Simultaneous Equation Models (SiEM)

Size: px
Start display at page:

Download "Simultaneous Equation Models (SiEM)"

Transcription

1 Simultaneous Equation Models (SiEM) Inter-University Consortium for Political and Social Research (ICPSR) Summer 2010 Sandy Marquart-Pyatt Department of Sociology Michigan State University This course considers systems of equations, drawing from two complementary approaches: the structural equation modeling with latent variables (SEM) literature and the econometrics literature (SiEM). In contrast to single equation models, these models have at least two equations. These simultaneous models can be grouped into two major types: recursive models, which do not create any special problems, and nonrecursive models, which require special treatment. For each of these major types, we will discuss the specification, identification, estimation, and assessment of these systems of simultaneous equations. Nonrecursive models introduce the problem of identification, or how to establish that the parameters of the model are estimable. These models also require alternative estimation techniques. As time permits, advanced topics including limited dependent variables, measurement error, and handling longitudinal data will be covered. Students should have a good understanding of multiple regression and matrix algebra. Most of the readings are drawn from four econometric texts: Greene, William H Econometric Analysis (6th ed.). Upper Saddle River, NJ: Prentice Hall. Gujarati, Damodar Basic Econometrics (5th ed.). New York: McGraw-Hill. (4 th ed in parentheses) Johnston, J. and J. DiNardo Econometric Methods 4th ed.. New York: McGraw- Hill. (Note: pages for Johnston, J. Econometric Methods 3 rd ed. (in parentheses)). Kmenta, Jan Elements of Econometrics (2nd ed.). New York: Macmillan Additional readings are drawn from the following structural equation modeling (SEM) texts: Bollen, Kenneth Structural Equations with Latent Variables. New York: Wiley. Kaplan, David Structural Equation Modeling: Foundations and Extensions. Thousand Oaks, CA: SAGE. All of the readings are available in the summer program library in the Newberry House. There will be approximately 6 assignments. Due dates of assignments will be announced in class. We will also be discussing application papers as appropriate to recursive and nonrecursive models (listed on last page of syllabus). Lab sessions will be announced in class.

2 Topics and I. Introduction to Simultaneous Equation Models a. A brief introduction to simultaneous equation models II: Review of the Classical Linear Regression model a. Review of matrix algebra Bollen, Kenneth A Structural Equations with Latent Variables. New York: Wiley. Appendix A. OR Gill, Jeff Essential Mathematics for Political and Social Research. Cambridge University Press. Chapters 3 and 4. OR Fox, John A Mathematical Primer for Social Statistics. SAGE Publications, Inc. QASS. Chapter 1, Section 1.1 pp and Section 1.4 pp OR Johnston and DiNardo: pp b. Classical linear regression model Gujarati: ch.4 Greene: ch.2 (ch. 6) Johnston & Dinardo: ch.3 (ed 3: ch 5) Note: for further review, read Gujarati ch.1-3 & 6, or Johnston &DiNardo chp.1-2, etc. first. III: Overview of simultaneous equation models Recursive vs. nonrecursive models; path diagrams/equations/matrices; reduced vs. structural form; direct, indirect and total effects. Gujarati: chp.18 Bollen: pp.32-34; Kmenta: 13.1 or Greene: (earlier editions of Greene 16.1, 16.2) IV: Recursive models a. Specification Kenny, David Correlation and Causality. Wiley. p (chap 2) Gujarati: p. 764 Johnston & DiNardo: pp (ed 3: ) Kmenta: pp

3 IV: Recursive models (cont.) b. Identification Bollen: p Kenny: p , Greene: 13.3 c. Estimation Gujarati: p Johnston: p (ed. 4: ) Kmenta: p. 720 d. Decomposition of effects Bollen: pp Fox, John Effect Analysis in Structural Equation Models. Sociological Methods and Research 9(1): 3-14 and Sobel, Michael "Direct and Indirect Effects in Structural Equation Models." pp in J. Scott Long (ed.) Common Problems/Proper Solutions: Avoiding Error in Quantitative Research. Newbury Park, CA: Sage. Defining mediation** (**see extended list on z: drive). Baron, Reuben M., and David A. Kenny The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology 51(6): *Classic* MacKinnon, David P. and Amanda Fairchild Current Directions in Mediation Analysis. Current Directions in Psychological Science 18(1): And references therein! Optional Reading: Sobel, Michael Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models. Sociological Methodology 13: Sobel, Michael Some new results on indirect effects and their standard errors in covariance structure models. Sociological Methodology 16: Preacher, Kristopher and Andrew Hayes Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models. Behavior Research Methods 40(3):

4 V: SUR (seemingly unrelated regressions) models Greene: 10.2, Kmenta: 12.3 Example: Sampson, Robert J Urban Black Violence: The Effect of Male Joblessness and Family Disruption. American Journal of Sociology 93(2): VI: Nonrecursive simultaneous equation models a. Specification. Reading: Gujarati: b. Identification Gujarati: chp Greene: Rigdon, Edward E "A Necessary and Sufficient Identification Rule for Structural Models Estimated in Practice." Multivariate Behavioral Research 30: c. Estimation: ILS, 2SLS, 3SLS, ML Reading: Gujarati: 20.1 c1. Indirect least squares Gujarati: 20.3 Johnston & DiNardo: pp. 314 (ed 3: ) c2. Two Stage Least Squares, aka 2SLS Gujarati: 20.4, 20.5 Greene: 13.4, , and Kmenta: pp Examples: Bollen, Kenneth A., and Robert W. Jackman Political Democracy and the Size Distribution of Income. American Sociological Review 50: Brehm, John and Wendy Rahn "Individual-level evidence for the causes and consequences of social capital." American Journal of Political Science 41:

5 VI: Nonrecursive simultaneous equation models (cont.) c3. 3SLS Johnston: pp Kmenta: pp Greene 13.6, c4. MLE Greene: d. Comparison of Estimation Methods Reading: Greene: 13.7 Kmenta: pp e. Decomposition of Effects Bollen: pp Fox, J "Effect Analysis in Structural Equation Models." Sociological Methods and Research 9:3-28. Bollen, Kenneth A "Total, Direct, and Indirect Effects in Structural Equation Models." pp in C.C. Clogg, ed., Sociological Methodology Washington D.C.: American Sociological Association. VII. Assessment of models a. Equation by equation a1. Endogeneity tests: Gujarati: Greene: 13.8 Hausman, J. A "Specification Tests in Econometrics." Econometrica 6: a2. Assessment of Instruments Bound, John, David A. Jaeger, and Regina M. Baker Problems with Instrumental Variables Estimation When the Correlation Between the Instruments and the Endogenous Explanatory Variable is Weak. Journal of the American Statistical Association 90(430): Hausman, J. A Specification and Estimation of Simultaneous Equation Models. Pp in Handbook of Econometrics, vol. 1, edited by Z. Griliches and M.D. Intriligator. New York: North-Holland.

