Next Research Project

OK - so details still need to be worked out, but I am ready to jump into my next research project, now that my presentation at the Southern Economic Association is over. I think my next research project will deal with worker flows and job flows - I'll be inserting myself into the world of economists like John Haltiwanger (Maryland), Robert Shimer (Chicago), and Robert Hall (Stanford) (each of these guys are really well respected - Haltiwanger and Shimer both have awesome websites with great data made publicly available). This research will also get me some real experience with macroeconomics, without leaving labor economics. Unemployment and job churning is really an interesting area because it's one of the few areas where labor economics (a traditionally "micro" endeavor) and macroeconomics meet. Anyway, I hope gaining some experience here can help set me up to go on and study labor and macro at University of Maryland, which would be a great academic background to have in an economics career.

Worker flow and job flow research emerges out of the idea that unemployment statistics mask underlying dynamics in the labor market. For example - the most recent unemployment rate was 6.5 percent (up from 6.1 percent in September). 6.5 percent of the people in the labor force were out of work in October, 2008. But what does this mean? It could mean that the hiring rate in October was zero and the separation rate was 0.4 percent (6.1 percent in September increases to 6.5 percent because 0.4 percent of the labor force lost jobs, and none gained). In reality, this isn't how it works. The hiring rate might be 7.3 percent, and the separation rate might be 7.7 percent, causing the net unemployment rate to increase by 0.4 percent. Or "churning" could be even greater - hiring could be at 11.2 percent, and the separation rate could be at 11.6 percent! You get the idea. Understanding these underlying dynamics that contribute to our snap-shot pictures of unemployment can go a long way toward diagnosing underlying problems, understanding issues in productivity growth, understanding the effect of different labor market institutions, etc.

Hiring and separation are "worker flow" concepts. Workers "do" those things. Another way of conceiving of the problem is with "job flows". If all firms employ the same amount of workers and the labor force does not grow, the unemployment rate should stay the same. However, if firms lower their employment levels (job destruction) or raise their employment levels (job creation), then unemployment will change. The distinction between these job flows and the worker flows that I mentioned earlier is important. Job flows can be thought of as a subset of worker flows. A worker flow (a hiring or separation) doesn't necessarily imply a job flow, as long as the worker who separated from his job is replaced, and the worker who was hired is replacing an old worker. However, net worker flows and net job flows have to be equal. A standard statement of this is:

Net change in employment = Hires - Separations = Job Creation - Job Destruction

There have been a few "accepted facts" that have been established for worker flows and job flows, and their relationship to unemployment - at least for the national economy:

1. Robert Hall, who primarily deals with worker flows, has established that recessions are caused by declines in the hiring rate, not by spikes in the separation rate (as is commonly thought). He also demonstrates that we shouldn't expect to see separation rates change in response to productivity shocks, and that if we do it is a sign of inefficient wage bargaining (he specifically attributes it to unionization).

2. Haltiwanger and his colleages, who primarily deal with job flows, have established that recessions are caused by spikes in the job destruction rate, and not by an increase in job creation.

These "facts" seem to contradict each other, but they don't have to. Job destruction does not equal separation and job creation does not equal hiring. But they do have different policy implications. Obama has proposed a job creation tax credit. Others propose public employment measures, and others propose cuts in the capital gains tax. There is new legislation in Congress to strengthen unionionization, which as Hall demonstrates - has major implications for separation rates. In other words - this line of research directly connects my labor interests to macroeconomics, and it has LOTS of very relevant "policy levers" to talk about.

The task that interests me most right now is looking at worker flows, job flows, and their relationship to unemployment at the local level. The Census Bureau has quarterly data on job flows and worker flows at the county level for many states - the mid-Atlantic region (I'm thinking of Pennsylvania, New Jersey, Delaware, Maryland, West Virginia, and Virginia) have data going back to before the 2001 recession. I'm interested in tracking the relationship between job and worker flows and unemployment for each county over this period, to ascertain whether Hall and Haltiwanger's "facts" hold true at the level of the local economy. I then want to look into what predicts cases where these "facts" don't hold true, to see if it will help explain the abysmally high unemployment rates in West Virginia, but unbelievably low unemployment rates in Northern Virginia and parts of Maryland. Could it be that the underlying relationship between job flows, worker flows, and unemployment is different in these areas? What implications would this have for policy?

Who knows where this will take me. What's exciting about this field is that new, better data is coming out all the time, and the data is very very accessible.

