Valuation with share repurchases and personal taxes

We derive a consistent valuation approach that integrates the interdependent effects of cash dividends, share repurchases and active debt management while considering personal taxes. The valuation approach is based on the assumption that a predetermined proportion of the flow to equity is used for share repurchases instead of cash dividends. Additionally, we examine the effects of share repurchases on the cost of equity by deriving appropriate adjustment formulae. Furthermore, we run simulations to investigate the valuation differences caused by the distribution of excess cash via cash dividends or share repurchases. The results show that share repurchases have a significant positive effect on equity market value.     

A Leland model for delta hedging in central risk books

Using a tractable extension of the model of Leland (1985), we study how a delta-hedging strategy can realistically be implemented using market and limit orders in a centralized, automated market-making desk that integrates trading and liquidity provision for both options and their underlyings. In the continuous-time limit, the optimal limit-order exposure can be computed explicitly by a pointwise maximization. It is determined by the relative magnitudes of adverse selection, bid–ask spreads, and volatilities. The corresponding option price—from which the option can be replicated using market and limit orders—is characterized via a nonlinear PDE. Our results highlight the benefit of tactical liquidity provision for contrarian trading strategies, even for a trading desk that is not a competitive market maker. More generally, the paper also showcases how reduced-form models are competitive with “brute force” numerical approaches to market microstructure. Both the estimation of microstructure parameters and the simulation of the optimal trading strategy are made concrete and reconciled with real-life high frequency data.     

Race-based affirmative action for higher education in Brazil: Impact assessment on performance,time, and delay in completion*

This paper aims to investigate the impact of race-based affirmative action for higher education in Brazil, through the effects of applying under a quota versus the open system for Black, Brown, and Indigenous people, on academic performance, time, and delay in completion. The data used were obtained by the survey of the National Student Performance Examination (Enade) from 2016 to 2018. Through the propensity score matching methodologies, entropy balancing, empirical quantile regression strategy, and Lewbel method, a small statistically significant negative impact on students' performance was observed. Significant effects on time and delay in completion were not found in most of the estimators used. We also observed that older students and students who are male, lack, or Indigenous are more likely to choose to enter via racial quotas, while students who live with their parents or spouse and students who have some source of income are less likely to participate in the policy.     

Comparing Internet and phone survey mode effects across countries and research contexts*

We compare Internet and telephone survey responses across 27 European Union nations and two research contexts: one, a choice experiment of willingness to pay to avoid power outages, and the other, a public acceptance of energy infrastructure question. The various forms of survey mode effects and the challenges of survey mode choice are documented and developed in the context of statistical theory and an application to an economics survey. We find evidence that survey mode effects vary across research contexts, and to a lesser extent, across nations. We suggest that the degree of measurement bias may be varying between research contexts, for example based on the availability of a perceived socially correct response within a given context. Future survey-based research should evaluate the choice of survey mode in a context- and region-specific manner.     

An analysis of Fundeb's contribution to the quality of public education in Brazilian municipalities

This study analyzed the effect of the Fund for the Maintenance and Development of Basic Education and for the Appreciation of Education Professionals (Fundeb) on the National System of Basic Education Assessment (Saeb) results of Brazilian municipalities by estimating a spatial panel model with information from 2007 and 2017, which include the 10 years of the fund's implementation. The results indicated that the 10% increase in the Fundeb amount per student received by the municipality raised the Saeb score by approximately one point. Furthermore, the increase in the fund's value in neighboring municipalities contributed to increasing the municipality's Saeb score by approximately three points. These results are evidence in favor of the hypothesis that Fundeb has encouraged the management and adoption of good practices in municipal education, which influence the decisions and behavior of the neighboring municipalities’ managers to also improve their practices and results.     

Hours risk and wage risk: repercussions over the life cycle*

We decompose earnings risk into contributions from hours and wage shocks. To distinguish between hours shocks, modeled as innovations to the marginal disutility of work, and labor supply reactions to wage shocks, we formulate a life-cycle model of consumption and labor supply. For estimation, we use data on married American men from the Panel Study of Income Dynamics. Permanent wage shocks explain 31 percent of total risk, permanent hours shocks 21 percent. Progressive taxation attenuates cross-sectional earnings risk, but its life-cycle insurance impact is much smaller. At the mean, a one-standard-deviation hours shock raises lifetime income by 11 percent, a wage shock by 13 percent.     