6 Optional reading** (see extended list on z: drive): Bartels, Larry M "Instrumental and 'Quasi-Instrumental' Variables." American Journal of Political Science 35: Baum, Christopher, Mark Schaffer, and Steven Stillman Instrumental Variables and GMM: Estimation and Testing. Stata Journal 3(1):1-31. Murray, Michael P "Avoiding Invalid Instruments and Coping with Weak Instruments." Journal of Economic Perspectives, 20(4): Kirby, James B. and Kenneth A. Bollen Using Instrumental Variable Tests to Evaluate Model Specification in Latent Variable Structural Equation Models. Sociological Methodology 39(1): b. Global goodness of fit statistics for overidentified models Bollen: pp Kaplan, David Structural Equation Modeling: Foundations and Extensions. Thousand Oaks, CA: SAGE Publications. pp Hu, Li-tze and Peter M. Bentler Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modeling 6(1):1-55. Additional Topics: (covered as time permits) Modeling change Finkel, Steven E Causal Analysis with Panel Data. Sage. Optional Reading: Kessler, Ronald C. and David F. Greenberg Linear panel analysis: Models of quantitative change. New York: Academic. [Classic textbook on longitudinal models] Consequences of measurement error Reading: Bollen: chp.5, Greene: 9.5

7 Simultaneous equations with limited dependent variables Winship, Christopher and Robert D. Mare "Structural Equations and Path Analysis for Discrete Data." American Journal of Sociology 89: Muthen, Bengt A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika 49: Bollen 1989: pp Optional readings: Maddala 5.1, 5.8, chapter 7 and chapter 8. MacKinnon, David P. and James H. Dwyer "Estimating mediated effects in prevention studies." Evaluation Review 17: [Discusses estimating mediation with a dichotomous mediator] Example: Bollen, Kenneth A., David K. Guilkey, and Thomas A. Mroz "Binary Outcomes and Endogenous Explanatory Variables: Tests and Solutions with an Application to the Demand for Contraceptive Use in Tunisia." Demography 32: Standard Errors of indirect effects Sobel, Michael E Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models. Sociological Methodology 13: Sobel, Michael E Some New Results on Indirect Effects and Their Standard Errors in Covariance Structure Models. Sociological Methodology 16: Sobel, Michael E Direct and Indirect Effects in Linear Structural Equation Models. Pp in Common Problems/Proper Solutions: Avoiding Error in Quantitative Research, edited by J. Scott Long. Sage. Preacher, Kristopher and Andrew Hayes Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models. Behavior Research Methods 40(3): Power Issues in Simultaneous Equations Bielby, William T., and Ross L. Matsueda Statistical Power in Nonrecursive Linear Models. Sociological Methodology 21: Matsueda, Ross and William Bielby Statistical Power in Covariance Structure Models. Pp in N.B. Tuma, ed. Sociological Methodology Washington, D.C.: American Sociological Association.

8 Lagged Endogenous Variables with autocorrelation Kmenta: 13.5 Fair, Ray C The Estimation of Simultaneous Equation Models with Lagged Endogenous Variables and First Order Serially Correlated Errors. Econometrica 38(3): Using simultaneous equations to handle spatial effects Land, Kenneth C., and Glenn Deane On the Large-Sample Estimation of Regression Models with Spatial- Or Network-Effects Terms: A Two-Stage Least Squares Approach. Sociological Methodology 22: Autocorrelation or heteroskedasticity in simultaneous equations Kmenta: 13.5 Harvey, A. C., and G. D. A. Phillips Testing for Serial Correlation in Simultaneous Equation Models. Econometrica 48(3): Application Papers: SUR: Presentation on Wednesday July 28. Sampson, Robert J Urban Black Violence: The Effect of Male Joblessness and Family Disruption. American Journal of Sociology 93(2): Nonrecursive: Presentation on Tuesday, Aug 3. Bollen, Kenneth A., and Robert W. Jackman Political Democracy and the Size Distribution of Income. American Sociological Review 50: Nonrecursive: Presentation on Thursday, Aug 5. Brehm, John and Wendy Rahn "Individual-level evidence for the causes and consequences of social capital." American Journal of Political Science 41: Issues to consider in your reading of the application paper 1. Describe what the paper is trying to do, highlighting the theoretical model and how it is implemented statistically. How well is this accomplished? 2. In what ways do complexities encountered by the authors intersect with issues we ve discussed in class?

Simultaneous Equation Models

Simultaneous Equation Models Simultaneous Equation Models Sandy Marquart-Pyatt Utah State University This course considers systems of equations. In contrast to single equation models, simultaneous equation models include more than

More information

Supplemental material to accompany Preacher and Hayes (2008)

Supplemental material to accompany Preacher and Hayes (2008) Supplemental material to accompany Preacher and Hayes (2008) Kristopher J. Preacher University of Kansas Andrew F. Hayes The Ohio State University The multivariate delta method for deriving the asymptotic

More information

1. GENERAL DESCRIPTION

1. GENERAL DESCRIPTION Econometrics II SYLLABUS Dr. Seung Chan Ahn Sogang University Spring 2003 1. GENERAL DESCRIPTION This course presumes that students have completed Econometrics I or equivalent. This course is designed

More information

INTRODUCTION TO STRUCTURAL EQUATION MODELS

INTRODUCTION TO STRUCTURAL EQUATION MODELS I. Description of the course. INTRODUCTION TO STRUCTURAL EQUATION MODELS A. Objectives and scope of the course. B. Logistics of enrollment, auditing, requirements, distribution of notes, access to programs.

