### Profile

### External Links

# Joseph E. Potter

### — Ph.D., Princeton University

*
Professor *

#### Contact

- E-mail: joe@prc.utexas.edu
- Phone: 512-471-8341
- 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 five-year 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 US-Mexico 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*.

### SOC 391L • Basic Demograph Meth And Matls

######
46615 •
Spring 2014

Meets
MW 330pm-500pm CLA 1.302A

show 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 health--in 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 mid-term exams for this course, as well as weekly or bi-weekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the mid-terms will account for 55 percent. Much of the homework will be done in groups.

### SOC 389K • Human Fertility

######
46340 •
Fall 2013

Meets
TH 300pm-600pm CLA 0.124

show description
This course is intended to provide a broad and in-depth 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 330pm-500pm CLA 1.302F

show description
**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 health--in 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 mid-term exams for this course, as well as weekly or bi-weekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the mid-terms will account for 55 percent. Much of the homework will be done in groups.

### SOC 321K • Population Processes & Models

######
45540 •
Fall 2012

Meets
MWF 1100am-1200pm BUR 480

show description
**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 mid-term and a final exam for this course, as well as weekly or bi-weekly homework assignments. The homework will account for 30 percent of the course grade, the mid-term 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 1230pm-200pm BUR 214

show description
**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 health--in 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 mid-term exams for this course, as well as weekly or bi-weekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the mid-terms will account for 55 percent. Much of the homework will be done in groups.

### SOC 389K • Human Fertility

######
45545 •
Fall 2011

Meets
T 300pm-600pm MAI 1704

(also listed as
LAS 381 )

show description
This course is intended to provide a broad and in-depth 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 US-Mexico 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 900am-1200pm MAI 1704

(also listed as
LAS 381 )

show description
coming soon

### SOC 391L • Basic Demograph Meth And Matls

######
46310 •
Spring 2011

Meets
MW 1230pm-200pm BUR 214

show description
**Description:**

*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 mid-term exams for this course, as well as weekly or bi-weekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the mid-terms will account for 55 percent.

### SOC 389K • Training Smnr In Demography

######
45710 •
Fall 2010

Meets
F 1030am-130pm BUR 214

show description
Offered on a CR/No CR basis only

### SOC 384M • Eval Of Social Pol In Lat Amer

######
46520 •
Spring 2010

Meets
F 900-1200 MAI 1704

(also listed as
LAS 381 )

show description
**SOCIAL POLICY EVALUATION**

**SOC 384M (46520)**

**Spring 2010**

** **

Prof. Joseph E. Potter Population Research Center

(joe@prc.utexas.edu) BUR 520

_________________________________________________________________

This PhD-level methods course offers an introduction to the practical application of microeconomic principles and cutting-edge 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 Inter-American Development Bank, to the governments of Brazil, Mexico, Kenya, Indonesia, and more. While the course does touch on cost-benefit analysis (*prospective* evaluation before a program is in place), the primary focus is on the design and execution of program evaluations (the assessment of on-going programs or of programs after the fact). Key features of the course include the following:

- Treatment of the formal logic of experimental and quasi-experimental 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, quasi-experimental 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 real-world studies and analyze large real-world 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, in-class presentations, fortnightly take-home exercises, and performance on two take-home 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 non-random 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**- Computer-intensive statistical techniques
- Robust statistical estimators
- Difference-in-differences estimators
- Matching estimators
- Non-parametric and semi-parametric 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

**Real-world 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 quasi-experimental 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 Quasi-Experimental 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

- W. Shadish, T. Cook, D. Campbell (2002), "Experiments and Generalized Causal Inference", Ch 1 in

**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 2-3, Ch 5, and Ch 12- B. Meyer (1995), "Natural and Quasi-Experiments in Economics",
*Journal of Business and Economic Statistics*, 13(2):151-161 - D. Campbell and J. Stanley (1963),
*Experimental and Quasi-Experimental Designs for Research*(skim for highlights) - Stata Lecture Packets 1-4 (browse as needed or desired)

**Week 3 (Feb 5): The Econometrics of Program Evaluation**

**Discussion: The NSW case**- Heteroskedasticity-robust 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.275-280- 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 difference-in-difference 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 Place-Based 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), "Single-Equation Models under Other Sampling Schemes", pp. 128-132 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):63-84 [Supplemental Reading Only] - M. Hudgens & M.E. Halloran (2008), "Toward Causal Inference With Interference",
*Journal of the American Statistical Association*, 103(482):832-842 [Supplemental Reading Only]

- H. Bloom (2005), "Randomizing Groups to Evaluate Place-Based Programs", Ch 4 in

**Week 5 (Feb 19): The PROGRESA Case, Part 1**

**Wrap-Up: The Balsakhi case****Introduction to the Progresa case**- Conditional cash transfer (CCT) programs
- The pragmatics of designing and implementing a large-scale randomized social experiment in a development setting
- Politics and bureaucracy versus good social science

- KEY READINGS:
- E. Rios-Neto (2008), "Pocket Book Poverty Alleviation",
*Americas Quarterly*, pp. 68-75 - S. Levy (2006),
*Progress Against Poverty: Sustaining Mexico's Progresa-Oportunidades Program*, Chs 1-2 - 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

- E. Rios-Neto (2008), "Pocket Book Poverty Alleviation",

**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):1769-1784 - J. Hoddinott & E. Skoufias (2004), "The Impact of Progresa on Food Consumption",
*Economic Development and Cultural Change*, 53(1):37-60 - T. Liao (1994), “Multinomial Logit Models”, pp.48-59 in
*Interpreting Probability Models*

- E. Skoufias, B. Davis, & S. de la Vega (2001), "Targeting the Poor in Mexico: An Evaluation of the Selection of Households into PROGRESA",