I think this will be one of two major "research planks" I will try to develop before grad school. The other is research on skilled labor and science and tech policy issues. I don't want to just be a "labor guy". I want to be more forward looking and I want to consider national competitiveness issues as well. A lot of this will come from migrating into some more macroeconomic topics - but I think emphasizing skilled labor and the economics of science and technology will help shape that research agenda as well. I think if I build up a resume with "economic nationalism" papers and presentations it will make admissions departments much more wary than if I have "job flows" papers and presentations - so I figure this is the stuff to work on now. I'll keep reading and thinking about everything, obviously.

Time to search for new calls for papers!

Gross Flows from the CPS!

John Haltiwanger, of the University of Maryland, is famous for introducing and popularizing the "job flows" approach to understanding labor market dynamics, rather than relying on changes in stock measures of employment and unemployment. He and his CES gang at Census has made gross job flow data for the manufacturing industry available for some time. More recently, the BLS has given us the JOLTS survey and the BED survey, which also provide this kind of data. Census also has the QWI which is derived from the LEHD.

But new to me - and now available from the BLS - is what they call "labor force status flow data" derived from the CPS, or what Haltiwanger has called "worker flows". Worker flows complement the job flows that Haltiwanger has done a lot of work with already.

This is really cool. People could always derive worker flows from the monthly CPS, but for someone like me who doesn't have the time to do that, this is really exciting!

I'll add on more later, including links to the other data sources I mentioned above and more on the significance of all this. I just don't have time now. For those who are curious, the Monthly Labor Review recently published an article contrasting three of these data sources (JOLTS, BED, and this new CPS data). This article first alerted me to the availability of this data.

A few cool updates...

I'm REALLY excited to read this new book that came in for birthday: "The Race Between Education and Technology"!! It's about the supply and demand of educated labor since 1900 - and how technological growth has outpaced educational growth since about 1980... implications of that for wages, inequality, etc. Right in line with my SEA presentation (which I really need to write). As soon as I'm done with my current pirate book I'm going to start reading this.

Also really impressed with the HBO miniseries on John Adams... started watching that from the beginning this weekend. I saw episodes 3 and 4 I think, but never saw the first two. Really really good and worth renting.

Finally - I bottled my "Blonde Bombshell" - a wheat ale. It's my first batch to go into glass bottles!!!!! I also brewed hard cider, which should be ready around halloween.

Fresh, Juicy Numbers!

OK, so there's a contingent of economists out there that salivate over the monthly release of some statistic or index by the federal government. I am usually not in this crowd. Nevertheless, two important statistics have come out on the cusp of this particular summer that I thought merited mention.

Today, the Bureau of Labor Statistics released the most recent unemployment data. No surprise - we hit a five year high for unemployment: 6.1%. Paul Krugman has an interesting, quizzical perspective on this figure in his blog this morning. To summarize: 6.1% is bad, but for some reason we're still not in a recession... as Krugman says, the economy is being "ground down" rather than crashing - and this may be what recessions start to look like in the relatively inflation-free early twenty first century.

The second bit of data is the annual Census release of the poverty figures. The Post reports that these figures show an unchanged poverty rate from last year - hanging at 12.5% (no statistically significant difference from last year's 12.3%). Median incomes have climbed slightly. The big story out of these Census numbers surrounds health insurance. The number of people without health insurance has declined by 1 million since last year, from 47 million to 45.7 million. This is unlikely to deflate the momentum behind national health care, but hopefully it will at least moderate some of the positions and move the emphasis away from "coverage" per se, and onto costs - which I think is the real problem.

New Research 2

OK, so the second paper that's been emerging is going to be called something like "Unemployment in the Upper Tidewater: A Job Flows Approach".

Background: Northern Virginia and Southern Maryland have had impressively low unemployment rates for the last two decades or so. I've read reports in the business press (which I should really track down again for this paper) refering to the region as "recession-proof". Oft-cited reasons are government contracts and the IT boom in the region, and the explosive population growth which keeps construction and service workers employed as well. It's very insightful to look at the BLS's LAUS (local area unemployment statistics) maps. Maps for 1999 and 2000 - before the last recession - are especially instructive. Northern Virginia is one big patch of white on the map's color scale - under 2% unemployment. The largest area of land in the country that had unemployment under 2% at the time. Not far to the west, West Virginia is dark purple - one of the largest contiguous areas of high unemployment in the country.

So lots of justifications for why Northern Virginia does so well have been forthcoming - one other explanation I want to explore is the relationship between job flows and unemployment. There are two job flows that people look at: job creation, and job destruction. Job creation occurs when a firm expands its workforce. Job creation statistics are different from hiring and firing statistics. A firm of 50 employs can hire 25 employees and fire 25 employees, and they've added nothing to job creation statistics. Job destruction is just the opposite - the number of positions a company has eliminated. So job creation and job destruction tell a slightly different story from employment, hiring, firing, and unemployment statistics. Net change in employment has to equal job creation minus job destruction - but the job flow dynamics in an economy may differ from their employment dynamics.

