Productivity

13th Time’s A Charm: Finally Grant Funded

James BaileyLeave a comment

I just found out I’ll be receiving a Course Buyout Grant from the Institute for Humane Studies. It will allow me to teach less next year in order to focus on my research on how Certificate of Need laws affect health care workers.

I’m happy about this because I think this research is valuable and time is my main constraint on doing it (especially doing it quickly enough to inform ongoing policy debates in several states). But I’m also happy because I finally got what I consider to be a “true” grant after many rejections.

I’ve received research funding many times before (e.g. Center for Open Science funding for replications), but it was always relatively small amounts that went directly to me. True grants tend to be larger and to be paid directly to the university. That’s the case with the course buyout grant, which essentially pays the university enough that they can hire someone else to teach my class.

I may have lost count but I’m pretty sure this was the 13th “true grant” I have applied for, and the 1st I will actually receive. Academics have to get used to rejection, since we need to publish and decent journals tend to reject 80%+ of the articles they receive. But for some reason I’ve found grants much harder even than that. From some combination of skill, luck, and targeting lower-tier journals than perhaps I could/should, my acceptance rate for journal articles is probably nearing 50%. I expected this to translate over to grants but it absolutely did not, they seem to be a much different ballgame, one I’m still figuring out.

I’d like to share some of those past misses, both to let junior people see the bumpy road behind success (like a CV of failures), and to try to extract lessons from an admittedly small sample. These proposals were not funded, and probably weren’t even close:

  • Peterson Foundation US 2050
  • MacArthur Foundation 100 & Change
  • RI INBRE (2x)
  • National Institute for Health Care Management (1x, waiting to hear but probably about to be 2x)
  • Kauffman Knowledge Challenge
  • Economic Security Project
  • Emergent Ventures
  • FTX Future Fund (sometimes rejection is a blessing in disguise)
  • Smith Richardson Foundation
  • AHRQ

What did these failures of mine all have in common? Me, of course. This is not just a truism; in most of these cases I was applying for major grants solo as an assistant professor without previous funding. The usual advice is to work your way up with smaller grants or, preferably, as the collaborator of a senior professor with lots of previous funding who knows how things work. I knew that would be smart but I’ve tended to be at institutions without senior people in similar fields; almost all my research has either been solo or coauthored with students or assistant professors. Even my PhD advisor was a brand-new assistant professor when we started working together. I had good reasons for ignoring the usual advice to work with well-known seniors, and it has mostly served me well, but grants seem to be the exception.

Twice, I think I did come close on grant proposals, and both times it involved help from seniors at other institutions who had lots of previous funding. At one foundation that funds a lot of social science, my senior coauthor and I got glowing external reviews, but the internal committee rejected us on the grounds that we could do the project without their funding. They were right in the sense that we did do project anyway with no funding; it got published and even won a best paper award. But with their funding we would have done it faster and better and they would have gotten credit for it.

I do think it is smart for funders to consider whether the research would happen anyway without them, or whether their funding really improves things. But I think it is rare for funders to actually do this, and taking this rejection as advice probably led me to more rejections. I tried to propose bigger, more ambitious projects that needed expensive data so it was clear that I really needed the funding; but for most funders this probably made things worse. I have since heard several times that people who get lots of funding from major funders like NIH tend to submit proposals for research they have essentially already finished; that is why their proposals can look so thorough, credible, and polished. They then use the funding to work on their next project (and next proposal) instead of what they said it was for. That seems sketchy to me, but it’s certainly ethical to turn the proposal dial back somewhat toward “obviously achievable for me” from “ambitious and expensive”, and that’s what I’ve done more recently.

The other time I came close was with an R03 proposal to the Agency for Healthcare Research and Quality. First I got a not-close rejection, as I mentioned in the big list, where my proposal was “not discussed”. But AHRQ allows resubmission. At the prompting of my (excellent) grants office, I got feedback on the proposal from two kind seniors at other schools who get lots of funding. I rewrote the proposal based on their comments plus the rejection comments (which were actually quite detailed despite it being “not discussed”) and resubmitted it. This went way better- the resubmission got discussed with an impact score of 30 and a percentile of 17. Lower scores are better for AHRQ/NIH so this was pretty good, good enough that it might have been funded in a normal year, but 2019 was a bad year for government funding (though through some weird quirk I never actually got rejected; 4 years later their system still says “pending council review”). Again, the key to getting close was getting detailed feedback from people who know what they are talking about.

