Statistical analysis is used to evaluate trends in the relative prices of natural resource commodity aggregates and to predict the adequacy of natural resource supplies. The model incorporates the Brown-Durbin custom test and Quandt's log-liklihood ratio. The results indicate that a relative price series is not stable enough to predict a consistent pattern of change and it would be unwise to base materials and extraction policies on this framework. This conclusion is reached, in part, because of the significant changes in the US economy and institutions in recent years. 22 references.

This study evaluates the effectiveness of a radon risk communication program based on how the estimated value of additional information varies across the six types of descriptive materials randomly assigned to a panel of homeowners participating in a radon utility model estimated with probit from respondents' answers to a contingent behavior question asking if they would purchase at a one-time price the services of a licensed technician to analyze their radon problems. The findings indicate that the information materials used most frequently by states and testing companies to explain radon's risk are the least effective of the six considered.

This paper develops and estimates a demand model to describe a household's demand for distance from a landfill with hazardous wastes. This model provides one basis for gauging the intensity of a household's desire to avoid living near this type of facility. Using the conceptual framework of a hedonic property value model to provide the basis for demand for distance questions, a survey in suburban Boston elicited this information from 609 households. The demand estimates imply that the average household would realize a consumer surplus between $330 to $495 annually for each mile between its residence and a landfill containing hazardous waste.

This paper proposes a method for measuring the effects of substitutions in the timing of recreational use on people's willingness to pay for nonmarketed resources. Using the three markets (peak, pre-peak, and post-peak) for weekly rentals of vacation properties along the Outer Banks of North Carolina, we are able to control for changes in the mix of site characteristics selected at different times and estimate the effects of temporal substitution on tradeoffs between other characteristics. Proximity to the ocean was found to be a significant determinant of temporal substitution between the peak and pre-peak seasons with ocean front properties having 1.9 percent to 4.7 percent smaller discounts for preseason rentals relative to other properties.

A specialized survey of Maine households' responses to information about the risks associate d with radon concentrations in their homes and water supplies was use d to evaluate how they form risk perceptions. The findings support a modified form of a Bayesian learning model to describe how individual s used the information to revise their risk perceptions. Moreover, in dividuals who took some mitigating actions reported lower risk percep tions after that action. The overall results are potentially importan t to the use of information programs as policy instruments for risk r eduction because they indicate that new information can affect risk p erceptions in a systematic way.

The presence or absence of seasonal influences on interest rates is an important issue both for policy (Gibson, 1970) and for estimation of monetary relationships (Lombra and Kaufman, 1975). Thus conflict between recent research findings of Barth and Bennett (1975) (hereafter B-B) in this REVIEW and previous work is unsettling.' B-B examined two sets of data: (a) monthly observations on several interest rate series over period 1947-1970, and (b) daily observations on 90-day Treasury bill rate from May 1961 to December 1965. Using monthly dummy variables they concluded that seasonal effects do not appear to be present in interest rates examined. However, daily observations do yield significant seasonal effects for short term Treasury rate. B-B resolve this conflict by suggesting that the process of averaging daily data into monthly arithmetic means reduces variation in interest rate enough that one cannot detect (1975, p. 82). In what follows we reformulate their model in a framework consistent with problems noted by Bagshaw and Phaup (1977) and Bolch and Huang (1977).2 Our results using monthly data from April 1951 to March 1973 indicate statistically significant seasonal influences. Moreover, we demonstrate that averaging a data series will not eliminate seasonal pattern underlying B-B model. Thus B-B explanation of conflict of their results with daily and monthly data is not appropriate.3 The method selected for estimating seasonal components of an economic time series will depend on definition selected for seasonality.4 B-B's findings are relevant to only one such definition and implicitly assume one can model seasonal influences on interest rates independently from modeling of process of change in rates themselves.5 Accordingly discrepancy with past evidence supporting seasonality may be result of these factors. To illustrate this point we have selected an amended model consistent with Barth and Bennett's own suggestions (1975, p. 80, fn. 2) and following Nelson's (1970) analysis of term structure of interest rates. Equation (1) defines our model:

