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Viewing: ECG 563 : Applied Microeconometrics

Last approved: Tue, 24 Apr 2018 08:01:21 GMT

Last edit: Fri, 20 Apr 2018 12:15:31 GMT

Catalog Pages referencing this course
Change Type
ECG (Graduate Economics)
563
032602
Dual-Level Course
No
Cross-listed Course
No
Applied Microeconometrics
App Microeconometrics
Poole College of Management
Economics (20EC)
Term Offering
Fall Only
Offered Every Year
Fall 2018
Previously taught as Special Topics?
Yes
1
 
Course Prefix/NumberSemester/Term OfferedEnrollment
ECG 590Fall 201715
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded/Audit
3
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture3
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Harrison Fell and Roger von Haefen
Associate Professor
Graduate Faculty

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture1010NoEnrollment is expected to slightly increase over time.
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote


Is the course required or an elective for a Curriculum?
No
This course will survey econometric methods for the analysis of panel and limited dependent variable data. Both the theoretical foundation and empirical application of methods will be covered. Topics include fixed and random effects, program evaluation, censored, truncated, discrete choice and count data models. Although not required, ECG 561, ST 511 or ST 512 is encouraged prior to taking this class.

This is the third course in our applied econometrics sequence, which is a major component of our economics master's programs. The first two courses (ECG 561 and 562) focus on applications of econometric methods for analyzing cross-sectional and time series data, while this course focuses on applications of econometric methods for analyzing individual or micro level data. With the arrival of the big data era, more and more micro level data have become available and there is a huge need in in industry for professionals with the skills to analyze such data. This course fills the void in our curriculum for this and will significantly expand the tool set for our students.  


No

Is this a GEP Course?
GEP Categories

Humanities Open when gep_category = HUM
Each course in the Humanities category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

This course is part of Drs. Fell and von Haefen's standard teaching load.

This course will survey econometric methods for the analysis of panel and limited dependent variable data.  Both the theoretical foundation and empirical application of methods will be covered.  Topics include fixed and random effects, program evaluation, censored, truncated, discrete choice and count data models. Although not required, ECG 561, ST 511 or ST 512 is encouraged prior to taking this class. 


Student Learning Outcomes

By the end of the course, students will be able to:



  1. analyze econometric data with the Stata programming language.

  2. formulate and apply alternative panel data and  program evaluation estimators to time series/cross sectional data; evaluate whether particular data environments are well suited for these estimators and the validity of model estimates.

  3. Formulate and apply apply maximum likelihood estimation techniques to limited dependent variable models.

  4. formulate and apply alternative censored and truncated linear regression models, discrete choice models, and count data techniques to limited dependent variable data; evaluate whether particular data environments are well suited for these estimators and the validity of model estimates.


Evaluation MethodWeighting/Points for EachDetails
Multiple exams70There will be two exams, each accounting for 35% of the final grade.
Homework25There will be 4 homeworks.
Participation5This includes classroom discussion.
TopicTime Devoted to Each TopicActivity
See syllabus
mlnosbis 3/23/2018:
1) Course length should be 16 weeks; week 16 is the final exam. The topical outline on the syllabus is correct.
2) Contact hours per week should be 3 to align with the lecture component ratio of credit:contact hours (https://oucc.dasa.ncsu.edu/courseleaf-2/instructional-formats/). The scheduled time you listed on the syllabus meets the requirement for 3 credit hours, you just need to update the CIM field to indicate 3 contact hours per week instead of 2.5.
3) Student Learning Outcomes should use stronger words than "understand." See Learning Outcomes Guidelines attached under Additional Documentation. Update CIM form and syllabus.
4) Syllabus notes-
- Use the new/proposed course number
- If you want, you can add a note that ECG 561 is encouraged to the end of the course description since it is not an official prereq. That way, students will see that recommendation in the course description.
- Include instructors' policy on late assignments.

cohen (3/25/2018):
1. Under the grading policy in the syllabus, I suspect that the intention is to have 86-87 convert to a B.
2. I would request that you consult with Statistics to see if there is a possibility of cross-listing the course and also to see if there is another course, in addition to ECG 561, that you might want to "encourage" students to take prior to taking the proposed course. Email the Statistics DGP (Wenbin Lu, wlu4@ncsu.edu) for consultation, and insert the results into the consultation summary field of the CIM form.

ABGS Reviewer Comments:
- No concerns.
xzheng (Thu, 29 Mar 2018 23:26:44 GMT): Responses from statistics DGP: Hi Xiaoyong, I have talked with the Statistics Department heads. The comment I received is that we have already cross-listed a bunch with the econometrics courses. So, it may not be necessary to cross-list this one. ECG 561 sounds a proper pre-req course for ECG 562. Student may also take ST 511 or 512 prior to taking the proposed course. Best, Wenbin All other comments have also been addressed.
Key: 23920