The aim of this page is to provide basic guidelines for Economic & Education PhD. students about "potential" courses to take. This information is based on our experience and is useful as a "starting point". Although we compromise to keep this section updated, you should always check the institutional information as well (like Econ, Stats, SIPA or PEPM).

Teachers College Class Schedule

Columbia Directory of Classes

Education

ITSF 4058 Economics of higher education. Thomas Bailey. Fall. Some economic and econometric background is very helpful. Two assignments and a final project are the course requirements. Syllabus

ITSF 4050 Economics of Education. Henry Levin. Fall. This course provides an overview of the major topics in the field such as rates of return to education, the education production function, and teacher labor markets. Four assignments, each of approximately 6 pages, are the course requirements. Syllabus

ITSF 4055 Resource Allocation in Education. Henry Levin. Spring. This course looks at cost-effectiveness analysis in education and examines the education production function in more detail. Four assignments, each of approximately 6 pages, are the course requirements.

ITSF 4155 Evaluating Educational Privatization & School Choice. Henry Levin. Spring. This course addresses the increasing emphasis on market-type choice systems including educational vouchers, for-profit educational firms, and charter schools. It places great emphasis on the theory of emerging empirical evidence underlying these developments in education. Syllabus

ITSF 4051 Education and Economic Development. Francisco Rivera-Batiz. Fall. The course provides an introductory survey of the links between education and economic development. One midterm and a final exam. Syllabus

ITSF 6050 Education and Economic Development. Advanced topics. Francisco
Rivera-Batiz
. Spring. Must take course for those interested in economic development. Advanced discussion of the links between education and economic development, including both theoretical frameworks and empirical models. Final paper required. Syllabus

ITSF 4057 Economics of urban and minority education. Francisco Rivera-Batiz. Spring.

ITSF 4060 The Latino population of the United States. Francisco Rivera-Batiz. Fall.

ITSF 4097 International and comparative studies in educational finance. Mun
Tsang. Fall. This is a course on international comparative studies in educational finance.  The contents of the course are focused on three themes: (1) the theory and policies of how nations in different parts of the world mobilize and allocate resources for education; (2) cross-national experience in the response to pressing issues in educational finance; and (3) methodologies for conducting international comparative studies in educational finance. The course is intended for both U.S. and international graduate students in education who may subsequently work as decision-makers, administrators, policy analysts, or researchers in a variety of educational organizations and institutions.  It is also relevant for other graduate students who will be engaged in development work, for example, as analysts or consultants of internationally oriented development organizations.

ITSF 5550 Workshop in economics and education. Levin and Bailey. This workshop is designed to get second year doctoral students in Economics and Education to produce research in a publishable form.  In particular, the workshop is designed so that each participant prepares an empirical paper of publishable quality that will ultimately be submitted to a journal. Participants who are not in EE, but with strong economic and econometric backgrounds, will also be considered for participation.  Permission of instructor is required. Students are expected to attend both in the Fall and Spring terms. However, it can only be taken for up to 3 credits. Student assessment will be based on the following: (1) one credit: preparation of a summary and criticism of three papers presented at the workshop; (2) two credits: preparation of a summary and criticism of six papers presented at the workshop; (3) three credits: writing and presenting a paper at the workshop. This course is a Pass-Fail course unless specifically discussed with the instructor.

ITSF 4151 Special Topics in Economics of Educaction: Microcroeconomics. Faculty. Fall

ITSF 4091. Comparative education. Lesley Bartlett and Gita Steiner-Khamsi. Fall. Introduction to theories in comparative education, cross-national comparative analysis, educational indicator research, educational transfer and borrowing, and relation between culture and education.

ORLH 4010 Purposes and policies of higher education. Gregory Anderson. Spring. An introduction to the U.S. system of higher education through an overview of the system and its history, a survey of the missions and purposes served by U.S. colleges and universities, and an investigation of some of the pressing policy questions now confronting those institutions.

