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Publication Open Access A characterization of the extended serial correspondence(Elsevier, 2015) Heo, Eun Jeong; Department of Economics; Yılmaz, Özgür; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 108638We study the problem of assigning objects to a group of agents. We focus on probabilistic methods that take agents' ordinal preferences over the objects. Importantly, we allow for indifferences among objects. Katta and Sethuraman (2006) propose the extended serial correspondence to solve this problem. Our main result is a characterization of the extended serial correspondence in welfare terms by means of stochastic dominance efficiency, stochastic dominance no-envy and "limited invariance," a requirement we adapt from Heo (2014a). We also prove that an assignment matrix is selected by the extended serial correspondence if and only if it satisfies "non-wastefulness" and "ordinal fairness," which we adapt from Kesten et al.
Publication Metadata only A two-sided reputation result with long-run players(Academic Press Inc Elsevier Science, 2013) Ekmekçi, Mehmet; Department of Economics; Atakan, Alp Enver; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 39383We establish reputation results, under two sided incomplete information, for a class of repeated games. We consider a repeated game that satisfies the assumptions of either Atakan and Ekmekci (2012) [3] or Cripps et al. (2005) [6] and we assume that both players are Stackelberg types with positive probability. If the stage game is not a common interest game, then equilibrium play converges to the unique equilibrium of a continuous time war of attrition as the stage game is repeated arbitrarily frequently. Alternatively, if the stage game is a common-interest game, then the players' equilibrium payoffs converge to their highest payoffs as the stage game is repeated arbitrarily frequently. (C) 2012 Elsevier Inc. All rights reserved.Publication Open Access Ambiguous business cycles: a quantitative assessment(Elsevier, 2020) Altuğ, Sumru; Collard, Fabrice; Mukerji, Sujoy; Department of Economics; Çakmaklı, Cem; Özsöylev, Han Nazmi; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 107818; N/AIn this paper, we examine the cyclical dynamics of a Real Business Cycle model with ambiguity averse consumers and investment irreversibility using the smooth ambiguity model of Klibanoff et al. (2005, 2009). Ambiguity of belief about the productivity process arises as agents do not know the process driving variation in aggregate TFP, and they must make inferences regarding the true process at the same time as they infer the behavior of the unobserved temporary component using a Kalman filtering algorithm. Our findings may be summarized as follows. First, the standard business cycle facts hold in our framework, which are not altered significantly by changes in the degree of ambiguity aversion. Second, we demonstrate a role for information and learning effects, and show that lower initial ambiguity or greater confidence coupled with learning dynamics lowers the volatility and increases the persistence in all of the key macroeconomic variables. Third, comparing the performance of our model to the New Keynesian business cycle model of Ilut and Schneider (2014) with maxmin expected utility, we find that the version of their model without nominal and real frictions turns out to have limited success at matching the moments for the quantity variables. In the maxmin expected utility framework, the worst case scenario instills too much caution on the part of agents who, in the absence of a key set of nominal and real frictions, end up excessively reducing their responses to TFP shocks.Publication Metadata only An experimental study of house allocation mechanisms(Elsevier Science Sa, 2004) Chen, Yan; Department of Economics; Sönmez, Tayfun; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AWe report an experiment on three house allocation mechanisms under complete information: random serial dictatorship with squatting rights, and two variants of the top trading cycles mechanism. Results show that the latter two are significantly more efficient than the former.Publication Metadata only An exploration in school formation: income vs. ability(2012) Alkan, Ahmet; Anbarcı, Nejat; Department of Economics; Sarpça, Sinan; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 52406We study stable school formation among four students that differ in ability and income. In the presence of ability complementarities and school costs to be shared, we identify the conditions under which a stable allocation is efficient, inefficient, nonexistent, and tell who become peers.Publication Metadata only Asymmetric response to monetary policy surprises at the long-end of the yield curve(Louisiana State University Press, 2012) Department of Economics; Department of Economics; Demiralp, Selva; Yılmaz, Kamil; Faculty Member; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; 42533; 6111This paper investigates the