John Haltiwanger, of the University of Maryland, has lead the way in research on job creation and destruction. In his most famous book on the subject (creatively called "Job Creation and Destruction"), Haltiwanger identifies many properites of job flows, and in one chapter explores the relationship between job flows and unemployment. The overarching conclusion is that during periods of high unemployment, job destruction spikes and job creation remains relatively constant. It sounds fairly straightforward, but it's an important finding with policy implications. The policy response to this finding would be different, for example, from the policy response if job destruction stayed relatively constant during recessions, and job creation declined significantly.

The problem with Haltiwanger's research is that he primarily looks at aggregate job flow and unemployment statistics. However, the Census's Quarterly Workforce Indicators provide county level job flow data to track whether these relationships occur at the local level. The problem is, these data are only available for certain states at certain times. Very important states - like Massachusetts, Ohio, and New York haven't even produced any. Some, like Maryland, produce the statistics as far back as 1990. So it's a crapshoot. I've been poking around each state's website to see how good their statistics are, and I've discovered that every state in the Fifth Federal Reserve District (Virginia, Maryland, West Virginia, DC, North Carolina, and South Carolina) have data going back to at least 1998 - in other words, covering the last recession.

My plan is to run Haltiwanger's basic analysis on every state in these counties, and determine whether high unemployment counties have a different relationship between job flows and unemployment than low unemployment counties in the district. In other words, does the Upper Tidewater behave just like Haltiwanger's national statistics - only with a smaller increase in job destruction - or does it show different patterns entirely? Perhaps the Upper Tidewater sees a spike of job creation and job destruction during recessions - a sort of "creative destruction" a la Schumpeter. I think it should be interesting.

If things work out, all these stats are available by industry as well.

I envision this being presented at a brown bag at work, where I'll refine it, and then submitted to a minor labor economics journal. Perhaps the Journal of Labor Research, which is published by George Mason. I want a good shot of getting in and publishing something in a journal for once - that's all. I think it's a decent idea - and it would be useful for policymakers in schizophrenic states with areas of very high and very low unemployment. Or even for whole countries where this occurs, like Belgium... in fact, I wonder if Belgium publishes gross job flow statistics....

New Research

OK, I'm far enough along on two "back burner" research projects that I think it's worth talking about them here.

The first is a paper that I'll be presenting at the Southern Economic Association conference in D.C. this November. It addresses the issue of "skills mismatch" in the United States, or more accurately - it computes an index of skills mismatch suggested by Petrongolo and Pissarides (2001) that I haven't seen estimated empirically anywhere and was curious about.

There are lots of "matching functions" out there that try to describe frictions involved with matching one party to another in any of a variety of transactions. The matching I'm concerned with is job matching. A job matching function is usually of the form: M = z(U, V). The number of matches is a function of the number of unemployed workers, the number of job vacancies, and a matching technology z. I won't get into the weeds here, but there is a variation on this model called the "ball-urn model" that looks like this: M = V(1-e^(U/V)). Petrongolo and Pissarides (2001) mention a variation of the ball-urn model that includes "K" - an index of skills mismatch: M = V(1-e^(KU/V)). With a little math, you can solve for K (although they don't). K is the percent of unemployed workers who are qualified for a job vacancy. As K goes up, the second equation I presented converges to the first equation. Anyway, its a nifty, easy little index they suggest that even this public policy grad student can understand - so I thought, why not calculate it for the U.S., and see what I can say about (1.) whether this is even a valuable index, and (2.) trends in skills mismatch in the U.S.

I use the Job Opening and Labor Turnover Survey (JOLTS) data produced by the Bureau of Labor Statistics, along with unemployment figures. The JOLTS data are relatively new - going back only to 2000 - but it is produced monthly, so there's a fair amount of data points. My calculations for K are below:
Conclusions so far? K is clearly very cyclical - it goes up in the summer and down in the winter. Not sure why this could be yet - I don't know much about the seasonality of unemployment. But basically that says that unemployed workers are more qualified for summer jobs than they are for other jobs. I guess that's believable... What is kind of neat is that K is not responsive to the U/V ratio (the red line above). The U/V ratio (also known as the Beveridge Curve) is an index of labor market tightness. When the ratio is high, it means that there are a lot of workers chasing very few jobs. If it is low, it means that there are a lot of jobs out there available for workers. U/V is also the denominator of K when you solve the matching function I presented above. So you would expect that when U/V increases dramatically (as it does in the first few months of the graph), K will decrease. Maybe you could convince me there's a slight drop at that period in time, but not really. K stays very consistent. This is probably a good thing. I don't think many people would be covinced by the idea that skills shortages in the US economy swing dramatically over time. If there are too many workers chasing too few jobs or too few workers chasing too many jobs, you would think the skills ratios among workers and jobs should stay pretty constant.

