zero order decision rules of chance constrained programming and multivariate normal distributions take the form of an extended version of the additive model of DEA. Contacts are also maintained with all of the other presently available deterministic DEA models in the form of easily identified extensions which can be used to formalize the treatment of efficiency when stochastic elements are present.     

Time to default in the UK mortgage market

This paper employs duration analysis to investigate the timing of default in the UK mortgage market. Our analysis is performed on an ex ante basis, in that our explanatory variables are available to mortgage lenders when the loan is first made. We estimate both standard Weibull distributions and generalizations of the Weibull that permit non-monotonic hazard functions. The models fit the data well, suggesting that we have captured the major sources of variation in duration. We find that ‘cash flow’ variables, such as salary and interest rate paid, play the largest role. Surprisingly, loan-to-value ratios are either insignificant or influence default times in a counter-intuitive direction.