This article examines the effects of unemployment compensation finance in a labor market in which firms pay efficiency wages. Two self‐financing unemployment compensation systems are compared: one in which benefits are financed by a proportional payroll tax and another in which experience rating is introduced by taxing firms in proportion to their separations. We find that experience rating leads to less unemployment, less shirking, and higher output.

In his Presidential Address five years ago, Zvi Griliches (1994) called attention to the severe difficulties that beset current attempts to measure the growth of labor productivity in the American economy. Because of these difficulties, it is likely that the true rate of economic growth is substantially underestimated. The root of the problem is the difficulty in measuring output in the service sector which now represents two-thirds of the economy. In such sectors as health care and information services, the contribution to gross domestic product (GDP) is measured by inputs rather than outputs, a procedure that makes it impossible to gauge accurately improvements in the quality of output. Thus, in the case of computers, which are transforming American society, economists have been unable, so far, to find a measurable contribution of computers to the rise in labor productivity—an astonishing paradox. I want to follow up on this problem of mismeasurements. My thesis is that the profession

Scott W. Barnhart, Robert McNown, Myles S. Wallace, Non-Informative Tests of the Unbiased Forward Exchange Rate, The Journal of Financial and Quantitative Analysis, Vol. 34, No. 2 (Jun., 1999), pp. 265-291

Earnings Patterns, Increasing Earnings, Valuation

Nonlinear modeling has become popular in applied macroeconomics. Successful attempts include Beaudry and Koop's CDR (current depth of the recession) model of real GNP, and various STAR (smooth transition autoregression) models of industrial production. However, these models have not been directly compared. We compare CDR and STAR models of U.S. real GNP and industrial production. We find (i) within sample, the CDR model fits slightly better than the STAR model; (ii) out of sample, the CDR model forecasts better than the STAR model; and (iii) the CDR model generates very different dynamics than the STAR model.

Many Japanese firms reduced dependence on banks following financial deregulation in the 1980s. The financial architecture of Japanese firms after liberalization provides an opportunity to investigate the choice of financing with public bonds versus monitored bank loans. Examination of accounting and stock price data for a sample of Japanese firms in the late 1980s suggests that debt structure is related to variables that serve as proxies for agency costs of debt. In particular, we find that the proportion of bond debt is inversely related to growth opportunities, while the proportion of bank debt is positively related to growth opportunities.

We simulate standard tests of performance persistence using alternative return-generating processes, survival criteria, and test methodologies. When survival depends on performance over several periods, survivorship bias induces spurious reversals, despite the presence of cross-sectional heteroskedasticity in performance. Look-ahead biased methodologies and missing final returns typical of U.S. mutual fund datasets can also materially affect persistence measures. Our results reinforce previous findings that U.S. mutual fund performance is truly persistent. When fund performance is truly persistent, fund attrition affects persistence measures, even when the sample includes all nonsurvivor returns. We also examine the specification and power of the various persistence tests.

This paper examines the relation between earnings and operating cash flow to derive and test an indicator of financial statement fraud. Accrual measurement concepts indicate that financial statement fraud should be associated with high levels of earnings relative to operating cash flow. We demonstrate that the excess of earnings over operating cash flow is extreme in most fraud cases in years immediately prior to the fraud discovery based on a sample of 56 fraud cases from 1978 to 1991. We compare the distribution of the earnings minus operating cash flow variable for fraud firms with that for a sample of 60,453 firm‐years for firms listed on COMPUSTAT. We test a logistic regression model in which the discovery/nondiscovery of fraud is the dependent variable, and earnings minus operating cash flow is the explanatory variable. Other control variables are included in the model based on prior studies. Results are consistent with expectations derived from accrual measurement theory. We then examine the predictive ability of the model using our sample of fraud firms and a sample of nonfraud firms in the same four‐digit SIC code industries. Observations for the fraud firms are for the fiscal year prior to the discovery of fraud. Observations for the nonfraud firms are for the same fiscal years as the fraud firms in the same industries. The predictive ability of the model, including the excess of earnings over operating cash flow, is substantially higher than the predictive ability of the model omitting this variable. We conclude that the earnings‐operating cash flow relation provides important information for those interested in identifying financial statement fraud, especially when considered in conjunction with other factors associated with fraud risk.