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on Contract Theory and Applications |
| By: | Giacomo Calzolari; Leonardo Felli; Johannes Koenen; Giancarlo Spagnolo; Konrad O. Stahl |
| Abstract: | We investigate the role of mutual trust in long-term vertical relationships involving trades of complex goods. High complexity is associated with high contract incompleteness and hence the increased relevance of trust-based relational contracts. Contrary to expectations, we find that changes in trust do not impact the quality of highly complex objects. Instead, higher trust improves the quality of less complex objects. Even more surprisingly, trust is associated with more competi-tion in procurement, again for low tech objects. This complexity-based difference persists even when the same supplier provides both types of objects, suggesting relational contracting may be object-specific. These findings are derived from a comprehensive survey of buyers and critical suppliers in the German automotive industry. We explain these results with a relational contracting model, where the cost of switching suppliers is technology-specific and increases with object complexity, shifting bargaining power and altering the effects of trust on each party’s incentives. |
| Keywords: | relational contracts, complexity, bargaining power, trust, high-tech industries |
| JEL: | D86 L14 L62 O34 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11170&r= |
| By: | Jibang Wu; Siyu Chen; Mengdi Wang; Huazheng Wang; Haifeng Xu |
| Abstract: | The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we propose a theoretical framework for aligning economic interests of different stakeholders in the online learning problems through contract design. The problem, termed \emph{contractual reinforcement learning}, naturally arises from the classic model of Markov decision processes, where a learning principal seeks to optimally influence the agent's action policy for their common interests through a set of payment rules contingent on the realization of next state. For the planning problem, we design an efficient dynamic programming algorithm to determine the optimal contracts against the far-sighted agent. For the learning problem, we introduce a generic design of no-regret learning algorithms to untangle the challenges from robust design of contracts to the balance of exploration and exploitation, reducing the complexity analysis to the construction of efficient search algorithms. For several natural classes of problems, we design tailored search algorithms that provably achieve $\tilde{O}(\sqrt{T})$ regret. We also present an algorithm with $\tilde{O}(T^{2/3})$ for the general problem that improves the existing analysis in online contract design with mild technical assumptions. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.01458&r= |
| By: | Patrick Rey; Yossi Spiegel; Konrad O. Stahl |
| Abstract: | We study the feasibility and profitability of predation in a dynamic environment, using a parsimonious infinite-horizon, complete information setting in which an incumbent repeatedly faces potential entry. When a rival enters, the incumbent chooses whether to accommodate or predate it; the entrant then decides whether to stay or exit. We show that there always exists a Markov perfect equilibrium, which can be of three types: accommodation, monopolization, and recurrent predation. We then analyze and compare the welfare effects of different antitrust policies, accounting for the possibility that recurrent predation may be welfare improving. |
| Keywords: | predation, accommodation, entry, legal rules, Markov perfect equilibrium |
| JEL: | D43 L41 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11172&r= |
| By: | Duarte, Marco; Ma, Meilin; Song, Yujing; Zhu, Xinrong |
| Keywords: | Industrial Organization, Agribusiness |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343858&r= |
| By: | Clemens, Marco (IAAEU, University of Trier); Sauermann, Jan (IFAU) |
| Abstract: | Performance pay has been shown to have important implications for worker and firm productivity. Although workers' skills may directly matter for the cost of effort to reach performance goals, surprisingly little is know about the heterogeneity in the effects of incentive pay across workers. In this study, we apply a dynamic difference-in-differences estimator to the introduction of a generous bonus pay program to study how salient performance thresholds affect incentivized and non-incentivized performance outcomes for low- and high-skilled workers. While we do find that individual incentive pay did not affect workers' performance on average, we show that this result conceals an underlying heterogeneity in the response to individual performance pay: individual performance pay has a significant effect on the performance of high-skilled workers but not for low-skilled workers. The findings can be rationalized with the idea that the costs of effort differ by workers' skill level. We also explore whether agents alter their overtime hours and find a negative effect, possibly avoiding negative consequences of longer working hours. |
| Keywords: | performance pay, incentives, productivity, skills, panel data |
| JEL: | M52 J33 C23 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17119&r= |