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Applied Econometrics for Researchers - 6 ECTS
Date and time
Tuesday 1 October 2024 at 09:00 to Wednesday 11 December 2024 at 12:00
Registration Deadline
Thursday 26 September 2024 at 23:55
Location
Kilen - room KL 2.53 (second floor),
Kilevej 14A,
2000 Frederiksberg
Kilen - room KL 2.53 (second floor)
Kilevej 14A
2000 Frederiksberg
Applied Econometrics for Researchers - 6 ECTS
Course coordinator: Hans Christian Kongsted, Department of Strategy and Innovation (SI)
Faculty
Professor Hans Christian Kongsted (HCK)
Department of Strategy and Innovation, CBS
Department of Strategy and Innovation, CBS
Prerequisites
The course requires that students have basic knowledge of statistics. It is assumed that students know how to calculate and interpret e.g. mean values, standard deviations and correlations, and how to perform basic statistical tests, e.g. comparing means. Knowledge of any particular programming language is not required although some programming experience will be an advantage. Stata will be the statistical software used and all students will be given access to it during the course.
The course requires that students have basic knowledge of statistics. It is assumed that students know how to calculate and interpret e.g. mean values, standard deviations and correlations, and how to perform basic statistical tests, e.g. comparing means. Knowledge of any particular programming language is not required although some programming experience will be an advantage. Stata will be the statistical software used and all students will be given access to it during the course.
Aim
The overall aim of the course is to provide econometric tools for data analysis to PhD students with limited prior econometric experience. Students will be able to identify the appropriate econometric technique given their research question and the available data. Students will be able to distinguish between different econometric models and understand the limitations and pitfalls of each tool taught.
The overall aim of the course is to provide econometric tools for data analysis to PhD students with limited prior econometric experience. Students will be able to identify the appropriate econometric technique given their research question and the available data. Students will be able to distinguish between different econometric models and understand the limitations and pitfalls of each tool taught.
Course content
The student will be equipped with tools ranging from Ordinary Least Square to Limited Dependent Variables Models and Count Models useful for cross sectional settings. In this context, students will learn how to handle sample selection bias and endogeneity problems. Furthermore, the student will be exposed to panel data estimation and tools for policy evaluation.
The student will be equipped with tools ranging from Ordinary Least Square to Limited Dependent Variables Models and Count Models useful for cross sectional settings. In this context, students will learn how to handle sample selection bias and endogeneity problems. Furthermore, the student will be exposed to panel data estimation and tools for policy evaluation.
Teaching style
Lectures, workshops, home exercises, student presentations of home exercises.
Lectures, workshops, home exercises, student presentations of home exercises.
Lecture plan
Lectures (in-class): Wednesdays 9.00-12.00
Workshops (on-line): Fridays 9.00-12.00
Lectures (in-class): Wednesdays 9.00-12.00
Workshops (on-line): Fridays 9.00-12.00
Tuesday 01/10-2024: Introduction to econometrics and Stata essentials (HCK/VR/JGC)
Room: KL2.53 Note: This will be 15.00-18.00, followed by a welcome dinner.
Wednesday 09/10-2024: Lecture: Ordinary Least Squares (HCK)
Room: KL2.53
Friday 11/10-2024: Workshop – Stata essentials (JGC)
Note: Fall break in Week 42
Note: Fall break in Week 42
Wednesday 23/10-2024: Lecture: OLS, Dummy Variables and Moderation Effects (HCK)
Room: KL2.53
Friday 25/10-2024: Workshop – Application and interpretation of OLS (JGC)
Wednesday 30/10-2024: Lecture: Limited-dependent Variable Models (HCK)
Room: KL2.53
Friday 01/11-2024: Workshop – Logit/probit models (JGC)
Thursday 07/11-2024: Lecture: Attrition and Selection Models (VR)
Room: KL2.53
Friday 08/11-2024: Workshop - Selection and Attrition (JGC)
Wednesday 13/11-2024: Lecture: Matching Methods (VR)
Room: KL2.53
Friday 15/11-2024: Workshop - Matching (NN)
Wednesday 20/11-2024: Lecture: Instrumental Variables (VR)
Room: KL2.53
Friday 22/11-2024: Workshop - Instrumental Variables (JGC)
Wednesday 27/11-2024: Lecture: Panel Data Models (VR)
Room: KL2.53
Friday 29/11-2024: Workshop - Panel Data (JGC)
Wednesday 04/12-2024: Lecture: Policy evaluation methods (HCK/VR) Room: KL2.53
Thursday 05/12-2024: Workshop – Policy evaluation (JGC)
Wednesday 11/12-2024: Presentations workshop (Note: in class): (HCK/VR/JGC)Room: KL2.53
Learning objectives
Subsequent attending this course, the student should feel substantially better equipped to tackle econometric challenges, conduct rigorous econometric studies, and to discuss and comment on econometric work of others.
