Joseph E. Potter
Ph.D., Princeton University
Professor
Contact
 Email: joe@prc.utexas.edu
 Phone: 5124718341
 Office: CLA 2.620C
 Campus Mail Code: G1800
Biography
Joseph Potter's interests lie in the areas of reproductive health, population and development, and demographic estimation. Since the Fall of 2011, he has been leading a fiveyear project—The Texas Policy Evaluation Project (TxPEP) to evaluate the impact of legislation enacted by the Texas Legislature in 2011 and 2013 affecting both funding for family planning and access to abortion care. Earlier, Potter was Principal Investigator of the Border Contraceptive Access Study (BCAS), an NICHD funded project on oral contraceptive use along the USMexico border in El Paso, Texas. Data were collected between September 2006 and December 2008, and now available for distribution through ICPSR.
Since 2008, Potter’s publications have appeared in Population and Development Review, Demography, Population Studies, Population Research and Policy Review, Social Forces, the American Journal of Public Health, Contraception, Obstetrics & Gynecology, the New England Journal of Medicine, Perspectives on Sexual and Reproductive Health, Birth, Women’s Health Issues, the Journal of Health Care for the Poor and Underserved, Poverty & Public Policy, the Journal for the Scientific Study of Religion, Estudios Demográficos y Urbanos, Redes, the Revista Latinoamericana de Población, the Bulletin of Latin American Research, and the Revista Brasileira de Estudos de População.
Courses
SOC 391L • Basic Demograph Meth And Matls
46615 • Spring 2014
Meets MW 330pm500pm CLA 1.302A
This course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Demographic methods and population dynamics are widely applied in sociology, economics, criminology, epidemiology, and public healthin almost every field where the growth and structure of population matters, or where there are duration dependent phenomena that are best handled with life table methodology.
You will learn to calculate demographic rates, construct a life table, and make population projections. We will have make intensive use of the time that we have available, and rely on frequent homework exercises. The level at which the material can be covered depends, to some extent, on the interests and previous mathematical training of the participants in the course. Although there is no mathematical prerequisite, there is ample use of algebraic notation. Students with some calculus may use this notation as well. Anyone wanting to refresh their mathematics is encouraged to do so with Quick Calculus, by D. Kleppner and N. Ramsey (John Wiley, 1972, 1985, ..., paperback).
The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography, which participants may wish to consult for an alternative presentation of some material.
To check on everyone’s progress, there will be two midterm exams for this course, as well as weekly or biweekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the midterms will account for 55 percent. Much of the homework will be done in groups.
SOC 389K • Human Fertility
46340 • Fall 2013
Meets TH 300pm600pm CLA 0.124
This course is intended to provide a broad and indepth exposure to substantive, theoretical and methodological issues in the study of human fertility. The emphasis will be on attempts to explain the dramatic declines in fertility that have taken place in the last four decades, and the policy issues that are now at the forefront of national and international debates regarding reproductive health and population. Participants interested in an empirical exercise will have the opportunity to analyze a fertility and contraceptive prevalence survey recently conducted in a country of their choosing, or to conduct an analysis of the various data sets collected by both the Border Contraceptive Access Study http://www.prc.utexas.edu/bcas/index.html
and the Texas Policy Evaluation Project
http://www.utexas.edu/cola/orgs/txpep/
There is no prerequisite for this seminar. Participants without previous training in, or exposure to demographic measurement or techniques will, however, need to spend some time on their own gaining familiarity with basic measures such as the Total Fertility Rate. Evaluation will be based on several empirical exercises (10 percent), a preliminary bibliographic paper due about half way through the semester (30 percent), a presentation/discussion leadership related to one of the course topics (20 percent), and a final “paper” that builds on the preliminary paper and could add to it either an empirical application or a proposal for future research (40 percent). More details on these assignments will be forthcoming as the semester proceeds.
Everyone will be expected to have read the assigned papers before class, and to participate in the discussion. Often, but not always, some questions related to the readings will be distributed in advance.
