Multivariate regression models for panel data

The paper examines the relationship between heterogeneity bias and strict exogeneity in a distributed lag regression of y on x. The relationship is very strong when x is continuous, weaker when x is discrete, and non-existent as the order of the distributed lag becomes infinite. The individual specific random variables introduce nonlinearity and heteroskedasticity; so the paper provides an appropriate framework for the estimation of multivariate linear predictors. Restrictions are imposed using a minimum distance estimator. It is generally more efficient than the conventional estimators such as quasi-maximum likelihood. There are computationally simple generalizations of two- and three-stage least squares that achieve this efficiency gain. Some of these ideas are illustrated using the sample of Young Men in the National Longitudinal Survey. The paper reports regressions on the leads and lags of variables measuring union coverage, SMSA, and region. The results indicate that the leads and lags could have been generated just by a random intercept. This gives some support for analysis of covariance type estimates; these estimates indicate a substantial heterogeneity bias in the union, SMSA, and region coefficients.     

Retesting positive results in screening for colorectal cancer: a marginal analysis

In the context of screening for colorectal cancer, Neuhauser and Lewecki (1975) have questioned the wisdom of the use of repeated guaiac-based stool tests, arguing that the cost of investigating an asymptomatic population rapidly escalates out of all proportion to the incremental change in the number of cancers detected. This paper addresses a broadly similar problem but makes use of contemporary clinical data from the Nottingham screening trial. Three practicble investigation regimes are evaluated, in terms of the number of cancers detected and the total costs of investigation. It is concluded that, when compared with a regime of direct internal investigation, the appropriate combination of proliminarty guaiac-based stool tests can lead to substantial resource savings at only a small cost in terms of the number of cancers detected.     

Option volume and stock price behavior: Some evidence from the Chicago board options exchange

This study examines the relationship between selected Chicago Board Options Exchange option volume and underlying stock prices using intraday data for the period January 3, 1989 to January 31, 1989. The data were prefiltered and aggregated into 15-minute intervals. Causality tests were performed using Granger's method. The test results indicate that the option volume-stock price relationship is largely characterized by feedback, with option volume causing stock price changes and vice versa. The evidence also suggests that the relationship only persists for very short time periods, with little or no opportunity for market participants to devise profitable trading strategies utilizing one market's information in the other market. Data for the study were generously provided by Itzhak Krinsky and Jason Lee of the DeGroote School.     

Education,income, and ability revisited

The paper examines two approaches to the omitted variable problem. Both of them try to correct for the omitted variable bias by specifying several equations in which the unobservable appears. The first approach assumes that the common left out variable is the only thing connecting the residuals from these equations, making it possible to extract this common factor and control for it. The second approach relies on building a model of the unobservable, by specifying observable variables which are causally related to it. A combination of these two methods is applied to the 1964 CPS-NORC veterans sample in order to evaluate the bias in income- schooling regressions caused by the omission of an unobservable initial ‘ability’ variable.