AØKA08088U Advanced Development Economics - Micro Aspects

Volume 2020/2021
Education

MSc programme in Economics – elective course

 

The PhD Programme in Economics at the Department of Economics:

  • The course is an elective course with research module. PhD students must contact the study administration AND the lecturer in order to register for the research module and write the research assignment.
Content

This course covers the microeconomics of development with focus on approaches to understanding the behavior of households and firms, and the functioning of markets and institutions in developing countries. Since development is a field with a strong empirical tradition, most of the course is centered on discussing and evaluating the empirical strategies used in the literature. Moreover, the course will also (via exercises) provide students with an opportunity for “hands-on” experience, as results in selected readings are replicated (and criticized) using appropriate software packages.

Key topics in the course include:

  1. Poverty and inequality,
  2. Agriculture and livelihoods,
  3. Risk, insurance, and climate change,
  4. Credit and microfinance,
  5. Land markets and property rights,
  6. Jobs, labor market and migration,
  7. Health and nutrition,
  8. Education and skills,
  9. Illicit flows, informality, and corruption,
  10. State capacity and armed conflicts.

 

The course will therefore:

  • Provide the students with a critical overview of the recent literature and important debates within the micro aspects of economic development.
  • Provide insight into methodological issues that arises when doing research on microeconomics of development. The emphasis will be on how theoretical microeconomic hypotheses may be tested with data and how to identify causal relationships. One aim is through exercises to gain insight into what makes a good empirical study.
  • Provide students with a “hands-on” experience on how to replicate empirical results using relevant econometric software. This will hopefully prepare students for original independent empirical research and help identify possible interesting thesis topics.
Learning Outcome

After completing the course the student is expected to be able to:

 

Knowledge:

  • Account for the basic concepts used in micro development economics.
  • Define the key elements of the more recent theories and development models.
  • Critically discuss theories and empirical evidence on micro economic development.
  • Reflect upon ongoing professional debate in areas within the topics highlighted in “Content”.
  • Present and discuss existing theory and empirical evidence related to the highlighted topics described in “Content”.

 

Skills:

  • Analyze current economic development issues with use of relevant micro theories and empirical methods
  • Summarize and assess theory and empirical evidence on the economic characteristics and functions of selected markets in developing countries.
  • Empirically analyze existing data relevant for development micro economics.

  • Empirically analyze new data using relevant software.

     

Competences_

  • Apply theoretical and empirical knowledge about economic development in a competent, coherent and original way in relation to current challenges.
  • Master relevant model setups within development and implement existing empirical models in new contexts.
  • Plan and solve new and complex empirical model setups within micro development economics in a professional and responsible manner.

 

Textbook: Bardhan and Udry (1999). “Development Microeconomics”, Oxford University Press.

Series of academic articles listed in the course-reading list.

The course builds upon knowledge gained during the under-graduate course “Development Economics”. However, although it is recommended that the students have taken this course it is not a requirement to follow "Advanced Development Economics - Micro Aspects".

It is also recommended that the students familiarize themselves with the program package Stata, as exercises are carried out using this particular software. Links to relevant tutorials for Stata will be available on the course homepage.
The format of the course is a combination of lectures, exercises and student assignments.

In the lectures core concepts, theories, empirical measures and methods within the field of micro development are presented.

In exercises classes students work in groups to understand and discuss central papers in the syllabus. During the exercises, students will learn to replicate and extend central papers in the syllabus, which will be of direct relevance for the mandatory assignment and the exam.

Pandemic:
In case of a pandemic like Corona the teaching in this course may be changed to be taught either fully or partly online. For further information, see the course room on Absalon.
Schedule:
2 hours lectures one time a week from week 6 to 20 (except holidays).
3 hours of exercise from week 6 or 7 to 20 (except holidays).

The overall schema can be seen at KUnet:
MSc in Economics => "courses and teaching" => "Planning and overview" => "Your timetable"
KA i Økonomi => "Kurser og undervisning" => "Planlægning og overblik" => "Dit skema"

Timetable and venue:
To see the time and location of lectures and exercise classes please press the link under "Timetable"/​"Se skema" at the right side of this page (F means Spring).

