Cornell University Registrar

Reviews lecture material presented in ECON 1110 lectures; provides problem-solving techniques, study tips, and additional problems to prepare for exams and problem sets; provides additional time for questions and discussion of concepts. Provides additional instruction for students who need reinforcement.

Reviews lecture material presented in ECON 1120 lectures; provides problem-solving techniques, study tips, and additional problems to prepare for exams and problem sets; provides additional time for questions and discussion of concepts. Provides additional instruction for students who need reinforcement.

This course is designed to prepare students for ECON 1110 and ECON 1120. Students are introduced to the economic way of thinking and to analyzing social problems. The objective of the course is to introduce students to the core principles in microeconomics and macroeconomics. The goal of the course is to improve the level of critical thinking and to improve communication skills. Topics include the explanation and evaluation of how the price system operates in determining what goods are produced, how goods are produced, who receives income, unemployment, inflation, balance of payments, and government deficits.

Explanation and evaluation of how the price system operates in determining what goods are produced, how goods are produced, who receives income, and how the price system is modified and influenced by private organizations and government policy.

Analysis of aggregate economic activity in relation to the level, stability, and growth of national income. Topics may include the determination and effects of unemployment, inflation, balance of payments, deficits, and economic development, and how these may be influenced by monetary, fiscal, and other policies.

This interdisciplinary course examines network structures and how they matter in everyday life. The course examines how each of the computing, economic, sociological and natural worlds are connected and how the structure of these connections affects each of these worlds. Tools of graph theory and game theory are taught and then used to analyze networks. Topics covered include the web, the small world phenomenon, markets, neural networks, contagion, search and the evolution of networks.

This course teaches students what they need to know in order to be excellent course assistants (CA's) in economics courses at Cornell. We will meet for an hour each week to talk about how students learn economics, and how best to help them learn. Students in this course will get concrete guidance on what to do as a CA, and we'll discuss the research behind this guidance. Students will be expected to do some reading outside class and either write a research paper on economic education or develop new teaching materials that can be incorporated into an economics course. Students will also facilitate small group activities in lecture courses (3 hours per week) and help other students in the Economics Support Center (2 hours per week).

Introduction to international economic principles and issues. Begins by surveying key topics such as the elements of comparative advantage, tariff and nontariff barriers, and multilateral institutions. The second part of the course treats selected topics in international finance, including exchange rates, balance of payments, and capital markets. Discusses current issues such as the effects of trade liberalization, trade and economic growth, and instability in international capital markets. Designed as a less technical introduction to concepts developed at a more advanced level in AEM 4300 and ECON 4510-ECON 4520.

The course is an introduction to game theory for students from diverse disciplinary backgrounds and interests. Game theory is a discipline barely one hundred years old. Its rise to prominence, with implications for various subjects, from economics, politics, and philosophy, to finance, diplomacy and computer science, in such a short time, has few parallels. The course is meant to be a primer on the subject for students who have no background in it. It can serve as groundwork for students pursuing different disciplines and also for those who intend to later take more advanced courses in game theory.

The pricing processes in a private enterprise economy are analyzed under varying competitive conditions, and their role in the allocation of resources and the functional distribution of national income is considered.

Introduces the theory of national income and determination and economic growth in alternative models of the national economy. Examines the interaction and relation of these models to empirical aggregate economic data. Reviews national accounts, output and employment determination, price stability and economic growth, in the context of alternative government policy programs and the impact of globalization.

This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based estimation, sampling distributions and hypothesis testing.

Introduction to the theory and application of econometric techniques. Emphasis is on both development of techniques and applications of econometrics to economic questions. Topics include estimation and inference in bivariate and multiple regression models, instrumental variables, regression with qualitative information, heteroskedasticity, and serial correlation. Students are expected to apply techniques through regular empirical exercises with economic data.

Provides an introduction to statistical inference and to principles of probability. It includes descriptive statistics, principles of probability, discrete and continuous distributions, and hypothesis testing (of sample means, proportions, variance). Regression analysis and correlation are introduced.

Introduction to the theory and application of econometric techniques. Emphasis is on foundations and development of econometric models, focusing on how a theoretical economic model can be placed into a statistical framework where data is used for the purposes of prediction/forecasting, measurement, and/or testing of economic theory. Topics include estimation and inference in bivariate and multiple regression models, instrumental variables, regression with qualitative information, heteroskedasticity, serial correlation.

This course covers methods used by social scientists to identify causal relationships in data, with a focus on evaluating the effects of real-world policies. Many social science analyses--including in the economics fields of public, labor, health, and development-aim to answer these types of policy-related causal questions: What is the effect of having health insurance on someone's health? Does the death penalty reduce crime? Will lowering class sizes increase students' academic achievement? The goal of this course is to train you to become both a high-quality consumer and producer of this type of research. You will learn about several research designs and data analysis methods for identifying causal relationships in data, read and assess empirical papers that apply these methods, and apply these methods to datasets yourself.

