P. Geoffrey Allen

A Meta-Analysis of Hypothetical Bias in Stated Preference Valuation

Individuals are widely believed to overstate their economic valuation of a good by a factor of two or three. This paper reports the results of a meta-analysis of hypothetical bias in 28 stated preference valuation studies that report monetary willingness-to-pay and that used the same mechanism for eliciting both hypothetical and actual values. The papers generated 83 observations with a median value of the ratio of hypothetical to actual value of 1.35, and the distribution has severe positive skewness. Since a comprehensive theory of hypothetical bias has not been developed, we use a set of explanatory variables based on issues that have been investigated in previous research. We find that a choice-based elicitation mechanism is important in reducing bias, though an insufficient number of studies and confounding with other variables prevents us from characterizing individual mechanisms. We provide some evidence that the use of student subjects may be a source of bias, but this variable is highly correlated with group experimental settings and no firm conclusions can be drawn. There is some weak evidence that bias increases when public goods are being valued, and that some calibration methods are effective at reducing bias. Results are quite sensitive to model specification, which will remain a problem until a comprehensive theory of hypothetical bias is developed.

Economic forecasting in agriculture

Abstract Forecasts of agricultural production and prices are intended to be useful for farmers, governments, and agribusiness industries. Because of the special position of food production in a nations security, governments have become both principal suppliers and main users of agricultural forecasts. They need internal forecasts to execute policies that provide technical and market support for the agricultural sector. Government publications routinely provide private decision makers with commodity price and output forecasts at regional and national levels and at various horizons. Routine forecasts are not found in the agricultural economics journals that are the sources for most of this review. The review emphasizes methodological contributions and changes. Short-term output or ‘outlook’ forecasting uses a unique form of leading indicator. Because the production process has long been well understood, production forecasts are based on the quantifiable features of livestock or a growing crop. Price forecasts are largely made by conventional econometric methods, with time series approaches occupying minor roles. Because of the dominance of agricultural economists, there has been an overemphasis on explanation, and little interest in the predictive power of models. In recent years, some agricultural economists have begun to compare forecasts from different methods. Findings generally conform to widely held beliefs. For short-term forecasting, combining leads to more accurate forecasts, better than those produced by vector autoregression, which surprisingly is the best single method. Also surprising is that econometric models and univariate methods both do badly compared with naive models.

Estimation of Substitution Possibilities between Water and Other Production Inputs

The traditional approach to measuring the demand for water by industries relies upon fixed water-use coefficients. Water supply planners base decisions about system expansion partly upon fixed coefficients applied to projected levels of industrial growth. Among the restrictive assumptions implied by this approach is that producers are generally unresponsive to the relative price of water compared with other factors. Earlier studies focused on industry-by-industry assessments of present and potential water use technologies and the possibilities for substituting other productive inputs for water. Most of these studies are economic engineering in form. Thompson and Young and Russell are analyses of the steam electric-generating industry and the petroleum refining and petrochemical industry, respectively. Because they used linear programming techniques, their results must be interpreted cautiously. The flexible functional forms which have become

Economic impact of marine recreational fishing in Massachusetts.

Abstract A sample of 2,125 recreational marine anglers in Massachusetts in 1988 provided expense data. For trip-related expenses, average expenditures per day fished were calculated for residents and nonresidents. For non-trip-related expenses, average annual expenditures per participant were calculated for the two residence categories. Averages from the sample were expanded to population total expenditure estimates by using National Marine Fisheries Service estimates of days fished and number of participants. Translators that allocated expenditures among different economic sectors were also estimated. The Regional Science Research Institutes PC I–O model was used to conduct an input-output analysis. The estimated US

Levels, Differences and ECMs - Principles for Improved Econometric Forecasting

92.7 million spent directly by nonresidents in 1988 resulted ultimately in nearly 3,300 jobs,

PROBABILITY-DISTRIBUTIONS OF SHORT-TERM ELECTRICITY PEAK LOAD FORECASTS

44.7 million in income,

Dynamics of Beef Supply in the Presence of Cointegration: A New Test of the Backward-Bending Hypothesis

3.6 million in state tax revenues, and

Estimating the benefits of recreation under conditions of congestion congestion

5.1 million in local tax revenues. Unless these nonresidents visited the state and spent the same money on other pursuits, the jobs,...

Comparing probability forecasts derived from theoretical distributions

Unit-root testing can be a preliminary step in model development, an intermediate step, or an end in itself. Some researchers have questioned the value of any unit-root and cointegration testing, arguing that restrictions based on theory are at least as effective. Such confusion is unsatisfactory. Needed is a set of principles that limit and define the role of the tacit knowledge of the model builders. In a forecasting context, we enumerate the various possible model selection strategies and, based on simulation and empirical evidence, recommend using these tests to improve the specification of an initial general vector autoregression model.

THE ECONOMICS OF OUTDOOR RECREATION CONGESTION: A CASE STUDY OF CAMPING

Abstract Electric companies schedule generator maintenance so as to equalize the risks of capacity shortfall. Distributions of peak loads for given future weeks, months and seasons provide information on the probability that a critical load level will be exceeded in the given time period. Day-to-day fluctuations in peak loads were assumed to be directly caused by weather variables whose distributions vary by week throughout the year. Forecast distributions of weekly peak loads were computed by non-parametric simulation and re-estimation for three regression models: (1) weekly peak loads dependent on time trend and dummy variables, (2) weekly peak loads dependent on socioeconomic and weather variables, and (3) a daily version of (2). Comparisons of actual peak loads against within-sample and post-sample forecast distributions of peak loads showed that (1) and (2) were statistically equivalent but (3) was significantly worse.