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Economics

Ec 11. Introduction to Economics. 9 units (3-2-4); first, second terms. An introduction to economic methodology, models, and institutions. Includes both basic microeconomics and an introduction to modern approaches to macroeconomic issues. Students are required to participate in economics experiments. Instructors: Plott, Rangel. 

Ec 97. Undergraduate Research. Units to be arranged; any term. Prerequisites: Advanced economics and instructor’s permission. This course offers advanced undergraduates the opportunity to pursue research in Economics individually or in a small group. Graded pass/fail. 

Ec 98 abc. Senior Research and Thesis. Prerequisite: instructor’s permission. Senior economics majors wishing to undertake research may elect a variable number of units, not to exceed 12 in any one term, for such work under the direction of a member of the economics faculty. 

Ec 101. Selected Topics in Economics. Units to be determined by arrangement with the instructor; offered by announcement. Topics to be determined by instructor. Instructors: Staff, visiting lecturers.

Ec 105. Industrial Organization. 9 units (3-0-6); first term. Prerequisites: Ec 11 or equivalent. A study of how technology affects issues of market structure and how market structure affects observable economic outcomes, such as prices, profits, advertising, and research and development expenditures. Emphasis will be on how the analytic tools developed in the course can be used to examine particular industries—especially those related to internet commerce—in detail. Each student is expected to write one substantial paper. Not offered 2017–18. 

Ec/Psy 109. Frontiers in Behavioral Economics. 9 units (3-0-6), first term. Prerequisites: Ec 11. Behavioral economics studies agents who are biologically limited in computational ability, willpower and pure self-interest. An important focus is how those limits interact with economic institutions and firm behavior. This reading-driven course will cover new papers that are interesting and draw attention to a topic of importance to economics. Readings will cover lab and field experiments, axiomatic models of behavioral phenomena, and welfare. Each weekly discussion will begin with a 10-minute overview, then an inspection of the paper’s scientific machinery, judge whether its conclusions are justified, and speculate about the scope of its generalizability. It should help students as referees and as writers. Assignments are two 1000-word summary-critiques. Not offered 2017–18.

Ec/ACM/CS 112. Bayesian Statistics. 9 units (3-0-6); third term. Prerequisites: Ma 3, ACM/EE 116 or equivalent. This course provides an introduction to Bayesian Statistics and its applications to data analysis in various fields. Topics include: discrete models, regression models, hierarchical models, model comparison, and MCMC methods. The course combines an introduction to basic theory with a hands-on emphasis on learning how to use these methods in practice so that students can apply them in their own work. Previous familiarity with frequentist statistics is useful but not required. Instructor: Rangel.

Ec 117. Matching Markets. 9 units (3-0-6); third term. We will tackle the fundamental question of how to allocate resources and organize exchange in the absence of prices. Examples includes finding a partner, allocating students to schools, and matching donors to patients in the context of organ transplantations. While the main focus will be on formal models, we will also reason about the practical implications of the theory. Instructor: Pomatto.

Ec 121 ab. Theory of Value. 9 units (3-0-6); first, second terms. Prerequisites: Ec 11 and Ma 1b (may be taken concurrently). A study of consumer preference, the structure and conduct of markets, factor pricing, measures of economic efficiency, and the interdependence of markets in reaching a general equilibrium. Instructors: Border, Saito.

Ec 122. Econometrics. 9 units (3-0-6); first term. Prerequisites: Ma 3. The application of statistical techniques to the analysis of economic data. Instructor: Sherman. 

Ec/SS 124. Identification Problems in the Social Sciences. 9 units (3-0-6); second term. Prerequisites: Ec 122. Statistical inference in the social sciences is a difficult enterprise whereby we combine data and assumptions to draw conclusions about the world we live in. We then make decisions, for better or for worse, based on these conclusions. A simultaneously intoxicating and sobering thought! Strong assumptions about the data generating process can lead to strong but often less than credible (perhaps incredible?) conclusions about our world. Weaker assumptions can lead to weaker but more credible conclusions. This course explores the range of inferences that are possible when we entertain a range of assumptions about how data is generated. We explore these ideas in the context of a number of applications of interest to social scientists. Instructor: Sherman.

Ec/SS 129. Economic History of the United States. 9 units (3-0-6); second term. Prerequisites: Ec 11. An examination of certain analytical and quantitative tools and their application to American economic development. Each student is expected to write two substantial papers - drafts will be read by instructor and revised by students. Not offered 2017–18. 

Ec/SS 130. Economic History of Europe from the Middle Ages to the Twentieth Century. 9 units (3-0-6); third term. Prerequisites: Ec 11. Employs the theoretical and quantitative techniques of economics to help explore and explain the development of the European cultural area between 1000 and 1980. Topics include the rise of commerce, the demographic transition, the Industrial Revolution, and changes in inequality, international trade, social spending, property rights, and capital markets. Each student is expected to write nine weekly essays and a term paper. Not offered 2017–18.  

Ec 135. Economics of Uncertainty and Information. 9 units (3-0-6); first term. Prerequisite: Ec 11. An analysis of the effects of uncertainty and information on economic decisions. Included among the topics are individual and group decision making under uncertainty, expected utility maximization, insurance, financial markets and speculation, product quality and advertisement, and the value of information. Instructor: Agranov.

Ec 140. Economic Progress. 9 units (3-0-6); first term. Prerequisites: Ec 11 and Ma 2; Ec 122 recommended. This course examines the contemporary literature on economic growth and development from both a theoretical and historical/empirical perspective. Topics include a historical overview of economic progress and the lack thereof; simple capital accumulation models; equilibrium/planning models of accumulation; endogenous growth models; empirical tests of convergence; the measurement and role of technological advancement; and the role of trade, institutions, property rights, human capital, and culture. Instructors: Border, Hoffman.

CS/SS/Ec 149. Algorithmic Economics. 9 units (3-0-6). For course description, see Computer Science. 

BEM/Ec 150. Business Analytics. 9 units (3-0-6). Prerequisites: ACM 118 or Ec 122, and knowledge of R. For course description, see Business Economics and Management.

Ec/PS 160 abc. Laboratory Experiments in the Social Sciences. 9 units (3-3-3); first, second, third terms. Section a required for sections b and c. An examination of recent work in laboratory testing in the social sciences with particular reference to work done in social psychology, economics, and political science. Students are required to design and conduct experiments. Instructor: Plott. 

PS/Ec 172. Game Theory. 9 units (3-0-6). For course description, see Political Science. 

Ec 181. Convex Analysis and Economic Theory. 9 units (3-0-6); second term. Prerequisites: Ma 2 ab, Ec 121 a. Introduction to the use of convex analysis in economic theory. Includes a rigorous discussion of separating hyperplane theorems, continuity and differentiability properties of convex and concave functions, support functions, subdifferentials, Fenchel conjugacy, saddle-point theory, theorem of the alternative, and linear programming. Emphasis is on the finite-dimensional case, but infinite-dimensional spaces will be discussed. Applications to the theory of cost and production functions, decision theory, and game theory. Instructor: Border.