This course provides an overview of the major programs that make up the social safety net in the United States. We will review the economic rationale behind social programs, identify the economic consequences of these programs, and assess the empirical research on these topics. A major emphasis of the course will be on understanding the strengths and limitations of the core methodologies used in the existing economics literature.

This course surveys topics in crime and crime prevention, with a focus on thinking critically about empirical evidence. The first part of the course briefly introduces an economic model of crime and reviews relevant empirical methods. The remainder of the course is spent discussing a range of crime-related topics, including policing, incarceration, employment, drugs & alcohol, firearms, education, and health. Students will consider trade-offs to different crime prevention policies and gain experience framing and summarizing evidence for policymakers.

Examines the causes and consequences of sustained economic growth, and the development of economics as a discipline, from pre-industrial mercantilist thought through the economics of John Maynard Keynes. Stresses the relationship between the consequences of 19th-century economic growth and the evolution of economic thought.

Surveys the history of social policy in Great Britain and the United States from 1800 to the adoption of the British welfare state after World War II. Topics include the role of poor relief in the early 19th century; the changing relationship between public relief and private charity; the adoption of social insurance programs and protective labor legislation for children and women; government intervention in the Great Depression; and the beginnings of the welfare state.

Examines topics in labor economics of particular relevance to individual managers and firms. Representative topics include recruitment, screening, and hiring strategies; compensation (including retirement pensions and other benefits); training, turnover, and the theory of human capital; incentive schemes and promotions; layoffs, downsizing, and buyouts; teamwork; and internal labor markets. Focuses on labor-related business problems using the analytic tools of economic theory and should appeal to students with strong quantitative skills who are contemplating careers in general business, consulting, and human resource management as well as in economics.

Should policy interventions target inequality between workers or disparities between places? Inequality has risen in most developed countries in recent decades. While top incomes have grown significantly, incomes at the bottom of the distribution have increased much less. In light of these trends, this course examines the role of labor market and place-based policies in reducing inequality, and discusses the trade-offs that arise between reducing inequality and promoting economic activity.

This course proposes a new and innovative approach to learning about economics. If you want to learn in a different manner, if you are attracted to visualizations in general, this course is for you. This course will challenge preconceptions about what economics is. The goal is to use visual arts to illustrate basic economic concepts that are general, and demonstrate how these tools can be used to analyze and understand a variety of human and social phenomena. The idea of using arts to teach a non-arts related topic stems from recent research in neurology suggesting that creative arts aid learning and memorizing. The course focuses on the core concepts and ideas in economics and is meant to be widely accessible.

This class investigates race and class in the American labor market from Colonial America to the present day. We investigate the circumstances and labor institutions that brought labor to the U.S. and how laborers of various classes were received. A primary goal of the class is to understand the degree to which social mobility was historically possible in different time periods in American history. Social mobility is intimately tied to labor market institutions and the ability for workers to get ahead within those institutions. Some of the institutions we study are Indentured Servitude, Slavery, tenant farming, the Great Migration and labor organization in the industrial north. Ultimately we hope to build an understanding of the historical roots of the role of race and class today.

This course examines economic approaches to how new technologies impact the labor market. We will study how new technologies affect the nature of jobs and tasks, the nature and flexibility of work contracts, as well as how firms and workers search and find each other. We will discuss the emergence of flexible work arrangements (gig economy, teleworking). The goal is to learn how economists approach and analyze these phenomena, both theoretically and empirically.

This course will provide an overview of new financial technologies (Fintech), cryptocurrencies, central bank digital currencies, and decentralized finance (DeFi). The implications of these novel technologies for the future of financial markets, central banking, and international finance will be examined. The course will also cover basic analytical models in open economy macroeconomics and international finance, focusing on capital flows and exchange rate dynamics.

The goal of this course is to expand students' understanding of the economics of developing countries. We will address questions like: why do some countries grow quickly and others slowly? What factors prevent countries, households, and individuals from escaping the cycle of poverty? How do policymakers balance economic growth and environmental sustainability? Why don't financial markets work well in most developing countries, and do informal institutions fill the gap? How do we analyze the challenges facing small-scale farming households, and how do decisions by those households influence migration, labor markets, and the growth of industry? How do we evaluate policies and programs in order to understand what works for development? The approach in this course will be primarily microeconomic, although a basic understanding of macroeconomics is important for some topics. Emphasis will be on theory, real-world examples, and reading and interpreting research and policy papers.