Subsequent attending this course, the student should feel substantially better equipped to tackle econometric challenges, conduct rigorous econometric studies, and to discuss and comment on econometric work of others.
Evaluation
Students are expected to follow the entire program of lectures and workshops and to develop a final assignment report. The assignment must be based on a replication of a published paper, preferably based within each student’s area of interest, using econometric methods taught in the course. Students will receive guidance in locating papers and associated data for the assignment. A 1-page description specifying key variables for the analysis and the research question addressed will be due by November 15. Students should prepare a 15-minute presentation for the class on December 11. The final assignment is a max. 15 pages report that conducts the empirical analysis, presents the results, and critically discusses the methods and assumptions employed by the empirical analysis. The final assignment report is due on December 18.
Students are expected to follow the entire program of lectures and workshops and to develop a final assignment report. The assignment must be based on a replication of a published paper, preferably based within each student’s area of interest, using econometric methods taught in the course. Students will receive guidance in locating papers and associated data for the assignment. A 1-page description specifying key variables for the analysis and the research question addressed will be due by November 15. Students should prepare a 15-minute presentation for the class on December 11. The final assignment is a max. 15 pages report that conducts the empirical analysis, presents the results, and critically discusses the methods and assumptions employed by the empirical analysis. The final assignment report is due on December 18.
Note: In case we receive more registrations for the course than we have seats, CBS PhD students will have first priority. Remaining seats will be filled on a first come first serve.
Course Literature (subject to change)
• Ai C., & Norton E.C., (2003). Interaction terms in logit and probit models. Economics Letters, 80 123-129.
• Cameron, A. and Trivedi, P., 2005: Microeconometrics: Methods and Applications, Cambridge University Press (selected chapters).
• Cameron, A. and Trivedi, P., 2005: Microeconometrics: Methods and Applications, Cambridge University Press (selected chapters).
• Certo, S., Busenbark, J., Woo, H., Semadeni, M, 2015. Sample selection bias and Heckman models in strategic management research, Strategic Management Journal 37 (13) 2639-2657.
• Hoetker G., (2007), The use of logit and probit models in strategic management research: critical issues. Strategic Management Journal, 28 331-343.
• Norton E.C., H. Wang, & Ai C., (2004). Computing interaction effects and standard errors in logit and probit models. The Stata Journal, 4(2) 154-167.
• Wooldridge, J. M. (2015), Introductory Econometrics - A Modern Approach, International Student Edition, 6th Edition, South Western (selected chapters).
• Wooldridge, J. M. (2002), Econometric Analysis of Cross Section and Panel Data, The MIT Press, Cambridge MA (selected chapters).
Note: In case we receive more registrations for the course than we have seats, CBS PhD students will have first priority. Remaining seats will be filled on a first come first serve. The course is offered annually.
Registration Deadline and Conditions
The registration deadline is 23 August 2024. If you wish to cancel your registration, it must be done by this date. By this deadline, we determine whether there are enough registrations to run the course or decide who should be offered a seat if we have received too many registrations.
If seats are still available, we will extend the registration deadline to fill the remaining spots. Once you receive our acceptance/welcome letter, your registration becomes binding, and no course fee refunds will be issued. The binding registration date is the deadline mentioned above.
Payment Methods
Ensure you choose the correct payment method when finalizing your registration:
CBS students:
Select the payment method CBS PhD students. The course fee will be deducted from your PhD course budget.
Students from Other Danish Universities:
Select the payment method Danish Electronic Invoice (EAN). Provide your EAN number, attention, and any relevant purchase (project) order number.
If you do not pay via EAN number, select Invoice to pay via electronic bank payment (+71).
Students from Foreign Universities:
Select the payment method Payment Card. If you are unable to pay by credit card, choose Invoice International to pay via bank transfer.
Event Location
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Organizer Contact Information
CBS PhD School
Nina Iversen
Phone: +45 3815 2475
ni.research@cbs.dk
Registration
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Organizer Contact Information
CBS PhD School
Nina Iversen
Phone: +45 3815 2475
ni.research@cbs.dk