Prof. Nathaniel Beck, 19 W. 4th St., Rm 407, x88535. TAs are Alex Herzog and Anjali Bohlken (with duties divided in a somewhat odd manner).

I will post the schedule, post data sets, course notes and other handouts here. Please note that the schedule will be updated as dates slip, etc., so please keep referring to this site. Any topics under the line refer to last year's course, and are just a placeholder/indicator of things to come.

The class meets in a seminar room so we can have discussion about issues unrelated to how do you do it in Stata. The Friday lab is in our computer lab, which is the appropriate place to discuss Stata issues.

Below are a set of topics and guesses about dates. This will be updated during the semester to reflect actual progress. Topics are keyed to readings in Cameron & Trivedi (CAT); handouts (pdf's) are also referenced. Data sets will be distributed in Stata format.

The general text is Cameron and Trivedi, Microeconometrics (Cambridge). There is an new Stata book by Cameron and Trividi, Microeconometrics using Stata, which will prove very useful for the practical issues and homework. For those interested in more, I will recommend additional readings. For those undertaking a project in a specific area, you will probably need to consult more than just CAT. There are a number of other excellent texts (Greene, Wooldridge) which you should feel free to consult. Most good departments have a course similar to this one; since you know how to google, you can easily find these sites. You will find that I have stolen from some sites (with permission, of course), and that others have borrowed from me.

I have listed some substantive applications. Where they are not keyed to a homework, feel free to think about other articles of interest that use the various methods. Class is much better if we can actually talk about how the methods are used by substantive reearchers. Substantive articles keyed to the homework are listed with the exercise.

Either you are intelligent people or you should not be here (and I presume the selection process gives me only the former). Some topics will be of great interest to some, some will be of limited utility to some. So beyond getting the basics (you never know what tool you will need to use someday), you can concentrate on the stuff you really care about. This will primarily manifest itself in the course paper, which should be done on something of great (or at least greater) interest to you.

Grading and such: There are weekly exercises. These will be discussed in the Friday section and are due the following Wednesday. Typically they are applications of what we have studied, and are done using Stata. The goal of the exercise (see assumption on intelligence), however, is NOT to show that you can type Stata commands, nor that you can cut and paste Stata output, but rather that you understand what is going on with the various models. There is a final project which involves your finding some extension of what we have done in class and applying it to some problem of interest to you. The exercises are worth 60 percent of your grade, the project is 30 percent and participation in class is worth 10 percent.

Date | Topic | Reading in text | Handout (if any) | Substantive reading | Exercise (if any) | Data, do file, anything else of use |
---|---|---|---|---|---|---|

Week 1 (1/20 and 22) | Some introductory materials and notation - asymptotics (in OLS context) and likelihood (intro) | CAT ch. 4.1-4.5 and Appendix A | Asymptotics and Likelihood (intro). | Exercise due 1/28t | Jacobson and Dimock article (look around Table 9) and Jacobson data and Example do file and OLS/MATA example. Please note that for all simulations and random variables used in exercises in the course, Stata now follows standard syntex for generating a wide variety of random draws - see MUS ch. 4 | |

Weeks 2 and 3 (1/27 and 29 and 2/ 3 and 5) | Maximum likelihood, including ols in ml and some simple applications (logit/probit) | CAT ch. 5 and 14.1-3 | maximum likelihood for Poisson, Likelihood (maths) and Likelihood (OLS), Limited Dependent Variables (intro) | Abrajano, Alvarez and Nagler JOP article (look around Tables 3 and 4) | Week 2 exercise (due 2/4) and Week 3 exercise (due 2/11) | Data for week 3 homeworks and example Stata file. Read MUS 11.1-3 and 11.7 |