You can find the similar information in English at
https:/​/​skema.ku.dk/​ku2021/​uk/​module.htm
-Select Department: “2200-Økonomisk Institut” (and wait for respond)
-Select Module:: “2200-F21; [Name of course]”
-Select Report Type: “List – Weekdays”
-Select Period: “Forår/Spring – Week 5-30”
Press: “ View Timetable”

Please be aware regarding exercise classes:
- The schedule of the exercise classes is only pre-planned and the schedule can change until the teaching begins without the participants´ acceptance. If this happens, you can see the new schedule in your personal timetable at KUNet, in the app myUCPH and at the links in the right side/the link above.
- The student is not allowed to participate in an exercise class not registered.
- That it is the students´s own responsibility to continuously update themselves about their studies, their teaching, their schedule, their exams etc. through the study pages, the course description, the Digital Exam portal, Absalon, KUnet, myUCPH app, the curriculum etc.
  • Category
  • Hours
  • Lectures
  • 28
  • Class Instruction
  • 42
  • Preparation
  • 112
  • Exam
  • 24
  • Total
  • 206
Oral
Individual
Collective
Peer feedback (Students give each other feedback)

 

Feedback is obtained throughout the semester by:

  • The lecturer answering questions in class.
  • The lecturer giving oral feedback on written questions from groups.
  • The teaching assistant giving oral feedback on written exercises in exercise classes.
  • Student peer feedback on one assignment.
Credit
7,5 ECTS
Type of assessment
Portfolio, 48 hours
The exam is a written assignment consisting of two parts:
• Part 1: The first part is based on the (one) mandatory assignment worked on during the course. The student can use the peer feedback received during the course to improve this assignment. This can be done before the exam period begins, where the assignment must be worked on individually.
• Part 2: The second part is a new assignment given in English. It takes approximately 24 hours to answer the new assignment.

Please be aware that:
• The students are allowed to communicate about the given problem-set for the new assignment but must work on the assignment individually.
• The plagiarism rules must be complied.
• All parts must be answered in English and all parts must be uploaded to Digital Exam in one file.

In the event that this summer's exams have to be conducted as online exams due to COVID-19, the reexam will be will be an online oral exam without preparation time.
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Exam registration requirements

To qualify for the exam the student must no later than the given deadlines during the course:

  • Hand in written programming files where two-third of the files have to be approved.
  • Hand in one mandatory assignment.
  • Provide useful written peer feedback based on specific criteria to the mandatory assignments of two other students.

 

Please be aware of:

  • The teaching assistant and/or the lecturer control the assignments and the feedback.
  • The programmingfiles, the assignment and the peer feedback must be written individually.
  • The assignments and the peer feedback must be written in English.
  • The mandatory assignments and the peer feedback are part of a portfolio exam. See “Type of assessment”

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Aid
All aids allowed

for the written exam.

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Marking scale
7-point grading scale
Censorship form
No external censorship
for the written exam.
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Exam period

The regular exam takes place:

From 26 June 2021 at 10 AM to 28 June at 10 AM

 

Exam information:

In special cases, the exam can change to another day.

 

Further information about the exam will be available in Digital Exam from the middle of the semester. 

 

More information about examination, rules, aids etc. is available at Master (UK) and Master (DK).

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Re-exam

The reexam takes place:

In week 35 and/or 36, August 2021

as a 20 minuts oral exam with 20 minuts preparation. 

No aids allowed during the preparation time and no aids allowed during the examination.

The questions cover the entire curriculum and may be based on the cases in the written assignments worked on during the semester.

 

In case of a pandemic crisis the oral exam as well as use of aids may be changed. In case of COVID-19 restrictions, look at "Type of assessment".

 

Reexam information:

More info is available in Digital Exam early August.

More info at Master(UK) and Master(DK).

Criteria for exam assesment

Students are assessed on the extent to which they master the learning outcome for the course.

 

To receive the top grade, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.