Contributions in Merlin

We study how the precision of managers’ private post-contract predecision information affects the pay-performance relation. Taking into account that the information environment in decentralized firms is often endogenously determined (e.g., by investment in internal accounting systems, hiring of consultants, or learning), we find that firms jointly choosing information precision and incentives may optimally tie executive pay closer to firm performance as agency problems become more pronounced. Specifically, the trade-off between information precision and incentives can render it optimal to provide agents with stronger incentives if agents are less productive, performance measures are less congruent or more susceptible to manipulation, or if agents are more risk averse. Considering that empirical studies frequently take the pay-performance sensitivity (PPS) as a measure of the efficiency of real world compensation arrangements, our results provide relevant insights for empirical research studying the determinants of the relation between executive pay and firm performance. Keywords: incentive contracting, predecision information, information design, pay-performance relation

Intersection joins over interval data are relevant in spatial and temporal data settings. A set of intervals join if their intersection is non-empty. In case of point intervals, the intersection join becomes the standard equality join. We establish the complexity of Boolean conjunctive queries with intersection joins by a many-one equivalence to disjunctions of Boolean conjunctive queries with equality joins. The complexity of any query with intersection joins is that of the hardest query with equality joins in the disjunction exhibited by our equivalence. This is captured by a new width measure called the IJ-width. We also introduce a new syntactic notion of acyclicity called iota-acyclicity to characterise the class of Boolean queries with intersection joins that admit linear time computation modulo a poly-logarithmic factor in the data size. Iota-acyclicity is for intersection joins what alpha-acyclicity is for equality joins. It strictly sits between gamma-acyclicity and Berge-acyclicity. The intersection join queries that are not iota-acyclic are at least as hard as the Boolean triangle query with equality joins, which is widely considered not computable in linear time.

Whether one looks at revenue, public and private investment, or media coverage; men's sports consistently do better than women's sports. Many people argue that these differences are driven by absolute differences in the quality of athletes in men's and women's sports. We begin by noting that absolute differences in athletic skill often do not drive demand in sports. We then move on to our primary research question: Can people truly see differences in men and women athletes? To answer this question, we use videos of professional women’s and men’s soccer. In some videos the gender of the athletes was clear to see. In other videos, though, the gender of the athletes was blurred. We find that participants only rate men’s soccer videos higher when the gender of the players is visible. These findings reveal a bias in the evaluation of men’s and women’s soccer relevant for many other fields. Our results demonstrate that factors other than performance, e.g., social beliefs and stereotypes, have an important influence on how individuals evaluate women in sports.

Standard strategic asset allocation procedures usually neglect market interaction. However, returns are not generated in a vacuum but are the result of the market's price discovery mechanism which is driven by investors' investment strategies. Evolutionary finance accounts for this and endogenizes asset prices. This paper develops a multi-asset evolutionary finance model. Requiring little more than dividend and interest rate data, it facilitates an interesting glimpse into the inner workings of financial markets and provides a valuable guide to this class of models. While traditional mean/variance optimization is static and concerned with finding the optimal asset allocation, evolutionary portfolio theory is dynamic and its focus is on finding the optimal investment strategy. This paper shows that yield-based strategies generate asset allocations that outperform competing alternatives. Therefore, strategic asset allocation approaches that rely on such an economic foundation are evolutionarily advantageous for multi-asset investors.

Investors in equities tend to follow well-defined investment strategies based on characteristics such as market capitalization and dividend yield or factors such as size, value, momentum and quality which capture the cross-section of asset returns. In this paper, we explore the interaction of such investment strategies in a demand-driven framework. The aim is to quantify the impact of a reallocation of capital between strategies on the cross-section of their performance. The main finding is that self- and cross-impact caused by the reallocation of capital can explain capacity of strategies, correlation of returns and the cyclical nature of investment strategies’ risk premia.

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We assess how investors’ willingness-to-pay (WTP) for sustainable investments responds to the impact of those investments, using a framed field experiment. While investors have a substantial WTP for sustainable investments, they do not pay more for more impact. This also holds for dedicated impact investors. When investors compare several sustainable investments, their WTP responds to differences in impact but not to the absolute level of impact. Investors experience positive emotions when choosing sustainable investments, irrespective of investments’ impact. Our findings suggest that the WTP for sustainable investments is driven by an emotional rather than a calculative valuation of impact.

Is deficit finance, explicit or implicit, free when borrowing rates are routinely lower than growth rates? Specifically, can the government make all generations better off by perpetually taking from the young and giving to the old? We study this question in simple closed and open economies and show that achieving Pareto gains requires implausible calibrations. Even then, the gains reflect, depending on the economy's openness, improved intergenerational risk-sharing, improved international risk-sharing, and beggaring thy neighbor – not intergenerational redistribution per se. Low government borrowing rates, including borrowing rates running far below growth rates, justify improved risk-sharing between generations and countries. They provide no convincing basis for using deficit finance to redistribute from young and future generations or other countries.

Climate change will impact current and future generations in different regions very differently. This paper develops a large-scale, annually calibrated, multi-region, overlapping generations model of climate change to study its heterogeneous effects across space and time. We model the relationship between carbon emissions and the global average temperature based on the latest climate science. Predicated average global temperature is used to determine, via pattern-scaling, region-specific temperatures and damages. Our main focus is determining the carbon policy that delivers present and future mankind the highest uniform percentage welfare gains – arguably the policy with the highest chance of global adoption. Damages from climate change are positive for all regions apart from Russia and Canada, with India and South Asia Pacific suffering the most. The optimal policy is implemented via a time-varying global carbon tax plus region- and generation-specific net transfers. Uniform welfare improving carbon policy can materially limit global emissions, dramatically shorten the use of fossil fuels, and raise the welfare of all current and future agents by over four percent. Unfortunately, the pursuit of carbon policy by individual regions, even large ones, makes only a limited difference. However, coalitions of regions, particularly ones including China, can materially limit carbon emissions.

In this paper, we propose a new method to estimate non-fundamental demand shocks for green financial assets based on the arbitrage activity of exchange-traded funds (ETFs). By estimating the monthly abnormal flows into environment-friendly ETFs, we construct a Green Sentiment Index that captures shifts in investors' appetite for environmental responsibility that are not yet priced in the value of the underlying assets. Our measure of green sentiment differs significantly from the news-based climate indexes proposed by the extant literature, and it has additional explanatory power on both stock returns and corporate decisions. Over the period 2010-2020, shifts in green sentiment anticipate a persistent stock-price out-performance of more environmentally responsible firms, (of approximately 53 basis points over six months for a one-standard-deviation higher green sentiment) as well as an increase in their capital investments and cash holdings, particularly for more equity-dependent ones.