AIM OF THE MODULE
This course provides a detailed grounding in key measurement and analysis methods in behavioural science. The initial phase of the module will cover the core components of survey design and detail the measurement platforms typically used in large-scale surveys. Common analytic methods in behavioural science including ordinary least squares regression, the use of fixed and random effects, and the specification of experimental designs will then be explained in detail. The use of subjective and psychometric scales and behavioural and biological measures are becoming increasingly common in policy, business and economics research and offer a key point of intersection between behavioural science and these disciplines. Techniques used to measure these characteristics, key features and limitations of such measurement, and techniques to overcome such limitations will be outlined. Finally, behavioural considerations in the measurement of economic constructs will be detailed.
MODULE LEARNING OBJECTIVES
1. To strengthen understanding of survey research methods.
2. To develop an awareness and understanding of large-scale surveys, how they are conducted, how data is collected, coded, stored, and accessed.
- Provide an understanding of how secondary datasets that have started to contain a large number of constructs (such as personality at multiple time points) give scope for researchers in behavioural science to capitalize on these resources.
2. To provide a basis for students to understand and implement a set of common regression techniques.
- Familiarize students with econometric methods for the analysis of survey data.
- Build an understanding of the self-reported and subjective measures that can be incorporated in economic and policy studies as explanatory variables explaining outcomes such as health and education.
- Develop an awareness of limitations in the use of subjective measures as dependent variables in standard regression designs (e.g. intercultural incomparability, use of non-probability samples) and the methods that have been used to overcome these (e.g. anchoring vignettes, high-frequency measurement).
3. A recent literature has examined how to integrate constructs from psychology into understanding economic outcomes. This literature is quickly becoming a major areas in fields such as health economics and education economics. However, there are many issues with using variables such as personality in econometric functions. We examine the measurement of psychological constructs and preference parameters and statistical designs for incorporating such measures.
- Enable students to understand and utilize novel measurement tools that have been produced chiefly in psychology (e.g. real-time activity tracking, Day Reconstruction Method) but are increasingly being incorporated into policy research and economics.
4. To provide an awareness of methods of measuring economic constructs and the role of behavioural factors in this measurement.
5. To provide a background to the measurement of biological functioning and genetic variation and how these factors can be used to understand economic behaviour and policy-relevant outcomes.
MODULE FORMAT AND TEACHING METHOD
The module will be taught by one two-hour lecture per week, supported by tutorials corresponding to quantitative analysis lectures where students will prepare datasets and conduct analyses.
Lectures Tuesday 11:00-13:00 Room 2A11
Seminars Tuesday 14:00-16:00 Room 2B41
Week 1 - 11/02/14 - Introduction and overview of the module
Week 2 - 18/02/14 - Secondary data sources
Week 3 - 25/02/14 - Regression analysis
Week 4 - 04/03/14 - Fixed-effects and random-effects
Week 5 - 11/03/14 - Natural experiments, IVs, RCTs
Week 6 - 18/03/14 - Measuring economic constructs
Week 7 - 25/03/14 - Mid-semester break
Week 8 - 01/04/14 - Daily experience & well-being measurement
Week 9 - 08/04/14 - Measuring psychological constructs & preferences
Week 10 - 15/04/14 - Health measurement in social science
Week 11 - 22/04/14 - Levels of measurement over the lifespan
Week 12 - 29/04/14 - Publication bias, integrity in research
All assessment elements are compulsory. To complete the module you must complete all of the assessment components. Resits examinations are only available to students who have completed all components of assessment. Assessment consists of two components: 30% coursework and 70% examination. The examination at the end of the semester will last two hours.
The module uses a variety of sources. Some are suggested below.
1. Borghans, Duckworth, Heckman & ter Weel (2008), The economics and psychology of personality traits, Journal of Human Resources
2. Boyce (2010), Understanding fixed effects in human well-being, Journal of Economic Psychology
3. Butz & Torrey (2006), Some frontiers in social science, Science
4. Hofer & Piccinin (2009), Integrative data analysis through coordination of measurement and analysis protocol across independent longitudinal studies, Psychological Methods
5. Kahneman, Krueger, Schkade, Schwarz & Stone (2004), A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method, Science
6. Mayer (2009), New directions in life course research, Annual Review of Sociology
7. Simmons, Nelson & Simonsohn (2011), False-positive psychology, Psychological Science
8. Tourangeau, Rips, & Rasinski (2000), The psychology of survey response, Cambridge University Press.
9. Weinstein et al. (2007), Biosocial Surveys