Luskin Center for History and Policy Workshop

“Putting History to Work” 

From Private Acts to Social Movements:

Using Quantitative Data to Effectively Describe the Problem 

Kenya L. Covington, UCLA Luskin School of Public Affairs

December 3, 2018


The third Luskin Center for History and Policy workshop of 2018-2019 was led by Dr. Kenya Covington, of the UCLA Luskin School of Public Affairs. Dr. Covington’s work deals with the problem of spatial inequality in metropolitan areas in the United States, and her presentation at the LCHP workshop focused on two important policy-related skills: using quantitative data in policy work and effectively defining a problem for policymakers in a policy brief or working paper.

Dr. Covington explained the basics of quantitative methods and defining a policy problem by describing a recent research project she undertook. She became interested in the issue of “spatial mismatch,” a problem whereby individuals are unable or do not live close to the majority of jobs for which they are eligible. This problem disproportionately affects Blacks and other people of color in US cities. Dr. Covington sought to explore whether unemployment related to spatial mismatch was related to racial inequality in access to public transportation or car ownership.

In order to investigate the problem, offer policy recommendations, and make her work accessible to policymakers, Dr. Covington followed four steps. First, she defined the exact policy problem should would seek to address. Second, she assembled quantitative data and developed a statistical model that would allow her to show that the problem affected a large number of people. Third, she weighed policy options and selected the recommendation she thought would most effectively offer a remedy to the problem. Fourth, she projected the outcomes were her policy recommendation to be implemented.

Dr. Covington then focused on the second of these tasks: assembling quantitative data. She noted that quantitative work should always begin with a descriptive analysis, including, for example, demographic data, unemployment statistics, etc. After gathering these metrics, quantitative models should control for other variables. Multivariate models do this best. She added that in order to capture the attention to policymakers, quantitative data must seek to capture a broad population, but it must also have a “logical” or clear descriptive explanation that can be outlined in a policy paper.

Dr. Covington then shifted to explaining how, after assembling data and developing a policy recommendation, researchers can effectively define a policy question in the first section of their policy paper. This is the most important statement that appears in a policy paper, and it should be drafted after all other research and recommendations have been conducted and selected. To develop a problem statement, researchers should follow five recommendations:

  1. Problem statements appear at the beginning of a policy paper. They should be one clear statement, preferably one sentence long.
  2. They should be normative and positive. In other words, they should incorporate objective facts (quantitative elements) of an argument, while taking a stand about a particular social issue.
  3. They should be specific, not general.
  4. They should be actionable. The policy recommendation itself should not be located in the problem statement, but it should be clear that the paper believes that a reasonable policy objective can be pursued in order to remedy the problem.

Dr. Covington also provided a reading list on quantitative and statistical basics for academics. To view the paper, please click here.

To view Dr. Covington’s paper on spatial inequality, click here.