Familiarizes students with the economic analysis of consumer policy issues. Uses the tools of microeconomic analysis to investigate the interaction between government and the marketplace, with an emphasis on how that interaction affects consumers. Examines the rationale for and effects of regulation of industry. Considers alternative theories of regulation, including the capture, economic, and public interest theories. Applies those theories to specific types of regulation, including economic regulation of specific industries (e.g., telecommunications, electricity, trucking, railroads, postal services) as well as to broader social regulation (e.g., health, safety, environmental). The effects of regulatory reform in numerous industries are also examined. An attempt is made to examine current topics relating to consumer policy.

Standard economic theory assumes that individuals are rational decision-makers; however, that is often not the case in the real world. Behavioral economics uses findings from psychology to determine ways in which individuals are systematically irrational to improve upon existing models. The first part of this course reviews these theories, while the second part of the course focuses on how these findings have been used to design better education, health, and tax policies as well as many others.

Risky health behaviors such as cigarette smoking, alcohol abuse, risky sex, drug use, poor diet and physical inactivity (leading to obesity), and self-harm are responsible for hundreds of thousands of preventable deaths and impose billions of dollars in medical care costs each year in the United States. This course teaches the economic approach to studying risky health behaviors. The research literature on the economic causes and correlates of risky health behaviors will be studied in detail. Numerous policies to modify risky health behaviors, such as the minimum legal drinking age and recreational marijuana use laws, will be debated in class. A policy wargame is conducted, with students creating advertisements, giving oral presentations, and lobbying policymakers to advocate a specific policy position.

Risky health behaviors such as drug abuse, alcohol abuse, cigarette smoking, risky sex, poor diet, physical inactivity, and self-harm are responsible for hundreds of thousands of preventable deaths and impose billions of dollars in medical care costs each year in the United States. This course teaches the economic approach to studying risky health behaviors. The research literature on the economic causes and correlates of risky health behaviors will be studied. Numerous policies to modify risky health behaviors, such as the minimum legal drinking age and recreational marijuana laws, will be debated in class. Students will also participate in a policy wargame on the subject of taxes on sugar-sweetened beverages.

This course will review and enhance existing knowledge of health care delivery and related policy issues, using the lens and tools of microeconomics. The topics covered will span consumer behavior, sources and markets for health insurance, provider markets, provider incentives and regulation, as well as market consolidation across a variety of key industries (e.g., physicians, hospitals, and post-acute care providers). Importantly, a key differentiator as well as pedagogical feature of the course will be extensive exposure to classic and contemporary empirical (i.e., data-driven) research tied to these topics. This aspect allows students to be aware of and accumulate knowledge from the frontier of what is scientifically known about key and salient health economics and health policy topics. The selected academic studies incorporated into each lecture will reinforce the core economic theories and insights accompanying a given topic and demonstrate how existing theories can be formally tested as well as refined or expanded using strong empirical research designs. This course should be highly relevant to students planning to work for or with healthcare-focused companies as well as those wishing to pursue master’s (e.g., MBA, MHA, MPH) or doctoral level academic programs (e.g., JD, MD, PharmD, or PhD) tied to healthcare.

The economics of education is about understanding how and why people make decisions to invest in education, the effect of education on long-term social and economic outcomes, the behavior of those institutions that produce education, and how best to design and implement public policies affecting the level and distribution of education resources. The basic tools of economics provide a framework to evaluate education policies including K-12 school finance, student financial aid, and college admissions. Throughout the course, there will be an emphasis on examining empirical tests of the economic theory and measuring the effects of policy initiatives on educational outcomes.

Is the U.S. college system a great equalizer or a cause of growing inequality? Improved access to higher education has brought millions of Americans into the middle class, and yet rising selectivity has meant that a disproportionate share of the economic elite come from a few top colleges. This course will explore the three big parts of the college experience --- (1) admissions and the college-going decision; (2) education while in college; and (3) college completion and labor market entry --- and ask how each part contributes to inequality in economic outcomes. Lectures and readings will focus on simple economic theories of higher education as well as the empirical methods used to test these theories.

Examines, through the lens of economic analysis, legal principles drawn from various branches of law, including contracts, torts, and property.

This course will examine issues that arise when a country attempts to implement and maintain a competition policy as a way of promoting economic growth and efficiency. The basic reading material will start with actual cases (most of them arising under U.S. antitrust law), and use those cases to probe the legal, economic and broad policy issues that the cases raise.

Networks II builds on its prerequisite course and continues to examine how each of the computing, economic, sociological and natural worlds are connected and how the structure of these connections affects these worlds. In this course, we will construct mathematical models for and analyze networked settings, allowing us to both make predictions about behavior in such systems, as well as reason about how to design such systems to exhibit some desirable behavior. Throughout, we will draw on real-world examples such as social networks, peer-to-peer filesharing, Internet markets, and crowdsourcing, that illustrate these phenomena.

