
on Economic Design 
Issue of 2018‒03‒05
six papers chosen by Guillaume Haeringer, Baruch College and Alex Teytelboym, University of Oxford 
By:  Paul R. Milgrom; Steven Tadelis 
Abstract:  In complex environments, it is challenging to learn enough about the underlying characteristics of transactions so as to design the best institutions to efficiently generate gains from trade. In recent years, Artificial Intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. This paper offers some recent examples of how Artificial Intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design. 
JEL:  D44 D82 L15 
Date:  2018–02 
URL:  http://d.repec.org/n?u=RePEc:nbr:nberwo:24282&r=des 
By:  Tilman Börgers; Jiangtao Li 
Abstract:  We define and investigate a property of mechanisms that we call “strategic simplicity,” and that is meant to capture the idea that, in strategically simple mechanisms, strategic choices are easy. We define a mechanism to be strategically simple if strategic choices can be based on firstorder beliefs about the other agents’ preferences alone, and there is no need for agents to form higherorder beliefs, because such beliefs are irrelevant to agents’ optimal choices. All dominant strategy mechanisms are strategically simple. But many more mechanisms are strategically simple. In particular, strategically simple mechanisms may be more flexible than dominant strategy mechanisms in the voting problem and the bilateral trade problem.. 
JEL:  D82 
Date:  2018 
URL:  http://d.repec.org/n?u=RePEc:ces:ceswps:_6844&r=des 
By:  Tomoya Kazumura; Debasis Mishra; Shigehiro Serizawa 
Abstract:  A seller is selling multiple objects to a set of agents. Each agent can buy at most one object and his utility over consumption bundles (i.e., (object,transfer) pairs) need not be quasilinear. The seller considers the following desiderata for her (allocation) rule, which she terms desirable: (1) strategyproofness, (2) expost individual rationality, (3) equal treatment of equals, (4) no wastage (every object is allocated to some agent). The minimum Walrasian equilibrium price (MWEP) rule is desirable. We show that at each preference profile, the MWEP rule generates more revenue for the seller than any desirable rule satisfying no subsidy. Our result works for quasilinear domain, where the MWEP rule is the VCG rule, and for various nonquasilinear domains, some of which incorporate positive income effect of agents. We can relax no subsidy to no bankruptcy in our result for certain domains with positive income effect. 
Date:  2017–10 
URL:  http://d.repec.org/n?u=RePEc:tcr:wpaper:e116&r=des 
By:  Yusuke Matsuki 
Abstract:  Abstract This study develops a simple distributionfree test of monotonicity of conditional expectations. The test is based solely on ordinary least squares (OLS) and exploits the property between conditional expectation and projection; we prove that the monotonicity of a conditional expectation function restricts the sign of a corresponding projection coefficient. The estimated projection coefficient is used for a onetailed ttest. The test  which is notably simpler than other monotonicity tests  is applied to bidding data from Japanese construction procurement auctions to empirically test firstprice sealed bid auction models with independent private values (IPV), assuming the data are generated from a symmetric Bayesian Nash equilibrium. We regress the bid level on the number of bidders and use the estimated projection coefficient for testing. We find that the test results depend on public work categories.Length: 25 pages 
URL:  http://d.repec.org/n?u=RePEc:tcr:wpaper:e110&r=des 
By:  Madhav Raghavan 
Abstract:  We consider a model in which projects are to be assigned to agents based on their preferences, and where projects have capacities, i.e., can each be assigned to a minimum and maximum number of agents. The extreme cases of our model are the social choice model (the same project is assigned to all agents) and the house allocation model (each project is assigned to at most one agent). We show that, with general capacities,an allocation rule satis es strategyproofness, groupnonbossiness, limited in uence, unanimity, and neutrality, if and only if it is a strong serial priority rule. A strong serial priority rule is a natural extension of a dictatorial rule (from the social choice model) and a serial priority rule (from the house allocation model). Our result thus provides a bridge between the characterisations in Gibbard (1973, \Manipulation of voting schemes: A general result", Econometrica, 41, 587601), Satterthwaite (1975,Strategyproofness and Arrow's Conditions: Existence and correspondence theorems for voting procedures and social welfare functions", Journal of Economic Theory, 10,187216) and Svensson (1999, \Strategyproof allocation of indivisible goods", Social Choice and Welfare, 16, 557567). 
JEL:  C78 D71 
Date:  2017–10 
URL:  http://d.repec.org/n?u=RePEc:lau:crdeep:17.17&r=des 
By:  Agnes Cseh (Institute of Economics, Research Centre for Economic and Regional Studies, Hungarian Academy of Sciences, and Corvinus University of Budapest); Telikepalli Kavitha (Tata Institute of Fundamental Research, Mumbai, India) 
Abstract:  Abstract Given a bipartite graph G=(A[B;E) with strict preference lists and given an edge e 2 E, we ask if there exists a popular matching in G that contains e. We call this the popular edge problem. A matching M is popular if there is no matching M0 such that the vertices that preferM0 toM outnumber those that preferM toM0. It is known that every stable matching is popular; however G may have no stable matching with the edge e. In this paper we identify another natural subclass of popular matchings called “dominant matchings” and show that if there is a popular matching that contains the edge e, then there is either a stable matching that contains e or a dominant matching that contains e. This allows us to design a linear time algorithm for identifying the set of popular edges. When preference lists are complete, we show an O(n3) algorithm to find a popular matching containing a given set of edges or report that none exists, where n = jAj+jBj. 
Keywords:  popular matching, matching under preferences, dominant matching 
JEL:  C63 C78 
Date:  2017–09 
URL:  http://d.repec.org/n?u=RePEc:has:discpr:1725&r=des 