More information

Econometrics I G (Part I) Fall 2004

Econometrics I G (Part I) Fall 2004 Econometrics I G31.2100 (Part I) Fall 2004 Instructor: Time: Professor Christopher Flinn 269 Mercer Street, Room 302 Phone: 998 8925 E-mail: christopher.flinn@nyu.edu Homepage: http://www.econ.nyu.edu/user/flinnc

More information

Longitudinal Data Analysis. Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago

Longitudinal Data Analysis. Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago Longitudinal Data Analysis Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago Course description: Longitudinal analysis is the study of short series of observations

More information

New York University Department of Economics. Applied Statistics and Econometrics G Spring 2013

New York University Department of Economics. Applied Statistics and Econometrics G Spring 2013 New York University Department of Economics Applied Statistics and Econometrics G31.1102 Spring 2013 Text: Econometric Analysis, 7 h Edition, by William Greene (Prentice Hall) Optional: A Guide to Modern

More information

Econometric Analysis of Cross Section and Panel Data

Econometric Analysis of Cross Section and Panel Data Econometric Analysis of Cross Section and Panel Data Jeffrey M. Wooldridge / The MIT Press Cambridge, Massachusetts London, England Contents Preface Acknowledgments xvii xxiii I INTRODUCTION AND BACKGROUND

More information

ADVANCED QUANTITATIVE METHODS READING LIST. January LOGISTIC/PROBIT & RELATED REGRESSION METHODS

ADVANCED QUANTITATIVE METHODS READING LIST. January LOGISTIC/PROBIT & RELATED REGRESSION METHODS ADVANCED QUANTITATIVE METHODS READING LIST January 1999 OUTLINE 1. LINEAR REGRESSION 2. LOGISTIC/PROBIT & RELATED REGRESSION METHODS 3. STRUCTURAL EQUATION MODELS 4. LONGITUDINAL DATA ANALYSIS 5. MULTILEVEL

More information

APEC 8212: Econometric Analysis II

APEC 8212: Econometric Analysis II APEC 8212: Econometric Analysis II Instructor: Paul Glewwe Spring, 2014 Office: 337a Ruttan Hall (formerly Classroom Office Building) Phone: 612-625-0225 E-Mail: pglewwe@umn.edu Class Website: http://faculty.apec.umn.edu/pglewwe/apec8212.html

More information

Course title SD206. Introduction to Structural Equation Modelling

Course title SD206. Introduction to Structural Equation Modelling 10 th ECPR Summer School in Methods and Techniques, 23 July - 8 August University of Ljubljana, Slovenia Course Description Form 1-2 week course (30 hrs) Course title SD206. Introduction to Structural

More information

An Introduction to Causal Mediation Analysis. Xu Qin University of Chicago Presented at the Central Iowa R User Group Meetup Aug 10, 2016

An Introduction to Causal Mediation Analysis. Xu Qin University of Chicago Presented at the Central Iowa R User Group Meetup Aug 10, 2016 An Introduction to Causal Mediation Analysis Xu Qin University of Chicago Presented at the Central Iowa R User Group Meetup Aug 10, 2016 1 Causality In the applications of statistics, many central questions

More information

St. Xavier s College Autonomous Mumbai. Syllabus For 4 th Semester Core and Applied Courses in. Economics (June 2019 onwards)

St. Xavier s College Autonomous Mumbai. Syllabus For 4 th Semester Core and Applied Courses in. Economics (June 2019 onwards) St. Xavier s College Autonomous Mumbai Syllabus For 4 th Semester Core and Applied Courses in Economics (June 2019 onwards) Contents: Theory Syllabus for Courses: A.ECO.4.01 Macroeconomic Analysis-II A.ECO.4.02

More information

Chapter 5. Introduction to Path Analysis. Overview. Correlation and causation. Specification of path models. Types of path models

Chapter 5. Introduction to Path Analysis. Overview. Correlation and causation. Specification of path models. Types of path models Chapter 5 Introduction to Path Analysis Put simply, the basic dilemma in all sciences is that of how much to oversimplify reality. Overview H. M. Blalock Correlation and causation Specification of path

More information

Outline

Outline 2559 Outline cvonck@111zeelandnet.nl 1. Review of analysis of variance (ANOVA), simple regression analysis (SRA), and path analysis (PA) 1.1 Similarities and differences between MRA with dummy variables

More information

Time Series Analysis

Time Series Analysis Time Series Analysis Genie Baker University of Oregon Course description: This course introduces statistical methods appropriate when sample observations are not independent, but rather, are logically

More information

Structural Equations with Latent Variables

Structural Equations with Latent Variables Structural Equations with Latent Variables Structural Equations with Latent Variables KENNETH A. BOLLEN Department of Sociology The University of North Carolina at Chapel Hill Chapel Hill, North Carolina

More information

G. S. Maddala Kajal Lahiri. WILEY A John Wiley and Sons, Ltd., Publication

G. S. Maddala Kajal Lahiri. WILEY A John Wiley and Sons, Ltd., Publication G. S. Maddala Kajal Lahiri WILEY A John Wiley and Sons, Ltd., Publication TEMT Foreword Preface to the Fourth Edition xvii xix Part I Introduction and the Linear Regression Model 1 CHAPTER 1 What is Econometrics?

