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31 - 40 of 52 results for: ECON

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ECON 258: Industrial Organization IIA

Topics may include theoretical and empirical analysis of bargaining, dynamic models of entry and investment, models of household borrowing, models of markets with asymmetric information, advertising, brands, and markets for information, and research at the boundaries between IO and neighboring fields such as trade, behavioral economics, and household finance. Prerequisite: Econ 257.
Terms: Win | Units: 3-5
Instructors: Gentzkow, M. (PI) ; Mahoney, N. (PI) ; Yurukoglu, A. (SI)

ECON 266: International Trade I

The first part of this course covers Ricardian, factor-proportions and monopolistic-competition models of international trade. The second part of the course covers commercial policy, with an emphasis on the economics of trade agreements. Students are expected to develop and present a research proposal. Prerequisites: Econ 202 or permission of instructor.
Terms: Win | Units: 3-5
Instructors: Bagwell, K. (PI)

ECON 271: Intermediate Econometrics II

Second course in the PhD sequence in econometrics at the Economics Department (as Econ 271) and at the GSB (as MGTECON 604). This course presents modern econometric methods with a focus on regression. Among the topics covered are: linear regression and its interpretation, robust inference, asymptotic theory for maximum-likelihood und other extremum estimators, generalized method of moments, Bayesian regression, high-dimensional and non-parametric regression, binary and multinomial discrete choice, resampling methods, linear time-series models, and state-space models. As a prerequisite, this course assumes working knowledge of probability theory and statistics as covered in Econ 270/ MGTECON 603. Enrollment is limited to Econ PhD students for the first two weeks of open enrollment, after which the remaining space will be available to all other interested students. Prerequisites: Econ 270/ MGTECON 603 or equivalent.
Terms: Win | Units: 3-5
Instructors: Spiess, J. (PI) ; Bocola, L. (SI) ; Warnick, M. (TA)

ECON 273: Advanced Econometrics I

Possible topics: parametric asymptotic theory. M and Z estimators. General large sample results for maximum likelihood; nonlinear least squares; and nonlinear instrumental variables estimators including the generalized method of moments estimator under general conditions. Model selection test. Consistent model selection criteria. Nonnested hypothesis testing. Markov chain Monte Carlo methods. Nonparametric and semiparametric methods. Quantile Regression methods.
Terms: Win | Units: 3-5
Instructors: Hong, H. (PI)

ECON 279: Behavioral and Experimental Economics II

This is part of a three course sequence (along with Econ 278 & 280-formerly 277) on behavioral and experimental economics. The sequence has two main objectives: 1) examines theories and evidence related to the psychology of economic decision making, 2) Introduces methods of experimental economics, and explores major subject areas (including those not falling within behavioral economics) that have been addressed through laboratory experiments. Focuses on series of experiments that build on one another in an effort to test between competing theoretical frameworks, with the objects of improving the explanatory and predictive performance of standard models, and of providing a foundation for more reliable normative analyses of policy issues. Prerequisites: 204 and 271, or consent of instructor.
Terms: Win | Units: 3-5
Instructors: Niederle, M. (PI)

ECON 282: Contracts, Information, and Incentives

Basic theories and recent developments in mechanism design and the theory of contracts. Topics include: hidden characteristics and hidden action models with one and many agents, design of mechanisms and markets with limited communication, long-term relationships under commitment and under renegotiation, property rights and theories of the firm.
Terms: Win | Units: 3-5
Instructors: Segal, I. (PI)

ECON 287: Topics in Market Design (MS&E 365)

Market design is a field that links the rules of the of the marketplace to understand frictions, externalities and more generally economic outcomes. The course provides theoretical foundations on assignment and matching mechanisms as well as mechanism design. Emphasis on theories at the intersection of economics, CS and operations as well as applications that arise in labor markets, organ allocation, platforms. Exposes students to timely market design challenges. Guest lectures and a research project. The class offers an opportunity to begin a research project. Students read and critique papers and write and present a final paper.
Terms: Win | Units: 3 | Repeatable for credit
Instructors: Ashlagi, I. (PI)

ECON 291: Social and Economic Networks

Synthesis of research on social and economic networks by sociologists, economists, computer scientists, physicists, and mathematicians, with an emphasis on modeling. Includes methods for describing and measuring networks, empirical observations about network structure, models of random and strategic network formation, as well as analyses of contagion, diffusion, learning, peer influence, games played on networks, and networked markets.
Terms: Win | Units: 3-5
Instructors: Chandrasekhar, A. (PI)

ECON 294: Continuous-time Methods in Economics and Finance

Continuous-time methods can, in many cases, lead to more powerful models to understand economic phenomena. The Black-Scholes option-pricing formula is significantly more tractable than discrete- time methods of option pricing based on binomial trees. There is an established tradition in continuous-time asset pricing, and there is increasing use of these methods in other fields, such as game theory, contract theory, market microstructure and macroeconomics. The goal of this class is to explore some of the old classic research as well as new economic models, and to discover areas of economics where continuous-time methods can help. The intention is to give graduate students a tool, which they can use to gain comparative advantage in their research, when they see appropriate. With this goal in mind, 25% of the class will focus on mathematics, but with economically relevant examples to illustrate the mathematical results. Up to one half of the class will cover established models, and the r more »
Continuous-time methods can, in many cases, lead to more powerful models to understand economic phenomena. The Black-Scholes option-pricing formula is significantly more tractable than discrete- time methods of option pricing based on binomial trees. There is an established tradition in continuous-time asset pricing, and there is increasing use of these methods in other fields, such as game theory, contract theory, market microstructure and macroeconomics. The goal of this class is to explore some of the old classic research as well as new economic models, and to discover areas of economics where continuous-time methods can help. The intention is to give graduate students a tool, which they can use to gain comparative advantage in their research, when they see appropriate. With this goal in mind, 25% of the class will focus on mathematics, but with economically relevant examples to illustrate the mathematical results. Up to one half of the class will cover established models, and the rest will focus on new papers. If students have their own work that uses continuous time, we can take a look at that as well. Coursework will include biweekly problem sets and a take-home final exam. There will also be room for short student presentations (related to homework assignments, economic papers, or definitions and results related to specific math concepts).
Terms: Win | Units: 3
Instructors: Sannikov, Y. (PI)

