INTRODUCTION TO RESEARCH METHODS IN ECONOMICS Topic 4 Research Design Part II: Getting the Answer These slides are copyright © 2010 by Tavis Barr. This work is licensed under a Creative Commons Attribution- ShareAlike 3.0 Unported License. See for further information.

Topic Outline ● General Criteria for Research Design ● Choosing an Approach ● Deciding on a Data Collection Strategy ● Formulating a Budget ● Defining Assumptions

Research Design: General Criteria ● Process should be universal: Any competent researcher should be able to carry it out – The research question is bigger than the researcher; the researcher is merely a catalyst – The beliefs and prejudices of the researcher should not affect the end results

Research Design: General Criteria ● Process should be universal: Any competent researcher should be able to carry it out – Counterexample: ● I am studying behavior of non-governmental organizations. ● I believe it is driven by donor needs. ● I ask only questions about donor needs.

Research Design: General Criteria ● Results should be repeatable by any other researcher who collects the data under the same circumstances and using the same parameters as specified in the research proposal – Results that are not repeatable do not answer the question universally

● Results should be repeatable by any other researcher who collects the data under the same circumstances and using the same parameters as specified in the research proposal – Counterexample: ● I am studying the relationship between study habits of students and exam performance. ● I ask all my friends detailed questions about their study habits, and find out their exam scores at the end of the semester. Research Design: General Criteria

● Controls should be specified and implemented as extensively as possible – Research is only repeatable if the circumstances are known and repeated exactly – Circumstances must be given to future researchers to allow for replication

● Controls should be specified and implemented as extensively as possible – Counterexample: ● I am studying the relationship between the organization of trucking companies and their profitability ● I only study formally registered enterprises, because their income accounts are more reliable ● I neglect to mention this last fact to anyone Research Design: General Criteria

● Outcome of observations should be measurable in an objective way – Counterexample: I am studying whether worker- management cooperation schemes leave workers more satisfied ● I study one plant that implements a scheme and one that does not ● I ask workers, “On a scale of 1 to 5, how satisfied are you with your job?”

● The criteria for measurement should be specified – Counterexample: I am studying whether larger firms pay more than small firms ● I survey workers and ask them their hourly income ● I also ask them, “Is your firm small, medium, or large?” Research Design: General Criteria

Choosing an Approach Quantitative Qualitative The phenomenon studied isObjective Socially constructed Your research question isPredictive Exploratory The relevant literature isLarge Limited Your desire for structure isHighLow ● Generally, economists do quantitative research ● You can do something qualitative if you justify it ● You can also conduct an experiment if it's feasible

Choosing an Approach Quantitative Qualitative The phenomenon studied isObjective Socially constructed Your research question isPredictive Exploratory The relevant literature isLarge Limited Your desire for structure isHighLow ● Examples: – You want to study firm organization in the commercial farming sector – You want to compare the changes in income inequality within different states

● The data should be collected in a way that is repeatable – For primary data, controls should be specified, as should criteria for admissibility (i.e., which data pass controls) – Example: ● We want to test whether the Commercial Bank of Ethiopia lends money to more poor people than private lenders. Which lenders should we include? Data Collection Strategies

● The data should be collected in a way that is repeatable – For secondary data, it should be specified which observations will be used and how (this will be refined later on in the process) – Example: ● You want to test whether having a high school diploma increases your earnings, and by how much ● You have a random sample of 2,000 Ethiopians ● Which observations do you include in your sample?

Data Collection Strategies ● The data should be sufficient to test the hypotheses – For primary data: Are you asking the necessary questions of the necessary people? – Example: ● You want to test whether people with more social contacts spend less time unemployed. ● What questions do you ask, and of whom?

Data Collection Strategies ● The data should be sufficient to test the hypotheses – For secondary data: What do the answers look like? Are they in a form that is sufficiently precise to answer your question? ● You want to test the relationship between hospital availability and infant mortality by state. ● What data do you need?

Data Collection Strategies ● Collection of the data should be feasible – For secondary data: ● Is the owner of the data making them available to you? ● Is it free of charge? If not, how will you pay? ● Are the data in a format that you can work with?

Data Collection Strategies ● Collection of the data should be feasible – For primary data: ● How will you find your subjects? ● Will they be willling to participate? ● Time budget: Finding subjects, interviewing, inputting data ● Monetary budget: Finding subjects, questionnaire, inputting data

Formuating a Budget ● For both primary and secondary: Expenses for analyzing data ● Example: ItemCost Computer time400 Printouts (100 pp)100 Flash drive300

Formuating a Budget ● For primary data: Expenses for conducting interviews, per interview ● Example: ItemUnit Cost Total for 100 ints 1 hr interviewer5 500 Questionnaire2 200 Transport3 300 Total

Formuating a Budget ● You should formulate a time budget, especially if you are doing interviews yourself ● Example: – Conducting 100 interviews: 100 hours – Inputting data: 20 hours – Analyzing data: 30 hours – Writing report: 20 hours ● You should put your time budget into a calendar

Defining Assumptions ● Without assumptions there are no conclusions ● Some assumptions are obvious; some are reasonable but not obvious

● Some are reasonable but not obvious ● Example: Suppose we wish to measure the return to education among bank employees in Addis Ababa – Assume that our measure of education is accurate – Assume our measure of income is accurate – Assume employees choose their level of education – Assume our sample is representative (more on representative samples later) Defining Assumptions

● Some are reasonable but not obvious ● Example: Suppose we wish to measure the effect of cell phone availability on a village's economic output – Assume that our measure of economic output is accurate – Assume we know what the village's economic output would be like without cell phones