More information

Lecture: Simultaneous Equation Model (Wooldridge s Book Chapter 16)

Lecture: Simultaneous Equation Model (Wooldridge s Book Chapter 16) Lecture: Simultaneous Equation Model (Wooldridge s Book Chapter 16) 1 2 Model Consider a system of two regressions y 1 = β 1 y 2 + u 1 (1) y 2 = β 2 y 1 + u 2 (2) This is a simultaneous equation model

More information

Longitudinal Analysis. Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago

Longitudinal Analysis. Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago Longitudinal Analysis Michael L. Berbaum Institute for Health Research and Policy University of Illinois at Chicago Course description: Longitudinal analysis is the study of short series of observations

More information

Longitudinal and Panel Data: Analysis and Applications for the Social Sciences. Table of Contents

Longitudinal and Panel Data: Analysis and Applications for the Social Sciences. Table of Contents Longitudinal and Panel Data Preface / i Longitudinal and Panel Data: Analysis and Applications for the Social Sciences Table of Contents August, 2003 Table of Contents Preface i vi 1. Introduction 1.1

More information

UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS. Minutes of Meeting

UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS. Minutes of Meeting UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS Minutes of Meeting Subject : B.A. (Hons) Economics Sixth Semester (2014) Course : 26 - Applied Econometrics Date of Meeting : 10 th

More information

Conducting Multivariate Analyses of Social, Economic, and Political Data

Conducting Multivariate Analyses of Social, Economic, and Political Data Conducting Multivariate Analyses of Social, Economic, and Political Data ICPSR Summer Program Concordia Workshops May 25-29, 2015 Dr. Harold D. Clarke University of Texas, Dallas hclarke@utdallas.edu Dr.

More information

Conceptual overview: Techniques for establishing causal pathways in programs and policies

Conceptual overview: Techniques for establishing causal pathways in programs and policies Conceptual overview: Techniques for establishing causal pathways in programs and policies Antonio A. Morgan-Lopez, Ph.D. OPRE/ACF Meeting on Unpacking the Black Box of Programs and Policies 4 September

More information

Introduction to Eco n o m et rics

Introduction to Eco n o m et rics 2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Introduction to Eco n o m et rics Third Edition G.S. Maddala Formerly

More information

Economics 308: Econometrics Professor Moody

Economics 308: Econometrics Professor Moody Economics 308: Econometrics Professor Moody References on reserve: Text Moody, Basic Econometrics with Stata (BES) Pindyck and Rubinfeld, Econometric Models and Economic Forecasts (PR) Wooldridge, Jeffrey

More information

Simultaneous (and Recursive) Equation Systems. Robert Dixon Department of Economics at the University of Melbourne

Simultaneous (and Recursive) Equation Systems. Robert Dixon Department of Economics at the University of Melbourne Simultaneous (and Recursive) Equation Systems Robert Dixon Department of Economics at the University of Melbourne In their History of Macroeconometric Model-Building, Bodkin, Klein and Marwah give "pride

More information

SC705: Advanced Statistics Instructor: Natasha Sarkisian Class notes: Introduction to Structural Equation Modeling (SEM)

SC705: Advanced Statistics Instructor: Natasha Sarkisian Class notes: Introduction to Structural Equation Modeling (SEM) SC705: Advanced Statistics Instructor: Natasha Sarkisian Class notes: Introduction to Structural Equation Modeling (SEM) SEM is a family of statistical techniques which builds upon multiple regression,

More information

Abstract Title Page. Title: Degenerate Power in Multilevel Mediation: The Non-monotonic Relationship Between Power & Effect Size

Abstract Title Page. Title: Degenerate Power in Multilevel Mediation: The Non-monotonic Relationship Between Power & Effect Size Abstract Title Page Title: Degenerate Power in Multilevel Mediation: The Non-monotonic Relationship Between Power & Effect Size Authors and Affiliations: Ben Kelcey University of Cincinnati SREE Spring

More information

But Wait, There s More! Maximizing Substantive Inferences from TSCS Models Online Appendix

But Wait, There s More! Maximizing Substantive Inferences from TSCS Models Online Appendix But Wait, There s More! Maximizing Substantive Inferences from TSCS Models Online Appendix Laron K. Williams Department of Political Science University of Missouri and Guy D. Whitten Department of Political

More information

Analysis of Panel Data: Introduction and Causal Inference with Panel Data

Analysis of Panel Data: Introduction and Causal Inference with Panel Data Analysis of Panel Data: Introduction and Causal Inference with Panel Data Session 1: 15 June 2015 Steven Finkel, PhD Daniel Wallace Professor of Political Science University of Pittsburgh USA Course presents

More information

, PhD Student NYU, Department of Politics

, PhD Student NYU, Department of Politics 030 " " " 030 amakarov@hseru PhD Student NYU Department of Politics denisstukal@nyuedu ogasparyan@hseru rkamalova@hseru) 07 07 07 07 Н я я я я 030 030 Ц ) ; 3 3 К ) 7 030 ) 3 030 ) ; ) ) 3 ) 3 ) ) ) 3

More information

Introduction to Econometrics

Introduction to Econometrics Introduction to Econometrics T H I R D E D I T I O N Global Edition James H. Stock Harvard University Mark W. Watson Princeton University Boston Columbus Indianapolis New York San Francisco Upper Saddle

More information

Heteroscedasticity. Jamie Monogan. Intermediate Political Methodology. University of Georgia. Jamie Monogan (UGA) Heteroscedasticity POLS / 11

Heteroscedasticity. Jamie Monogan. Intermediate Political Methodology. University of Georgia. Jamie Monogan (UGA) Heteroscedasticity POLS / 11 Heteroscedasticity Jamie Monogan University of Georgia Intermediate Political Methodology Jamie Monogan (UGA) Heteroscedasticity POLS 7014 1 / 11 Objectives By the end of this meeting, participants should

More information

Syllabus. By Joan Llull. Microeconometrics. IDEA PhD Program. Fall Chapter 1: Introduction and a Brief Review of Relevant Tools

Syllabus. By Joan Llull. Microeconometrics. IDEA PhD Program. Fall Chapter 1: Introduction and a Brief Review of Relevant Tools Syllabus By Joan Llull Microeconometrics. IDEA PhD Program. Fall 2017 Chapter 1: Introduction and a Brief Review of Relevant Tools I. Overview II. Maximum Likelihood A. The Likelihood Principle B. The

More information

Multivariate Modeling with Stata and R

Multivariate Modeling with Stata and R Multivariate Modeling with Stata and R ICPSR Summer Program Workshops in Social Science Research Concordia University May 2016 Instructors: Harold Clarke, Ashbel Smith Professor, School of Economic, Political

More information

New developments in structural equation modeling

New developments in structural equation modeling New developments in structural equation modeling Rex B Kline Concordia University Montréal Set A: SCM A1 UNL Methodology Workshop A2 A3 A4 Topics o Graph theory o Mediation: Design Conditional Causal A5

More information

Campbell, D.T. and Stanley, J.C. (1963, 1966). Experimental and Quasi-Experimental Designs for Research. Rand McNally, Chicago, Illinois.

