Timothy J. Bartik, an ECI network member, is a Senior Economist at the W.E. Upjohn Institute for Employment Research. His research focuses on state and local economic development and local labor markets, which includes studies of how taxes and public services, such as education, affect local and national economies. Among his many publications, Dr. Bartik's “Jobs for the Poor: Can Labor Demand Policies Help?” in 2001 was named a "Noteworthy Book in Industrial Relations and Labor Economics" by Princeton University's Industrial Relations Section. He received his B.A. in Political Philosophy from Yale University in 1975 and his M.S. and Ph.D. in Economics from the University of Wisconsin-Madison in 1982.
Describe your area of study and how it relates to current issues of inequality?
I focus most of my research on evaluating various policies affecting local prosperity, particularly local prosperity brought about through improving local labor markets. I focus in part on labor demand policies that try to intervene with firms to encourage both more jobs and better jobs at the local level in the US. I also focus on policies that affect the quality of the local labor supply, which includes preschool as well as education and college scholarship policies and job training policies. So basically I’m concerned with what can create a more prosperous local economy.
I think how this research relates to current policy discussions surrounding inequality is that given current paralysis of the federal government on many policy issues, what state and local governments do to affect local prosperity is of increasing importance. And given some inefficiencies that sometimes occur in federal policy, it is wise to allow for state and local initiatives.
In other words, one advantage that’s been noted about local policy in the US is that local areas can ideally be laboratories of democracy. They can try out new policies either in encouraging job growth, encouraging better job growth, or encouraging better quality local labor supply and they allow an opportunity for experimentation.
But of course those experiments aren’t of much use unless someone actually evaluates whether the experiments worked. So a lot of my work is concerned with trying to better evaluate what state and local policy makers are doing to alter local labor markets and how effective it is, not just in improving the overall number and quality of local jobs or improving overall human capital, but how those improvements are distributed across different income groups and different ethnic groups.
What areas in the study of inequality are most in need of new research?
We know some things about this local labor market research area. We know that simply giving cash to companies -- through tax incentives like Wisconsin did with Foxconn -- is an approach that can work but at a pretty high cost per job. It doesn’t do enough to create jobs relative to the cost.
So, if we’re really going to improve job growth and quality job growth at the state and local level, we need more effective policies. A lot of my work has promoted the idea that we need to either target policies to identify industries and firms that have higher multipliers, that is that for every job created in the target firms we’re going to get more spillover jobs in related industries and clusters of industries, so we need to identify higher multiplier effects, or we need to identify policies that have more effect per dollar on inducing firms to expand.
I’ve done some research on manufacturing extension and customized job training that shows that these customized services to companies can be more effective. However, I don’t think there’s been enough research done on these services. There has been nowhere near enough evaluation work. There are a few good studies, but we don’t fully understand what kind of customized business services really work and why. We don’t have nearly enough knowledge.
On the labor supply quality front, I think we know that high quality pre-K can work. We know that certain expansions of K- 12 spending can work, such as lower class size, extending learning time through high quality summer school, and high intensity tutoring. We know that place-based college scholarship programs, such as the Kalamazoo Promise, can pay off. We don’t know enough about what particular elements make for the highest quality in these programs.
For example, in pre-K, we talk about quality pre-K making a difference, and we have some ideas about what goes into high quality pre-K, but we could certainly use more good studies that really show what are the key elements of high quality. I think the same is true of the K-12 educational system as well as with college scholarships. We have some knowledge about what works, but nowhere near enough about what are the key components of quality.
To summarize: I would say we know something about what works in the case of both encouraging quality job creation by firms, and encouraging higher-quality labor supply by local workers, but we don’t have the in-depth knowledge that policy makers want about what are the key components of quality. So I would encourage researchers to be looking more at the details for what makes for a high quality program, both on the labor demand side and the labor supply side.
What advice do you have for emerging scholars in your field?
My advice is, first of all, to talk to policy makers. Learn more about what some of their concerns are, learn more about what are some of the problems they’re running into, and the challenges they’re running into when they’re running quality programs. Take seriously what some of those concerns and details are. I also think scholars should talk more to firms about what’s going on, and what are some of the barriers these firms see to creating quality jobs. Also, spend some time talking to job seekers. In other words, I think acquiring some institutional knowledge can stand you in good stead.
Obviously, a lot of scholars, especially in economics, come out these days and their computer skills are great, their econometric skills are great. But I think if these quantitative skills were complemented with some institutional knowledge that would stand people in good stead.
I also think we need more work that takes numbers very seriously. In other words, it’s not just important to identify if some variable has in some estimate a high t-statistic, we need to actually worry a lot about what quantitatively the numbers mean in terms of whether the policy passes a benefit cost test or not. Sometimes in work I review for journals, I see a lot of authors who don’t seem to worry enough about what do their estimates mean for policy makers? Is this number a large number, a small number, and what do I mean by large or small? I think it’s useful to think about the numbers you produce and what role they would play in a benefit cost analysis. Are they large, are they small? And of course sometimes a number can be both large in some ways and small in other ways, so it’s actually a tough question to ask yourself. More people should worry about the quantitative importance of their findings. If that were done, I think that would increase the quality of a lot of research that’s been done.