Auditing, Internal control judgement, Meta Analysis

This article uses very detailed information on graduates of the University of Michigan Law School to examine male-female pay differences in that population. Men and women in this population have virtually identical human capital on graduation from law school, allowing us to examine carefully the different impact of children and work history on men's and women's careers and earnings. Taking time from work in order to care for children reduces wages significantly, but a rich set of controls, including childcare, work history, school performance, and job setting measures, still leave one-fourth to one-third of the earnings gap unexplained.

Garbade, Kenneth, Methods of Examining the Stability of Regression Coefficients, Journal of the American Statistical Association 72 (Mar. 1977), 54-63. Godfrey, L. G., Against General Autoregressive and Moving Average Error Models when the Regressors Include Lagged Dependent Variables, Econometrica 46 (Sept. 1978), 1293-1301. Harvey, Andrew C., and Garry D. A. Phillips, for Stochastic Parameters in Regression S.S.R.C. supported project on Testing for Specification Error in Econometric Models, Working Paper No. 1, University of Kent at Cantebury (1976). _ Maximum Likelihood Estimation of Regression Models with Autoregressive-Moving Average Disturbances, Biometrika 66 (1979), 49-58. Johnson, N. L., and S. Kotz, Distribution in Statistics: Continuous Multivariate Distributions (New York: Wiley, 1972). LaMotte, R., and A. McWhorter, Jr., An Exact Test for the Presence of Random Walk Coefficients in a Linear Regression Model, Journal of the American Statistical Association 73 (Dec. 1978), 816-819. Mizon, Grayham E., and David F. Hendry, An Empirical Application and Monte Carlo Analysis of of Dynamic Specification, Review of Economic Studies 47 (Jan. 1980), 21-46. Pagan, Adrian R., Some Identification and Estimation Results for Regression Models with Stochastically Varying Coefficients, Journal of Econometrics 13 (1980), 341-363. Pagan, Adrian R., and K. Tanaka, A Further Test for Assessing the Stability of Regression Coefficients, Australian National University, unpublished manuscript (1979). Quandt, Richard E., Tests of the Hypothesis that a Linear Regression System Obeys Two Separate Regimes, Journal of the American Statistical Association 55 (Dec. 1960), 873-880. Rosenberg, Barr, The Analysis of a Cross-Section of Time Series by Stochastically Convergent Parameter Regression, Annals of Economic and Social Measurement 2 (1973), 399-428. Watson, Mark W., A Test for Regression Coefficient Stability when a Parameter Is Identified only Under the Alternative, H.I.E.R. Discussion Paper 906 (1982). , Applications of Kalman Filter Models in Econometrics, Ph.D. Dissertation, University of California at San Diego (1980). Watson, Mark W., and Robert F. Engle, Alternative Algorithms for the Estimation of Dynamic Factor, MIMIC, and Varying Coefficient Regression Models, Journal of Econometrics 23 (Dec. 1983), 385-400.

ABSTRACT The behavior of time‐weighted bid–ask spreads over the trading day are examined. The plot of minute‐by‐minute spreads versus time of day has a crude reverse J ‐shaped pattern. Schwartz identifies four determinants of spreads: activity, risk, information, and competition. Using a linear regression model, a significant relationship between these same factors and intraday spreads is demonstrated, but dummy variables for time of day have a reverse J ‐shape. For given values of the activity, risk, information and competition measures, spreads are higher at the beginning and end of the day relative to the interior period.

ABSTRACT This paper tests the effectiveness of techniques proposed by: Scholes‐Williams; Dimson; Fowler, Rorke, and Jog; and Cohen, Hawawini, Maier, Schwartz, and Whitcomb to control for bias in beta estimates from thin trading and price adjustment delays. Each technique produces beta estimates that reduce the amount of this bias, but the amount of reduction in the best case is only 29%.

Abstract An intermarket sweep order (ISO) is a limit order that automatically executes in a designated market center even if another market center is publishing a better quotation. An investor submitting an ISO must satisfy order protection rules by concurrently submitting orders to the markets with better prices. We find that ISOs represent 46% of trades and 41% of volume in our sample. ISO trades have a significantly larger information share despite their small trade size relative to non-ISO trades. Post trade return analysis suggests that informed institutions are the main users of ISO trades.