Campbell, D.T. and Stanley, J.C. (1963, 1966). Experimental and Quasi-Experimental Designs for Research. Rand McNally, Chicago, Illinois. General Mostly Harmless Econometrics by Angrist (MIT labor economist) and Jorn-Steffen Pischke has excellent discussions of key econometric issues. This is very intuitive and helpful for thinking about

More information

UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS. Minutes of Meeting

UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS. Minutes of Meeting UNIVERSITY OF DELHI DELHI SCHOOL OF ECONOMICS DEPARTMENT OF ECONOMICS Minutes of Meeting Subject : B.A. (Hons) Economics (CBCS) Fifth Semester (2017) DSEC Course : ii) Applied Econometrics Date of Meeting

More information

Introduction. Consider a variable X that is assumed to affect another variable Y. The variable X is called the causal variable and the

Introduction. Consider a variable X that is assumed to affect another variable Y. The variable X is called the causal variable and the 1 di 23 21/10/2013 19:08 David A. Kenny October 19, 2013 Recently updated. Please let me know if your find any errors or have any suggestions. Learn how you can do a mediation analysis and output a text

More information

Autocorrelation. Jamie Monogan. Intermediate Political Methodology. University of Georgia. Jamie Monogan (UGA) Autocorrelation POLS / 20

Autocorrelation. Jamie Monogan. Intermediate Political Methodology. University of Georgia. Jamie Monogan (UGA) Autocorrelation POLS / 20 Autocorrelation Jamie Monogan University of Georgia Intermediate Political Methodology Jamie Monogan (UGA) Autocorrelation POLS 7014 1 / 20 Objectives By the end of this meeting, participants should be

More information

Comparing Change Scores with Lagged Dependent Variables in Models of the Effects of Parents Actions to Modify Children's Problem Behavior

Comparing Change Scores with Lagged Dependent Variables in Models of the Effects of Parents Actions to Modify Children's Problem Behavior Comparing Change Scores with Lagged Dependent Variables in Models of the Effects of Parents Actions to Modify Children's Problem Behavior David R. Johnson Department of Sociology and Haskell Sie Department

More information

Departamento de Economía Universidad de Chile

Departamento de Economía Universidad de Chile Departamento de Economía Universidad de Chile GRADUATE COURSE SPATIAL ECONOMETRICS November 14, 16, 17, 20 and 21, 2017 Prof. Henk Folmer University of Groningen Objectives The main objective of the course

More information

A NOTE ON THE EFFECT OF THE MULTICOLLINEARITY PHENOMENON OF A SIMULTANEOUS EQUATION MODEL

A NOTE ON THE EFFECT OF THE MULTICOLLINEARITY PHENOMENON OF A SIMULTANEOUS EQUATION MODEL Journal of Mathematical Sciences: Advances and Applications Volume 15, Number 1, 2012, Pages 1-12 A NOTE ON THE EFFECT OF THE MULTICOLLINEARITY PHENOMENON OF A SIMULTANEOUS EQUATION MODEL Department of

More information

New developments in structural equation modeling

New developments in structural equation modeling New developments in structural equation modeling Rex B Kline Concordia University Montréal Set B: Mediation A UNL Methodology Workshop A2 Topics o Mediation: Design requirements Conditional process modeling

More information

The Effect of Monetary Policy on Market Value of Stocks and Bonds Analytical Study for a Sample of Arab Gulf Countries

The Effect of Monetary Policy on Market Value of Stocks and Bonds Analytical Study for a Sample of Arab Gulf Countries - - Awsjwejatee@yahoo.com - - VAR AIC. The Effect of Monetary Policy on Market Value of Stocks and Bonds Analytical Study for a Sample of Arab Gulf Countries Rafiaa I. Al hamdani (PhD) Lecturer Department

More information

Correspondence Analysis of Longitudinal Data

Correspondence Analysis of Longitudinal Data Correspondence Analysis of Longitudinal Data Mark de Rooij* LEIDEN UNIVERSITY, LEIDEN, NETHERLANDS Peter van der G. M. Heijden UTRECHT UNIVERSITY, UTRECHT, NETHERLANDS *Corresponding author (rooijm@fsw.leidenuniv.nl)

More information

Instrumental Variables and GMM: Estimation and Testing. Steven Stillman, New Zealand Department of Labour

Instrumental Variables and GMM: Estimation and Testing. Steven Stillman, New Zealand Department of Labour Instrumental Variables and GMM: Estimation and Testing Christopher F Baum, Boston College Mark E. Schaffer, Heriot Watt University Steven Stillman, New Zealand Department of Labour March 2003 Stata Journal,

More information

A Course on Advanced Econometrics

A Course on Advanced Econometrics A Course on Advanced Econometrics Yongmiao Hong The Ernest S. Liu Professor of Economics & International Studies Cornell University Course Introduction: Modern economies are full of uncertainties and risk.