The course will focus on how legal rules and regulations impact consumers in the marketplace. A significant portion of this course will focus on how developments in tort law, contract law, property law, and regulatory law influence social welfare and serve to protect consumers in their interactions with the marketplace. The course will also focus on how the federal regulatory agencies function and analyze the effectiveness of these agencies in protecting consumers. The course will focus specifically on the Food and Drug Administration and the Federal Trade Commission. In addition to students interested in public policy and economics, the course can be helpful to students who are interested in attending law school as students will get exposed to many of the concepts they will address in a first year law school curriculum.

Introduction to the use of economics as a tool in forming and evaluating environmental policy, with a focus on how economists measure effects of environmental quality and regulation. Topics include: externalities in an environmental context; regulation methods such as command and control, Pigouvian taxation, and cap and trade; methods for measuring the costs and benefits of environmental policy; overview of current environmental legislation; environmental quality and health; regulation and environmental justice.

This course introduces the concepts and methods used by economists to study not only cities, regions and their relationships with each other, but, more generally, the spatial aspects and outcomes of decision-making by households and firms. Areas examined include determinants of urban growth and decline, land and housing markets, transportation issues, segregation and poverty, and the allocation and distribution of urban public services.

AEM 4500/ECON 3860 introduces students to the economics of renewable and nonrenewable natural resources. Topics covered include the valuation and use of land; water economics, management, and conservation; the extraction and management of nonrenewable resources such as minerals, rare earth elements, and energy resources; renewable and nonrenewable sources of energy; forest management; fishery economics; groundwater; natural resource markets, demand, and supply; and sustainability. Students will learn how to use dynamic models to analyze decision-making over time, and to solve dynamic optimization problems analytically and numerically. Students will also learn how to analyze and explain the intuition and logic behind the theory and concepts. Students will apply the methods, quantitative tools, and concepts to analyze natural resource issues at global and local levels; to introspectively reflect on their own lives and future aspirations; and to draw lessons and implications for leadership, management, and policy. A solid background in calculus is required.

This class will focus on the role of the environment in the theory and practice of economics. It will make use of microeconomic analysis at the intermediate level and will incorporate real-world examples. It examines market failure, externalities, benefit-cost analysis, nonmarket valuation techniques, and cost-effective policy instruments.

Course focuses on global health challenges, and how they are related to poverty and inequality.

Why do most economic activities happen within managed organizations (i.e., firms) and not in markets (i.e., purchased from others)? More fundamentally, what is a firm? This course provides an introduction to *organizational economics* that seeks to understand the nature and workings of organizations-a collection of different people with dispersed information, responsibilities and non-aligned interests. You will learn about the theories of the boundaries of the firm that help unravel the neoclassical economics' blackbox view of the firm and the theories on the provision of incentives that ultimately shape firms. While the class takes a predominantly theoretical approach, you will also learn how the theories are in conversation with empirical evidence.

Studies mathematical models of conflict and cooperation in situations of uncertainty (about nature and about decision makers).

Statistical Decision Theory provides a normative framework to think about how to best use data to aid decision making under uncertainty. The goal of this course is to provide an undergraduate introduction to Statistical Decision Theory. At the end of the course, the students will be able to de?ne Statistical Models, Statistical Decision Problems, Statistical Decision Rules, Risk Functions, and to describe di?erent optimality criteria for statistical decision making (Bayes risk minimization, the minimax principle, and the minimax regret principle). The course will present di?erent applications to Economics, Econometrics, and Machine Learning.

Introduces fundamental frameworks for program evaluation and causal inference in empirical research and the industry, and studies how modern predictive machine learning methods can be applied to get more credible estimates of causal effects. Problems are formulated and discussed in terms of formal econometric models, but the focus will be the applied and practical perspectives, especially in economics. Requires statistic and econometric knowledge at the level of ECON 3140 or equivalent, and programing experience in R or Python.

A systematic treatment of the determinants of the money supply and the volume of credit. Economic analysis of credit markets and financial institutions in the United States.

This course provides an introduction to state and local public finance. The course has two goals: first, to provide institutional detail about U.S. state and local governments and their policies, and, second, to use economic theory to analyze public policy issues that arise in the state and local government setting. The course is divided into eight parts. Parts I and II provide background by reviewing key theoretical concepts in public finance and public choice: Part I covers the normative economic theory of the role of government in a market economy and Part II covers some standard positive theories of policy-making. Part III introduces the theory of fiscal federalism, which seeks to provide guidance on the appropriate role of state and local governments. Parts IV and V discuss different ways in which the provision of state and local goods and services are financed: Part IV deals with non-tax sources of finance and Part V covers commonly used taxes. Part VI explains the budget process of state and local governments. Part VII describes how three of the most important state and local government responsibilities are organized: education, transportation, and health and welfare. Finally, Part VIII discusses state and local government policies towards residential and business development.

This is an advanced course intended for upper level economics undergraduates who enjoy learning about and analyzing economic models. The course provides an introduction to the economic analysis of politics. Part I discusses collective choice and introduces some core ideas from social choice theory. Part II provides an overview of economic theories of political behavior. Part III discusses how political decisions are distorted away from those that would be made by the benevolent governments from public economics textbooks. Part IV offers economic perspectives on a number of contemporary issues in American politics.

