REP 531 Syllabus
“The art of the econometrician consists in finding the set of assumptions which are both sufficiently specific and sufficiently realistic to allow him or her to take the best possible advantage of the data available to him or her.”
E. Malinvaud. 1966. Statistical Methods of Econometrics. Amsterdam: North Holland, p. 514.
Why the conventional wisdom is so often wrong… How “experts”- from criminologists to real-estate agents to political scientists-bend the facts… Why knowing what to measure, and how to measure it, is the key to understanding modern life… What is “freakonomics,” anyway?
Steven D. Levitt and Stephen J. Dubner, Freakonomics. New York: William Morrow.
“Sometimes I just don’t know what’s going on, things are so strange and change so quickly, I’ll think I’ll go and lie down” Eeyore the Donkey.
Time: Tuesday and Thursday; 8:00-9:15 AM
Location: Winslow 201
Prerequisites: REP530, ECO530, or permission.
Instructor: Kathleen P. Bell, 200 Winslow Hall
Office hours: Tuesday and Thursday 1:30-3:00 PM. If you cannot come during these time periods, please email me to make an appointment.
The course provides an introduction to econometric techniques commonly used in applied micro-economics research. The course covers 8 broad topics: (1) seemingly unrelated regression; (2) simultaneous equations; (3) time-series data; (4) spatial data; (5) panel data; (6) nonlinear and maximum likelihood estimation; (7) qualitative dependent variables; and (8) limited dependent variables. The course emphasizes applications by linking theoretical textbook readings on techniques with journal articles featuring applications of these techniques.
The course has two objectives: (1) expose students to theories and applications of contemporary applied econometric techniques and (2) provide students with applied econometrics research skills.
Griffiths, W. E., R. C. Hill, and G. G. Judge. 1993. Learning and Practicing
Econometrics, John Wiley & Sons, New York, New York. (G)
Kennedy, P. 2003. A Guide to Econometrics, The MIT Press, Cambridge, MA. (K)
Haab, T.C. and K.E. McConnell. 2002. Valuing Environmental and Natural Resources: The Econometrics of Non-market Valuation, Edward Elgar Publishing. (HM)
Readings will be assigned from the course texts and professional applied economics and statistical journals. Refer to the detailed course schedule for more information on these readings. These readings are stored in PDF format in the REP531 class folder on the N Drive.
SAS and LIMDEP will be the primary course software packages. Additional software packages, including GeoDa, will be introduced, as necessary.
Letter grades will be assigned based on the following class work: homework assignments (60%) and research project (40%).
Students are expected to have completed the assigned reading prior to lecture.
Homework assignments will involve applied econometrics research. These assignments will require computer programming, analytical thinking, and communication skills. Late homework assignments will receive a grade of 0 (see absence/tardiness policy below for exceptions).
The research project serves as the opportunity for students to demonstrate their fulfillment of the course objectives. Students will begin their project by accessing and becoming familiar with an “economics” dataset. Using this dataset, students are required to pose and answer a relevant economics question by applying one of the techniques covered in class. Research project topics will require approval by the instructor. All students will prepare a short paper and give a brief presentation outlining the methods and findings of their projects.
Class Attendance Policy:
You are expected to attend all class sessions and to be prepared for class.
If a student wishes to receive credit for a late homework, its tardiness must be authorized. If illness is the reason for a late homework, please submit written documentation of this illness from the health center or a doctor to the instructor.
If you have a disability for which you may be requesting an accommodation, please contact either Professor Bell or Ann Smith, Director of Disability Services at their new location in East Annex, 581-2319, as early as possible in the term.
Reference Texts (suggested):
Allison, P. 1995. Survival Analysis Using the SAS System: A Practical Guide, SAS Institute.
Allison, P. 1999. Logistic Regression Using the SAS System: Theory and Application, SAS Institute.
Berndt, E.R. 1990. The Practice of Econometrics, Addison-Wesley.
Cameron, C. and P.K. Trivedi. 1998. Regression Analysis of Count Data, Cambridge University Press.