SOC 391L • Basic Demograph Meth And Matls
45965 • Spring 2013
Meets MW 330pm500pm CLA 1.302F
Description
This course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Demographic methods and population dynamics are widely applied in sociology, economics, criminology, epidemiology, and public healthin almost every field where the growth and structure of population matters, or where there are duration dependent phenomena that are best handled with life table methodology.
You will learn to calculate demographic rates, construct a life table, and make population projections. We will have make intensive use of the time that we have available, and rely on frequent homework exercises. The level at which the material can be covered depends, to some extent, on the interests and previous mathematical training of the participants in the course. Although there is no mathematical prerequisite, there is ample use of algebraic notation. Students with some calculus may use this notation as well. Anyone wanting to refresh their mathematics is encouraged to do so with Quick Calculus, by D. Kleppner and N. Ramsey (John Wiley, 1972, 1985, ..., paperback).
Texts
The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography, which participants may wish to consult for an alternative presentation of some material.
Grading and Requirements
To check on everyone’s progress, there will be two midterm exams for this course, as well as weekly or biweekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the midterms will account for 55 percent. Much of the homework will be done in groups.
SOC 321K • Population Processes & Models
45540 • Fall 2012
Meets MWF 1100am1200pm BUR 480
Description:
This advanced course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Topics include demographic rates and measures, the life table, population projection, and indirect estimation of demographic rates from incomplete data.
Required Texts:
The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography(Guilford, 1990), which participants may wish to consult for an alternative presentation of some material. Many of the classroom presentations and homework exercises will use Excel.
Grading Policy:
There will be both a midterm and a final exam for this course, as well as weekly or biweekly homework assignments. The homework will account for 30 percent of the course grade, the midterm will account for 30 percent, and the final exam for 40 percent.
Prerequisites:
While there are no formal prerequisites for this course, some mathematical background is necessary, and a course in Calculus would be useful.
SOC 391L • Basic Demograph Meth And Matls
45760 • Spring 2012
Meets MW 1230pm200pm BUR 214
Description:
This course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Demographic methods and population dynamics are widely applied in sociology, economics, criminology, epidemiology, and public healthin almost every field where the growth and structure of population matters, or where there are duration dependent phenomena that are best handled with life table methodology.
You will learn to calculate demographic rates, construct a life table, and make population projections. We will have make intensive use of the time that we have available, and rely on frequent homework exercises. The level at which the material can be covered depends, to some extent, on the interests and previous mathematical training of the participants in the course. Although there is no mathematical prerequisite, there is ample use of algebraic notation. Students with some calculus may use this notation as well. Anyone wanting to refresh their mathematics is encouraged to do so with Quick Calculus, by D. Kleppner and N. Ramsey (John Wiley, 1972, 1985, ..., paperback).
Texts:
The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography, which participants may wish to consult for an alternative presentation of some material.
Grading and requirements:
To check on everyone’s progress, there will be two midterm exams for this course, as well as weekly or biweekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the midterms will account for 55 percent. Much of the homework will be done in groups.
SOC 389K • Human Fertility
45545 • Fall 2011
Meets T 300pm600pm MAI 1704
(also listed as LAS 381)
This course is intended to provide a broad and indepth exposure to substantive, theoretical and methodological issues in the study of human fertility. The emphasis will be on attempts to explain the dramatic declines in fertility that have taken place in the last three decades in countries such as Brazil, Mexico, Thailand, Spain, Italy, and the countries of the former Soviet Union, as well as the relative stability of fertility in the countries of Northern Europe and the United States. It will also address the policy issues that are now at the forefront of national and international debates regarding reproductive health and population, as well as the likely course of fertility in various settings. Participants interested in an empirical exercise will have the opportunity to analyze a fertility and contraceptive prevalence survey recently conducted in a country of their choosing, or in the analysis of a prospective survey of oral contraceptive use along the USMexico border in El Paso, Texas.