More information

2005 ICPSR SUMMER PROGRAM REGRESSION ANALYSIS III: ADVANCED METHODS

2005 ICPSR SUMMER PROGRAM REGRESSION ANALYSIS III: ADVANCED METHODS 2005 ICPSR SUMMER PROGRAM REGRESSION ANALYSIS III: ADVANCED METHODS William G. Jacoby Department of Political Science Michigan State University June 27 July 22, 2005 This course will take a modern, data-analytic

More information

12E016. Econometric Methods II 6 ECTS. Overview and Objectives

12E016. Econometric Methods II 6 ECTS. Overview and Objectives Overview and Objectives This course builds on and further extends the econometric and statistical content studied in the first quarter, with a special focus on techniques relevant to the specific field

More information

Misspecification in Nonrecursive SEMs 1. Nonrecursive Latent Variable Models under Misspecification

Misspecification in Nonrecursive SEMs 1. Nonrecursive Latent Variable Models under Misspecification Misspecification in Nonrecursive SEMs 1 Nonrecursive Latent Variable Models under Misspecification Misspecification in Nonrecursive SEMs 2 Abstract A problem central to structural equation modeling is

More information

Online Appendix to Yes, But What s the Mechanism? (Don t Expect an Easy Answer) John G. Bullock, Donald P. Green, and Shang E. Ha

Online Appendix to Yes, But What s the Mechanism? (Don t Expect an Easy Answer) John G. Bullock, Donald P. Green, and Shang E. Ha Online Appendix to Yes, But What s the Mechanism? (Don t Expect an Easy Answer) John G. Bullock, Donald P. Green, and Shang E. Ha January 18, 2010 A2 This appendix has six parts: 1. Proof that ab = c d

More information

U26120 Researching the Social World 1 (Semester 1)

U26120 Researching the Social World 1 (Semester 1) U26120 Researching the Social World 1 (Semester 1) View Online Aldridge, Alan and Levine, Kenneth (2001a) Surveying the social world: principles and practice in survey research. Buckingham: Open University

More information

Testing and Interpreting Interaction Effects in Multilevel Models

Testing and Interpreting Interaction Effects in Multilevel Models Testing and Interpreting Interaction Effects in Multilevel Models Joseph J. Stevens University of Oregon and Ann C. Schulte Arizona State University Presented at the annual AERA conference, Washington,

More information

Small-Area Population Forecasting Using a Spatial Regression Approach

Small-Area Population Forecasting Using a Spatial Regression Approach Small-Area Population Forecasting Using a Spatial Regression Approach Guangqing Chi and Paul R. Voss Applied Population Laboratory Department of Rural Sociology University of Wisconsin-Madison Extended

More information

Paloma Bernal Turnes. George Washington University, Washington, D.C., United States; Rey Juan Carlos University, Madrid, Spain.

Paloma Bernal Turnes. George Washington University, Washington, D.C., United States; Rey Juan Carlos University, Madrid, Spain. China-USA Business Review, January 2016, Vol. 15, No. 1, 1-13 doi: 10.17265/1537-1514/2016.01.001 D DAVID PUBLISHING The Use of Longitudinal Mediation Models for Testing Causal Effects and Measuring Direct

More information

Package crossreg. February 19, 2015

Package crossreg. February 19, 2015 Package crossreg February 19, 2015 Type Package Title Confidence intervals for crossover points of two simple regression lines Version 1.0 Date 2014-07-08 Author Maintainer This package

More information

Instrumental Variables Estimation in Stata

Instrumental Variables Estimation in Stata Christopher F Baum 1 Faculty Micro Resource Center Boston College March 2007 1 Thanks to Austin Nichols for the use of his material on weak instruments and Mark Schaffer for helpful comments. The standard

More information

Specifying Latent Curve and Other Growth Models Using Mplus. (Revised )

Specifying Latent Curve and Other Growth Models Using Mplus. (Revised ) Ronald H. Heck 1 University of Hawai i at Mānoa Handout #20 Specifying Latent Curve and Other Growth Models Using Mplus (Revised 12-1-2014) The SEM approach offers a contrasting framework for use in analyzing

More information

Revision list for Pearl s THE FOUNDATIONS OF CAUSAL INFERENCE

Revision list for Pearl s THE FOUNDATIONS OF CAUSAL INFERENCE Revision list for Pearl s THE FOUNDATIONS OF CAUSAL INFERENCE insert p. 90: in graphical terms or plain causal language. The mediation problem of Section 6 illustrates how such symbiosis clarifies the

More information

Lecture Notes on Measurement Error

Lecture Notes on Measurement Error Steve Pischke Spring 2000 Lecture Notes on Measurement Error These notes summarize a variety of simple results on measurement error which I nd useful. They also provide some references where more complete

More information

The Stated Preference Approach to Environmental Valuation

The Stated Preference Approach to Environmental Valuation The Stated Preference Approach to Environmental Valuation Volume I: Foundations, Initial Development, Statistical Approaches Edited by Richard T. Carson University of California, San Diego, USA ASHGATE

More information

Modeling Mediation: Causes, Markers, and Mechanisms

Modeling Mediation: Causes, Markers, and Mechanisms Modeling Mediation: Causes, Markers, and Mechanisms Stephen W. Raudenbush University of Chicago Address at the Society for Resesarch on Educational Effectiveness,Washington, DC, March 3, 2011. Many thanks

More information

Structural equation modeling

Structural equation modeling Structural equation modeling Rex B Kline Concordia University Montréal E ISTQL Set E SR models CFA vs. SR o Factors: CFA: Exogenous only SR: Exogenous + endogenous E2 CFA vs. SR o Factors & indicators:

More information

SOCI 221 Basic Concepts in Sociology

SOCI 221 Basic Concepts in Sociology SOCI 221 Basic Concepts in Sociology Session 3 Sociology and Other Related Social Science Disciplines Lecturer: Dr. Samson Obed Appiah, Dept. of Sociology Contact Information: soappiah@ug.edu.gh College

More information

A Comparison of Methods to Test Mediation and Other Intervening Variable Effects

A Comparison of Methods to Test Mediation and Other Intervening Variable Effects Psychological Methods Copyright 2002 by the American Psychological Association, Inc. 2002, Vol. 7, No. 1, 83 104 1082-989X/02/$5.00 DOI: 10.1037//1082-989X.7.1.83 A Comparison of Methods to Test Mediation

More information

Time Series Analysis

Time Series Analysis Time Series Analysis Professor Genie Baker University of Oregon Course description: This course introduces statistical methods appropriate when sample observations are not independent, but rather, are