ECON 299: Practical Training

Students obtain employment in a relevant research or industrial activity to enhance their professional experience consistent with their degree programs. At the start of the quarter, students must submit a one page statement showing the relevance of the employment to the degree program along with an offer letter. Submit this documentation to the Econ professor, who has agreed to the student enrolling in their Econ 299 section. At the end of the quarter, a three page final report must be supplied documenting work done and relevance to degree program. May be repeated for credit.
Terms: Aut, Win, Spr, Sum | Units: 1-10 | Repeatable for credit
Instructors: Abramitzky, R. (PI) ; Akbarpour, M. (PI) ; Allcott, H. (PI) ; Amemiya, T. (PI) ; Arora, A. (PI) ; Athey, S. (PI) ; Attanasio, O. (PI) ; Auclert, A. (PI) ; Bagwell, K. (PI) ; Baker, L. (PI) ; Baron, D. (PI) ; Bekaert, G. (PI) ; Bernheim, B. (PI) ; Bettinger, E. (PI) ; Bhattacharya, J. (PI) ; Bloom, N. (PI) ; Bocola, L. (PI) ; Boskin, M. (PI) ; Brady, D. (PI) ; Bresnahan, T. (PI) ; Brynjolfsson, E. (PI) ; Bulow, J. (PI) ; Callander, S. (PI) ; Canellos, C. (PI) ; Carroll, G. (PI) ; Chandrasekhar, A. (PI) ; Chaudhary, L. (PI) ; Clerici-Arias, M. (PI) ; Cogan, J. (PI) ; Cuesta, J. (PI) ; Diamond, R. (PI) ; Duffie, D. (PI) ; Duggan, M. (PI) ; Dupas, P. (PI) ; Einav, L. (PI) ; Fafchamps, M. (PI) ; Fearon, J. (PI) ; Fetter, D. (PI) ; Fitzpatrick, M. (PI) ; Garber, A. (PI) ; Gentzkow, M. (PI) ; Goldin, J. (PI) ; Gould, A. (PI) ; Goulder, L. (PI) ; Greif, A. (PI) ; Haak, D. (PI) ; Haber, S. (PI) ; Hall, R. (PI) ; Hamilton, J. (PI) ; Hammond, P. (PI) ; Hanson, W. (PI) ; Hanushek, E. (PI) ; Harris, D. (PI) ; Harstad, B. (PI) ; Hartmann, W. (PI) ; Henry, P. (PI) ; Hong, H. (PI) ; Hope, N. (PI) ; Horvath, M. (PI) ; Hoxby, C. (PI) ; Imbens, G. (PI) ; Jackson, M. (PI) ; Jagadeesan, R. (PI) ; Jagolinzer, A. (PI) ; Jha, S. (PI) ; Jones, C. (PI) ; Jost, J. (PI) ; Judd, K. (PI) ; Kehoe, P. (PI) ; Kessler, D. (PI) ; Klenow, P. (PI) ; Kochar, A. (PI) ; Kojima, F. (PI) ; Krueger, A. (PI) ; Kuran, T. (PI) ; Kurlat, P. (PI) ; Kurz, M. (PI) ; Larsen, B. (PI) ; Lau, L. (PI) ; Levin, J. (PI) ; Li, H. (PI) ; MaCurdy, T. (PI) ; Mahoney, N. (PI) ; Makler, C. (PI) ; Malmendier, U. (PI) ; McClellan, M. (PI) ; McKeon, S. (PI) ; Milgrom, P. (PI) ; Miller, G. (PI) ; Morten, M. (PI) ; Naylor, R. (PI) ; Nechyba, T. (PI) ; Niederle, M. (PI) ; Noll, R. (PI) ; Owen, B. (PI) ; Pencavel, J. (PI) ; Persson, P. (PI) ; Piazzesi, M. (PI) ; Pistaferri, L. (PI) ; Polinsky, A. (PI) ; Qian, Y. (PI) ; Reiss, P. (PI) ; Richards, J. (PI) ; Roberts, J. (PI) ; Romano, J. (PI) ; Romer, P. (PI) ; Rossi-Hansberg, E. (PI) ; Rossin-Slater, M. (PI) ; Rosston, G. (PI) ; Roth, A. (PI) ; Royalty, A. (PI) ; Rozelle, S. (PI) ; Sargent, T. (PI) ; Schaffner, J. (PI) ; Schneider, M. (PI) ; Segal, I. (PI) ; Sharpe, W. (PI) ; Shotts, K. (PI) ; Shoven, J. (PI) ; Singleton, K. (PI) ; Skrzypacz, A. (PI) ; Sorkin, I. (PI) ; Spiess, J. (PI) ; Sweeney, J. (PI) ; Taylor, J. (PI) ; Tendall, M. (PI) ; Topper, M. (PI) ; Voena, A. (PI) ; Vytlacil, E. (PI) ; Wacziarg, R. (PI) ; Weingast, B. (PI) ; Williams, H. (PI) ; Wilson, R. (PI) ; Wolak, F. (PI) ; Wolitzky, A. (PI) ; Wright, G. (PI) ; Wright, M. (PI)
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