There is no prerequisite for this seminar. Participants without previous training in, or exposure to demographic measurement or techniques will, however, need to spend some time on their own gaining familiarity with basic measures such as the Total Fertility Rate. Evaluation will be based on several empirical exercises (10 percent), a preliminary bibliographic paper due about half way through the semester (30 percent), a presentation/discussion leadership related to one of the course topics (20 percent), and a final “paper” that builds on the preliminary paper and could add to it either an empirical application or a proposal for future research (40 percent). More details on these assignments will be forthcoming as the semester proceeds.
Everyone will be expected to have read the assigned papers before class, and to participate in the discussion. Often, but not always, some questions related to the readings will be distributed in advance.
SOC 384M • Evaluation Of Social Policy
46244 • Spring 2011
Meets F 900am1200pm MAI 1704
(also listed as LAS 381)
coming soon
SOC 391L • Basic Demograph Meth And Matls
46310 • Spring 2011
Meets MW 1230pm200pm BUR 214
Description:
This course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Demographic methods and population dynamics are widely applied in sociology, economics, criminology, epidemiology, and public healthin almost every field where the growth and structure of population matters, or where there are duration dependent phenomena that are best handled with life table methodology.
You will learn to calculate demographic rates, construct a life table, and make population projections. We will have make intensive use of the time that we have available, and rely on frequent homework exercises. The level at which the material can be covered depends, to some extent, on the interests and previous mathematical training of the participants in the course. Although there is no mathematical prerequisite, there is ample use of algebraic notation. Students with some calculus may use this notation as well. Anyone wanting to refresh their mathematics is encouraged to do so with Quick Calculus, by D. Kleppner and N. Ramsey (John Wiley, 1972, 1985, ..., paperback).
Texts:
The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography, which participants may wish to consult for an alternative presentation of some material.
Grading:
To check on everyone’s progress, there will be two midterm exams for this course, as well as weekly or biweekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the midterms will account for 55 percent.
SOC 389K • Training Smnr In Demography
SOC 384M • Eval Of Social Pol In Lat Amer
46520 • Spring 2010
Meets F 9001200 MAI 1704
(also listed as LAS 381)
SOCIAL POLICY EVALUATION
SOC 384M (46520)
Spring 2010
Prof. Joseph E. Potter Population Research Center
(joe@prc.utexas.edu) BUR 520
_________________________________________________________________
This PhDlevel methods course offers an introduction to the practical application of microeconomic principles and cuttingedge statistical techniques to evaluating social policy, program, and treatment effects. The substantive focus will be on programs in health, education, welfare, and workforce training. Students will be invited to work through a series of concrete program evaluations conducted for a number of international and national organizations ranging from the World Bank and the InterAmerican Development Bank, to the governments of Brazil, Mexico, Kenya, Indonesia, and more. While the course does touch on costbenefit analysis (prospective evaluation before a program is in place), the primary focus is on the design and execution of program evaluations (the assessment of ongoing programs or of programs after the fact). Key features of the course include the following:
 Treatment of the formal logic of experimental and quasiexperimental research design
 Multivariate statistical tools (distance measures, cluster analysis, factor analysis)
 Managing large databases
 Acquiring some mastery of the Stata statistical analysis package
 Statistical techniques for dealing with selection bias and other commonly encountered threats to internal validity
 And much more…
Readings draw from the literature on program evaluation, quasiexperimental design, and the emerging field of microeconometrics. While oftentimes challenging, these developments in statistical methodology have important implications on the way we conduct public policy analysis. Students will write occasional commentaries on realworld studies and analyze large realworld datasets.
The core textbook for this course is the newly published:
S. Khandker, G. Koolwal, & H. Samad (2010), Handbook on Impact Evaluation: Quantitative Methods and Practices, The World Bank
Students willl be evaluated in terms of the quality of class participation, inclass presentations, fortnightly takehome exercises, and performance on two takehome examinations.
