Agency Costs,Mispricing, and Ownership Structure

Standard theories of ownership assume insiders ultimately bear all agency costs and therefore act to minimize conflicts of interest. However, overvalued equity can offset these costs and induce listings associated with higher agency costs. We explore this possibility by examining a sample of public listings of Japanese subsidiaries. Subsidiaries in which the parent sells a larger stake and subsidiaries with greater scope for expropriation by the parent firm are more overpriced at listing, and minority shareholders fare poorly after listing as mispricing corrects. Parent firms often repurchase subsidiaries at large discounts to valuations at the time of listing and experience positive abnormal returns when repurchases are announced.     

The out-of-region bias: Distance estimations based on geographic category membership

This research addresses estimations of distance, an important factor in numerous consumer decisions (e.g., store choice, willingness to pay for travel). Our central hypothesis is that when two places are located in the same geographic category, individuals estimate them to be closer to each other than when they are located in different categories, a bias we term ??the out-of-region bias.?? In study 1, we demonstrate that participants are more willing to visit a store located in the city in which they live rather than a store located in a neighboring city because they mistakenly think that a store in their city is closer to home. In studies 2a and b, we show that the out-of-region bias leads consumers to express higher willingness to pay for an airline ticket that involves travel across versus within regions because they inaccurately estimate greater distance between cities that are located in different regions (vs. the same region). Study 2a also demonstrates that the out-of-region bias is ameliorated in the presence of a map, indicating that the bias is a conceptual (vs. perceptual) bias, and study 2b rules out an alternative explanation for our results based on consumers?? tendency to exaggerate north?Csouth distances.     

Monitoring Job Search as an Instrument For Targeting Transfers

Redistribution programs are constrained because those not working may be either unable to work, voluntarily unemployed or involuntarily unemployed. The inability to distinguish among these three cases inhibits the targeting of transfers to those most in need. Enabling the government to monitor whether unemployed individuals are searching for work and accepting any offered jobs increases its ability to redistribute income. We show that these monitoring activities are complementary, and consider how a minimum wage might be a useful adjunct to monitoring contingent tax-transfer policies.     

Criteria used by venture capitalists to evaluate new venture proposals

A questionnaire was administered to one hundred venture capitalists to determine the most important criteria that they use to decide on funding new ventures. Perhaps the most important finding from the study is direct confirmation of the frequently iterated position taken by the venture capital community that above all it is the quality of the entrepreneur that ultimately determines the funding decision. Five of the top ten most important criteria had to do with the entrepreneur's experience or personality. There is no question that irrespective of the horse (product), horse race (market), or odds (financial criteria), it is the jockey (entrepreneur) who fundamentally determines whether the venture capitalist will place a bet at all.The question is if this is the case, then why is so much emphasis placed on the business plan? In a business plan there is generally little to indicate the characteristics of the entrepreneur—it is generally devoted to a detailed discussion of the product/service, the market, and the competition. To us, the implications are obvious—such content is necessary, but not sufficient. The business plan should also show as clearly as possible that the “jockey is fit to ride” —namely, indicate by whatever feasible and credible means possible that the entrepreneur has staying power, has a track record, can react to risk well, and has familiarity with the target market. Failing this, he or she needs to be able to pull together a team that has such characteristics and show that he or she is capable of leading that team.Factor analysis of the results indicate that venture capitalists appear to assess ventures systematically in terms of six categories of risk to be managed. These are: risk of losing the entire investment: risk of being unable to bail out if necessary; risk of failure to implement the venture idea; competitive risk; risk of management failure; and risk of leadership failure.Finally, three clusters of venture capitalists were identified: those who carefully assess the competitive and implementation risks: those who seek easy bail out; and those who deliberately keep as many options open as possible.     

Robust min–max portfolio strategies for rival forecast and risk scenarios

We consider an extension of the Markowitz mean–variance optimization framework to multiple return and risk scenarios. It is well known that asset return forecasts and risk estimates are inherently inaccurate. The method proposed provides a means for considering rival representations of the future. The optimal portfolio is computed, simultaneously with the worst case, to take account of all rival scenarios. This is a min-max strategy which is essentially equivalent to a robust pooling of the scenarios. Robustness is ensured by the noninferiority of min–max. For example, a basic worst-case optimal return is guaranteed in view of multiple return scenarios. If robustness happens to have too high a cost, guided by the min–max pooling, it is also possible to explore other pooling alternatives. A min–max algorithm is used to solve the problem and illustrate the robust character of min–max with return and risk scenarios. We study the properties of the min–max risk–return frontier and compare with the potentially suboptimal worst-case where the investment strategy and the worst case are computed separately.     

Finite sample evidence on the performance of stochastic frontier models using panel data

Most stochastic frontier models have focused on estimating average productive efficiency across all firms. The failure to estimate firm-specific effiicency has been regarded as a major limitation of previous stochastic frontier models. In this paper, we measure firm-level efficiency using panel data, and examine its finite sample distribution over a wide range of the parameter and model space. We also investigate the performance of the stochastic frontier approach using three estimators: maximum likelihood, generalized least squares and dummy variables (or the within estimator). Our results indicate that the performance of the stochastic frontier approach is sensitive to the form of the underlying technology and its complexity. The results appear to be quite stable across estimators. The within estimatoris preferred, however, because of weak assumptions and relative computational ease.The refereeing process of this paper was handled through J. van den Broeck.