Chatfield, C. 2003. The Analysis of Time Series: An Introduction, 6th edition, Champman and Hall.
Greene, W.H. 2003. Econometric Analysis, Prentice Hall.
Hamilton, J.D. 1994. Time Series Analysis, Princeton University Press.
Judge, G.G.,Hill, R.C., Griffiths, W.E., Lutkepohl, H. and T.C. Lee. 1988. Introduction to the Theory and Practice of Econometrics, Second Edition,Wiley.
Maddala, G.S. 1983 Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press.
Patterson, K. 2000. An Introduction to Applied Econometrics: A Time Series Approach, MacMillan Press.
Train, K. 2003. Discrete Choice Methods with Simulation, Cambridge University Press, 2003
Woolridge, J.M. 2002. Econometric Analysis of Cross Section and Panel Data, The MIT Press.
Find these and additional texts by visiting section HB139 in the Fogler Library Stacks.
Course Schedule and Reading Assignments:
Week 1 Course Introduction
January 17 & January 19
K: Chapter 21
G: Chapter 26
Leamer, E.E. 1983. “Let’s take the Con out of Econometrics,” American Economic Review 73(1) 31-43. (LEAMER.PDF)
Week 2 SUR
G: Chapter 17
Dalton, T.J., Masters, W.A., and K.A. Foster. 1997. “Production Costs and input substitution in Zimbabwe’s smallholder agriculture,” Agricultural Economics 17: 201-209. (DALTON.PDF)
Week 3 Simultaneous Equations
G: Chapters 18 and 19
K: Chapters 10
Liu, X. 2005. “Explaining the relationship between CO2 emissions and national income – The role of energy consumption,” Economic Letters 87: 325-328. (LIU.PDF)
Week 4 Time Series Analysis
G: Chapters 20 and 21
Wachter, J.A. 2006. “A consumption-based model of the term structure of interest rates,” Journal of Financial Economics 79: 365-399. (WACHTER.PDF)
K: Chapters 18 and 19
Klug, A., London-Lane, J.S., and E.N. White. 2005. “How could everyone be so wrong? Forecasting the Great Depression with railroads,” Explorations in Economic History 42: 27-55. (KLUG.PDF)
Clements, M.P. amd R. Madlener. 1999. “Seasonality, Cointegration, and Forecasting Using UK Residential Energy Demand,” Scottish Journal of Political Economy 46(2): 185-206. (CLEMENTS.PDF)
Week 5 Spatial Econometrics
Anselin, L. 2003. “Under the Hood: Issues in the Specification and Interpretation of Spatial Regression Models,” Agricultural Economics 17 (3), 2002: 247-267. (ANSELIN.PDF)
Anselin, L. Florax, R., and S. Rey. 2003. “Econometrics for Spatial Models: Recent Advances,” in Advances in Spatial Econometrics, New York: Springer, pp. 1-24. (FLORAX.PDF)
Bell, K.P. and N.E. Bockstael. 2000. “Applying the Generalized Method of Moments Approach to Spatial Problems Involving Micro-Level Data,” Review of Economic and Statistics 82(1): 72-82. (BELL.PDF)
Brueckner, J.K. and L.A. Saavedra. 2001. “Do Local Governments Engage in Strategic Property Tax Competition?” ,National Tax Journal 54(2): 203-229. (BRUECKNER.PDF)
Week 6 Panel Data
K: Chapter 17
List, J.A. and M. Kunce. 2000. “Environmental Protection and Economic Growth: What do the Residuals Tell Us?” Land Economics, 76(2): 267-282. (LIST.PDF)
Geronimus, A.T. and S. Korenman. 1992. “The Socioeconomic Consequences of Teen Childbearing Reconsidered,” Quarterly Journal of Economics 107(4): 1187-1213. (GERONIMUS.PDF)
