M2600
High quality research data - Sources, collection and processing
Lecturers
Dr. Lena Kuhn, Kuhn@iamo.de
Dr. Ihtiyor Bobojonov, Bobojonov@iamo.de
Prof. Dr. Dr. h. c. Thomas Glauben
Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Theodor-Lieser-Str. 2, 06120 Halle (Saale)
Course description
The quality of research data has strong influence on the success of any scientific work. The selection, collection and processing of data influences the quality and time required for research projects. This course offers guidelines for PhD students to plan their data strategy and thus build the fundament for a high-quality thesis. The aim of this lecture is to improve practical, basic methodological and analytical skills of participants in preparation and is thus complimentary to existent courses on statistics and econometrics. While we touch upon the topic of qualitative data collection and procession, the examples and exercises are mainly focusing on quantitative data.
The course helps to find answers to following question:
Which type of data is appropriate for my research aim?
How to properly design and implement my own survey?
How to process and employ primary and secondary data to guarantee scientifically sound results? How to avoid methodological mistakes that will bias my data?
How to check the trustworthiness of my data source?
How can experimental data and Big Data help to solve more complex research problems?
Course requirements
The course aims at junior researchers from the field of economics, sociology and geography. Participants are required to fill a questionnaire on their research interests as well as prepare a short presentation of a research topic of their choice prior to the course. Demonstrations and exercises will be conducted with R Studio. Participants without any prior experience in R and quantitative methods are recommended to get accustomed with the basic functions of the software prior to the course. Advanced econometric and statistical methods are not the focus of this course.
Course credits
You will receive course credits (3 credits) for completing exercises during the course and submitting your seminar assignment within four weeks after the conclusion of the course.
Course outline
Day 1: Basics of research data collection and management
- Introduction: Ethics and Empirics in research
- Data quality criteria
- Sampling
Day 2: Survey data
- Survey mode
- Data recording method
- Survey organization
- Survey modules
- Drafting good questions and answer options
Day 3: Working with secondary data
- Data sources for agricultural economists
- Data documentation
- Quality assessment Detecting and fixing format issues
- Detecting data quality issues (missing data, problematic data points, sampling)
- Fixing data quality issues
Day 4: Mastering causality
- Requirements for causality
- Natural experiments
- Quasi-experiments
- Statistical approaches
- True experiments
Day 5: Big Data
- Definitions and Opportunities
- Download and Processing
- Analysis
- Practical Examples
References
- Deaton, Angus (1997): The analysis of household surveys. A microeconometric approach to development policy. Baltimore: John Hopkins University Press.
- Donaldson, Dave; Storeygard, Adam (2016): The View from Above. Applications of Satellite Data in Economics. In: Journal of Economic Perspectives 30 (4), S. 171–198. DOI: 10.1257/jep.30.4.171 .
- Grosh, Margaret; Glewwe, Paul (Hg.) (2000): Designing household survey questionnaires for developing countries. Lessons from 15 years of the Living Standards Measurement Study. Oxford: The World Bank.
- Groves, R.M.; Fowler, F.J.; Couper, M.P.; Lepkowski, J.M.; Singer, E.; Tourangeau, R. (eds.) (2009): Survey methodology. 2nd ed., Hoboken, NJ: Wiley.
- Harkness, J.A.; Van de Vijver, F.J.R.; Mohler, P.P. (2003): Cross-Cultural Survey Methods. Hoboken, NJ: Wiley.
- Kagel, John H.; Roth, Alvin E. (1997): The Handbook of Experimental Economics. Princeton: Princeton University Press.
- Scheaffer, Richard L.; Mendenhall III, William; Ott, R. Lyman; Gerow, Kenneth G. (2011): Elementary survey sampling. Sixth Edition. Duxbury: Cengage Learning.
- Tourangeau, R.; Rips, L.J.; Rasinski, K. (2009): The Psychology of Survey Response. 10th ed., Cambridge: Cambridge University Press.
- Yin, Robert K. (2008): Case Study Research: Design and Methods. 4th ed. Thousand Oaks, Cal.: Sage Publications.