Researchers in the field of economics are increasingly realizing that race and ethnicity are the main determinants of economic outcomes.
However, convincingly assessing potential causes and identifying solutions is often complicated by the lack of high-quality data. The work of a typical economist focuses mainly on proposing relationships and testing causal mechanisms across a wide array of economic phenomena.
The consequences of race in race study and market interactions have long been hampered by the relative lack of longitudinal data collected on indicators of relevant discrimination, racism and related long-term consequences.
Within the framework of these limitations, a special joint session convened an expert panel of academics, statistics authority officials and non-profit organizations. (American Economic Association Economic Statistics Committee, in collaboration with the National Economic Association, in Allied Social Science Societies).
2021 meeting in January. Its main objectives were to assess the state of federal statistical data and its ability to document significant racial inequalities. Participants also discussed the difficulties in accessing and collecting administrative data, possibly linked between institutions. Such data can help facilitate new research and identify where the most pressing problems continue and how they can be addressed.
An important theme that emerged from the discussion was that the available data sets were of limited utility for determining the breadth and extent of the results and examples of racism.
Three main points emerged from this discussion:
First, most standard datasets such as the National Longitudinal Study of Youth (NLSY), Survey of Consumer Finance (SCF), and Panel Study of Income Dynamics (PSID) do not provide sufficient observation for groups such as Asians and American Indians.
Therefore, there is a need to expand existing data sets with excess samples of certain groups that are not typically included in existing longitudinal studies. Without such data, there will continue to be a lack of persuasive empirical research for specific groups and populations.
A second point regarding the lack of available data relates to the fact that important aspects of discrimination and racism are not often measured in standard data sets.
Specifically, this refers to all the “behind closed doors” discussions where hiring, promotion or loan decisions are made. There was an important claim that additional data was needed to allow researchers to identify different rates of application and denial by racial and ethnic groups for various economic activities.
While undoubtedly difficult to capture, these covert activities are important in determining the true rates of discrimination in society. More work needs to be done to force new data collection methods that provide direct or indirect measures of these important non-market factors and behaviors.
The third point that emerges from this discussion is the emerging opportunities that exist for linking administrative datasets at the federal and perhaps state government levels. These large datasets can have sufficient observations to make meaningful segregation and analysis according to racial and ethnic groups without the need for additional data collection.
There are new studies and analyzes showing the potential of this data source in measuring racism and discrimination. In fact, this activity is in line with a new Presidential Executive Order (EO) aimed at promoting racial equality through the US Federal government.
“Therefore, the policy of my administration is that the Federal Government should take a comprehensive approach to promote equality for all, including people of color and historically inadequate service. People who are marginalized and suffered from persistent poverty and inequality.”
In particular, EO provides a Fair Data Working Group committee. The committee of federal officials was tasked with “determining the shortcomings in the existing Federal data collection programs, policies and infrastructure across institutions and the strategies to address all the deficiencies identified”.
EO said, “… many Federal datasets are not disaggregated by race, ethnicity, gender, disability, income, seniority, or other important demographic variables. This lack of data has cascade effects and hinders efforts to measure and improve equity. The first step in promoting equality in government action is to collect the necessary data to inform this effort.”
In our own study, we felt the difficulty of conducting research on discrimination and racism due to the lack of data. In fact, we had to link data between public, private, and confidential usage datasets to run most of our work. These creations were the only way research in these areas was possible, even in a limited sense.
Akee’s work on the impact on federal land allocation and home ownership for Native Americans in the early 1900s. Akee (and a few research assistants) had to use historical census data to link individuals together over time.
In another study, we correlated data on an individual’s race or ethnicity with annual income metrics to create measures of income inequality and income mobility over time by racial groups. Similarly, Casey’s study of identifying racial and ethnic price differences and neighborhood ranking behavior in residential markets combined longitudinal housing transactions data with the US Census and Home Mortgage Disclosure Act (HMDA) data.
While in all cases these data represented a significant advance, there were important limitations or omissions that ultimately prevented strong conclusions about the source of these inequalities. In particular, such longitudinal data is difficult to access, link and secure use. Opening opportunities for access to data to all research levels will likely lead to more creative and precise research in the future.
Akee, Randall. “Land titles and dispossession: Allotment on American Indian reservations.” Journal of Economics, Race, and Policy (2019): 1-21.
Akee, Randall, Maggie R. Jones, and Sonya R. Porter. “Race matters: Income shares, income inequality, and income mobility for all US races.” Demography 56, no. 3 (2019): 999-1021.
Bayer, Patrick, Marcus Casey, Fernando Ferreira, and Robert McMillan. “Racial and ethnic price differentials in the housing market.” Journal of Urban Economics 102 (2017): 91-105.
Biden Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government, Jan 20, 2021.
“American Economic Association Committee on Economic Statistics and National Economic Association Joint Session on Measuring the Economic Effects of Systemic Racism and Discrimination: A Summary.” February 2021.