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In this article, the author comments on the research paper of John J. Wiorkowski titled "Estimating Volumes of Remaining Fossil Fuel Resources: A Critical Review," published in the September 1981 issue of "Journal of the American Statistical Association." According to the author, the strength of Wiorkowski's paper is in bringing the important problem of petroleum resource estimation to the attention of statisticians. The major weaknesses are in the organization and classification of models and the gaps in coverage. The major issues in resource estimation that Wiorkowski discusses are models for estimating the total oil and gas remaining to be found and a closely related problem, estimating the amount of appreciation in known fields. The problem with the discussion of the models is the lack of a proper classification scheme. Although Wiorkowski mentions the model of researchers E. Barouch and G.M. Kaufman, he fails to note that it is one of a general class of models that are based on the discovery process and fails to emphasize that it is a play model, whereas the others he discusses are used at a higher level of aggregation.

This article estimates the import-price function in the United States using a varying-parameter model. The results show that the short-run nonoil import-price changes have become relatively less responsive to exchange-rate changes than to foreign-cost changes since the generalized floating began in the early 1970s. Concomitantly, the markup has varied significantly, failing when the dollar fell and rising when it rose. Thus “pricing to market” is confirmed even for overall U.S. imports. [ABSTRACT FROM AUTHOR]

A new bias-corrected estimator is developed for dynamic panel model with both fixed and spatial effects. The estimator is asymptotically unbiased, normally distributed, and it has good finite sample properties (low finite sample bias and root mean squared error). Applying the estimator to annual consumption data for the continental U.S. states shows that state consumption growth is not significantly affected by its own (lagged) consumption growth. However, it is affected by lagged consumption growth of nearby states. These results support external habit formation model, which have been used to explain the behavior of U.S. stock retums. [ABSTRACT FROM AUTHOR]

This article uses a new nonparametric, unconditional, hyperbolic order-α quantile estimator to construct a hyperbolic version of the Malmquist index. Unlike traditional nonparametric efficiency estimators, the new estimator is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and 2004. We find that larger banks experienced larger efficiency and productivity gains than small banks, consistent with the presumption that recent changes in regulation and information technology have favored larger banks. [ABSTRACT FROM AUTHOR]

Calibration is commonly used in survey sampling to include auxiliary information at the estimation stage of a population parameter. Calibrating the observation weights on population means (totals) of a set of auxiliary variables implies building weights that when applied to the auxiliaries give exactly their population mean (total). Implicitly, calibration techniques rely on a linear relation between the survey variable and the auxiliary variables. However, when auxiliary information is available for all units in the population, more complex modeling can be handled by means of model calibration; auxiliary variables are used to obtain fitted values of the survey variable for all units in the population, and estimation weights are sought to satisfy calibration constraints on the fitted values population mean, rather than on the auxiliary variables one. In this work we extend model calibration considering more general superpopulation models and use nonparametric methods to obtain the fitted values on which to calibrate. More precisely, we adopt neural network learning and local polynomial smoothing to estimate the functional relationship between the survey variable and the auxiliary variables. Under suitable regularity conditions, the proposed estimators are proven to be design consistent. The moments of the asymptotic distribution are also derived, and a consistent estimator of the variance of each distribution is then proposed. The performance of the proposed estimators for finite-size samples is investigated by means of simulation studies. An application to the assessment of the ecological conditions of streams in the mid-Atlantic highlands in the United States is also carried out. [ABSTRACT FROM AUTHOR]

Examines the performance of maximum likelihood estimation technique to using numerical analysis in the U.S. Utilization of the short-term interest rate of the country as test case; Evaluation of the quality of approximations; Negligible error of the maximum likelihood estimator.

The generalized estimating equations procedure (GEE) widely applied in the analysis of correlated binary data requires that missing data depend only on remote covariates or that they be missing completely at random (MCAR); otherwise GEE regression parameter estimates are biased. A weighted generalized estimating equations (WGEE) approach that accounts for dropouts under the less stringent assumption of missing at random (MAR) through dependence on observed responses gives unbiased estimation of parameters in the model for the marginal means if the dropout mechanism is specified correctly. WGEEs are applied in the estimation of 7-year trends in cigarette smoking in the United States from a cohort of 5,078 black and white young adults. Analysis using WGEE suggests that there was a general decline in cigarette smoking only among white females, whereas the only other subgroup for which smoking declined was white males of the older birth cohort (1955-1962) with college degrees. The results of WGEE are compared to a likelihood-based method valid under MAR that does not require specification of a missing data model. [ABSTRACT FROM AUTHOR]

In this article, the author comments on the research paper of John J. Wiorkowski titled "Estimating Volumes of Remaining Fossil Fuel Resources: A Critical Review," published in the September 1981 issue of "Journal of the American Statistical Association." The author says, Wiorkowski is to be congratulated for a lucid survey of a confused field. His table 4 reporting the projections of researchers L. Bromberg and J.A. Hartigan is misleading, however, because the time for which those projections were made is not included. The estimates were done in 1975 using data up to 1973, and the total recoverable reserves of oil, excluding Alaska and offshore, were then 199 billion barrels, with a 95 percent confidence interval of billion barrels. The author has serious doubts about the adequacy and relevance of the time series data as a basis for such projections. It is apparent that in the continental U.S. most of the new recoverable oil is due not to drilling, which discovers new fields and extends old ones, but to revisions that allow new estimates of the amount of recoverable oil when the price of oil changes, more oil can be recovered because the present technology becomes cost effective.

