Knowledge that Transforms

We study the problem of measuring the uncertainty of computable general equilibrium (CGE) (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Baycsian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show how they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

The interpretation of seasonality in terms of economic behavior depends on the form of the econometric time-series model that allows for a description of seasonality. Popular models often assume either approximate deterministic seasonality (cf. Miron (1996)) or stochastic trend seasonality (cf. Hylleberg (1994)). Inference from an inappropriate model can be shown to be invalid. Since much graphical evidence clearly suggests that seasonal fluctuations are not constant over time, we investigate whether the finding of seasonal unit roots can be due to neglected mean shifts. We provide relevant asymptotic theory and critical values for various test statistics. For a set of real gross domestic product series we find that much evidence for seasonal unit roots tends to disappear when a shift in the seasonal means is allowed. When we incorporate deterministic mean shifts in the deterministic seasonality model, we find that qualitative results on the presence of the so-called seasonal cycle documented in, for example, Miron and Beaulieu (1996) are robust.

We reformulate the “Hotelling valuation principle” to take into account the special production characteristics of hard-rock minerals. The data requirements of the revised model are still parsimonious, but the resultant valuations are some 40% below those produced by the Hotelling valuation principle. Our valuation equations are also “user-friendly,” allowing the valuer to specify price and cost expectations that need not comply with the Hotelling rule. Empirically, our model provides estimates of market value for producing mineral properties that are more accurate than those produced by the Hotelling valuation principle.

In 1978 BLS adopted an estimator for U.S. CPI component indexes that incorporates scientific samples of outlets and varieties and that allows the calculation of reliable standard errors. Consumer substitution of outlets and varieties offering better values could cause bias in these indexes. A more important source of bias is, however, a tendency to give excessive weight to items whose initial price is temporarily low. The empirical evidence is striking. Average price series and matched food CPIs grew at almost the same rate before 1978, but between 1980 and 1992 the CPIs average about 1.4% per year more growth. For unleaded gasoline, the discrepancy averages 0.8% per year. © 1998 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

We generalize the Franke-Härdle (1992) spectral-density bootstrap to the multivariate case. The extension is nontrivial and facilitates use of the Franke-Härdle bootstrap in frequency-domain econometric work, which often centers on crossvariable dynamic interactions. We document the bootstrap's good finite-sample performance in a small Monte Carlo experiment, and we conclude by highlighting key directions for future research.

Bayesian inference and model comparisons are easily performed quite accurately using Gibbs sampling, even if (1) the likelihood is analytically intractable and (2) nonstandard prior probability density functions (pdfs) are required. In this study Bayesian model comparisons are performed among five competing theories of endogenous protection. Tariff and nontariff barrier data from 1983 between the United States and five OECD partner countries-Japan, France, Germany, Italy, and the United Kingdom-are used in the analysis. Posterior odds based on two priors show special-interest models to be more likely than other models in determining U.S. protection.

Using survey data on consumer product purchases, this paper introduces an approach to estimate jointly individual utility functions and risk perceptions implied by their decisions. The behavioral risk beliefs reflected in consumers' risky decisions differ from the stated probabilities given to them in the survey. These results are not consistent with a Bayesian learning model in which the information respondents utilize is restricted to what the survey presents. The results are, however, potentially consistent with models in which prior risk information is influential or models in which people do not act in a fully rational manner.

The paper is concerned with developing a production theory for the case when some inputs have nonlinear prices because the price depends on endogenous quality. This involves extending the notion of a cost function to the case where nonlinear prices are parameters of costs. After developing the appropriate theory, we apply our results to the case of coal-fired electric power generation where fuel quality depends on sulfur and ash impurities. Environmental regulations induce a negative value on sulfur whereas ash impurities degrade performance and thus reduce production possibilities. A number of empirical results emerge, including significant rates of technological change that are sulfur and ash saving though capital using. This change may explain in part the recent drop in the price of sulfur allowances in the United States.

General equilibrium models of international fluctuations that assume complete asset markets predict that consumption will be highly correlated across countries, while the data display correlations that are rather low. It has become common to characterize this empirical regularity by noting that cross-country consumption correlations tend to be lower than corresponding output correlations. This note reconsiders that charac-terization and demonstrates that it is not particularly robust. It also documents a related regularity that is more pervasive: Consumption fluctuations are more highly correlated with domestic production than with world output. This provides an alternative standard for evaluating models of international fluctuations.