ORLH 4031 Financial administration of higher education institutions
. Kevin Dougherty. Fall. The course is intended for those who will be involved in the budgeting process at colleges and universities. No previous financial training is required. The course is an introduction to business principles and their importance for decision making in higher education. Topics include budgeting, accounting, financial reporting, and planning.

ORLH 4040 The American college student. Kevin Dougherty. Fall. Reviews the demographic data about students, the changing relations of students to colleges, the diverse patterns of structure and function by which colleges individualize education and provide for student development, and the influence of colleges upon students.

HUDF 4021 - Sociology of education.

Economics

G6211 Microeconomic analysis I. Paolo Siconolfi and Massimiliano Amarante. Fall.

G6212 Microeconomic analysis II. Prajit K Dutta and Rajiv Sethi. Spring.

G6451 Economics of Labor I. Janet Currie. Fall.

G6452 Economics of Labor II. Till von Wachter. Spring. The course is part of a sequence of two courses constituting the labor field. This self-contained part focuses on recently developed empirical methods applied to core questions in labor economics. Familiarity with econometrics is required. Grade is based on one or two referee reports and empirical problems plus a final research proposal related to the course.

G6807 Public Finance III. Miguel Urquiola. Spring. The course surveys topics under the heading of Public Sector and Development Economics. Applications are in many areas, the most frequent being education. The final grade is based on four criteria: a referee report; presentation of a paper from the syllabus; presentation of research ideas/work in progress related to the course, and class attendance and participation. Students are strongly encouraged to take this course.

G6301 Economic Growth & Development I. Xavier Sala-i-Martin. Fall. Second year course in the Economic Program. The course basically covers Barro & Sala-i-Martin book "Economic Growth". One final exam at the end of the semester or a research paper are the main requirements. Syllabus

G6303 Economic Growth & Development II. Christian Pop-Eleches. Spring. The course examines the micro-economic development literature, with an emphasis on empirical applications. Good background books are Ray (1998) or Deaton (1997). Prof. Pop-Eleches requires short weekly responses on readings, a final presentation and a final exam.

Econometrics

W4330 Regression and Multilevel Models. Andrew Gelman. Fall. A second course in regression analysis at the MA of statistics. Most of the course covers multilevel regression. Prof. Gelman uses R and BUGS for computation and the course require weekly assignments, midterm and final exam.

4107 Statistical Inference. Various Professors. Fall and Spring. M.A.- level course in Statistics, background is statistics is assumed.

W4912 Multivariate Political Analysis. Gregory Wawro. Spring. Great course for those still with doubts about linear regressions models. Computations are in R and there are weekly assignments, a midterm and a final exam. Syllabus

G6412 Introduction to Econometrics II. Alexei Onatski. Spring. Must-take course. Good background in econometrics is required (or lot of time available to catch up!). Covers almost all the topics that you are suppose to know as Economist of Education. Four to six assignments theoretical and practical (using Matlab or STATA) problem sets, midterm and final exam.

W4291 Advance Topics in Quantitative Research. Gregory Wawro. Fall. The course cover in extent limited and qualitative dependent variable models and some longitudinal analysis. In this course, Prof. Wawro uses GAUSS for four assignments, a midterm and final take-home exams and a final project.

W4437 Time Series Analysis. Jiehua Chen. Syllabus

G6417 Econometrics III. Bernard Salanie. Fall. The main "informal" requirement for this course is Econometric II. The course covers topics in applied econometrics, both theory and applications from labor economics, finance, trade and public economics. Some homeworks and a final paper are required.

G6427 Topics in Econometrics I. Rajeev Dehejia. Fall. This course presents two main topics: causal inference and Bayesian methods. Econometric II is presupposed and can be taken sequentially with Econometric III. Advanced, but excellent and a very useful course. A final presentation is the course requirement. Currently taught by Dennis Kristensen and focuses on the application of large sample methods in deriving the asymptotic properties of nonlinear estimators and non and semiparametric methods

G6102 Statistical Modelling/Data Analysis II. Andrew Gelman. Spring. The course is essentially Applied Bayesian Statistics. PhD- level course in Statistics. Prof. Gelman uses R and BUGS for computation and the course require weekly assignments, a quiz, and final take-home exam.

