Developing a research question and research topic

1. Developing a research question and research topic Hans P. Binswanger-Mkhize Visiting Professor China Agricultural University May 3, 2013

2. Start with a policy-relevant question • Directly relevant: it answers a specific question • how much to invest in agricultural research? • what incentives to provide to researchers to increase their productivity? • Whether to subsidize agricultural mechanization? • Indirectly relevant: It analyzes an underlying behavior or theory: • What motivates people to buy pension insurance? • Is the induced innovation theory correct? • You can test relevance of the question • What difference would it make if answer is yes or no

3. How do you find such a question? • The question is important for your employer or funder • Risk research at ICRISAT; research on impact of credit at the World Bank • The question knocks at your door • Testing induced innovation hypothesis • Research on herbicides at ICRISAT • Research on decentralization, community empowerment, and rural development

4. More ways to find a question • It can come up in your courses • Via knowledge of literature, and additional review • Research on: What is the historic origin of large scale farm systems around the world? • A major insight during research leads to new questions • Why do village money lenders not lend out deposits? • Led to work on covariant risk and production relations in agriculture • Other lucky breaks

5. The answer should be unknown, i.e. not answered by previous research • A globally unsolved question • It is not easy to find such questions • or to answer them, • otherwise someone else would already have done so • Examples • Is the induced innovation theory of Hayami and Ruttan correct? • How does risk aversion influence investment of farmers? • What is the historic origin of large scale farms? • You will easily be able to publish in global journals

6. Answer not known in your country, region or sector • Example: What are the recent changes in economies of scale in chinese farming? • Relevant to the proposed changes in land laws • Approaches and techniques are known • Publish globally or nationally, depending on how generalized the interest in the answer is • You must do the literature review • to find out whether the question is already answered • to find out how to answer the question

7. Finding a question for an especially rich data set • Example: We may have a new especially rich panel survey of household incomes and behaviors and their rural governments • There are lots of questions that you can answer with such multi-purpose data sets. • But first you must have an interesting question • Try to figure out one for yourself • Dialogue with your advisors, or with another user of the data set. • Example: What is the impact of local government expenditures on household incomes, their farm production, health, education……?

8. Finding a question for a specific technique • Eg: I want to use principle components analysis, an economic experiment, or a programming model • Not generally a good idea • Techniques are like tools: You use a hammer for putting in nails, and a screwdriver for putting in a screw. • There is nothing specially good about the hammer versus the screwdriver, or about econometrics versus experimental techniques • So you need to choose the tool to fit the question • Simple partial budgeting • Analysis of survey data • Econometrics • Controlled Experiments • Modeling

9. But there are exceptions: • If you master a technique, people seek your help for their topic. You are their consultant and/or collaborator, and can become a co-author • Or a technique is very new, and there are many unanswered issues • Esther Duflo only uses randomized experiments to evaluate impact of approaches to development • She has the whole World to choose from for interesting problems • Example: Microfinance in Hyderabad: no impact on consumption, education, health, women empowerment, but impact on durable goods spending and new businesses

10. Using the right data • First try to find data that is already available • But the right data may not exist • Measurement of risk, risk aversion in India • Adoption of mechanization in Africa • Impact of land rights in Africa • Impact of governance arrangements on village development in India or China • Then you have to develop the data from scratch • Or sometimes the data exist, but data components are missing: add the missing data • That is a lot of effort. Therefore • Make sure the data can answer the question • If not you are wasting your time

11. How to establish causal relations Topic of my next lecture

12. Summary Criteria for Research Question • Are you really interested in it? • Is it policy relevant, directly, or indirectly? • For whom? • What difference would alternative answers make? • Is the answer unknown? • Globally or locally? • In terms of methods and/or results • What data are needed? • Are they already available, or at least partially available • Do they have to be collected from scratch