If You Are So Smart,Why Aren't You an Entrepreneur? Returns to Cognitive and Social Ability: Entrepreneurs Versus Employees

How valuable are cognitive and social abilities for entrepreneurs’ relative to employees’ earnings? We answer three questions: (1) To what extent does a composite measure of ability affect an entrepreneur's earnings relative to wages earned by employees? (2) Do different cognitive abilities (e.g., math ability, language, or verbal ability) and social ability affect earnings of entrepreneurs and employees differently?, and (3) Does the balance in these measured ability levels affect an individual's earnings? Our (difference‐of‐difference) estimates of the returns to ability for spells in entrepreneurship versus wage employment account for selectivity into entrepreneurial positions insofar as they are determined by fixed individual characteristics. Our robust results provide the following answers to the three questions: General ability has a stronger impact on entrepreneurial incomes than on wages. Moreover, entrepreneurs and employees benefit from different sets of specific abilities: verbal and clerical abilities have a stronger impact on wages, whereas mathematical, social, and technical ability are more valuable for entrepreneurs. The balance in the various kinds of ability also generates a higher income, but only for entrepreneurs: This finding supports Lazear's Jack‐of‐all‐Trades theory.     

The effect of estimation method and sample size in multilevel structural equation modeling

Multilevel structural equation modeling (multilevel SEM) has become an established method to analyze multilevel multivariate data. The first useful estimation method was the pseudobalanced method. This method is approximate because it assumes that all groups have the same size, and ignores unbalance when it exists. In addition, full information maximum likelihood (ML) estimation is now available, which is often combined with robust chi‐squares and standard errors to accommodate unmodeled heterogeneity (MLR). In addition, diagonally weighted least squares (DWLS) methods have become available as estimation methods. This article compares the pseudobalanced estimation method, ML(R), and two DWLS methods by simulating a multilevel factor model with unbalanced data. The simulations included different sample sizes at the individual and group levels and different intraclass correlation (ICC). The within‐group part of the model posed no problems. In the between part of the model, the different ICC sizes had no effect. There is a clear interaction effect between number of groups and estimation method. ML reaches unbiasedness fastest, then the two DWLS methods, then MLR, and then the pseudobalanced method (which needs more than 200 groups). We conclude that both ML(R) and DWLS are genuine improvements on the pseudobalanced approximation. With small sample sizes, the robust methods are not recommended.     

Earnings functions: Testing for the demand side

To analyze labor market phenomena, one may simultaneously grade workers (by education) and jobs (by level of difficulty and complexity). Human capital theory predicts earnings based on only worker quality. Thurow's version of a segmented labor market theory predicts that only the job level is relevant, and the assignment theory predicts that both variables are relevant. Using three different data sets for The Netherlands, testing demonstrates convincingly the superiority of the assignment theory.     

On compensation for risk aversion and skewness affection in wages

This paper presents extensive empirical testing of the hypothesis that greater post-schooling earnings risk requires higher expected returns. Expanding on this notion, on the basis of utility theory, we predict that workers not only care about risk but also about the skewness in the distribution of the compensation paid: workers exhibit risk aversion and skewness affection. To test these hypotheses, this paper carefully develops various measures of risk and skewness by occupational/educational classification of the worker and finds supportive evidence: for men, wages rise with occupational earnings variance and decrease with skewness, for women only the negative effect of skewness is significant.     

Cross-sectional learning and short-run persistence in mutual fund performance

Using monthly return data of more than 6400 US equity mutual funds we investigate short-run performance persistence over the period 1984–2003. We sort funds into rank portfolios based on past performance, and evaluate the portfolios’ out-of-sample performance. To cope with short ranking periods, we employ an empirical Bayes approach to measure past performance more efficiently. Our main finding is that when funds are sorted into decile portfolios based on 12-month ranking periods, the top decile of funds earns a statistically significant, abnormal return of 0.26 percent per month. This effect persists beyond load fees, and is mainly concentrated in relatively young, small cap/growth funds.     

“Hot Hands” in bond funds

We investigate persistence in the relative performance of 3549 bond mutual funds from 1990 to 2003. We show that bond funds that display strong (weak) performance over a past period continue to do so in future periods. The out-of-sample difference in risk-adjusted return between the top and bottom decile of funds ranked on past alpha exceeds 3.5 percent per year. We demonstrate that a strategy based on past fund returns earns an economically and statistically significant abnormal return, suggesting that bond fund investors can exploit the observed persistence. Our results are robust to a wide range of model specifications and bootstrapped test statistics.     

Turkish Clothing in Amsterdam: The Rise and Fall of a Perfectly Competitive Labour Market

While the Dutch textile industry declined rapidly, Turkish entrepreneurs created a growing industry for fashion goods with highly flexible demand in an informal sector that was initially tolerated by the authorities and attracted many undocumented immigrants. It led to the unusual spectacle of a labour market visibly in perfect competition; predictions of that model are clearly supported. Crackdown of the authorities led to the demise of the sector: production, capital, and labour all proved internationally mobile.     

Self-selection bias in estimated wage premiums for earnings risk

This note develops a simple occupational choice model to examine three types of selection biases that may occur in empirically estimating the premium for uncertain wages. Individuals may select themselves into risky (wage-uncertain) jobs because they have (1) lower risk aversion, or (2) lower income risks, or (3) higher individual ability. We show that (1) gives no bias, (2) biases the OLS estimate of the risk-premium in a wage regression upward, and (3) yields a bias that analytically may be positive or negative, but empirically is more likely to be negative if our occupational choice model is correct.