Lecture 7: Introduction to Qualitative Data Research Methods I Lecture 7: Introduction to Qualitative Data

Introduction Principals of research design (lecture 5) and sampling (lecture 6) basically hold for quantitative and qualitative data However, they apply most easily to quantitative analysis Qualitative analysis has different foci Qualitative analysis relatively (to quant; other soc sci) unused in economics

Qualitative techniques: types Case study Fieldwork (ethnography) Observation Unstructured interviews Analytic induction/grounded theory Discourse analysis Theoretical sampling

Qualitative techniques: principals Qual often = not quantitative Can use quant for pattern detection, qual for causal analysis Or use qual and quant as equals in inference (triangulation) Quantification often inappropriate See Merriam (1988)

Qualitative techniques: principals Interpretivism, verstehen Used to be associated only with using autobiography, letters, personal documents, diaries Ethnography fairly recent: Robert Park 1920s Chicago school Focus on cases rather than generality

Qualitative techniques: principals Analysis not really a separate stage of research Design, data collection and analysis all simultaneous and continuous Open-ended approach: Theory and conclusions formed iteratively Imagination is crucial Recognise importance of exceptions Context is crucial

Fieldwork Study of people acting in their daily lives Access a group but remain somewhat detached Approach with key questions Significance of objets trouvés Teams get range of perspectives Danger of self-perception and bias

Participant Observation Adopt perspectives of subject group in order to understand them Learning language, customs, behaviours, work, leisure, etc. Hanging around and learning the ropes (Wax, 1983) Being an outsider can changes subjects’ behaviour (Hawthorne effect) Complete participation - researcher wholly concealed –  contamination and artificiality

Participant Observation Researchers can go native (internalise group lifestyle) Covert researchers can be in danger (e.g. Polsky 1967 criminals) or create detrimental behaviour (Mitchell, 1991 survivalists) Researchers can be “piggy in the middle” (Shipman) Covert: recording observations can be difficult (e.g. need hidden cameras) Serious ethical issues with covert observation

Employ analytic induction Go in with prejudices and theories Revise theory in light of evidence Generate new theories until evidence seems to fit Flexibility accorded but also required by the researcher Need to be open to disconfirming cases

Grounded theory Glaser and Strauss (1967) Data collected Develop categories (with inevitable theoretical priors and language) Categories checked by data Once categories seem secure and grounded in the evidence, formulate interconnection between categories

Evaluation Broad range of qualitative techniques Control over the investigation; less data driven; flexibility much greater than quantitative studies Logistically difficult: Huge amounts of data produced and problems with manipulation (although Nvivo will help with this) Must be careful to collect evidence widely to avoid bias Can be ethical issues re: data collection and reporting