In this course we will study two major features of modern economies. The first is the large dispersion across households in income and wealth, the second is the existence of persistent unemployment. We will be interested in understanding the models and tools that economists have developed to represent these phenomena, as well as in using these models to analyze the welfare implications of various government interventions. Topics to be covered include: Dynamic programming. Solution Methods of General Equilibrium models. Heterogeneous-agent macroeconomic models. Search, matching and equilibrium unemployment.

This course introduces and develops the leading modern theories of economies open to trade in financial assets and real goods. The goal is to understand how cross-country linkages in influence macroeconomic developments within individual countries; how financial markets distribute risk and wealth around the world; and how trade changes the effectiveness of national monetary and fiscal policies. In exploring these questions, we emphasize the role that exchange rates and exchange rate policy take in shaping the consequences of international linkages. We apply our theories to current and recent events, including growing geoeconomic conflict between Eastern and Western countries, hyperinflation in Argentina, Brexit, and recent Euro-area debt crises.

The course will cover foundations of modern theory of decision making under risk. The first part of the course will cover the functioning of financial markets with focus on asset pricing. The main part of the course will focus on how consumers perceive and evaluate risk, as well as issues arising from asymmetric information, such as adverse selection and moral hazard. The latter part of the course will discuss the functioning of various insurance markets and welfare implications of potential policy interventions.

This course takes a game theoretic approach to the study of markets and market power. Topics include pricing, collusion, entry, product differentiation, advertising, and bargaining.

This course takes a game theoretic and computational approach to the study of firms, markets, and competition. Topics include firms' pricing, product, and investment decisions in the face of competition. For each topic, the course covers theory and both analytical and computational approaches.

This course introduces students to behavioral economics, a subfield of economics that incorporates insights from psychology and other social sciences into economics. The course reviews some of the standard assumptions made in economics, and examines evidence on how human behavior systematically departs from these assumptions. The course then investigates alternative models of human decision making, and assesses to what extent these alternative models help improve economic analyses.

The course will appeal to students who have strong quantitative skills and would like to see applications of economic theory to analyze issues prominent in major public debates. Currently, we offer a very limited number of advanced courses that require students to do independent research, discuss their ideas in teams, present their work, and write a research proposal.

This course provides an introduction to the economics of asymmetric information, contracts and mechanism design. Topics covered include: bilateral contracting problems with moral hazard and/or adverse selection, bargaining with asymmetric information, the design of optimal auctions and other multilateral mechanisms, signaling and incomplete contacts. Prerequisites include intermediate microeconomics and statistics. The student is expected to be comfortable with basic probability (random variables, expectation, independence, and conditional probability) and calculus.

This independent study course offers economics majors (i.e., undergraduates whose applications to affiliate with the economics major have been approved) an opportunity to reflect on concepts from economics as they were encountered and applied in a recent internship. Students write a short paper describing their work experience and how it connects to the educational objectives of the economics major.

This independent study course offers economics majors (i.e., undergraduates whose applications to affiliate with the economics major have been approved) an opportunity to reflect on concepts from economics as they were encountered and applied in a recent internship. Students write a short paper describing their work experience and how it connects to the educational objectives of the economics major.

Independent study.

Topics in consumer and producer theory.

Topics in consumer and producer theory, equilibrium models and their application, externalities and public goods, intertemporal choice, simple dynamic models and resource depletion, choice under uncertainty.

Topics in Non-Cooperative Game Theory.

This course teaches the fundamentals of non-cooperative game theory and classic applications used in applied work in economics and related fields such as finance, marketing, operations, and accounting. The course begins with a brief primer on non-cooperative game theory that covers pure versus mixed strategies, Nash equilibrium, and various equilibrium refinements. Coverage then turns to basic frameworks that utilize game theory to model a wide range of settings in economics and related fields. These include agency analysis, classic asymmetric information models such as adverse selection and signaling, time inconsistency, and repeated games and reputation.

Covers the following topics: static general equilibrium; intertemporal general equilibrium: infinitely lived agents models and overlapping generations models; welfare theorems; equivalence between sequential markets and Arrow-Debreu Markets; Ricardian proposition; Modigliani-Miller theorem; asset pricing; recursive competitive equilibrium; the Neoclassical Growth Model; calibration; and introduction to dynamic programming.

Covers the following topics: dynamic programming; stochastic growth; search models; cash-in-advance models; real business-cycle models; labor indivisibilities and lotteries; heterogeneous agents models; optimal fiscal and monetary policy; sustainable plans; and endogenous growth.

