1. Using secondary data sources
Research Methods, Management and Thesis Course (MAAE 508)
B.T. Hanyani-Mlambo

2. overview Literature Review – the concept.
Why is secondary data useful?
Limitations of secondary data.
Sources of secondary data.
Recording details of secondary data.
Evaluating secondary data.
Working with secondary data.

3. Literature review – the concept
What? – desk studies/lit. review/ sec. data.
Elements of secondary data (lit. review):-
(i) Conceptual framework.
(ii) Theoretical perspective.
(iii) Related literature.
Conceptual Framework:-
Concepts – abstract ideas (situations, events + individuals) e.g. community, SHFs, RPFs, CA, CSA.
Concepts, definitions, interrelations + operationalization (x2).
ODs – old based on literature (comparison) or new (context).

4. Theoretical Perspective:-
Analytical lens.
Theories – logical explanations of facts
e.g. soccer fans as hooligans.
Theories – What? How? Why? Prediction + Generalization (certain conditions).
Choice – values + assumptions.
Related Literature:-
Acquaint – research done (recent).
What? How? Why? Gaps? Etc.

5. Figure 1: Value Chain Approach (ACDI-VOCA, 2013).

6. Figure 2: Agribusiness Model

7. Figure 3:
The Sustainable Livelihoods Approach (DFID, 2004).

8. Figure 4
The policy formulation, implementation and analysis framework (Adapted from ADM, 2000).

9. why is secondary data useful?
Role of related literature:-
 Allows for a more precise definition of the
research problem being investigated e.g. A, B
+ C (value addition from D) + RQs, ROs & Hs.
 Understanding of theory in the field enables
researcher to place the problem in
perspective e.g. Structural, AKIS, AOA + IPs.
 Insights – procedures + instruments have
proved useful/less promising, successes/ failures.

10.  Avoids unintentional replication of previous studies. (N. B
 Avoids unintentional replication of previous studies. (N.B. Intentional replication OK or additional variables).  Provide intellectual context – facilitates interpretation or determination of significance of own results (increase credibility of own findings).  Identifies gaps in current knowledge (BOEB).  Identify researchers in the same/related fields (research network).  Increase your knowledge base.  Identify opposing views e.g. FTLRP.  Discover transferable information + ideas.

11. Limitations of secondary data
Access – e.g. accessing variables of interest (not in public domain/unpublished).
Relevance – e.g. data collected by others for different purposes (specific research problem).
Reliability – e.g. info on how data was collected (bias + error).
Conceptualization – e.g. HH, income data, sales, 2012/13 (several sources).
Timescale – e.g. data out-of-date, estimates + extrapolations (popn. growth).
Source bias – e.g. vested interests (objectivity) – MAMID/FAO; MAMID/WFP; External EPEs/M&E reports.

12. Sources of secondary data
Internal info sources – e.g. GMB delivery volumes/stocks (disaggregated) vs. annual reports.
External info sources – e.g. agric. research/extn. orgns., hospitals + clinics, websites.
Development statistics – FAOSTAT, WB websites, Millennium Development Goal Indicators.
Non-official sources
- Consultancy reports.
- M&E reports e.g. baseline surveys.
- Other project documents.

13. Recording details of secondary data
Author(s).
Date of publication.
Title of the work cited.
Publisher.
Place of Publication.

14. Evaluating secondary data
Literature evaluated for accuracy + usefulness.
Guiding evaluation questions:-
(i) What was the purpose of the study? – variables,
reporting domains + degree of precision.
(ii) Who collected the info? – expertise +
credibility.
(iii) What info was collected? – e.g. HH income(all)?
(iv) When was the info collected? – interpretation
e.g. nature of season vs. HH FS.
(v) Which geographical area does the data
represent? - e.g. diff. sources/time frames.

15. (vi) How was the data collected
(vi) How was the data collected? – quality (sample size), observation/recall, single/multiple visits. (vii) Is info consistent with other info? – triangulation (multiple sources) + credibility (similar conclusions).

16. Working with secondary data
3 broad ways in which secondary data is used:-
Res. using aggregated secondary data to inform a study that will generate its own primary data
e.g. lit. review of marketing decisions + HH survey.
Res. using aggregated secondary data as a major source of info e.g. comparisons of development indicators or poverty levels.
Res. using disaggregated secondary data (in raw form) as a major source of info e.g. modelling agric. supply response using secondary data (ZimStats).