The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Economics of Information

The paper provides a road map to the burgeoning literature on two-sided markets and presents new results. It identifies two-sided markets with markets in which the structure, and not only the level of prices charged by platforms matters. The failure of the Coase theorem is necessary but not sufficient for two-sidedness. The paper builds a model integrating usage and membership externalities, that unifies two hitherto disparate strands of the literature emphasizing either form of externality, and obtains new results on the mix of membership and usage charges when price setting or bargaining determine payments between end-users.

/pdf/two-sided-markets-a-progress-report-40yp4ugn2p.pdf

Two-sided markets: a progress report

It is widely believed that current disparities in economic, political, and social outcomes reflect distinct institutions. Institutions are invoked to explain why some countries are rich and others poor, some democratic and others dictatorial. But arguments of this sort gloss over the question of what institutions are, how they come about, and why they persist. They also fail to explain why institutions are influenced by the past, why it is that they can sometimes change, why they differ so much from society to society, and why it is hard to study them empirically and devise a policy aimed at altering them. This 2006 book seeks to overcome these problems, which have exercised economists, sociologists, political scientists, and a host of other researchers who use the social sciences to study history, law, and business administration. It presents a multi-disciplinary perspective to study endogenous institutions and their dynamics.

/pdf/institutions-and-the-path-to-the-modern-economy-4dlla029fs.pdf

Institutions and the path to the modern economy

Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. A central question regards the impact of these sharing economy platforms on incumbent firms. We study the case of Airbnb, specifically analyzing Airbnb’s entry into the short-term accommodation market in Texas and its impact on the incumbent hotel industry. We first explore Airbnb’s impact on hotel revenue, by using a difference- in-differences empirical strategy that exploits the significant spatiotemporal variation in the patterns of Airbnb adoption across city-level markets. We estimate that in Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8-10% range; moreover, the impact is non-uniformly distributed, with lower-priced hotels and those hotels not catering to business travelers being the most affected. We find that this impact materializes through less aggressive hotel room pricing, an impact that benefits all consumers, not just participants in the sharing economy. The impact on hotel prices is especially pronounced during periods of peak demand, such as SXSW. We find that by enabling supply to scale – a differentiating feature of peer-to-peer platforms – Airbnb has significantly crimped hotels’ ability to raise prices during periods of peak demand. Our work provides empirical evidence that the sharing economy is making inroads by successfully competing with, differentiating from, and acquiring market share from incumbent firms.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2872361_code1846454.pdf?abstractid=2366898&mirid=1

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Toward a Comparative Institutional Analysis

Standard incentive theory models provide a rich framework for studying informational problems but assume that contracts can be perfectly enforced. This paper studies the design of self-enforced relational contracts. I show that optimal contracts often can take a simple stationary form, but that self-enforcement restricts promised compensation and affects incentive provision. With hidden information, it may be optimal for an agent to supply the same inefficient effort regardless of cost conditions. With moral hazard, optimal contracts involve just two levels of compensation. This is true even if performance measures are subjective, in which case optimal contracts terminate following poor performance. (JEL C73, D82, L14)

/pdf/relational-incentive-contracts-3x2w1j4pk8.pdf

Relational Incentive Contracts

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).

/pdf/estimating-dynamic-models-of-imperfect-competition-3ko56auuq6.pdf

Estimating Dynamic Models of Imperfect Competition

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors, and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).

/pdf/estimating-dynamic-models-of-imperfect-competition-4fw5kfqjeo.pdf

Local governments can provide services with their own employees or by contracting with private or public sector providers. We develop a model of this "make-or-buy" choice that highlights the trade-off between productive efficiency and the costs of contract administration. We construct a dataset of service provision choices by U.S. cities and identify a range of service and city characteristics as significant determinants of contracting decisions. Our analysis suggests an important role for economic efficiency concerns, as well as politics, in contracting for government services.

/pdf/contracting-for-government-services-theory-and-evidence-from-36zyshh7cf.pdf

Contracting for government services: theory and evidence from u.s. cities*: government services contracts: evidence of u.s. cities

The quality and quantity of data on economic activity are expanding rapidly. Empirical research increasingly relies on newly available large-scale administrative data or private sector data that often is obtained through collaboration with private firms. Here we highlight some challenges in accessing and using these new data. We also discuss how new data sets may change the statistical methods used by economists and the types of questions posed in empirical research.

http://science.sciencemag.org/content/sci/346/6210/1243089.full.pdf

Jonathan Levin

Papers

Relational Incentive Contracts

Estimating Dynamic Models of Imperfect Competition

Estimating Dynamic Models of Imperfect Competition

Contracting for government services: theory and evidence from u.s. cities*: government services contracts: evidence of u.s. cities

Economics in the age of big data.