Topical Overview
 Central theme of the course
 The microeconometrics of evaluating policy, program, and treatment effects
 Substantive foci of the course
 The formal principles of social science research design
 Statistical analysis of nonrandom samples
 Selection biases and other endogeneities
 Problems of missing data
 Truncated or censored data
 Advanced tools for exploiting the power of panel datasets
 Working with large, complex, and messy datasets
 Appreciating the power and sophistication of the Stata statistical software package
 Conditional cash transfer (CCT) programs in Latin America
 Methods and tools
 Computerintensive statistical techniques
 Robust statistical estimators
 Differenceindifferences estimators
 Matching estimators
 Nonparametric and semiparametric regression
 Instrumental variable methods
 Maximum likelihood estimation
 Logit and probit models (binary, multinomial, and ordinal)
 Incidental truncation estimators
 Switching regressions
 Fixed and random effects models
 Hierarchical linear models
 Realworld case studies and datasets
 National Supported Work Demonstration project (USA)
 Balsakhi school tutoring program (India)
 PROGRESA education, nutrition, and health program (Mexico)
 Red de Protección Social program (Nicaragua)
 Bolsa Familia program (Brazil)
 The Job Training Partnership Act (USA)
 Indonesian Family Life Survey on midwifery (Indonesia)
 Seguro Popular de Salud program (Mexico)
COURSE OUTLINE AND READINGS
Week 1 (Jan 22): Introduction and Overview
 Random sampling, random assignment, and random variables
 Experimental vs quasiexperimental research
 The critical question of ex ante versus ex post control over the selection of observations and assignment to treatment
 The "Fundamental Evaluation Problem" and the challenges it poses to statisical analysis
 Testing the difference between two means: Review
 Seven ways to measure the standard error of the difference in sample means
 Introduction to the Stata statistical package
 KEY READINGS:
 W. Shadish, T. Cook, D. Campbell (2002), "Experiments and Generalized Causal Inference", Ch 1 in Experimental and QuasiExperimental Designs for Generalized Causal Inference
 H. Bloom (2005). Learning More from Social Experiments: Evolving Analytical Approaches, Ch. 1
 Handbook on Impact Evaluation, “Introduction to Stata”, skim Ch 11
Week 2 (Jan 29): Research Design in Randomized Experiments
 Internal and external validity: Hallmark issues in social policy research
 Standard notation for depicting research designs
 Bias due to selection, missing data, and failing to properly control for unobservables
 Translating the difference in means into the language of linear regression
 The "Difference in Differences" (DDIF) method for evaluating pretest/posttest control group designs
 Introduction to the National Supported Work (NSW) case
 KEY READINGS:
 Handbook on Impact Evaluation, Chs 23, Ch 5, and Ch 12
 B. Meyer (1995), "Natural and QuasiExperiments in Economics", Journal of Business and Economic Statistics, 13(2):151161
 D. Campbell and J. Stanley (1963), Experimental and QuasiExperimental Designs for Research (skim for highlights)
 Stata Lecture Packets 14 (browse as needed or desired)
Week 3 (Feb 5): The Econometrics of Program Evaluation
 Discussion: The NSW case
 Heteroskedasticityrobust and bootstrapped standard errors
 The regression discontinuity design
 Introduction to the Balsakhi case and dataset
 "Long" vs "Wide" dataset formats in Stata
 KEY READINGS:
 Handbook on Impact Evaluation, “Regression Discontinuity and Pipeline Methods”, Ch 7
 Stata User's Guide (Release 9), "Obtaining Robust Variance Estimates", pp.275280
 W. Trochim (2002), "The Regression Discontinuity Design" and related material available at: www.socialresearchmethods.net/research/RD/RD%20Intro.pdf
 The MIT Poverty Action Lab Policy Briefcase (2005), "From Schools to Learning: Meeting the Needs of Marginalized Children"