Covers selected topics in matrix algebra (vector spaces, matrices, simultaneous linear equations, characteristic value problem), calculus of several variables (elementary real analysis, partial differentiation) convex analysis (convex sets, concave functions, quasi-concave functions), classical optimization theory (unconstrained maximization, constrained maximization), Kuhn-Tucker optimization theory (concave programming, quasi-concave programming).

Gives the probabilistic and statistical background for meaningful application of econometric techniques. Topics include probability theory probability spaces, random variables, distributions, moments, transformations, conditional distributions, distribution theory and the multivariate normal distribution, convergence concepts, laws of large numbers, central limit theorems, Monte Carlo simulation; statistics: sample statistics, sufficiency, exponential families of distributions. Further topics in statistics are considered in ECON 6200.

A continuation of ECON 6190 covering statistics: estimation theory, least squares methods, method of maximum likelihood, generalized method of moments, theory of hypothesis testing, asymptotic test theory, and nonnested hypothesis testing; and econometrics: the general linear model, generalized least squares, specification tests, instrumental variables, dynamic regression models, linear simultaneous equation models, nonlinear models, and applications.

This course teaches the economic approach to studying risky health behaviors such as cigarette smoking, drug use, alcohol abuse, risky sex, and poor diet and physical inactivity (leading to obesity), and suicide. We will examine in detail the research literature on the demand for health, economic models of addiction, the economic causes and correlates of risky health behaviors (e.g. education, prices, peers), and policies for modifying risky behaviors (e.g. taxes and other financial incentives, and providing information).Classes will begin with a lecture on how an aspect of microeconomic theory can be applied to the study of risky health behaviors, and testable predictions will be discussed. Critical discussions of the relevant health economics literature follow. Students will take turns presenting published research papers. You will write referee reports on three recent, cutting-edge working papers. Each student will also write an original research paper, testing predictions from microeconomic theory by acquiring suitable data and estimating the appropriate econometric model. You will present your research findings in a poster presentation and a research seminar.

This course belongs to the health economics sequence. In addition to health economics, some topics cover public and labor economics. Students will also learn how to develop research sketches. First, we talk about U.S. health insurance and its intersection with the labor market. Then, we talk about health care providers, their reimbursement and behavior. Next, we study social insurance systems for health risks, such as disability or sick leave insurance. Finally, we cover specific topics like health measurement, the value of a statistical life or cost-benefit analysis. The lectures will not cover health behaviors (PUBPOL 6410), human capital and early childhood effects, the environment-health literature, and effects of income, education, and unemployment on health (behaviors).

Focuses on empirical strategies to identify the causal effects of public policies and programs. The course uses problem sets based on real-world examples and data to examine techniques for analyzing nonexperimental data including control function approaches, matching methods, panel-data methods, selection models, instrumental variables, and regression-discontinuity methods. The emphasis throughout, however, is on the critical role of research design in facilitating credible causal inference. The course aids students in both learning to implement a variety of statistical tools using large data sets, and in learning to select which tools are best suited to a given research project.

This course is the second of a two-course sequence. Both PUBPOL 6090 and this course are, for the most part, targeted at students looking to do empirical research into the effects of some X on some Y. Both courses require students to complete problem sets that involve hands-on exercises - some based on real data and some using Monte Carlo simulations. The hope is that this learning by doing will reinforce what is taught in class. Usually, the first course covers core methods, specifically regression adjustment, matching and instrumental variables. This second course covers additional topics in matching (we will touch on machine learning methods in the process), regression discontinuity designs, panel data methods, and mediation analysis.

Social science research almost always combines empirical observation (data), the construction of concepts (language), and the logical analysis of the relations between observations and concepts (statistics). This course examines the relations between these three dimensions as the analyst moves from one to the other both as practice and in the crafting of a formal summary of findings and argument. We will be particularly interested in the foundational assumptions that underpin the connections between empirical reality, language, and statistical analysis. While these foundational assumptions are often taken for granted by social scientists, they vary dramatically between social science disciplines. The implicit contradiction between that variance and their doxic acceptance within disciplines will be a primary focus of the course.

The principal objective of this course is to explore empirical evidence on the role of government intervention in the economy. The focus of the course will be on reading important papers and learning techniques that will allow you to produce original research in public economics and to analyze critically existing research in the field.

Independent study.

This course explores links between urbanization and real estate markets. High downtown rents reflect the benefits of proximity to other companies and natural features like port facilities. High housing costs reflect proximity to jobs and the lure of urban amenities. At the same time, segregation and congestion are often exacerbated by urbanization, the costs of which are seen in inequality, crime, pollution, and traffic jams. Urban real estate markets are also affected by local government policy, including enforcement of property rights, zoning, tax and subsidy programs. Shrinking rust belt cities and work from home threaten to undermine urban real estate markets, while volatility and uncertainty contributes to mispricing. These and related ideas will be explored drawing on context from countries around the world.

