We consider optimal pricing mechanisms of a profit-maximizing platform running a dynamic search and matching market. Buyers and sellers enter in cohorts over time, meet and bargain under private information. The optimal direct mechanism is shown to involve no delay and can be decentralized through participation fees charged by the intermediary to both sides. The sum of buyers’ and sellers’ fees equals the sum of semi-elasticities and their ratio equals the ratio of bargaining weights. We also show that a monopolistic intermediary in a search market may be welfare enhancing.
“On Platforms, Incomplete Contracts, and Open Source Software”, accepted by the International Journal of Industrial Organization
We consider a firm A initially owning a software platform (e.g. operating system) and an application for this platform. The specific knowledge of another firm B is needed to make the platform successful by creating a further application. When B’s application is completed, A has incentives to expropriate the rents. Netscape claimed e.g. that this was the case with its browser running on MS Windows. We will argue that open sourcing or standardizing the platform is a warranty for B against expropriation of rents. The different pieces of software are considered as assets in the sense of the property rights literature (see Hart and Moore (Journal of Political Economy, 1990)). Two cases of joint ownership are considered beyond the standard cases of integration and non-integration: platform standardization (both parties can veto changes) and open source (no veto rights). In line with the literature, the more important a party’s specific investments the more rights it should have. In contrast to Hart and Moore, however, joint ownership can be optimal in our setting. Open source is optimal if investments in the applications are more important than in the platform. The results are driven by the fact that in our model firms invest in physical (and not in human) capital and that there is non-rivalry in consumption for software.
Breaking Up a Research Consortium, with Jianjun Wu, International Journal of Industrial Organization, Volume 31, Issue 4, July 2013, 342-353
Inter-firm R&D collaborations through contractual arrangements have become increasingly popular, but in many cases they are broken up without any joint discovery. We provide a rationale for the breakup date in R&D collaboration agreements. More specifically, we consider a research consortium initiated by a firm A with a firm B. B has private information about whether it is committed to the project or a free-rider. We show that under fairly general conditions, a breakup date in the contract is a (second- best) optimal screening device for firm A to screen out free-riders. With the additional constraint of renegotiation proofness, A can only partially screen out free-riders: entry by some free-riders makes sure that A does not have an incentive to renegotiate the contract ex post.
“Applying Markowitz’s Critical Line Algorithm”, with Daniel Niedermayer, 2010, “Handbook of Portfolio Construction: Contemporary Applications of Markowitz Techniques” edited by John Guerard, London: Springer
We provide a Matlab quadratic optimization tool based on Markowitz’s critical line algorithm that significantly outperforms standard software packages and a recently developed operations research algorithm. As an illustration: For a 2000 asset universe our method needs less than a second to compute the whole frontier whereas the quickest competitor needs several hours. This paper can be considered as a didactic alternative to the critical line algorithm such as presented by Markowitz and treats all steps required by the algorithm explicitly. Finally, we present a benchmark of different optimization algorithms’ performance.
Fee-Setting Mechanisms: On Optimal Pricing by Intermediaries and Indirect Taxation, with Simon Loertscher, supercedes our previous paper titled “When is Seller Price Setting with Linear Fees Optimal for Intermediaries?”
Mechanisms according to which private intermediaries or governments charge transaction fees or indirect taxes are prevalent in practice. We consider a setup with multiple buyers and sellers and two-sided independent private information about valuations. We show that any weighted average of revenue and social welfare can be maximized through appropriately chosen transaction fees and that in increasingly thin markets such optimal fees converge to linear fees. Moreover, fees decrease with competition (or the weight on welfare) and the elasticity of supply but decrease with the elasticity of demand. Our theoretical predictions fit empirical observations in several industries with intermediaries.
Assessing the Performance of Simple Contracts Empirically: The Case of Percentage Fees, with Simon Loertscher
This paper estimates the cost of using simple percentage fees rather than the broker optimal Bayesian mechanism, using data for real estate transactions in Boston in the mid-1990s. This counterfactual analysis shows that intermediaries using the best percentage fee mechanisms with fees ranging from 5.4% to 7.4% achieve 85% or more of the maximum profit. With the empirically observed 6% fees intermediaries achieve at least 83% of the maximum profit and with an optimally structured linear fee, they achieve 98% or more of the maximum profit.
Fee Setting Intermediaries: On Real Estate Agents, Stock Brokers, and Auction Houses, with Simon Loertscher
Mechanisms according to which intermediaries charge commission fees and let sellers set prices are prevalent in practice. We analyze such fee-setting mechanisms within a dynamic random-matching model, in which, in every period, privately informed buyers and sellers are randomly matched with intermediaries. We show that every intermediary can achieve the maximum profit with a fee-setting mechanism. Consequently, fee setting is an equilibrium outcome. We derive the conditions for optimal fees to be linear and show that equilibrium fees decrease and become more linear in rematching frequency. The model fits many stylized facts observed in real estate brokerage.
“Informational Hold-Up, Disclosure Policy, and Career Concerns on the Example of Open Source Software Development,” (with Marc Blatter, University of Bern)
We consider software developers who can either work on an open source project or on a closed source project. The former provides a publicly available signal about their talent, whereas the latter provides a signal only observed by their employer. We show that a talented employee may initially prefer a less paying job as an open source developer to commercial closed source projects, because a publicly available signal gives him a better bargaining position when renegotiating wages with his employer after the signal has been revealed. Also, we derive conditions under which two effects suggested by standard intuition are reversed: a pooling equilibrium (with both talented and untalented workers doing closed source) is less likely if differences in talent are large; a highly visible open source job leads to more effort in a career concerns setup. The former effect is because a higher productivity of talented workers raises not only the value but also the cost of signaling; the latter stems from more effort and the choice of a high visibility job being substitutes for the purpose of signaling. Results naturally apply to other industries with high and low visibility jobs, e.g. academic rather than commercial research, consulting rather than management.
“Does a Platform Monopolist Want Competition?”, (Revise & Resubmit Journal of Economics & Management Strategy)
We consider a software vendor first selling a monopoly platform and then an application running on this platform. He may face competition by an entrant in the applications market. The platform monopolist can benefit from competition for three reasons. First, his profits from the platform increase. Second, competition serves as a credible commitment to lower prices for applications. Third, higher expected product diversity may lead to higher demand for his application. Results carry over to non-software platforms and, partially, to upstream and downstream firms. The model also explains why Microsoft Office is priced significantly higher than Microsoft’s operating system.
“Java vs. Microsoft: Compatibility, Innovation and Anti-Trust Law”, Extended Essay as part of the MSc Economics program, London School of Economics, 2003
“Bank Regulation: Effects of the Capital Adequacy Requirements of the New Basel Accord”, Masters Thesis, University of Bern, 2002