Of course, it also helps to get to know people at the funders and to become more senior yourself. It’s not surprising that my first major grant is coming from IHS given that I’ve been involved with them in all sorts of ways since going to a Liberty & Society seminar way back in 2009. Most funding goes to more senior people who have more connections, knowledge, and proven experience. This is extreme at perhaps the largest funder of research, the National Institutes of Health, where less than 2% of funded principal researchers are under age 36.

This may be the real secret for winning grants- just get older. My 12 rejections all came when I was younger than 36, while my first acceptance came less than a month after my 36th birthday.

In all seriousness, thanks to the Institute for Humane Studies, and I hope that a year from now I’ll be writing here about the great work that came out of this. For everyone with a growing pile of rejections, maybe the 13th time will be the charm for you too.

Basic Immigration Logic

Zachary Bartsch2 Comments

Economists overwhelmingly favor looser immigration controls. Allowing people to immigrate would improve the allocation of scarce labor and capital and it is a far cheaper way to aid poorer families than sending direct payments or trying to develop an entire country. Let’s cover some static analysis basics for migrating workers and their dependents.

Workers, Labor Markets, & Output Markets

There are two markets to consider: The new home country and the old home country. If workers leave the old country in search of the higher wages in the new country, then world employment remains unchanged. Employment obviously rises in the new country and falls in the old country. With identical laborers (a terrible assumption that’s the least charitable to immigration), wages in the new country fall and wages in the old country rise. This logic illustrates the cheap aid of which economists are fond.

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Video of Joy Buchanan on Tech Jobs and Who Will Program

Joy Buchanan2 Comments

Here are some show notes for a keynote lecture to a general audience in Indiana. This was recorded in April 2023.

Minute Topic
2:00“SMET” vs STEM Education – Does Messaging Matter?  
(Previous blog post on SMET)
5:00Is Computer Programming a “Dirty Job”? Air conditioning, compensating differentials, and the nap pods of Silicon Valley  
(post on the 1958 BLS report)
7:50Wages and employment outlook for computer occupations
10:00Presenting my experimental research paper “Willingness to be Paid: Who Trains for Tech Jobs?” in 23 minutes  

Motivation and Background 10:00 – 15:30
Experimental Design         15:30 – 22:00
Results                    22:00 – 30:00
Discussion                 30:00 – 33:30
33:50Drawbacks to tech jobs  

See also my policy paper published by the CGO on tech jobs and employee satisfaction
35:30The 2022 wave of layoffs in Big Tech and vibing TikTok Product Managers  

I borrowed a graph on Tech-cession from Joey Politano and a blog point from Matt Yglesias, and of course reference the BLS.
39:00Should You Learn to Code? (and the new implications of ChatGPT)  

Ethan Mollick brought this Nature article to my attention. 
Tweet credits to @karpathy and @emollick
48:00Q&A with audience

Health Insurance and Wages: Compensating Differentials in Reverse?

James Bailey9 Comments

One of the oldest theories in economics is the idea of compensating differentials. A job represents not just a certain amount of money per hour, but a whole package of positive and negative things. Jobs have more or less stability, flexibility, fun, room to grow, danger… and non-cash benefits like health insurance. The idea of compensating differentials is that, all else equal, jobs that are good on these other margins can pay lower cash wages and still attract workers (thus, the danger of doing what you love). On the other hand, jobs that are bad on these other margins need high wages if they want to hire anyone (thus, the deadliest catch)

I think this theory makes perfect sense, and we see evidence for it in many places. But when it comes to health insurance, everything looks backwards. A job that offers employer-provided health insurance is better to most employees than one that doesn’t, so by compensating differentials it should be able to offer lower wages. There’s just one problem: US data shows that jobs offering health insurance also offer significantly higher wages. The 2018 Current Population Survey shows that workers with employer-provided health insurance had average wages of $33/hr, compared to $24/hr for those without employer insurance.

