Journal of Economic and Social Measurement

The X-11 Model has been suggested as a potential analytical procedure for auditing theory and practice. The Model statistically decomposes a time series of data into three components (trend-cycle, seasonal, and irregular), each of which possesses an underlying economic interpretation. This paper applies the X-11 Model to actual monthly financial data for ten firms in an audit planning context and analyzes the output obtained from the Model using the firm and ledger effects' methodologies. Expected econometric behaviors for the firm and ledger effects are hypothesized, and the results of the econometric analysis are compared with those expected behaviors.

The analysis of the firm effect indicates that the substantial components are: the seasonal component for utilities, the trend-cycle component for financial institutions, the irregular component for the extractive industry, and both the seasonal and irregular components for manufacturing and retail companies. In addition, the analysis of the ledger effect reveals that an increasing volatility of the irregular component for specific income statement accounts is most prevalent for the sample firms.

The Statistics of Income Panel of Individual Returns is a simple random sample of tax returns that is maintained by the University of Michigan as a part of the Ernst and Young Tax Research Database. Sampling errors during the period 1982–1984 resulted in the inclusion of 66 spurious returns in the Panel. These spurious returns were selected for the Individual Tax Model files, which are stratified random samples. Traditional estimators assume simple random sampling, so inferences about population parameters based on Panel statistics are biased if the dependent variable is related to the stratification. This paper describes the sampling procedures and the impact these spurious returns have on the panel and suggests a weighting procedure that allows the retention of these returns in sample statistics.

The availability of direct measurement of job training provides an opportunity to test directly theories dealing with the relationship among training, schooling, wage growth, and labor mobility. Since most training is informal, obtaining a good estimate is complicated but crucial. This paper analyzes and compares the training information provided by two data sets: The Panel Study of Income Dynamics and the DOT. The analysis shows that the PSID reports only partially training obtained via vocational education and experience in other jobs. The average reported training in the DOT is, therefore, higher, but the correlation between the two measures is high.

In this paper we have delineated a new approach to measuring the(in)equality-efficiency trade-off in an economy. The approach utilizes aggregate historical data, and permits values of the trade-off to be estimated ex post for each policy variable in any chosen bundle, which have been in operation during the period and could have redistributional implications. We do find evidence of a trade-off for several policy variables. It is not by any means clear that the more sophisticated and informationally demanding micro-based approaches to evaluating the trade-off, which economists have devised, can be as revealing.

In this paper we discuss the issue of whether and how to value government and employer provided in-kind medical benefits in determining who is poor. Consideration of this issue leads to the suggestion that the fungible portion of medical care transfers should be included in the income of the poor as they constitute a significant percentage of their resources available for the purchase of goods and services. Fungible medical care transfers are defined as third party payments for medical benefits except those for hospital and nursing home care, on the premise that the latter are for nonroutine medical services that do not increase an individual's well-being. Estimates of the fungible portion of government and private in-kind medical benefits are developed from Health Care Financing Administration data that indicate that of the two, the former is less fungible.