Week 7 Nonlinear Least Squares and Maximum Likelihood Estimation
G: Chapter 22
HM: Appendix A
HM: Chapter 9
Week 8 Dichotomous Choice (Binary Probit and Logit)
G: Chapter 23
K: Chapter 15
HM: Chapter 2
Loomis, J.P., P. Kent, E. Strange, K. Fausch, and A. Covich. 2000. “Measuring the total economic value of restoring ecosystem services in an impaired river basin: Results from a contingent valuation survey,” Ecological Economics 33:103-117. (LOOMIS.PDF)
Thompson, G.D. and J. Kidwell. 1998. “Explaining the Choice of Organic Produce: Cosmetic Defects, Prices, and Consumer Preferences,” American Journal of Agricultural Economics 80(2):277-87. (THOMPSON.PDF)
Week 9 Polychotomous Choice (Multinomial Probit and Logit, Conditional Logit; Nested Logit)
K: Chapter 15 (pp. 262-263; 268-271; 275-278)
HM: Chapter 8 (pp. 190-212)
Choo, S. and P.L. Mokhtarian . 2004. “What Type of Vehicle Do People Drive? The Role of Attitude and Lifestyle in Influencing Vehicle Type Choice,” Transportation Research: Part A: Policy and Practice 38(3): 201-22. (CHOO.PDF)
Davies, P.S., Greenwood, M.J., and L. Haizheng. 2001. “A Conditional Logic Approach to U.S. State-to-State Migration,” Journal of Regional Science 41(2): 337-360. (DAVIES.PDF)
Kling, C.L. and Thomson, C.J. 1996. “The Implications of Model Specification for Welfare Estimation in Nested Logit Models,” American Journal of Agricultural Economics 78(1):103-14. (KLING.PDF)
Week 10 Polychotomous Choice (Ordered Response Models)
K: Chapter 15 (p. 263; pp. 271-272; 278-279)
Capeau, B., Decoster, A., and F. Vermeulen. 2003. “Homeownership and the Life Cycle,” Center for Economic Studies, University of Leuven. (CAPEAU.PDF)
Deller, S.C., Walzer, N., and M. Shields. 1997. “Support for Local Economic Development Strategies: A Microeconomic Analysis,” Journal of Regional Analysis and Policy 27(1):19-33. (DELLER.PDF)
Mixon, F.G. and M.T. Gibsob. 2001. “The retention of state-level concealed handgun laws,” Public Choice 107:1-20. (MIXON.PDF)
Week 11 Count Models
K: Chapter 15 (pp. 263-264; 272; 279-280)
HM: Chapter 7 (pp. 164-174)
Haab, T.C. and K.E. McConnell. 1996. “Count Data Models and the Problem of Zeros in Recreation Demand Analysis,” American Journal of Agricultural Economics 78(1): 89-102. (HAAB.PDF)
Noland, R. 2004. “Motor Vehicle Fuel Efficiency and Traffic Fatalities,” The Energy Journal 25(4): 1-27. (NOLAND.PDF)
Week 12 Limited Dependent Variables (Tobit Models)
Maddala, Chapter 6, (pp. 149-162)
K: Chapter 16 (pp. 279-284; 289-291; 294-296)
HM: Chapter 7 (pp. 149-163)
Van Doren, T.D., Hoag, D.L., and T.G. Field. 1999. “Political and Economic Factors Affecting Agricultural PAC Contribution Strategies,” American Journal of Agricultural Economics 81(2): 397-407. (VANDOREN.PDF)
Week 13 Limited Dependent Variables (Sample Selection)
Maddala, Chapter 9, (pp. 231-234; 257-267)
K: Chapter 16 (pp. 284-287; 291-294; 296-297)
Bockstael, N.E, Strand I.E., McConnell, K. E., and A. Firuzeh. 1990. “Sample Selection Bias in the Estimation of Recreation Demand Functions: An Application to Sportfishing,” Land Economics 66(1), 40-49. (BOCKSTAEL.PDF)
HM: pp. 183-189
Week 14 Student Presentations
May 2 & May 4
May 11 (Student Presentations – if necessary)