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I am Jorge D. Ramos-Mercado, an Assistant Professor of finance and economics at the EGADE Business School (Tecnológico de Monterrey). My research focuses on dynamic information economics and study questions like: what is the relation between pricing power and learning in contracting settings with interdependence?; how should one organize a wartime, peace negotiation?; How to optimally conduct experiments? What role does the nature of criminal evidence plays in false convictions?; among others.  

I completed my PhD in Economics at the University of Minnesota, Department of Economics in 2023. Prior to my PhD studies, I was a research associate in the Center for Retirement Research at Boston College from 2014 to 2017. My work there focused on career transitions of older workers as well as issues pertaining to mortality and morbidity differences across genders, race, education, and socio-economic status. Once in Minnesota, I was first a research assistant in the Opportunity and Inclusive Growth Center in the Federal Reserve Bank of Minneapolis between 2019-2021. I worked with multiple researchers who worked in projects ranging from Industrial Organization and the welfare implication of government programs. Lastly, I worked as an instructor teaching advanced, undergraduate students Industrial Organization. 

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Research Interest.

I am an economist working in the intersection between applied microeconomics and economic theory. In particular, my research studies the role of dynamic learning in real-world microeconomic applications on note. My PhD has primarily focused on two projects discussed below.

The first project studies the Coase conjecture in auctions. Economic theory suggests that a seller who auctioned an item that failed to sell has the incentive to quickly re-auction his item at the next available offering. I find limited evidence for this behavior. Looking at Impressionist artworks brought up to auction in the 80s in the main offices of Sothebys and Christies, I make several observations. First, 30 percent of artworks failed to sell and (among these artworks) roughly 90 percent are not re-offered at a major auction house in 10 years. If an artwork is brought back to auction, I find that sellers pick a different auction house and location more than 60 percent of the time and wait an average of 5.5 years since the previous offering. This implies that artworks are seldom serially auctioned and is at odds with the prevailing theory. In the paper, I rationalize why artworks might not be serially auctioned by allowing buyers to have interdependent valuations. For instance, valuations for a painting may be interdependent when buyers value the artwork's resale value. I find that learning among buyers limits how many times an artwork can be gainfully auctioned. Moreover, I provide conditions for when the seller never re-auctions his item and may attain revenues equal to a benchmark in which the seller is not required to be sequentially rational. 

The second project (and my job market paper) studies why the share of wartime negotiations leading to lasting peace agreements fell after 1914. Before 1914 roughly 40 percent of wartime negotiations led to a lasting peace agreement, but after 1914 this rate fell to 13 percent. I find that major international policy changes at the turn of the century prompted combatants to hold more negotiations while they paused hostilities (i.e., during ceasefires). I find that each day combatants negotiate a peace treaty during a ceasefire is associated with 10 more days of fighting. The question is why ceasefires are associated with protracted conflicts and a decline in the share of negotiations leading to lasting peace. In order to answer this question, I build a bargaining model of wartime negotiation and prove that negotiating during a ceasefire leads to worse bargaining outcome than negotiations taking place while combatants fight. In the model, this happens to be the case since observing the fighting induces new learning dynamics which, in turn, prompt combatants to reach agreements expediently. 

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