Weeks 4 and 5 and 6.1 (2/10, 14, 17, 19 and 24) | Discrete Dependent Variables (mostly discrete choice | (Readings for specific days will be announced in class) CAT ch. 14 (through section 5), ch. 15 and 20 (though section 4, this chapter is on count data and is read for the last class in this section) | More advanced binary dv models, Multinomial overheads and Event count overheads. | Nagler, "Scobit," AJPS, 38(1994):230-55, Franklin and Kosaki "Republican Schoolmaster," AJPS (application of ordered probit), Alvarez and Nagler, "When Politics and Models Collide," AJPS, 42(1998) | More complicated ml exercise (due 2/18); Multinomial logit exercise and event count exercise (both due 2/25) | Stata data set of 1992 NES for binary dependent variable exercise and codebook for NES data. Stata data set of 1992 NES for ordered probit, Stata event count data. Dutch conditional data set, Dutch unconditional data set and Dutch codebook and a short file to help you with some Stata intricacies for clogit |

Week 6.2 and 7 (2/26, 3/3 and 5) | Duration models | CAT, ch. 17-19 | Continuous Time and Discrete Time | Bennett "Testing Alternative Models of Alliance Duration" | Exercise on duration models (due 3/4 and 11, in two parts) | King, Alt, Laver and Burns, "A Unified Model of Cabinet Dissolution" (AJPS),Coalition data |

Week 8 (3/10 and 12) | Endogeneity, simultaneity, instrumental variables | CAT ch. 2 and 4.7-4.11 | Identification and Instrumental Variables | Miguel, Satyanath and Sergenti "Economic Shocks and Civil Conflict: An Instrumental Variables Approach" (JPE. 112:725-53, 2004), Erikson and Palfrey "Campaign Spending and Incumbency" (JOP, 60:355-73, 1998), Bartels "Instrumental and 'Quasi-Instrumental' Variables" (AJPS, 35(3):777-800, 1991) | Exercise on identification (due 3/25) | |

Week 9 (3/17 and 3/19) | Break - no class | |||||

Week 10.1 (3/24) | Discussion of term paper topics | |||||

Week 10.2 (3/26) | Continuation on IV's | make sure to read the readings you didn't do for Week 8, especially Bartels | Exercise on IV estimaation (due 4/1) | MSS data | ||

Week 11 (3/31 and 4/2) | Selection Models | CAT ch. 16. | Overheads | Lemke and Reed, "War and Rivalry among Great Powers," AJPS, 45(2001), Geddes, "How the Cases You Choose Affect the Answers You Get: Selection Bias in Comparative Politics," PA, 2(1990), Romer and Snyder, "An Empirical Investigation of the Dynamics of PAC Contributions," AJPS, 38(1994), von Stein, "Do Treaties Constrain or Screen? Selection Bias and Treaty Compliance," APSR, 99(2005), Dubin and Rivers, "Selection bias in linear regression, logit and probit models," Sociological Methods & Research, 18(1989/1990) |
Tobit exercise and
Heckman excercise (due 4/9) |
Tobit data |

Week 12 and 13 (4/7,9 and 14) | Causal Inference | CAT ch. 25 | Overheads | Gordon and Huber "The effect of electoral competitiveness on incumbent behavior" (QJPS, 2007), Gilligan and Sergenti "Do UN Interventions Cause Peace?" (2007) | Excercise on matching (due 4/15) | data from Gilligan and Sergenti> |

Weeks 13-15 (4/16, 21, 23, 28 and 30) | Times-series--cross-section data | Continuous DV TSCS notes, Time series issues (continouos) and Time series issues (discrete) | Beck and Katz "Time-Series-Cross-Section Issues: Dynamics, 2004," Draft of July 24, 2004, Beck and Katz "Random Coefficient Models for Time-Series-Cross-Section Data: Monte Carlo Experiments," PA, 15:182-195, 2007, Plumper and Troeger "Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects," PA, 15:124-139, 2007, Wilson and Butler "A Lot More to Do: The Sensitivity of Time-Series Cross-Section Analyses to Simple Alternative SpeciÞcations," PA, 15:101-123, 2007 | Exercise on TSCS data (due 4/29) and Exercise on binary TSCS data (due 5/6) | Garrett data and Data for binary exercise and Oneal and Russett preprint |

Last modified: April 22, 2008