This course is an advanced course in International Trade, targeted at second year PhD students. It covers theoretical models of international trade and economic geography, the gravity-type structure of trade through a variety of micro-foundations, and techniques to estimate trade models and assess counterfactuals. The course will also touch on global value chains, multinational productions, international diffusion of ideas, migration, and the consequences of trade for inequality.

This course introduces econometric and machine learning methods that are useful for causal inference. Modern empirical research often encounters datasets with many covariates or observations. We start by evaluating the quality of standard estimators in the presence of large datasets, and then study when and how machine learning methods can be used or modified to improve the measurement of causal effects and the inference on estimated effects. The aim of the course is not to exhaust all machine learning methods, but to introduce a theoretic framework and related statistical tools that help research students develop independent research in econometric theory or applied econometrics. Topics include: (1) potential outcome model and treatment effect, (2) nonparametric regression with series estimator, (3) probability foundations for high dimensional data (concentration and maximal inequalities, uniform convergence), (4) estimation of high dimensional linear models with lasso and related methods, (5) estimation of high dimensional generalised linear models with L1 regularisation, (6) introduction to other machine learning methods such as neural networks, regression trees and random forests, (7) inference on semiparametric models with high dimensional components, orthogonalisation, de-biased machine learning, (8) other related topics, such as balancing methods, treatment choice problems, etc. Class slides will be circulated and students are expected to read theoretic and empirical research papers that involve machine learning methods.

This course discusses recent developments in Econometrics and Machine Learning. The topics covered will vary every year.

An overview of the models and methods for analyzing data with cross-sectional dependence, i.e., those able to explicitly test behavioral models with interdependent agents' decisions. The technicalities are presented in a basic formulation, favoring the transmission of ideas, intuitions, and stressing the links with underlying behavioral mechanisms essential to guiding the interpretation of the results. The open questions in the economics literature are emphasized. They include: 1) the definition of the reference group; 2) the possible presence of unobserved attributes that may generate a problem of confounding variables (spurious spatial correlation); and 3) simultaneity in agents' behavior that may hinder identification of exogenous effects, i.e., influence of agents' attributes) from endogenous effects, i.e., influence of agents' outcomes. This short course focuses on identification issues.

This course explores how production networks shape macroeconomic outcomes. We develop models in which firms interact through input-output linkages and examine how shocks propagate along supply chains. We also study how networks are formed, and how the impact of taxes and other distortions can be affected by the structure of the production network.

The course introduces students to Bayesian time series methods. Students will learn how to make likelihood-based inference about unobserved quantities, e.g. model parameters, policy impacts or future outcomes, conditional on the observed data. Applications include structural vector autoregressions, state space models and linearized dynamic stochastic general equilibrium macro models. Student will become familiar with numerical posterior simulation techniques such as Gibbs sampling and the Metropolis-Hasting algorithm. The course is useful for any students interested in empirical work that involves time series and/or structural likelihood-based estimation.

This course focuses on ?rm dynamics, causes of size and productivity differences as well as patterns of growth, entry, and exit over the life cycle. It also studies how ?rms interact through production networks, the economic forces that shape these relationships, and the consequences for aggregate outcomes.

Many economic decisions have to be made in settings in which many interacting agents have imperfect and diverse information about pay-off relevant variables. This course gives an overview of existing research in macroeconomics and finance that deviates from settings with perfectly informed rational agents. The course will cover both methodological and substantial aspects of the existing literature.

Develops a mathematical and highly analytical understanding of the role of government in market economies and the fundamentals of public economics and related issues. Topics include generalizations and extensions of the fundamental theorems of welfare economics, in-depth analysis of social choice theory and the theory on implementation in economic environments, public goods and externalities and other forms of market failure associated with asymmetric information. The theoretical foundation for optimal direct and indirect taxation is also introduced along with the development of various consumer surplus measures and an application to benefit cost analysis. Topics of an applied nature vary from semester to semester depending on faculty research interests.

Focused on analytical models of political institutions, this course is organized around canonical models and their applications. These include voting models, menu auctions, models of reputation, and cheap talk games. These models are used to explain patterns of participation in elections, institutions of congress, lobbying, payments to special interest groups and other observed phenomena.

Includes reading and discussion of selected topics in labor economics. Stresses applications of economic theory and econometrics to the labor market and human resource areas.

Includes reading and discussion of selected topics in labor economics. Stresses applications of economic theory and econometrics to the labor market and human resource areas. The combination of ILRLE 7450 and ILRLE 7460 constitute Ph.D.-level sequence in labor economics.