Next on the list:

(1.) measuring a standard Cobb-Douglas matching function (M = b0 + b1ln(U) + b2ln(V)), allowing b0 to vary over time. b0 is equivalent to the matching technology "z", that I mentioned above. It's an index of general frictions in matching. I'll then chart K against z to determine whether K is really picking up skills mismatch, or whether its just "the share of workers who have a tough time matching to jobs."

(2.) The American Community Survey collects information on the time it takes to travel to work, which could be a proxy for spatial mismatch - one of the most common types of mismatch discussed in the literature. Its an annual survey, unfortunately, so I won't get nearly as many data points - but I want to compare changes in spatial mismatch to K to make sure K isn't picking up those changes accidentally.

(3.) I'm going to reestimate K after differentiating between full time and part time job seekers. In effect, the equation will look like this: M = V(1-e^((-KFT + PT)/V)). This version of K assumes that all part-time job seekers are qualified for whatever jobs they may seek, but some full time job seekers may not be. High paid consultants aside, this seems like a reasonable assumption... and it may get some different dynamics for K.

OK, I need to get a few things ready for work now, so I won't talk about my second research project right now - but here's a teaser title for you:

"Unemployment in the Upper Tidewater: A Job Flows Explanation"... using Quarterly Workforce Indicators data from Census.

Jobs and China

The Economic Policy Institute released a policy brief yesterday which claimed that 2.3 million American jobs were lost between 2001 and 2007 as a result of the trade deficit with China.

Granted, the report is really talking about gross job loss, not net job loss. They don't talk about how many jobs were created by trade with China. Still, the story is pretty clear cut. With trade deficits as massive as the ones we're running with the Middle Kingdom, jobs and money go over there and products come over here - there's not much arguing with that.

We can't slip into mercantilism, as I've warned before - we can't cut off trade out of fear, because we do indeed benefit from cheap products and a more efficient use of the global labor supply... but...

Let's not hollow out the American economy in a free-trade frenzy. You can be a patriotic free trader that prefers to buy American and invest in American economic infrastructure - there's nothing anti-market about that.

Call for Papers

IZA (Instituts zur Zukunft der Arbeit - Institute for the Study of Labor), one of the most important labor research groups in the world, issued a call for papers for its first annual meeting on the economics of risky behaviors, which will be held in Washington, D.C., in the spring of 2009!

I'll hopefully be submitting (pending approval from the Department of Health and Human Services) the Vulnerable Youth project we've been working on at the Urban Institute.

This is really great because most of IZA's activities go on in Bonn, Germany.

Interesting Science, Technology, and Innovation Research Resources

So "skilled labor" is a pretty firm part of my fluctuating list of research interests now, and I've been collecting a bunch of research resources - mostly data - that I'd like to use one day for some work on it. Some is on the high skill labor market, some on innovation in general (patents, R&D spending, etc.)

1. SESTAT is a collection of datasets maintained by the National Science Foundation, and I believe the surveys themselves are done by Mathematica. SESTAT focuses on college graduates in science, technology, engineering, and math fields (STEM). The most interesting dataset in SESTAT to me is the survey of recent college graduates. This survey has detailed employment information on recent STEM graduates - including job search variables and information on how much they use what they learned in school on the job. I could think of some great "human capital utilization" variables that could be constructed from this that would be comparable to the "capital utilization" data collected on manufacturing plants by the federal reserve banks. There is also a survey of all college graduates that surveys a sample drawn from the decennial census. The advantage of this data is that it provides a cross section of the skilled laborforce. The disadvantage is that since these aren't recent graduates it doesn't give a good picture of recent changes to skilled labor supply, or what to expect in the future.

2. NSF provides lots of other data as well - the most interesting to me being a long time-series on R&D funding by source. It would be interesting to track how federal vs. state R&D funding has changed over time, and where they've been spending it.