Recent studies at both the theoretical and empirical levels (Feldstein and Rothschild, 1974, Nickell, 1975, Feldstein and Foot, 1971, Eisner, 1972 and Bitros and Kelejian, 1974) have offered accumulating evidence inconsistent with the neoclassical investment theory assumption that replacement investment is a constant fraction of the capital stock.' While this assumption was accepted largely on theoretical grounds, with renewal theory implying in the long run (given capital growing at a constant rate) that replacement investment will approach a constant proportion of capital stock, Feldstein and Rothschild have recently presented a series of contrasting theoretical arguments that suggest that it is likely to be untenable. To date, the most conclusive set of empirical results in support of this view has been Bitros and Kelejian's (hereafter B-K) analysis using annual data for the U.S. electric utility industry for the period 1946 to 1971. Unfortunately, the B-K analysis is subject to several important problems which involve the measurement of capacity and the nature of the electric utility industry.2 The purpose of this paper is to re-examine the B-K results, accounting for each of these issues. Given the importance of the proportionality assumption of neoclassical investment theory (particularly in the development of capital stock and user cost series), a reconsideration of the B-K evidence is warranted. Section II briefly reviews the B-K model, data, and results. The third section outlines each of the problems with their analysis. In section IV we present estimates of an amended version of their model using a relatively homogeneous component of the electric power industry, class A and B privately-owned firms for the period 1946 to 1971. Furthermore, we test this model for specifications errors and compare our findings with those of B-K. The last section summarizes the results.

T HE most frequently used estimating technique for applied economic research has been ordinary least squares (OLS). There are two theoretical justifications for its use. First, the Gauss-Markov theorem suggests that OLS estimators will outperform all other techniques in the class of linear unbiased estimators.1 Secondly, under the assumption that the error terms are normally distributed, OLS estimators can be derived as the maximum likelihood estimates. Frequently when OLS is introduced in elementary texts, the method of minimizing the sum of absolute deviations (MAD) is presented for comparison purposes, but rarely is it given serious consideration for applied uses.) Certainly one reason for such behavior stems from previous evaluations of OLS versus MAD estimators. Asher and Wallace (1963) found that the use of MAD meant one should be prepared to give up considerable efficiency 3 More recently Glahe and Hunt (1970), suggested several estimators derived under the general minimization criterion. In contrast to the Asher-Wallace study, the Glahe-Hunt model was a two-equation linear simultaneous system. Their results show that neither form of absolute deviation estimator outperformed either OLS or two-stage least squares.4 The purpose of this paper is to suggest that in at least one aspect these comparisons have given OLS a differential advantage. That is, both of these studies employed errors for their hypothesized models which were drawn from normal distributions. Consequently the OLS estimators are both maximum likelihood and best linear unbiased estimators (BLUE) under such circumstances. Since recently published works by Zeckhauser and Thompson (1970), Fama (1965) and others have called into question the assumption of normally distributed error terms, attention has begun to shift to other alternatives.5 Blattberg and Sargent (1971) have examined three techniques including both OLS and MAD when the errors are drawn from a stable Paretian distribution. Their findings indicate that the MAD estimator . performs sufficiently well that it deserves further study and elaboration. G Accordingly we have chosen to explore the relative merits of OLS and MAD for a single equation model whose errors are drawn from a double exponential parent distribution. This distribution was chosen because both estimators will exhibit theoretically desirable properties. OLS remains the BLUE estimator, while MAD is the maximum likelihood estimator. Furthermore, this distribution is one member of the power distribution suggested by Zeckhauser and Thompson as an alternative to the normal. This paper is divided into, three sections. The first describes the design of the experiments. Section II presents the empirical results and the last summarizes the primary findings of the paper.

V. Kerry Smith, Raymond B. Palmquist, Paul Jakus, Combining Farrell Frontier and Hedonic Travel Cost Models for Valuing Estuarine Quality, The Review of Economics and Statistics, Vol. 73, No. 4 (Nov., 1991), pp. 694-699

Wage hedonic models are estimated with the Health and Retirement Study to measure the risk-wage tradeoffs (value of statistical lives) for older workers. The analysis explicitly allows for multiple employment states, including retirement, using a multinomial selection model. The results suggest that the oldest and most risk-averse workers require significantly higher, not lower, compensation to accept increases in job-related fatality risks. 2004 President and Fellows of Harvard College and the Massachusetts Institute of Technology. Classification-JEL: I12