2019-20 Catalog

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.

Weekly seminar by a member of the Caltech Social Sciences faculty to discuss a topic of their current research or teaching at an introductory level. The course can be used to learn more about different areas of study and about undergraduate courses within the Social Sciences. The course will also be useful to those interested in pursuing the BEM, EC or PS options, or participating in research (SURF, for example) under supervision of the Social Science faculty. Graded pass/fail.

This course offers advanced undergraduates the opportunity to pursue research in Economics individually or in a small group. Graded pass/fail.

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.

Topics to be determined by instructor.

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.

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.

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.

We will tackle the fundamental question of how to allocate resources and organize exchange in the absence of prices. Examples include 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.

This course provides a survey from the perspective of economics of public policy issues regarding the management of natural resources and the protection of environmental quality. The course covers both conceptual topics and recent and current applications. Included are principles of environmental and resource economics, management of nonrenewable and renewable resources, and environmental policy with the focus on air pollution problems, both local problems (smog) and global problems (climate change).

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.

The application of statistical techniques to the analysis of economic data.

This course uses advanced econometric tools to analyze why people make the choices that they do in many domains- whether to make investments in peer-to-peer lending, consumer shopping between brands, where to go to college (Caltech or MIT?), choosing between modes of transportation (car, metro, Uber/Lyft, or bicycle), etc. We will focus on applications of discrete choice models (in which the dependent variable to be explained is usually a 0-1, Yes or No choice). The statistical models create estimates of behavioral parameters which describe numerically how much people value different goods or outcomes and how random their responses are. Models studied include logit, nested logit, probit, and mixed logit etc. Simulation techniques that allow estimation of otherwise intractable models will also be discussed. Models of this kind are routinely used in business and government, but are often misused and misinterpreted unless they are deeply understood.

The class studies different mechanisms to allocate a scarce resource, frequently called markets, using theoretical models. We will cover centralized markets, which clear via a single price, waiting or rationing, or use centralized algorithms to allocate demand and supply; decentralized markets, which clear via search; and auction markets. In each case, we will study how market rules determine the incentives of market participant and how to design these markets, focusing on efficiency and revenue maximization. Applications to electricity markets, concert tickets, ride-sharing, labor markets, school choice, dating markets, sponsored search ad auctions, and spectrum auctions will be covered.

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.

This course is an intermediate-level class on individual-level theory. The method used posits precise assumptions about general behavior (axioms) then finds equivalent ways to model them in mathematically convenient terms. We will cover both the traditional "rational'' approach, and more recent "behavioral'' models that incorporate psychological principles, in domains of intertemporal choice, random (stochastic) choice, menu choice, and revealed preferences. Students are expected to understand rigorous mathematical proofs. The class also includes serious discussion of the value of experimental evidence motivating new theories.

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.

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.

This course is an introduction to non-cooperative game theory, with applications to political science and economics. It covers the theories of normal-form games and extensive-form games, and introduces solutions concepts that are relevant for situations of complete and incomplete information. The basic theory of repeated games is introduced. Applications are to auction theory and asymmetric information in trading models, cheap talk and voting rules in congress, among many others.

Introduction to the use of convex analysis in economic theory. Includes separating hyperplane theorems, continuity and differentiability properties of convex and concave functions, support functions, subdifferentials, Fenchel conjugates, saddlepoint theorem, theorems of the alternative, polyhedra, linear programming, and duality in graphs. Introduction to discrete convex analysis and matroids. Emphasis is on the finite-dimensional case, but infinite-dimensional spaces will be discussed. Applications to core convergence, cost and production functions, mathematical finance, decision theory, incentive design, and game theory.