 A. Bannerjee, S. Cole, E. Duflo, & L. Linden (2004), "Remedying Education: Evidence from Two Randomized Experiments in India" (the "Balsakhi Case")
Week 4 (Feb 12): Randomized Experiments in the Developing World
 Discussion: The Balsakhi case
 Working with differenceindifference models
 Randomizing by groups rather than by individuals
 Adjusting standard errors for clustered observations
 Special practical challenges posed by social policy evaluation in the developing world
 More on the regression discontinuity design
 KEY READINGS:
 H. Bloom (2005), "Randomizing Groups to Evaluate PlaceBased Programs", Ch 4 in Learning More from Social Experiments
 E. Duflo & M. Kremer (2003), "Use of Randomization in the Evaluation of Development Effectiveness", MIT Department of Economics, prepared for the World Bank Operations Evaluation Department
 R. Wooldridge (2002), "SingleEquation Models under Other Sampling Schemes", pp. 128132 in Econometric Analysis of Cross Section and Panel Data
 G. Burtless (1995), "The Case for Randomized Field Trials in Economic and Policy Research", Journal of Economic Perspectives, 9(2):6384 [Supplemental Reading Only]
 M. Hudgens & M.E. Halloran (2008), "Toward Causal Inference With Interference", Journal of the American Statistical Association, 103(482):832842 [Supplemental Reading Only]
Week 5 (Feb 19): The PROGRESA Case, Part 1
 WrapUp: The Balsakhi case
 Introduction to the Progresa case
 Conditional cash transfer (CCT) programs
 The pragmatics of designing and implementing a largescale randomized social experiment in a development setting
 Politics and bureaucracy versus good social science
 KEY READINGS:
 E. RiosNeto (2008), "Pocket Book Poverty Alleviation", Americas Quarterly, pp. 6875
 S. Levy (2006), Progress Against Poverty: Sustaining Mexico's ProgresaOportunidades Program, Chs 12
 P. Bate (2008), "The Story Behind Oportunidades", IDB America at www.iadb.org/idbamerica/index.cfm?thisid=3049
 E. Skoufias (2001), " PROGRESA and its Impacts on the Human Capital and Welfare of Households in Rural Mexico: A Synthesis of the Results of an Evaluation by IFPRI", International Food Policy Research Institute (IFPRI)
 T.P. Schultz (2001), "School Subsidies for the Poor: Evaluating the Mexican PROGRESA Poverty Program", Yale University Economic Growth Center Discussion Paper No. 834
Week 6 (Feb 26): The PROGRESA Case, Part 2
 Discussion: The PROGRESA case
 The selection of treatments and controls
 The econometrics of evaluating the PROGRESA program
 Multinomial logit and probit modeling of PROGRESA outcomes
 KEY READINGS:
 E. Skoufias, B. Davis, & S. de la Vega (2001), "Targeting the Poor in Mexico: An Evaluation of the Selection of Households into PROGRESA", World Development, 29(10):17691784
 J. Hoddinott & E. Skoufias (2004), "The Impact of Progresa on Food Consumption", Economic Development and Cultural Change, 53(1):3760
 T. Liao (1994), “Multinomial Logit Models”, pp.4859 in Interpreting Probability Models
Week 7 (Mar 5): The Red de Protección Social (RPS) Case
 WrapUp: The Progresa case
 Did the greatest gains go to the poorest of the poor?
 The transferability of the PROGRESA program to other settings
 Introduction to the Red de Protección Social case
 Heterogeneity of program impacts: Introduction to quantile regression
 KEY READINGS:
 Handbook on Impact Evaluation, “Measuring Distributional Program Effects”, Ch 8
 J. Maluccio, et al (2005), “Red de Protección Social: Breaking the Cycle of Poverty”, International Food Policy Research Institute
 A. Dammert (2009), “Heterogeneous Impacts of Conditional Cast Transfers: Evidence from Nicaragua”, Economic Development and Cultural Change, 58(1):5383
Week 8: (Mar 12): Day before Spring Break
 This is a “slack timeslot” for our yettobe scheduled discussion of Brazil’s Bolsa Familia program. All other dates in the syllabus are likely to shift depending on the timing of our guest lecturer’s visit to UT.