Since the 1980s, American cities have exhibited increasingly divergent trends. This Great Divergence has had profound effects on local employment, income, political preferences, health outcomes, and intergenerational mobility. As more detailed data become available, recent research seeks to uncover the causes of this divergence and evaluate how policy interventions might mitigate its negative effects. Building on this research, this course explores recent advancements at the crossroads of labor and spatial economics. It begins by examining the growing disparities between cities and regions in terms of productivity, labor market opportunities, and amenities, in several countries. It then investigates the rationale behind place-based policies and their potential to stimulate local development. Finally, the course will provide students with essential tools and theories to study the sorting of workers and firms over space and to understand its implications for economic growth and inequality.

This course aims to provide an in-depth perspective on three important themes in modern labor economics: (1) Job search, (2) Technological change and new forms of work, (3) Sorting of workers and firms. Both micro and macro perspectives will be considered.

This course offers a graduate-level introduction to theoretical models in industrial organization. It is designed to prepare researchers to identify interesting questions and rigorously motivate empirical work. Topics include supermodular games, collusion, bargaining, auctions, industry dynamics, and productivity.

Rounds out some topics in the theory of industrial organization with the specific intent of addressing the empirical implications of the theory. Reviews empirical literature in the SCP paradigm and in the NEIO paradigm.

This course provides an overview of the field of behavioral economics. The course reviews evidence on how human behavior systematically departs from the standard assumptions of economics, and discusses how one might formally model alternative assumptions based on this evidence. The course then examines attempts to empirically test these theories. The goal is not merely to point out problems with traditional economic assumptions, rather, it is to develop alternative assumptions and to investigate whether these alternative assumptions can be usefully incorporated into mainstream economics.

This course introduces students to the key theories, canonical papers, and current frontiers in the microeconomics of international development. We cover topics related to agricultural household models, consumption smoothing, labor markets, trade and search, relational contracts, and public finance. Paired with AEM 7621 to form a graduate sequence in development economics.

This course is an extension of AEM 7620/ECON 7660 and will cover current microeconomic issues of developing countries including but not limited to factors influencing human capital accumulation (e.g. health, education), contracting and firm structure, credit and saving, and behavioral economics and development. Most lectures will begin with applied theory and then discuss leading papers on that topic. The course is also designed with a focus on empirical methods and testing theories with data. Finally, the course contains classes on how to prepare for field work in order to provide a foundation for many of the practical skills needed to move a project forward.

Advanced seminar explores recent empirical research and evaluation literature on issues of health, nutrition, education and intrahousehold decision-making in developing countries.

Analytical approaches to the economics of developing nations and development processes. Topics include: introduction to development economics; distribution analysis: theory and evidence; modeling employment, unemployment, wages, and labor markets; and policy analysis for economic development.

This course introduces graduate students to the main concepts and ideas of law and economics, founded on elementary game theory. These ideas are then applied to contemporary policy concerns, from promoting economic development and designing welfare interventions in developing countries, to controlling corruption and financial fraud. The defining feature of the course is the structuring of these topics within a common conceptual framework, and training students to develop these ideas further and apply them to new research questions.

The purpose of this course is to familiarize you with basic models and empirical regularities in the area of macro-development. That is, the use of structural models and micro data to answer policy relevant questions related to the process of economic development and with focus on developing countries.

Research workshop featuring guest lecturers.

Research workshop featuring guest lecturers.

Research workshop featuring guest lecturers.

Research workshop featuring guests lecturers. Presentations of completed papers and work in progress by faculty members, advanced graduate students, and speakers from other universities. Focuses on the formulation, design, and execution of dissertations.

Research workshop featuring guest lecturers.

Research workshop featuring guest lecturers.

Research workshop featuring guest lecturers.

Research workshop featuring guest lecturers.

Ph.D. students in the Field of Economics are required to take this year-long research seminar, and receive a grade of Satisfactory, in order to remain in good standing in the Ph.D. program. Students present and discuss each second-year paper, which must be completed before the semester opens and Economics 7850 meets for the first time. Students also present at least two additional papers or paper plans. These are intended to be part of the core of the student's thesis proposal, which must be given as part of the student's A Exam prior to the start of the fourth year of graduate study in the economics Ph.D. program. Economics 7851 ends with a mini-conference, attended by faculty and other Ph.D. students, in which each student makes a formal presentation in standard economics conference format, and each student discusses one of these presentations. Professional writing and presentation coaching is also provided.

Ph.D. students in the Field of Economics are required to take this year-long research seminar, and receive a grade of Satisfactory, in order to remain in good standing in the Ph.D. program. Students present and discuss each second-year paper, which must be completed before the semester opens and Economics 7850 meets for the first time. Students also present at least two additional papers or paper plans. These are intended to be part of the core of the student's thesis proposal, which must be given as part of the student's A Exam prior to the start of the fourth year of graduate study in the economics Ph.D. program. Economics 7851 ends with a mini-conference, attended by faculty and other Ph.D. students, in which each student makes a formal presentation in standard economics conference format, and each student discusses one of these presentations. Professional writing and presentation coaching is also provided.

Research workshop for members of the economics graduate field; featuring guest speakers.