Contributions in Merlin

Katja Rost and Bruno S. Frey address an important topic. They compare two kinds of rankings, a conventional allegedly "quantitative“ publication ranking, and a ranking based on the membership on editorial boards of academic journals, which they call "qualitative“. They find that the relation between the two rankings is not linear, but inversely u-shaped. Consequently, they argue that maximizing publication rankings may lead to a decline in research quality. Therefore, basing promotion decisions solely on publication rankings could be counterproductive for science and hence should be avoided.

This paper investigates whether the sentimental preferences of investors influence market efficiency. We use a betting exchange market environment to analyze the influence of sentimental bettors on market efficiency in 2,333 soccer matches played between 2006-2014 during the last three hours of the pre-play period. Contrary to bookmaker markets, there is no intermediary in a betting exchange and, thus, the market prices solely reflect the beliefs of person to person betting. We use three different proxy variables to measure the bettor sentiment and find that price changes are more likely to be inefficient for betting events that are more prone to sentiment. Based on that finding, we propose a trading strategy that generates positive returns before considering the transaction costs and commission fees. Although the returns turn negative after considering the transaction costs and commission fees, the proposed trading strategy still outperforms a random betting strategy.

We examine how interruptions and personal and contextual factors affect the manifestation of psychological momentum (PM). Using men’s singles tennis point-by-point data from the two Grand Slam tournaments, Wimbledon and Roland Garros, between 2009 and 2014 (N=29,934), we employ realized break points as the potential triggers of PM and rest periods between two sequential games as the exogenous task interruptions. Controlling for player ability and the state of the match, we find that players are more likely to win the next game after realizing a break point only if there is no rest period between games. Thus, our results suggest that interruptions terminate the momentum effect. Further-more, we find that the effect of PM increases for players with a lesser relative ability and at a later stage within a match, showing the importance of personal and contextual factors for PM.

This paper examines how professional athletes can optimize commercial revenues from endorsement and sponsorship agreements throughout their careers. We use athlete brand management, defined as the balancing of brand building and brand selling activities, to understand the dynamics of commercial revenues optimization. We develop a conceptual framework that consists of two main blocks. First, we investigate four key determinants for the generation of athletes' accumulated commercial revenues. Second, we analyze appropriate brand management strategies at different stages of an athlete's life cycle. We propose a number of contingencies that refer to an athlete's characteristics, situation, and environment and argue that these contingencies determine the appropriate, i.e. revenues-optimizing, brand management strategy of an athlete at any career stage. Examples of professional athletes' brand management strategies support our framework. To our knowledge, this is the first paper to examine athletes' long-term commercial revenues optimization through athlete brand management.

The probability of a miner finding a valid block in the bitcoin blockchain is assumed to follow the Poisson distribution. However, simple, descriptive, statistical analysis reveals that blocks requiring a lot of time to find — long blocks — are won only by miners with a relatively higher hash power per second. This suggests that relatively bigger miners might have an advantage with regard to winning long blocks, which can be understood as a sort of “within block learning”. Modelling the bitcoin mining problem as a race, and by means of a multinomial logit model, we can reject that the time spent mining a particular block does not affect the probability of a miner finding a valid version of this block in a manner that is proportional to her size. Further, we postulate that the probability of a miner finding a valid block is governed by the negative hypergeometric distribution. This would explain the descriptive statistics that emerge from the data and be aligned with the technical aspects of bitcoin mining. We draw an analogy between bitcoin mining and the classical “urn problem” in statistics to sustain our theory. This result can have important consequences for the miners of proof-of-work cryptocurrencies in general, and for the bitcoin mining community in particular.

We analyze how banks’ allocations of mortgage credit across regions change when an online platform enables them to offer to regions where they have no branches, staff or legacy. Unique data from an online platform with offers from different banks to each mortgage application yield three novel findings. First, banks offer more and cheaper credit to borrowers in less competitive offline markets. Second, banks offer more credit to more distant locations, where house prices appear less over-heated, and past price growth is less correlated with that in their existing portfolio. Third, over time offers become more automated, lowering operational costs.

Corporate insiders, particularly managers, not only have access to their firms' private information, but also control over their firms' operational decisions. In this paper, we consider a setting where managers manipulate the firms' real activities in anticipation of subsequent insider trading opportunities. We find these managers choose production quantities that are strictly higher than the quantities absent insider trading. The overproduction leads to lower firm profits but higher consumer surplus. When we allow the managers to trade both in their own firms' and their rival firms' stocks, we find that the competition among insiders in the financial market drives down the expected insider trading profits and their incentives to distort production decisions. We then discuss the scenario of "substitute trading" when the managers only trade in their rival firms' shares, and show that the managers can earn some insider benefits without sacrificing their firms' profitability. We also explore the possibility of endogenizing the managers' ownership through compensation contracts.

A significant portion of CEOs in publicly-listed Chinese state-owned enterprises receive zero pay from the companies for which they work. Instead, they are paid directly by their controlling shareholder, which can be the Chinese government or parent firms that are controlled by the Chinese government. We explore how these “unpaid” executives are motivated and whether the outcomes of this unusual incentive mechanism differ from the conventional approach. Consistent with career concerns as their main incentive mechanism, we find that these CEOs have a significantly higher probability of future promotion than other CEOs. This result holds when we look at subsamples in which individual CEOs switch payment regimes. We also find that compared to their peers with paid CEOs, firms with unpaid CEOs in general have higher return on assets, higher asset turnover, higher asset growth, and engage in less tunneling. To mitigate concerns of that our results are driven by CEO selection and to further investigate the use of implicit incentives, we conduct an event study using the Split Share Structure Reform in 2006. The Reform liberalized the Chinese stock market, thus strengthening the role of the market as an incentive mechanism. This mechanism provides a potential replacement for promotion incentives. Our evidence is generally consistent with a reduction in the strength of promotion incentives following the reform.

Recent empirical research shows that both financial and value-related considerations prevail for an individual’s decision to invest in companies or products deemed sustainable or socially responsible. This paper investigates how different investor motivations vary across forms of sustainable investment strategies, in particular between broad sustainable investments and targeted impact investments. We use a unique dataset of retail investors engaged in a development oriented microfinance investment vehicle to analyze how different motives affect the demand for distinct sustainable investments. Our results show that different motives trigger different types of sustainable investments. While decisions to engage in general sustainable investments are mainly linked to return and risk expectations, the investment decision for the impact investment vehicle is connected more strongly to value attributes. In line with previous findings on general sustainable investments, we find that the decision to invest is driven more by value-related criteria while the amount invested is driven by financial motivations. Our analysis furthermore shows that distrust in the financial markets is a major driver for the share invested in general sustainable investments, but not in impact investments.

We study the causal effects of negative and positive demand shocks on the returns to specific skills by using variation from international trade shocks. To measure specific skills, we use task information from an o cial data set for career guidance and merge this information with a large register data set. Our results show that negative demand shocks result in larger earnings losses for workers with specific skills than for those with general skills, but workers with specific skills also profit much more from positive demand shocks. Thus, demand shocks lead to risk-return trade-offs for workers with specific skills.