Steven P. Peterson

Factors affecting student retention probabilities: A case study

A comprehensive model of retention based on Tinto’s goal commitment and institutional commitment combined with financial considerations is evaluated for the case of an urban public university enrolling large numbers of non-traditional students. The model was evaluated using data from all freshman and sophomore students over the years 1989–1992. White and minority students were also analyzed separately to determine if there were different sensitivities to various enrollment factors. Academic and social integration factors were found to be the most significant factors in persistence in these years. Financial considerations were of less importance in the persistence decision.

An Analysis of Student Enrollment Demand.

Abstract This paper analyzes the sensitivity of white and black enrollment yields to changes in real net cost at a large (21,000), urban, public university over a six year time period (1988–1993). Estimation is by GLS random effects and controls for a number of financial, academic, and qualitative variables. The major conclusion is that, while enrollment yields are generally insensitive to changes in net cost, sensitivity for blacks is roughly two-thirds higher than for whites. This would suggest that since minority students have been responding positively to financial aid, cuts in grant funding by state legislators or Congress may restrict minority access to higher education in the future. [ JEL I21]

Investor behavior and the persistence of poorly-performing mutual funds

Abstract Recent studies tentatively suggest some mutual funds have near-term, persistent positive performance, but reinforce earlier findings that other funds have long-term, persistent negative performance. In this paper we ask how consistently underperforming mutual funds are able to persist nevertheless. We compare two models: One model incorporates the assumption that investors choose funds on the basis of past risk-adjusted returns. The other model, motivated by the representativeness heuristic, assumes investors react to recent returns without considering the predictive validity of returns. Our analysis of a sample of no-load growth funds supports a model of investor behavior combining two extremes: when choosing among funds investors respond to returns ignoring differences in systematic risk and expenses, but upon choosing a fund they stick fast forsaking the sensitivity to returns displayed in evaluating funds.

Covariance Misspecification in Asset Allocation

Series of returns to broad asset classes often possess histories of unequal length and have been subject to smoothing. Estimates of covariances are generally based on the common, although shorter, series length, and covariances for smoothed series are necessarily biased downward. These characteristics pose serious problems that can generate suboptimal and misleading allocations among asset classes. The article discusses elements of the underlying theory in proposing an informationally efficient covariance estimator. The estimator is then compared with conventional covariance estimates in an empirical application. Covariance estimates are found to be sensitive to both truncated estimates involving shorter series and the effects of smoothing. Problems related to estimation of mean returns are well known, but problems related to covariance estimation are thought to be benign. In applications, however, solutions to quadratic optimization problems often fail because of ill-conditioned covariance matrices. This problem is especially relevant for the search for optimal allocations among broad asset classes whose covariance estimates must first circumvent a number of obstacles—in particular, return series of unequal length and return smoothing. We find that cross-moments estimated on truncated return series (because of different series lengths) are informationally inefficient and that smoothing biases volatilities downward. In both cases, covariance estimates can produce seriously misleading portfolio allocations. Drawing together the theoretical literature on these issues, we propose a procedure for covariance estimation that is informationally rich, more efficient than in traditional methods, and free of the biases associated with naive estimates. Empirically, we compare this improved estimator with the naive estimator in applications to allocations for asset classes typically considered by large institutional investors. We use a framework from the literature that maximizes the informational efficiency in constructing covariance estimates for series of different length. We extend this framework to provide an algorithm for updating covariances sequentially, and we include a formal process that addresses some common types of return smoothing. We also analyze relative portfolio performance in a Monte Carlo experiment that isolated and measured the allocative inefficiency and higher risk common to portfolios based on naive covariance estimates for truncated and smoothed series. Using historical returns to seven asset classes and applying the corrections for truncation and smoothing, we first estimated a corrected covariance matrix, which we contrasted to the corresponding naive covariances. We then addressed allocative inefficiency in the Monte Carlo experiment, in which we used this corrected covariance matrix with a corresponding vector of asset-class returns to generate repeated samples of quarterly returns. We then estimated corrected and naive covariance matrices and mean returns for each sample, and we used these data as arguments in separate mean–variance-optimization problems to solve for the optimal portfolio. Because the “true” returns and covariances that generated these samples were known a priori, these simulated portfolios could be compared with the “full-information” portfolio. On the one hand, we found that for N = 10,000 repetitions, the average quarterly misallocation (measured as deviation in asset-class weights from the true weight vector) for the naive portfolio was 28.66 percent. And a Wilcoxon test easily rejected the null hypothesis that the weight distributions for the full-information and naive estimates are equal. On the other hand, the corrected covariances reduced misallocation by 8.14 percentage points per quarter, and we failed to reject the null hypothesis that the corrected and full-information portfolio weight distributions share the same median. Moreover, the median quarterly naive return underperformed both the full-information and corrected median quarterly returns. The naive portfolio’s tendency to take on extreme positions could be clearly seen in this portfolio’s return volatility (2.51 percent) per quarter relative to the volatility of the full-information portfolio (2.17 percent) and corrected portfolio (2.22 percent). Finally, a long-only constraint exacerbated underperformance of the naive portfolio; it forced approximately 13 percent more extreme (zero-weight) positions than did the full-information portfolio, whereas the corrected covariance portfolio produced only 5 percent more extreme positions. In general, naive covariance estimates generate portfolios with lower returns and higher risks than corrected estimates, and naive covariance estimates underestimate true value at risk.

The rationality of expectations: the blomqvist experiment reconsidered

Abstract This paper raises some methodological and empirical criticisms of a recent experimental study of the Rational Expectations Hypothesis (REH) by Blomqvist (1989, published in this journal). With respect to experimental methodology, the reward structure employed leaves open the question of subject motivation. With regard to the empirical findings we conclude the following: (1) Tests of unbiasedness may yield biased estimators due to the distribution of the forecasting objective. (2) Using aggregated data is potentially confounding in that individual rationality may be obscured. (3) Contrary to Blomqvists conclusions, we find strong support for the REH based upon the estimates of a rational learning model.

Some experimental evidence on the efficiency of dividend signaling in resolving information asymmetries

Abstract An experimental market has managers of two firms making investment and dividend decisions to maximize firm value. Dividends are paid to shareholders who trade in the shares of both firms. In a separate control group, dividend and investment decisions are made exogenously to maximize the informational content of the dividend signal. Compared to the control groups (i) dividend surprises do not reflect the information contained in earnings shocks; (ii) firms with low rates of return on investment underinvest, losing earnings power, (iii) managers are unsuccessful in using dividend signals to inflate share prices and hence payoffs.

An examination of the issue of form versus substance in an experimental asset market: A pilot study

Abstract A series of experiments are conducted in a security asset market that comprises two long-lived securities with identical pre-tax fundamental values but different payout structures. One security pays taxable dividends every period while the other security accumulates earnings to be distributed at random intervals. The results of the experiments indicate that traders ignore tax considerations and pay a premium for the security distributing dividends every period. But this premium is negatively correlated with the size of the accumulated earnings of the other firm. Thus, it appears that the market confuses the issues of form and substance, and that form appears to matter. Investors segregate the small steady dividends with either a capital gain or capital loss associated with the sale of the security. As the accumulated earnings of the other firm grow, investors preferences shift; they now integrate the relatively large accumulated earnings with the potential capital loss associated with this security.