Poststratification estimation is a technique used in sample surveys to improve efficiency of estimators. Survey weights are adjusted to force the estimated numbers of units in each of a set of estimation cells to be equal to known population totals. The resulting weights are then used in forming estimates of means or totals of variables collected in the survey. For example, in a household survey the estimation cells may be based on age/race/sex categories of individuals, and the known totals may come from the most recent population census. Although the variance of a poststratified estimator can be computed over all possible sample configurations, inferences made conditionally on the achieved sample configuration are desirable. Theory and a simulation study using data from the U.S. Current Population Survey are presented to study both the conditional bias and variance of the poststratified estimator of a total. The linearization, balanced repeated replication, and jackknife variance estimators are also examined to determine whether they appropriately estimate the conditional variance. [ABSTRACT FROM AUTHOR]

Accurate estimation of price indices for residential property is an essential feature of real estate research, especially in view of recent efforts to forecast price trends for the 1990s. In this article, price trends are estimated by using the sales price, assessed value and date of sale for every residential property transaction between independent parties. This assessed value (AV) methodology is compared to the repeat sales (RS) method. This article develops a simple method for correcting the effect of the measurement errors associated with assessed value, We demonstrate that the large samples available with the AV method allow the measurement error problem to be reduced to negligible proportions. Using data on the Hartford, Connecticut metropolitan area, we find that price trends estimated from the AV and RS methods are substantially similar over a seven-year period. But the RS method is inefficient because it uses a relatively small subset of the data. Our results indicate that it remains inefficient when the researcher has a dataset much richer in repeat sales than ours. [ABSTRACT FROM AUTHOR]

This article reviews the methodological issues associated with estimating and testing competitive markets with panel data and applies it to an important new arena, international economics. We investigate differences in housing consumption and male labor supply across households in Germany and the United States with data from the German Socio Economic Panel and the Panel Study of Income Dynamics. Observations are treated as equilibrium outcomes, generated by a set of competitive markets that accommodate varying degrees of integration. After controlling for differences in the sample populations and aggregate shocks, we find that the estimated structural parameters are surprisingly similar across these two countries. [ABSTRACT FROM AUTHOR]

This article examines the impact of macroeconomic variables on the level of income inequality in the United States. The innovation is that we introduce what is known as an index space representation to do so. In an index space representation, income shares are considered as a linear combination of what are known as index functions. An index function is a polynomial function whose order is specified by the given index. The macroeconomic variables affect the function parameters corresponding to each index function. In early years, we have only quintile data, but we can still derive a well-behaved Lorenz curve, Gini coefficient, Theil's entropy measure, standard deviation of the logarithm of the share function, and Atkinson's inequality measure. [ABSTRACT FROM AUTHOR]

This study considers testing for a unit root in a time series characterized by a structural change in its mean. The analysis is in the spirit of Perron (1990a), who showed that the existence of such a shift in a stationary time series biases the usual tests for a unit root toward nonrejection. The approach is, however, different given that we suppose the date of the change to be unknown. The statistic of interest is then the minimal t statistic over all possible breakpoints in regressions similar to those proposed by Perron (1990a). Other related statistics are also discussed. We derive and tabulate the asymptotic distributions of interest. Most of the emphasis, however, is given to the tabulation of finite-sample critical values using simulation experiments. Particular attention is given to the effect, on the finite-sample critical values, of various procedures to select the appropriate order of the estimated autoregressions. We apply the tests to analyze the issue of purchasing power parity between the United States and the United Kingdom and also between the United States and Finland, whose real exchange rates are characterized by apparent shifts in level when using particular price indexes. [ABSTRACT FROM AUTHOR]

In this article, a production-theory-based model of firms' markup behavior is constructed. The theoretical structure is based on variants of generalized Leontief cost and expenditure functions. This framework yields a specification of behavior from which the impacts of both supply and demand shocks on firms' markup behavior can be assessed through elasticities. Adjustment costs on both labor and capital and economies of scale are incorporated. Estimation is carried out using manufacturing data for the United States and Japan from 1960 through 1981. The empirical results suggest that markups for manufacturing firms in both the United States and Japan have increased over time but have somewhat different cyclical characteristics stemming primarily from differential investment behavior, in addition, capacity utilization and especially returns to scale tend to counteract the short-run profit potential from markup behavior so that markups measured assuming constant returns are typically biased downward. Finally, both supply and demand shocks appear to have significant systematic impacts on markups. [ABSTRACT FROM AUTHOR]

Two aspects of reliability—revisions and errors—need separate analysis. Revisions in gross national product (GNP) estimates are large in relation to the size of changes that matter to businesses and policy makers; nevertheless, preliminary estimates convey a tot of information about what the revised estimates will show. Errors in GNP estimates can plausibly be either larger or smaller than revisions. The distinction between gathering errors and adjustment errors helps us understand (a) the absence of any measure of the size of GNP errors and (b) the ways in which national-income statisticians go about reducing errors. These ideas suggest several guidelines for improving GNP estimates. [ABSTRACT FROM AUTHOR]

In this article, we show that the production, aggregation, and estimation theories that lead to a stochastic-coefficients production function are more general than those leading to a fixed-coefficients production function. Estimates of productivity changes implied by these two types of Cobb-Douglas production functions are compared for several U.S. manufacturing sectors for the period 1955-1982. All of the estimates of the stochastic-coefficients Cobb-Douglas function have the right algebraic sign for all industries considered, whereas some of the estimates of its fixed-coefficients counterpart have the wrong sign. [ABSTRACT FROM AUTHOR]