 RPS assignment due
Week 9 (Mar 26): The Challenges of QuasiExperimental Research
and Introduction to NonParametric Matching Techniques
 Wrapup: Red de Protección Social case
 Assessing causality in quasiexperimental research: Creating counterfactuals to impute the missing potential outcomes for treatment and control
 Sidebar on cluster analysis and factor analysis
 Matching treatment observations to controls with multivariate distance measures: Onetoone matching, Onetomany matching
 Introduction to propensity scores and propensity score matching
 The contribution of Rosenbaum & Rubin (1983) to the “curse of dimensionality”
 The question of "common support" of the covariates associated with the treatment and control groups
 The average treatment effect on the population (ATE) versus the average treatment effect on the treated (ATT)
 Introduction to Stata's NNMATCH and PSMATCH2 routines
 Revisiting the National Supported Work (NSW) case
KEY READINGS:
 J. Currie (2003), "When Do We Really Know What We Think We Know?: Determining Causality", UCLA Department of Economics Working Paper
 R. Moffitt (2005), "Remarks on Causal Relationships in Population Research", Demography, 42(1):91108
 M. Ravallion (2001), "The Mystery of the Vanashing Benefits: Mr Speedy Analyst's Introduction to Evaluation", World Bank Economic Review, 15(1):115140
 Human Resource Development Canada [HRDC] (1998), "QuasiExperimental Evaluation"
 Handbook on Impact Evaluation, “Propensity Score Matching”, Ch 4
 A. Abadie, D. Drukker, J. Herr, & G. Imbens (2001), "Implementing Matching Estimators for Average Treatment Effects in Stata", The Stata Journal, 1(1):118
Week 10 (Apr 2): Virtues and Limitations of Matching Methods
 Discussion: The National Supported Work (NSW) case
 Risks in using propensity score matching
 Blocking on the propensity score
 Sensitivity analysis for matching estimators
 Introduction to the Bangladesh Microcredit case
 KEY READINGS:
 Handbook on Impact Evaluation, “Propensity Score Matching Technique”, Ch 13
 D. Peikes, L. Moreno, & S. Orzol (2008), "Propensity Score Matching: A Note of Caution for Evaluators of Social Programs", The American Statistician, 62(3):222232
 T. Nannicini (2007), "SimulationBased Sensitivity Analysis for Matching Estimators", The Stata Journal, 7(3):334348
 T. Cook, W. Shadish, & V. Wong (2008), “Three Conditions under Which Experiments and Observational Studies Produce Comparable Causal Estimates”, Journal of Policy Analysis and Management, 27(4):724750
 M. Caliendo and S. Kopeinig (2008), "Some Practical Guidance for the Implementation of Propensity Score Matching", Journal of Economic Surveys, 22(1):1:3172 (good reference; skim for highlights)
Week 11 (Apr 9): Further Ways to Exploit Propensity Scores
 Discussion: The Bangladesh Microcredit case
 Using the propensity score in place of the covariates in regression analysis
 Weighting outcomes by the propensity score
 Combining regression and matching methods
 Nonparametric and semiparametric regression estimators
 KEY READINGS:
 G. Imbens and J. Wooldridge (2009), “Recent Developments in the Econometrics of Program Evaluation”, Journal of Economic Literature, 47(1):586
 A comprehensive and authoritative (but fairly dense) review of the state of the art in the microeconometrics of program evaluation. Read pp. 3242 and skim the rest as desired.