3. Just yesterday I discovered the National Bureau of Economic Research's (NBER's) Science and Engineering Workforce Project. It's just a general forum and resource for relevant research - the usual suspects are here: George Borjas, Richard Freeman, etc. It also has a link to an intriguing project called the “Nanobank". This is how the Nanobank describes it's work:

This project uses econometric methods to estimate the impact of nanoscale science and technology (nano S&T) research, and associated interdisciplinary research, directly on firms' entry and success and hence on U.S. economic growth, standard of living, and competitiveness. The research team also performs scientometric and institutional analyses of diffusion and networks in nano S&T and converging fields, and the reciprocal effects of institutions on nano S&T and of academic scientists' involvement in commercialization on their scientific productivity and teaching.

It also has some beta test data available for download on patents, patent citations, NSF grants, and NIH grants. I assume it is all nano-specific patents and grants here. The patent data interest me most. Another NBER source for patent data is Hall, Jaffe, and Tratjenberg's (2001) file. It looks like these patents are from 1963 to 1999 - roughly 3 million of them, with data on 16 million citations. I get the impression these are only specific industries, though - much like the nano-data. That's not a major constraint for me with the "innovation diffusion" modeling I have in mind, but if you need more than that you can always go to the Patent Office website. It's REALLY obnoxious to get data from here - you have to do it a page at a time so extracting millions of patents right from the website is not an option - but you do have access to information on every single patent ever issued since the beginning of the republic... that's pretty freaking cool.

4. The Integrated Postsecondary Education Data System (IPEDS), produced by the National Center for Education Statistics in the Department of Education has detailed graduate data for every postsecondary institution in the country - including graduations by field, race, and gender. It also has lots of finance information at the school level, although unfortunately not at the degree program level (i.e. - you can track federal grants going to the school, but not federal grants going to the school's physics department). I used this data in a report by Hal Salzman on the STEM workforce , but I think there is a LOT more that could have been done with it. I still need to read the final product, but I think I would take issue with some of the intepretations that Hal applied (more related to the labor demand side of the skilled labor market, which I didn't not help him with or even read yet - rather than the labor supply side which I'm more familiar with).

More resources to come, potentially... maybe I should put up some international resources for potential research on comparing the U.S. to other countries.

MDRC on Career Academies

Just back from the Hill for the release of this new MDRC report on career academies. Interesting stuff, awesome looking data... I'm gonna bug the authors to see if it's publicly available for one of my current research ideas:

"Should we be evaluating employment programs like we evaluate new drugs?: Group Based Trajectory Analysis as an evaluation methodology"

George Will on High-Skilled Immigration

This morning, George Will wrote about high-skilled immigrants, and advocated increasing the number of H1-B visas that these workers use to enter the U.S. I'm very torn on this issue. On the one hand, I can't reasonably oppose free markets and open borders. The logic behind these policies is absolutely unimpeachable, in my mind. However, that doesn't mean there aren't extenuating circumstances, market failures, and opportunities for government to pursue a "sub-optimal solution" that satisfies other goals.


One thing that Will does make a good point on is the irony that we throw the doors wide open for foreign students to study in the U.S., and then errect barriers to coming here to work. These foreign students take up as much as two-thirds of the slots in prestigious science and technology graduate programs in the U.S., and are then forced to go back to their home countries, or to Europe for employment. Essentially that means that we are subsidizing the economic growth and human capital stock of our competitors, and that is ridiculous. We need to open the doors to our universities and our corporations in a coordinated way - if we only let students in, but not workers, we are shooting ourselves in the foot.


However, there is a very real question about whether a skills shortage even exists in the U.S., an issue which Lou Dobbs addresses with his usual gusto. If this research is correct and skills shortages don't really drag down the U.S. economy, there is no reason to get apoplectic about the availability of H1-B visas. In fact, strong evidence against the existence of real skill shortages may even force us to reconsider further cuts in H1-B visas, although I'm not necessarily convinced that's a wise move right now. I'm going to be exploring this issue further in a paper I'll present at the 2008 Southern Economic Association conference, and I may blog on this research in the future.


Currently I'm an agnostic on this issue, but Will raises interesting points. It's also great that he considers student visas and H1-B visas together - they do need to be understood as two sides of the same coin. Ultimately, I'd like us to be able to have a very liberal student visa and H1-B visa policy - but I don't think we should move there until we find a way to get American companies to hire American graduates in these high-skill fields. As the research summarized by Lou Dobbs suggests, we seem to have a surplus of American graduates... who is hiring them???


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A second note that my more philosophically inclined readers may be interested in:


I was struck by one line in the Will article about modernity. Speaking of computer chips, he wrote: "modernity means the multiplication of dependencies on things utterly mysterious to those who are dependent"


An interesting thought. But that leads me to ask... how is that any different from pre-modern dependencies on various superstitions and shibolleths?