responsiveness of asset markets to monetary policy path revisions. Using federal funds futures contracts to extract near-term path revisions, we find that the responsiveness of longer term Treasury securities to path revisions is significantly asymmetric, the magnitude of which increases during tightenings and decreases during easings. These findings blend nicely with the earlier literature that documents asymmetric effects of monetary policy on output. (C) 2012 Elsevier Inc. All rights reserved.Publication Metadata only Backward unraveling over time: the evolution of strategic behavior in the entry level British medical labor markets(Elsevier Science Bv, 2001) Department of Economics; Ünver, Utku; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AThis paper studies an evolutionary programming technique, namely a genetic algorithm, to analyze how a population of decision-makers learn to coordinate the selection of an equilibrium or a social convention in a two-sided matching game with incomplete information. In the contexts of centralized and decentralized entry-level labor markets, evolution and adjustment paths of unraveling are explored using this technique in an environment inspired by the Kagel and Roth (2000. Quarterly Journal of Economics 115(1), 201-235) experimental study. As an interesting result, it is demonstrated that stability need not be required for the success of a matching mechanism under incomplete information in the long run.Publication Metadata only Can pre-arranged matches be avoided in two-sided matching markets?(Academic Press Inc, 1999) Department of Economics; Sönmez, Tayfun; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AWe study manipulation via pre-arranged matches in the context of centralized two-sided matching markets. We show that the solution that is used to match the hospitals and medical residents in the United States, namely the hospital-optimal stable rule, is manipulable in this way. Unfortunately this is a general problem: We show that there is no solution that is both stable and non-manipulable.Publication Metadata only Carbon price forecasting models based on big data analytics(2019) Çanakoğlu, Ethem; Ağralı, Semra; Department of Economics; Yahşi, Mustafa; PhD Student; Department of Economics; College of Administrative Sciences and Economics; N/AAfter the establishment of the European Union's Emissions Trading System (EU-ETS) carbon pricing attracted many researchers. This paper aims to develop a prediction model that anticipates future carbon prices given a real-world data set. We treat the carbon pricing issue as part of big data analytics to achieve this goal. We apply three fundamental methodologies to characterize the carbon price. First method is the artificial neural network, which mimics the principle of human brain to process relevant data. As a second approach, we apply the decision tree algorithm. This algorithm is structured through making multiple binary decisions, and it is mostly used for classification. We employ two different decision tree algorithms, namely traditional and conditional, to determine the type of decision tree that gives better results in terms of prediction. Finally, we exploit the random forest, which is a more complex algorithm compared to the decision tree. Similar to the decision tree, we test both traditional and conditional random forest algorithms to analyze their performances. We use Brent crude futures, coal, electricity and natural gas prices, and DAX and S&P Clean Energy Index as explanatory variables. We analyze the variables' effects on carbon price forecasting. According to our results, S&P Clean Energy Index is the most influential variable in explaining the changes in carbon price, followed by DAX Index and coal price. Moreover, we conclude that the traditional random forest is the best algorithm based on all indicators. We provide the details of these methods and their comparisons.Publication Metadata only Cheating and incentives in a performance context: evidence from a field experiment on children(Elsevier, 2020) Alan, Şule; Department of Economics; N/A; Ertaç, Seda; Gümren, Mert; Faculty Member; Researcher; Department of Economics; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 107102; N/AWe study cheating behavior in a large sample of elementary school children in the context of a creative performance task, in the presence and absence of performance incentives. Our data come from a sample of 720 elementary school children with an average age of 8, and contain rich information on a large set of correlates, such as risk and time preferences, IQ, gender and family characteristics. We document that children with higher IQ and higher socioeconomic status have a higher likelihood of cheating. We find that the presence of incentives for better performance does not increase cheating behavior. We also document an interesting interaction between altruism and incentives: altruistic students cheat significantly less in the presence of incentives. (C) 2019 Elsevier B.V. All rights reserved.