U8990 Quantitative Program Evaluation. Fall. This goal of this course is to provide students with a basic knowledge of how to perform some more advanced statistical methods useful in answering policy questions using observational or experimental data. It will also allow them to more critically review research published that claims to answer causal policy questions.  The prerequisite is the first two semesters of quantitative analysis or the equivalent as approved by the instructor. The primary focus is on the challenge of answering causal questions, that is, those that take the form "Did A cause B?," using data that do not conform to a perfectly controlled randomized study.  Examples from real public policy studies will be used throughout the course to illustrate key ideas and methods.  First, we will explore how best to design a study to answer causal questions given the logistical and ethical constraints that exist.  Different philosophies of causation will be introduced.  We then discuss several approaches to drawing causal inferences from observational studies including propensity score matching, instrumental variables, difference in differences, fixed effects models and regression discontinuity designs.

T8510 Advanced Methods in Policy Analysis. Ron Mincy and Jane Waldfogel. Spring. The methods covered in this course will include randomized experiments, observational studies with extensive covariates, propensity score approaches, structural equation modeling, instrumental variables models, difference-in-difference models, fixed effects, and regression discontinuity approaches. Grade is based on reading summaries and an empirical paper. 

U6312 Applied Quantitative Analysis for International Affairs. Cornelia McCarthy. Spring. This course covers regression analysis using Wooldridge's Introductory Econometric book. Problem sets, midterm, final, and a project are the requirements of the course.

Courses at NYU

PhD students may take courses outside Columbia University through the Inter-University Consortium.

B30.3351 Applied Econometrics. William Greene. Fall. Topics to be studied include specification, estimation, and inference in the context of models that include then extend beyond the standard linear multiple regression framework. After a review of the linear model, we will develop the asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods. Inference techniques used in the linear regression framework such as t and F tests will be extended to include Wald, Lagrange multiplier and likelihood ratio and tests for nonnested hypotheses such as the Hausman specification test and Davidson and MacKinnon’s J test. Syllabus and class notes are available at the professor's webpage.

B55.9912 Econometric Analysis of Panel Data. William Greene. Spring. Topics to be studied include specification, estimation, and inference in the context of models that include individual (firm, person, etc.) effects.  We will  begin with a development of the standard linear regression model, then extend it to panel data settings involving 'fixed' and 'random' effects.  The asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models will be reviewed or developed as we proceed.. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods.  The linear model will be extended to dynamic models and recently developed GMM and instrumental variables techniques. The classical methods of maximum likelihood and GMM and Bayesian methods, expecially MCMC techniques, are applied to models with individual effects. The last third of the course will focus on nonlinear models.  Theoretical developments will focus on heterogeneity in models including random parameter variation, latent class (finite mixture) and 'mixed' and hierarchical models.  We will also visit the theory for  techniques for optimization in the setting of nonlinear models.  We will consider numerous applications from the literature, including static and dynamic regression models, heterogeneous parameters models (e.g., Fama-Macbeth), random parameter variation, and specific nonlinear models such as binary and multinomial choice and models for count data. Syllabus and class notes are available at the professor's webpage.

E10.2902 Financing Schools: Equity and Adequacy in Public Education. Sean Corcoran. This course introduces the concepts, structure, practice, economics, and public policy of elementary and secondary school finance in the United States. A particular focus of the course will be on the measurement of equity and adequacy in school funding and the individual state policies designed to meet these objectives. We will examine the causes and consequences of legislative and court-ordered finance reform, and their impact on the level and distribution of school spending, student achievement, and other educational outcomes. Syllabus is available at the professor's webpage.