More information

St. Xavier s College Autonomous Mumbai T.Y.B.A. Syllabus For 6 th Semester Courses in Statistics (June 2016 onwards)

St. Xavier s College Autonomous Mumbai T.Y.B.A. Syllabus For 6 th Semester Courses in Statistics (June 2016 onwards) St. Xavier s College Autonomous Mumbai T.Y.B.A Syllabus For 6 th Semester Courses in Statistics (June 2016 onwards) Contents: Theory Syllabus for Courses: A.STA.6.01 Probability & Sampling Distributions

More information

Econometrics I. Professor William Greene Stern School of Business Department of Economics 1-1/40. Part 1: Introduction

Econometrics I. Professor William Greene Stern School of Business Department of Economics 1-1/40. Part 1: Introduction Econometrics I Professor William Greene Stern School of Business Department of Economics 1-1/40 http://people.stern.nyu.edu/wgreene/econometrics/econometrics.htm 1-2/40 Overview: This is an intermediate

More information

Instrumental variables estimation using heteroskedasticity-based instruments

Instrumental variables estimation using heteroskedasticity-based instruments Instrumental variables estimation using heteroskedasticity-based instruments Christopher F Baum, Arthur Lewbel, Mark E Schaffer, Oleksandr Talavera Boston College/DIW Berlin, Boston College, Heriot Watt

More information

Simultaneous Equations Models: what are they and how are they estimated

Simultaneous Equations Models: what are they and how are they estimated Simultaneous Equations Models: what are they and how are they estimated Omar M.G. Keshk April 30, 2003 1 Simultaneity Or Reciprocal Causation in Political Science Suppose that a researcher believes that

More information

Nonrecursive Models Highlights Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised April 6, 2015

Nonrecursive Models Highlights Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised April 6, 2015 Nonrecursive Models Highlights Richard Williams, University of Notre Dame, https://www3.nd.edu/~rwilliam/ Last revised April 6, 2015 This lecture borrows heavily from Duncan s Introduction to Structural

More information

Using EViews Vox Principles of Econometrics, Third Edition

Using EViews Vox Principles of Econometrics, Third Edition Using EViews Vox Principles of Econometrics, Third Edition WILLIAM E. GRIFFITHS University of Melbourne R. CARTER HILL Louisiana State University GUAY С LIM University of Melbourne JOHN WILEY & SONS, INC

More information

Methods for Integrating Moderation and Mediation: Moving Forward by Going Back to Basics. Jeffrey R. Edwards University of North Carolina

Methods for Integrating Moderation and Mediation: Moving Forward by Going Back to Basics. Jeffrey R. Edwards University of North Carolina Methods for Integrating Moderation and Mediation: Moving Forward by Going Back to Basics Jeffrey R. Edwards University of North Carolina Research that Examines Moderation and Mediation Many streams of

More information

Introductory Econometrics

Introductory Econometrics Based on the textbook by Wooldridge: : A Modern Approach Robert M. Kunst robert.kunst@univie.ac.at University of Vienna and Institute for Advanced Studies Vienna October 16, 2013 Outline Introduction Simple

More information

Mplus Code Corresponding to the Web Portal Customization Example

Mplus Code Corresponding to the Web Portal Customization Example Online supplement to Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67,

More information

ECONOMICS DEPARTMENT, UNIVERSITY OF UTAH

ECONOMICS DEPARTMENT, UNIVERSITY OF UTAH ECONOMETRICS FIELD EXAM SUMMER 2001, PART I ECONOMICS DEPARTMENT, UNIVERSITY OF UTAH Part 1 of this exam (Hans Ehrbar) has three subparts a. b, and c. Part 2 is provided by Peter Philips. For part 1a (a

More information

Econometrics. Week 8. Fall Institute of Economic Studies Faculty of Social Sciences Charles University in Prague

Econometrics. Week 8. Fall Institute of Economic Studies Faculty of Social Sciences Charles University in Prague Econometrics Week 8 Institute of Economic Studies Faculty of Social Sciences Charles University in Prague Fall 2012 1 / 25 Recommended Reading For the today Instrumental Variables Estimation and Two Stage

More information

Computationally Efficient Estimation of Multilevel High-Dimensional Latent Variable Models

Computationally Efficient Estimation of Multilevel High-Dimensional Latent Variable Models Computationally Efficient Estimation of Multilevel High-Dimensional Latent Variable Models Tihomir Asparouhov 1, Bengt Muthen 2 Muthen & Muthen 1 UCLA 2 Abstract Multilevel analysis often leads to modeling

More information

Mediation question: Does executive functioning mediate the relation between shyness and vocabulary? Plot data, descriptives, etc. Check for outliers

Mediation question: Does executive functioning mediate the relation between shyness and vocabulary? Plot data, descriptives, etc. Check for outliers Plot data, descriptives, etc. Check for outliers A. Nayena Blankson, Ph.D. Spelman College University of Southern California GC3 Lecture Series September 6, 2013 Treat missing i data Listwise Pairwise

More information

Causal Inference Using Nonnormality Yutaka Kano and Shohei Shimizu 1

Causal Inference Using Nonnormality Yutaka Kano and Shohei Shimizu 1 Causal Inference Using Nonnormality Yutaka Kano and Shohei Shimizu 1 Path analysis, often applied to observational data to study causal structures, describes causal relationship between observed variables.