Martingale Schrödinger bridges and optimal semistatic portfolios

Finance and Stochastics - In a two-period financial market where a stock is traded dynamically and European options at maturity are traded statically, we study the so-called martingale...     

Linguistic cues of chief executive officer personality and its effect on performance

Chief Executive Officer (CEO) personality belongs to the most important constructs for business practice and research, but its measurement remains a major obstacle. Therefore, I propose a language-based approach of freely available, large-scale corporate documents to study linguistic hints regarding CEOs' personality dimensions by applying a validated, closed-based approach developed to a sample of Fortune 500 companies. I compare the results to validated, machine learning-trained open-based results obtained from conference calls of 3000 CEOs of S&P 1500 companies. In order to provide a basis for comparison, I supplement these linguistic personality profiles with a sample of convicted criminal CEOs that provide an archetype of extreme linguistic cases. Finally, after controlling for commonly used content analytical constructs (e.g., entrepreneurial orientation, market orientation) to capture CEOs' cognitive state, I link these cross-sectional linguistic profiles to longitudinal firm-level performance data. The analysis indicates that the linguistic manifestations of CEO personality explain a great share of firm performance in conjunction with observable individual, industry, and firm-level data. While there appear to be complementarities between open-based and closed-based language approaches, the analysis also indicates that the open-based linguistic trait of neuroticism is negatively related to various measures of firm performance. In particular, these measures appear to be more robust against genre effects and language that are unique among CEOs (self-selection effects). Therefore, the approach sheds light on the important role of validation procedures in the realm of computer-aided content analysis (CATA) and the conducive and detrimental effects of CEO personality cues on firm performance. The paper discusses practical implications for stakeholders and shareholders wishing to infer personality cues of key decision-makers from large-scale corporate documents and theoretical implications for the advancement of the upper echelon research.     

Entrepreneurial Ecosystems as Amplifiers of the Lean Startup Philosophy: Management Control Practices in Earliest-Stage Startups*

Entrepreneurial ecosystems play a key role in the development of startups not only by providing support—such as flexible office space and access to skilled employees, mentors, and investors—but moreover by promoting concrete ideals about “good” entrepreneurship. However, we know less about the role that ecosystems play in managerial practices of startups. In our empirical analysis of management control systems (MCSs) in earliest-stage startups, we witness a strong influence of entrepreneurial ideals—above all, the Lean Startup philosophy—on the MCSs analyzed. Building on cross-sectional field study data resulting from a comprehensive field-immersion strategy and 50 interviews with key actors in an entrepreneurial ecosystem as well as with founder-managers of startups, we consider the entrepreneurial ecosystem as a collective meso-level community that mediates between macro-level institutional pressures and micro-level practices of startups. We show how this community, through a variety of what we term amplifying mechanisms, actively deinstitutionalizes a legacy entrepreneurial philosophy epitomized by the business plan concept. At the same time, the community propagates the Lean Startup philosophy so that this alternative has become the dominant institutional philosophy in the studied ecosystem and its startups. Due to the amplifying mechanisms exerted by the meso level, startups use MCSs that play a crucial role in the rapid experimentation and learning process toward finding a scalable business model that is characteristic of the Lean Startup philosophy. We highlight that this philosophy of scientific experimentation has, to a significant degree, transformed intuitive entrepreneurial processes into a set of transactions that can be steered and accelerated by MCSs.     

Closed-loop Nash competition for liquidity

We study a multiplayer stochastic differential game, where agents interact through their joint price impact on an asset that they trade to exploit a common trading signal. In this context, we prove that a closed-loop Nash equilibrium exists if the price impact parameter is small enough. Compared to the corresponding open-loop Nash equilibrium, both the agents' optimal trading rates and their performance move towards the central-planner solution, in that excessive trading due to lack of coordination is reduced. However, the size of this effect is modest for plausible parameter values.