Knowledge that Transforms

Fairly recent data for about one hundred countries indicate that as the average level of schooling increases, educational inequality first increases and, after reaching a peak, starts declining in later phases of educational expansion. The turning point occurs when average schooling is about seven years. The observed empirical generalization, which seems quite robust, appears to have important implications for educational and distributional policies and for research on the linkage between education and income inequality.

This paper develops a two-country micro-theoretic model consistent with the Ricardian equivalence hypothesis. Specifically, tax increases used to retire government debt will not affect private spending or the current account balance. However, increases in government spending, regardless of the means of finance, can be expected to induce a current account deficit. An unconstrained vector autoregression shows some patterns in the recent U.S. data that appear to be inconsistent with the Ricardian equivalence hypothesis. Rigorous testing of the model, however, does not allow the authors to reject the independence of the record federal government budget and current account deficits.

Asymptotic Distributions of Impulse Response Functions and Forecast Error Variance Decompositions of Vector Autoregressive Models, The Review of Economics and Statistics, Vol. 72, No. 1 (Feb., 1990), pp. 116-125

A nonparametric frontier approach is used to calculate the overall, technical, pure technical, allocative, and scale efficiencies for a sample of 322 independent banks. The sample was drawn from the Federal Deposit Insurance Corporation tapes on the Reports of Conditions and Reports of Income (Call Reports) for the year 1986. The results indicate a low level of overall efficiency. The main source of inefficiency is technical in nature, rather than allocative. Separate efficiency frontiers are constructed to test the effect of branching. However, the distributions of efficiency measures for branching and nonbranching banks are not found to be different. Coauthors are Richard Grabowski, Carl Pasurka, and Nanda Rangan.

Many economic researchers have attempted to measure the effect of aggregate market or public policy variables on micro units by merging aggregate data with micro observations by industry, occupation, or geographical location, then using multiple regression or similar statistical models to measure the effect of the aggregate variable on the micro units. The methods are usually based upon the assumption of independent disturbances, which is typically not appropriate for data from populations with grouped structure. Incorrectly using ordinary least squares can lead to standard errors that are seriously biased downward. This note illustrates the danger of spurious regression from this kind of misspecification, using as an example a wage regression estimated on data for individual workers that includes in the specification aggregate regressors for characteristics of geographical states.

A multivariate time series model with time varying conditional variances and covariances, but constant conditional correlations is proposed. In a multivariate regression framework, the model is readily interpreted as an extension of the Seemingly Unrelated Regression (SUR) model allowing for heteroskedasticity. Parameterizing each of the conditional variances as a univariate Generalized Autoregressive Conditional Heteroskedastic (GARCH) process, the descriptive validity of the model is illustrated for a set of five nominal European U.S. dollar exchange rates following the inception of the European Monetary System (EMS). When compared to the pre- EMS free float period, the comovements between the currenciess are found to be significantly higher over the later period.