Valuation on the Frontier: Calibrating Actual and Hypothetical Statements of Value

The lack of robust evidence showing that hypothetical behavior directly maps into real actions remains a major concern for proponents of stated preference nonmarket valuation techniques. This article explores a new statistical approach to link actual and hypothetical statements. Using willingness-topay field data on individual bids from sealed-bid auctions for a $350 baseball card, our results are quite promising. Estimating a stochastic frontier regression model that makes use of data that any contingent valuation survey would obtain, we derive a bid function that is not statistically different from the bid function obtained from subjects in an actual auction. If other data can be calibrated similarly, this method holds significant promise since an appropriate calibration scheme, ex ante or ex post, can be invaluable to the policy maker that desires more accurate estimates of use and nonuse values for nonmarket goods and services.calibration, contingent valuation, stochastic frontier

Is Investment in Environmental Quality a Solution to Recessions? Studying the Welfare Effects of Green Animal Spirits

Assume that 'green accounting' has been adopted and implemented, does an investment in environmental quality play a role similar to the investment in capital in towing the economy out of a recession? To answer the question, we integrate 'green accounting' into a stochastic dynamic general equilibrium model to study the short-run consequences of investment in environmental quality and hereby addressing if there is an incentive-based fiscal environmental solution to recessions. Surprisingly and counter intuitive, we found that reducing the rate at which humans consume the environment renders a fiscal policy - that engage in environmental investment - less effective in providing a thrust out of a recession. Conditional on the proposed model and the calibrated parameters, we conclude that an increase of one percent in environmental investment will crowd out real quarterly consumption in a range from $102.74 billions to$ 171.11 billions, on average, in every quarter for seven years following the investment (measured in chained 2000 dollars). Therefore, we argue that investment in environmental quality is not a solution to recessions. This result is a striking contrast to the conclusion reached in Weitzman and Löfgren (1997, Journal of Environmental Economics and Management, 32 (2), 139-153).Environmental Quality, Green Accounting, Stochastic Dynamic General Equilibrium models

ON THE FRONTIER OF GENERATING REVEALED PREFERENCE CHOICE SETS: AN EFFICIENT APPROACH

Deterministic rules for generating choice sets are often employed by analysts confronting universal sets with large numbers of alternatives. For destination choice analysis, site exclusion rules defined by travel time, distance, or quality have a behavioral appeal, yet are fundamentally limited by their one-dimension scope. To remedy this shortcoming while maintaining the concept that trips require costly inputs to yield utility generating outputs, we develop and test an exclusion rule for generating choice sets defined by efficiency measures derived from stochastic frontier econometric models. Choice set composition, site choice efficiency and probability of selection, and consumer surplus are compared with results obtained under alternative exclusion rules.Research Methods/ Statistical Methods,

Count Data Stochastic Frontier Models, With An Application To The Patents-R&Amp;D Relationship

This article introduces a new count data stochastic frontier model that researchers can use in order to study efficiency in production when the output variable is a count (so that its conditional distribution is discrete). We discuss parametric and nonparametric estimation of the model, and a Monte Carlo study is presented in order to evaluate the merits and applicability of the new model in small samples. Finally, we use the methods discussed in this article to estimate a production function for the number of patents awarded to a firm given expenditure on R&D. © 2012 Springer Science+Business Media, LLC

Predictors Of Gaps In Patient Safety And Quality In U.S. Hospitals

Objective: To explore predictors of gaps between observed and best possible Hospital Compare scores in U.S. hospitals. Data Sources: American Hospital Association Annual Survey; Area Resource Files; Centers for Medicare and Medicaid Services Medicare Provider and Analysis Review; and Hospital Compare data. Study Design: Using Stochastic Frontier Analysis and secondary cross-sectional data, gaps between the best possible and actual scores of Hospital Compare quality measures were estimated. Poisson regressions were used to ascertain financial, organizational, and market predictors of those gaps. Data Extraction: Data were cleaned and matched based on hospital Medicare IDs. All U.S. hospitals that matched on analysis variables in 2007 were in the study (1,823–2,747, depending upon gap variable). Principal Findings: Most hospitals have a greater than 10 percent gap in quality indicators. Payer mix, registered nurse staffing, size, case mix index, accreditation, being a teaching hospital, market competition, urban location, and region were strong predictors of gaps, although the direction of the association with gaps was not uniform across outcomes. Conclusions: A significant percentage of hospitals have gaps between their best possible and observed quality scores. It may be better to use gap scores than observed scores in payments systems. More SFA research is needed to know how to lower gaps through changes in hospital and market characteristics

sfcount: Command for count-data stochastic frontiers and underreported and overreported counts

In this article, we introduce a new command, sfcount, to t count-data stochastic frontier models. Although originally designed to estimate production and production-cost functions, this new command can be used to estimate mean regression functions when count data are suspected to be underreported or over- reported

sfcount: Command for count-data stochastic frontiers and underreported and overreported counts

In this article, we introduce a new command, sfcount, to t count-data stochastic frontier models. Although originally designed to estimate production and production-cost functions, this new command can be used to estimate mean regression functions when count data are suspected to be underreported or over- reported

U.S. nursing homes. Are they cost efficient?

Utilizing a system of allocative efficiency functions and a short-run variable cost frontier, the following analysis avoids many statistical problems associated with measuring efficiency. Using an underutilized data base, the authors find that inefficiency increases costs only a trivial amount. © 1994

Employment Determination In Macroeconomic Models: Some Empirical Evidence

The specification of how employment is determined has important implications for short-run macroeconomic policy prescriptions. Heretofore, there have been two main methods for testing this specification: comparing an equilibrium model to a disequilibrium model and using a switching regression model. This paper introduces a new method which is based on the distribution of the error term and the sign and significance of the real wage coefficient in a reduced form equation for employment. It is found that for the years 1948-1984 inclusive, the United States labor market has been operating under a fixed wage regime in which employment is being determined by the short-side of the market. Furthermore, the tests also indicate that the real wage is as likely to be below the equilibrium real wage as it is to be above it. As such, one cannot even make the case that, even though employment is determined by the short-side of the market, it acts as if it was demand determined. © 1993