**Week 7 (Mar 5): The Red de Protección Social (RPS) Case**

**Wrap-Up: 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):53-83

** **

**Week 8: (Mar 12): ***Day before Spring Break*** **

*This is a “slack time-slot” for our yet-to-be 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 Quasi-Experimental Research**

** and Introduction to Non-Parametric Matching Techniques**

**Wrap-up: Red de Protección Social case**- Assessing causality in quasi-experimental 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: One-to-one matching, One-to-many 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):91-108 - M. Ravallion (2001), "The Mystery of the Vanashing Benefits: Mr Speedy Analyst's Introduction to Evaluation",
*World Bank Economic Review*, 15(1):115-140 - Human Resource Development Canada [HRDC] (1998), "Quasi-Experimental 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):1-18

**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):222-232 - T. Nannicini (2007), "Simulation-Based Sensitivity Analysis for Matching Estimators",
*The Stata Journal*, 7(3):334-348 - 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):724-750 - M. Caliendo and S. Kopeinig (2008), "Some Practical Guidance for the Implementation of Propensity Score Matching",
*Journal of Economic Surveys*, 22(1):1:31-72 (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
- Non-parametric and semi-parametric regression estimators

- KEY READINGS:
- G. Imbens and J. Wooldridge (2009), “Recent Developments in the Econometrics of Program Evaluation”,
*Journal of Economic Literature,*47(1):5-86- A comprehensive and authoritative (but fairly dense) review of the state of the art in the microeconometrics of program evaluation. Read pp. 32-42 and skim the rest as desired.

- G. Imbens and J. Wooldridge (2009), “Recent Developments in the Econometrics of Program Evaluation”,

**Week 12 (Apr 16): Fixed/Random Effects Models in Program Evaluation**

**Discussion: The NSW case**- One-way and two-way 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*, “Double-Difference 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 fixed-effects and random-effects 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 quasi-experiments: 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):386-398 - D. Powers (2005), "Censored Regression, Sample Selection, Endogenous Switching, and Treatment-Effect Regression", UT Dept of Sociology Working Paper
- J. Angrist & G. Imbens (1995), "Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity",
*Journal of the American Statistical Association*, 90(430):431-442 [Supplementary reading only]

- R. Berk (1983), "An Introduction to Sample Selection Bias in Sociological Data,

**Week 14 (Apr 30): Instrumental Variable Solutions to Problems of Bias**

**Discussion: The Indonesian Midwives case**- Review of instrumental variables and two-stage 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):253-265 - 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):577-599 - W. Evans and D. Lien (2005), "Does Prenatal Care Improve Birth Outcomes? Evidence from the PAT Bus Strike",
*Journal of Econometrics*, 125(1-2):207-239 - J. Potter, C. Schmertmann, & S. Cavenaghi (2002), "Fertility and Development: Evidence from Brazil",
*Demography*, 39(4):739-761

**Week 15 (May 7): Wrap-Up**

**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):479-506 *Handbook on Impact Evaluation*, “Regression Discontinuity Design”, Ch 16

- G. King, et al (2007), “A ‘Politically Robust’ Experimental Design for Public Policy Evaluation, with Application to the Mexican Universal Health Insurance Program”,

### SOC 391L • Basic Demograph Meth And Matls

######
46585 •
Spring 2010

Meets
MW 1230pm-200pm BUR 214

show description
SOCIOLOGY 391 L

Unique No. 46585

Basic Demographic Methods and Materials

Spring Semester 2010

** **

**Mon-Weds 12:30-2:00 p.m., Burdine 214 Instructor: J. E. Potter**

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 mid-term exams for this course, as well as weekly or bi-weekly homework assignments or problem sets. The homework will account for 45 percent of the course grade, and the mid-terms will account for 55 percent.

READING LIST AND SCHEDULE

1. __Population, Rates and Standardization__ __ Jan. 20-Feb. 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, Age-specific rates and probabilities.

Newell, Colin. 1988. __Methods and Models in Demography__. New York: The Guilford Press. Chapters 1-5.

Wachter, K. W. forthcoming. Chapters 1 & 2.

2. __The Life Table__ __Feb. 8-22__

*Preston et al. 2001. Chapters 3 & 4: The Life Table and Single Decrement Processes, Multiple Decrement Processes

MID-TERM EXAM #1 Feb. 24

3. __Population Dynamics__ __Mar. 1-29__

*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): 557-563.

Coale, A.J. 1972. __The Growth and Structure of Human Populations__. Princeton, N.J.: Princeton University Press. (See Chapters 1-3, pp. 3-65.)

Newell, Colin. 1988. __op. cit.__ Chapters 9-11 & 15.

Dorn, H. 1950. Pitfalls in population forecasts and projections. __Journal of the American Statistical Association__ 45: 311-334.

MID-TERM EXAM #2 Mar. 31

4. __Model Life Tables and Modeling Age Patterns of Fertility__ __Apr. 5-14__

*Preston et al. 2001. Chapter 9: Modeling Age Patterns of Vital Events.

*Wachter, K.W. forthcoming. Chapter 7, pp. 173-177.

*Schmertmann, C. P. 2003. A system of model fertility schedules with graphically intuitive parameters. __Demographic Research __9: 82-110.

Coale, A.J.; and Demeny, P. 1983. __Regional Model Life Tables and Stable Populations__. Second Edition. New York: Academic Press. (See pp. 1-36.)

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. 69-110. London: Taylor and Francis.

5. __Indirect Estimation__ __Apr. 19-28__

*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 3-5__

### SOC 389K • Human Fertility

######
46700 •
Fall 2009

Meets
TH 300pm-600pm MAI 1704

(also listed as
LAS 381 )

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