 G. Imbens and J. Wooldridge (2009), “Recent Developments in the Econometrics of Program Evaluation”, Journal of Economic Literature, 47(1):586
Week 12 (Apr 16): Fixed/Random Effects Models in Program Evaluation
 Discussion: The NSW case
 Oneway and twoway fixed effects models: Controlling for the level effects of unobservables
 The relationship betweeen fixed effects and difference in differences
 Random effects models and empirical Bayes estimators
 Relationship between random effects models and robust/cluster adjustments for variance estimates
 Introduction to the Job Training Partnership Act (JTPA) case
 KEY READINGS:
 Handbook on Impact Evaluation, “DoubleDifference Method”, Ch 14
 J. Brüderl (2005), "Panel Data Analysis", Universität Mannheim Working Paper
 J. Frain (2008), “Stata Commands for Unobserved Effects Panel Data”, unpublished manuscript, Trinity College, Dublin
 [Review the logic of fixedeffects and randomeffects models in your favorite standard econometrics textbook]
Week 13 (Apr 23): More on Selection on Unobservables
 Discussion: The JTPA case
 Review of truncated and censored regression
 The Heckman procedure
 Switching regressions to control for selection bias in quasiexperiments: An extension of the Heckman procedure
 Application of the Heckman procedure to the NSW dataset
 A sidelight on dealing with missing data in evaluation studies
 Introduction to the Indonesian Family Live Survey case
 KEY READINGS:
 R. Berk (1983), "An Introduction to Sample Selection Bias in Sociological Data, American Sociological Review, 48(3):386398
 D. Powers (2005), "Censored Regression, Sample Selection, Endogenous Switching, and TreatmentEffect Regression", UT Dept of Sociology Working Paper
 J. Angrist & G. Imbens (1995), "TwoStage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity", Journal of the American Statistical Association, 90(430):431442 [Supplementary reading only]
Week 14 (Apr 30): Instrumental Variable Solutions to Problems of Bias
 Discussion: The Indonesian Midwives case
 Review of instrumental variables and twostage least squares regression in econometrics
 KEY READINGS:
 Handbook on Impact Evaluation, “Instrumental Variable Estimation”, Ch 6 and Ch 15
 E. Frankenberg and D. Thomas (2001), "Women's Health and Pregnancy Outcomes: Do Services Make a Difference?", Demography, 38(2):253265
 P. Ender (2004), "Instrumental Variables Regression", a tutorial using Stata, UCLA School of Education at www.gseis.ucla.edu/courses/ed231c/notes3/instrumental.html
 S. Black (1999), "Do Better Schools Matter? Parental Valuation of Elementary Education", Quarterly Journal of Economics, 114(2):577599
 W. Evans and D. Lien (2005), "Does Prenatal Care Improve Birth Outcomes? Evidence from the PAT Bus Strike", Journal of Econometrics, 125(12):207239
 J. Potter, C. Schmertmann, & S. Cavenaghi (2002), "Fertility and Development: Evidence from Brazil", Demography, 39(4):739761
Week 15 (May 7): WrapUp
 Introduction/Discussion: Mexico’s Seguro Popular de Salud case
 “Triple robustness” to minimize threats to internal validity
 The fuzzy regression discontinuity design
 KEY READINGS:
 G. King, et al (2007), “A ‘Politically Robust’ Experimental Design for Public Policy Evaluation, with Application to the Mexican Universal Health Insurance Program”, Journal of Policy Analysis and Management, 26(3):479506
 Handbook on Impact Evaluation, “Regression Discontinuity Design”, Ch 16
SOC 391L • Basic Demograph Meth And Matls
46585 • Spring 2010
Meets MW 1230pm200pm BUR 214
SOCIOLOGY 391 L
Unique No. 46585
Basic Demographic Methods and Materials
Spring Semester 2010
MonWeds 12:302:00 p.m., Burdine 214 Instructor: J. E. Potter
This course provides grounding in the principal techniques of demographic analysis together with an understanding of how mortality and fertility determine the growth and structure of human populations. Demographic methods and population dynamics are widely applied in sociology, economics, criminology, epidemiology, and public healthin almost every field where the growth and structure of population matters, or where there are duration dependent phenomena that are best handled with life table methodology.
You will learn to calculate demographic rates, construct a life table, and make population projections. Some of the classroom presentations and homework exercises will use Mathcad, a versatile and easy to learn computer program for working with formulas, numbers, text and graphs that is available in the lab in the Population Research Center, and available for purchase from the Campus Computer Store (I am exploring other options with the company).