More information

Unpublished manuscript. Power to Detect 1. Running head: THE POWER TO DETECT MEDIATED EFFECTS

Unpublished manuscript. Power to Detect 1. Running head: THE POWER TO DETECT MEDIATED EFFECTS Unpublished manuscript. Power to Detect 1 Running head: THE POWER TO DETECT MEDIATED EFFECTS The Power to Detect Mediated Effects in Experimental and Correlational Studies David P. MacKinnon and Chondra

More information

Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case

Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case Arthur Lewbel Boston College Original December 2016, revised July 2017 Abstract Lewbel (2012)

More information

Christopher Dougherty London School of Economics and Political Science

Christopher Dougherty London School of Economics and Political Science Introduction to Econometrics FIFTH EDITION Christopher Dougherty London School of Economics and Political Science OXFORD UNIVERSITY PRESS Contents INTRODU CTION 1 Why study econometrics? 1 Aim of this

More information

Estimation, Detection, and Identification CMU 18752

Estimation, Detection, and Identification CMU 18752 Estimation, Detection, and Identification CMU 18752 Graduate Course on the CMU/Portugal ECE PhD Program Spring 2008/2009 Instructor: Prof. Paulo Jorge Oliveira pjcro @ isr.ist.utl.pt Phone: +351 21 8418053

More information

BGPE course: Regional and Urban Economics

BGPE course: Regional and Urban Economics BGPE course: Regional and Urban Economics Instructor: Gilles Duranton Email: duranton@wharton.upenn.edu Web: http://real.wharton.upenn.edu/~duranton/index.html Objectives: This course will explore a range

More information

Small-Sample Methods for Cluster-Robust Inference in School-Based Experiments

Small-Sample Methods for Cluster-Robust Inference in School-Based Experiments Small-Sample Methods for Cluster-Robust Inference in School-Based Experiments James E. Pustejovsky UT Austin Educational Psychology Department Quantitative Methods Program pusto@austin.utexas.edu Elizabeth

More information

STRUCTURAL EQUATION MODELS WITH LATENT VARIABLES

STRUCTURAL EQUATION MODELS WITH LATENT VARIABLES STRUCTURAL EQUATION MODELS WITH LATENT VARIABLES Albert Satorra Departament d Economia i Empresa Universitat Pompeu Fabra Structural Equation Modeling (SEM) is widely used in behavioural, social and economic

More information

Bootstrap Approach to Comparison of Alternative Methods of Parameter Estimation of a Simultaneous Equation Model

Bootstrap Approach to Comparison of Alternative Methods of Parameter Estimation of a Simultaneous Equation Model Bootstrap Approach to Comparison of Alternative Methods of Parameter Estimation of a Simultaneous Equation Model Olubusoye, O. E., J. O. Olaomi, and O. O. Odetunde Abstract A bootstrap simulation approach

More information

Role and treatment of categorical variables in PLS Path Models for Composite Indicators

Role and treatment of categorical variables in PLS Path Models for Composite Indicators Role and treatment of categorical variables in PLS Path Models for Composite Indicators Laura Trinchera 1,2 & Giorgio Russolillo 2! 1 Dipartimento di Studi sullo Sviluppo Economico, Università degli Studi

More information

Structural equation modeling

Structural equation modeling Structural equation modeling Rex B Kline Concordia University Montréal ISTQL Set B B1 Data, path models Data o N o Form o Screening B2 B3 Sample size o N needed: Complexity Estimation method Distributions

More information

Methodological Issues in Quantitative Research on Race and Ethnicity

Methodological Issues in Quantitative Research on Race and Ethnicity Methodological Issues in Quantitative Research on Race and Ethnicity Phillip Bowman University of Michigan Co-Instructors: Angela Ebreo, Tyrone Forman, John Garcia, & Ray Massenburg Workshop: 2 credits.

More information

Case of single exogenous (iv) variable (with single or multiple mediators) iv à med à dv. = β 0. iv i. med i + α 1

Case of single exogenous (iv) variable (with single or multiple mediators) iv à med à dv. = β 0. iv i. med i + α 1 Mediation Analysis: OLS vs. SUR vs. ISUR vs. 3SLS vs. SEM Note by Hubert Gatignon July 7, 2013, updated November 15, 2013, April 11, 2014, May 21, 2016 and August 10, 2016 In Chap. 11 of Statistical Analysis

More information

Chapter 8. Models with Structural and Measurement Components. Overview. Characteristics of SR models. Analysis of SR models. Estimation of SR models

Chapter 8. Models with Structural and Measurement Components. Overview. Characteristics of SR models. Analysis of SR models. Estimation of SR models Chapter 8 Models with Structural and Measurement Components Good people are good because they've come to wisdom through failure. Overview William Saroyan Characteristics of SR models Estimation of SR models

More information

Purpose and Objectives. Grading. Office Hours. G-83 McCarty Mon. & Wed. 3:00-4:30. Web Site

Purpose and Objectives. Grading. Office Hours. G-83 McCarty Mon. & Wed. 3:00-4:30. Web Site ECONOMETRIC METHODS I AEB 6571 Spring 2007 Instructor: R. D. Emerson remerson@ufl.edu 392-1881 x 316 Purpose and Objectives The purpose of the course is to introduce the student to current econometric

More information

Statistical Methods for Causal Mediation Analysis

Statistical Methods for Causal Mediation Analysis Statistical Methods for Causal Mediation Analysis The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Accessed Citable

More information

Causal Inference Lecture Notes: Causal Inference with Repeated Measures in Observational Studies

Causal Inference Lecture Notes: Causal Inference with Repeated Measures in Observational Studies Causal Inference Lecture Notes: Causal Inference with Repeated Measures in Observational Studies Kosuke Imai Department of Politics Princeton University November 13, 2013 So far, we have essentially assumed

More information

NIH Public Access Author Manuscript Psychol Methods. Author manuscript; available in PMC 2010 February 10.

NIH Public Access Author Manuscript Psychol Methods. Author manuscript; available in PMC 2010 February 10. NIH Public Access Author Manuscript Published in final edited form as: Psychol Methods. 2002 March ; 7(1): 83. A Comparison of Methods to Test Mediation and Other Intervening Variable Effects David P.

More information

SEM REX B KLINE CONCORDIA D. MODERATION, MEDIATION

SEM REX B KLINE CONCORDIA D. MODERATION, MEDIATION ADVANCED SEM REX B KLINE CONCORDIA D1 D. MODERATION, MEDIATION X 1 DY Y DM 1 M D2 topics moderation mmr mpa D3 topics cpm mod. mediation med. moderation D4 topics cma cause mediator most general D5 MMR

More information