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on Contract Theory and Applications |
| By: | Kang, Kee-Youn; Jang, Inkee |
| Abstract: | We develop a dynamic model of debt contracts with adverse selection and belief updates. In the model, entrepreneurs borrow investment goods from lenders to run businesses whose returns depend on entrepreneurial productivity and common productivity. The entrepreneurial productivity is the entrepreneur's private information, and the lender constructs beliefs about the entrepreneur's productivity based on the entrepreneur's business operation history, common productivity history, and terms of the contract. The model provides insights on the dynamic and cross-sectional relation between firm age and credit risk, cyclical asymmetry of the business cycle, slow recovery after a crisis, and the constructive economic downturn. |
| Keywords: | Adverse selection, Bayesian learning, Debt contracts, Belief update |
| JEL: | C78 D82 E44 G0 |
| Date: | 2020–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:99071&r=all |
| By: | Francis de Véricourt, (ESMT European School of Management and Technology and E.CA Economics); Huseyin Gurkan, (ESMT European School of Management and Technology) |
| Abstract: | This paper explores how firms that lack expertise in machine learning (ML) can leverage the so-called AI Flywheel effect. This effect designates a virtuous cycle by which, as an ML product is adopted and new user data are fed back to the algorithm, the product improves, enabling further adoptions. However, managing this feedback loop is difficult, especially when the algorithm is contracted out. Indeed, the additional data that the AI Flywheel effect generates may change the provider’s incentives to improve the algorithm over time. We formalize this problem in a simple two-period moral hazard framework that captures the main dynam- ics between machine learning, data acquisition, pricing and contracting. We find that the firm’s decisions crucially depend on how the amount of data on which the machine is trained interacts with the provider’s effort. If this effort has a more (resp. less) significant impact on accuracy for larger volumes of data, the firm underprices (resp. overprices) the product. Further, the firm’s starting dataset, as well as the data volume that its product collects per user, significantly affect its pricing and data collection strategies. The firm leverages the virtuous cycle less for larger starting datasets and sometimes more for larger data volumes per user. Interestingly, the presence of incentive issues can induce the firm to leverage the effect less when its product collects more data per user. |
| Keywords: | Data, machine learning, pricing, incentives and contracting |
| Date: | 2020–03–03 |
| URL: | http://d.repec.org/n?u=RePEc:esm:wpaper:esmt-20-01&r=all |
| By: | Samir Wadhwa; Roy Dong |
| Abstract: | The advent of machine learning tools has led to the rise of data markets. These data markets are characterized by multiple data purchasers interacting with a set of data sources. Data sources have more information about the quality of data than the data purchasers; additionally, data itself is a non-rivalrous good that can be shared with multiple parties at negligible marginal cost. In this paper, we study the multiple-principal, multiple-agent problem with non-rivalrous goods. Under the assumption that the principal's payoff is quasilinear in the payments given to agents, we show that there is a fundamental degeneracy in the market of non-rivalrous goods. Specifically, for a general class of payment contracts, there will be an infinite set of generalized Nash equilibria. This multiplicity of equilibria also affects common refinements of equilibrium definitions intended to uniquely select an equilibrium: both variational equilibria and normalized equilibria will be non-unique in general. This implies that most existing equilibrium concepts cannot provide predictions on the outcomes of data markets emerging today. The results support the idea that modifications to payment contracts themselves are unlikely to yield a unique equilibrium, and either changes to the models of study or new equilibrium concepts will be required to determine unique equilibria in settings with multiple principals and a non-rivalrous good. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2004.00196&r=all |
| By: | Juan Pablo Atal; Hanming Fang; Martin Karlsson; Nicolas R. Ziebarth |
| Abstract: | To insure policyholders against contemporaneous health expenditure shocks and future reclassification risk, long-term health insurance constitutes an alternative to community-rated short-term contracts with an individual mandate. Relying on unique claims panel data from a large private insurer in Germany, we study a real-world long-term health insurance application with a life-cycle perspective. We show that German long-term health insurance (GLTHI) achieves substantial welfare gains compared to a series of risk-rated short-term contracts. Although, by its simple design, the premium setting of GLTHI contract departs significantly from the optimal dynamic contract, surprisingly we only find modest welfare differences between the two. Finally, we conduct counterfactual policy experiments to illustrate the welfare consequences of integrating GLTHI into a system with a “Medicare-like” public insurance that covers people above 65. |
| JEL: | G22 I11 I18 |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26870&r=all |
| By: | Reiter, Michael (IHS, Vienna and NYU Abu Dhabi); Zessner-Spitzenberg, Leopold (Vienna Graduate School of Economics and IHS, Vienna) |
| Abstract: | Long-term debt contracts transfer aggregate risk from borrowing firms to lending banks. When aggregate shocks increase the future default probability of firms, banks are not compensated for the default risk of existing contracts. If banks are highly leveraged, this can lead to financial instability with severe repercussions in the real economy. To study this mechanism quantitatively, we build a macroeconomic model of financial intermediation with long-term defaultable loan contracts and calibrate it to match aggregate firm and bank exposure to business cycle risks. Our model exhibits banking crises that closely resemble observed crisis episodes. We find that such crises do not arise in an economy with short-term debt. Our results on the role of long-term debt completely reverse if financial regulation is implemented to increase banks' risk bearing capacity. The financial sector is then well equipped to take on the aggregate risk, such that long-term lending stabilizes the business cycle by providing insurance to the corporate sector. |
| Keywords: | Banking, Financial frictions, Maturity transformation |
| JEL: | E32 E43 E44 G01 G21 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:ihs:ihswps:13&r=all |