Method: We will have make intensive use of the time that we have available, and rely on frequent homework exercises. The level at which the material can be covered depends, to some extent, on the interests and previous mathematical training of the participants in the course. Although there is no mathematical prerequisite, there is ample use of algebraic notation. Students with some calculus may use this notation as well. Anyone wanting to refresh their mathematics is encouraged to do so with Quick Calculus, by D. Kleppner and N. Ramsey (John Wiley, 1972, 1985, ..., paperback).
Reading List: The text for this course is Demography: Measuring and Modeling Population Processes by Samuel Preston, Patrick Heuveline, and Michel Guillot (Malden, Mass.: Blackwell, 2001). In addition to chapters from this text, some journal articles will be assigned to complement the text, either as background, or as additional material. A slightly more accessible basic text that corresponds fairly well to the subject matter we will cover is Colin Newell's Methods and Models in Demography, which participants may wish to consult for an alternative presentation of some material. Starred items on the reading list are required. Another text that is available on Bb as a pdf file is Kenneth W. Wachter’s Essential Demographic Methods (forthcoming).
Evaluation: To check on everyone’s progress, there will be two midterm exams for this course, as well as weekly or biweekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the midterms will account for 55 percent.
READING LIST AND SCHEDULE
1. Population, Rates and Standardization Jan. 20Feb. 3
*Lee, R. 2001. The Decline of Formal and Aggregate Analysis: Demography Abandons Its Core. Presented at the Annual Meeting of the PAA, 2001. (pdf file, 6 pages, available on BB)
*Preston et al. 2001, Chapters 1 & 2. Basic concepts and measures, Agespecific rates and probabilities.
Newell, Colin. 1988. Methods and Models in Demography. New York: The Guilford Press. Chapters 15.
Wachter, K. W. forthcoming. Chapters 1 & 2.
2. The Life Table Feb. 822
*Preston et al. 2001. Chapters 3 & 4: The Life Table and Single Decrement Processes, Multiple Decrement Processes
MIDTERM EXAM #1 Feb. 24
3. Population Dynamics Mar. 129
*Preston et al. 2001. Chapters 5, 6, and 7: Fertility and Reproduction, Population Projection, and the Stable Population Model.
*Arthur, W.B. 1981. Why a population converges to stability. American Mathematical Monthly 88(8): 557563.
Coale, A.J. 1972. The Growth and Structure of Human Populations. Princeton, N.J.: Princeton University Press. (See Chapters 13, pp. 365.)
Newell, Colin. 1988. op. cit. Chapters 911 & 15.
Dorn, H. 1950. Pitfalls in population forecasts and projections. Journal of the American Statistical Association 45: 311334.
MIDTERM EXAM #2 Mar. 31
4. Model Life Tables and Modeling Age Patterns of Fertility Apr. 514
*Preston et al. 2001. Chapter 9: Modeling Age Patterns of Vital Events.
*Wachter, K.W. forthcoming. Chapter 7, pp. 173177.
*Schmertmann, C. P. 2003. A system of model fertility schedules with graphically intuitive parameters. Demographic Research 9: 82110.
Coale, A.J.; and Demeny, P. 1983. Regional Model Life Tables and Stable Populations. Second Edition. New York: Academic Press. (See pp. 136.)
Newell, Colin. 1988. op. cit. Chapters 4, 5, 12 and 13.
Brass, W. 1971. On the scale of mortality. In: Biological Aspects of Demography, edited by W. Brass, pp. 69110. London: Taylor and Francis.
5. Indirect Estimation Apr. 1928
*Preston et al. 2001. Chapter 11. Indirect Estimation Methods.
Brass et al. 1968. The Demography of Tropical Africa (Princeton: Princeton U. Press), Chapter 3.
6. To be determined May 35
SOC 389K • Human Fertility
46700 • Fall 2009
Meets TH 300pm600pm MAI 1704
(also listed as LAS 381)
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