All the economists are thinking now: that’s not a problem, compensating differentials is an “all else equal” claim, but not all else is equal here. The jobs with health insurance pay higher wages because they are trying to attract higher-skilled workers than the jobs that don’t offer insurance.

That’s what I thought too. It is true that jobs with insurance hire quite different workers on average:

Source: 2017 CPS analyzed here

The problem is, once we control for all the observable ways that insured workers differ, we still find that their wages are significantly higher than workers who don’t get employer-provided insurance. Like, 10-20% higher. That’s after controlling for: year, sex, education, age, race, marital status, state of residence, health, union membership, firm size, whether the firm offers a pension, whether the employee is paid hourly, and usual hours worked. I’ve thrown in every possibly-relevant control variable I can think of and employer-provided health insurance always still predicts significantly higher wages. Of course, there are limits to what we get to observe about people using surveys; I don’t get any direct measures of worker productivity. Possibly the workers who get insurance are more skilled in ways I don’t observe.

We can try to account for these unobserved differences by following the same person from one job to another. When someone switches jobs, they could have health insurance in both jobs, neither, only the new, or only the old. What happens to the wages of people in each of these situations? It turns out that gaining health insurance in a new job on average brings the biggest increase in wages:

What could be going on here? One possibility is that health insurance makes people healthier, which improves their productivity, which improves their wages. But we control for health status and still find this effect. The real mystery is that papers that study mandatory expansions of health insurance (like the ACA employer mandate and prior state-level mandates) tend to find that they lower wages. Why would employer-provided health insurance lower wages when it is broadly mandated, but raise wages for individuals who choose to switch to a job that offers it?

My current theory is that “efficiency benefits” are offered alongside “efficiency wages”. The idea of efficiency wages is that some firms pay above-market wages as a way of reducing turnover. Workers won’t want to leave if they know their current job pays above-market, and so the company saves money on hiring and training. But this only works if other firms aren’t doing it. The positive correlation of wages and insurance could be because the same firms that pay “efficiency wages” are more likely to pay “efficiency benefits”- offering unusually good benefits as a way to hold on to employees.

I still feel like these results are puzzling and that I haven’t fully solved the puzzle. This post summarizes a currently-unpublished paper that Anna Chorniy and I have been working on for a long time and that I’ll be presenting at WVU tomorrow. We welcome comments that could help solve this puzzle either on the empirical side (“just control for X”) or the theoretical side (“compensating differentials are being overwhelmed here by X”).

Why are desktop computers so cheap?

James Bailey4 Comments

I recently bought a used desktop computer for what seemed like next to nothing. $240 for a machine more powerful than my much-more-expensive 2019 MacBook Pro, most notably due to its 32GB of RAM. Desktops have always been cheaper than equivalently powerful laptops, Windows computers cheaper than Macs, and used computers cheaper than new, so this isn’t totally shocking. But the extent of the difference still surprised me. For instance, buying a new desktop from Dell with similar specs to the used one I just got would cost $1399.

So why is the used discount so big right now? My guess is that its one more knock-on effect of work-from-home. Remote work has been the most persistent change from Covid, and there’s been a huge decline in the demand for office space, with occupancy rates still half of pre-Covid levels.

This means that offices are on sale relative to their pre-Covid prices. Office REITs are down 37% over the past year even after the Covid-induced drop of the previous two years. So it makes sense that all sorts of office equipment is on sale too. Offices tend to be full of employer-owned desktop computers, but when employees work from home they typically use their own machine or a company laptop. That means less demand for office desktops going forward, and a big overhang of existing office desktops that are being under-used. Employers realizing this may just sell them off cheap. Several things about the refurbished desktop I bought, such as its Windows Pro software, indicate that it used to be in an office.

Self-Replicating Machines: A Practical Human Response

Zachary Bartsch3 Comments

Currently, we have software that can write software. What about physical machines that can produce physical machines? Indeed, what about machines that can produce other machines without human direction?

First of all, machines-building machines (MBM) still require resources: energy, transportation, time, and other inputs. A well-programmed machine that self-replicates quickly can grow in number exponentially. But where would the machines get the resources that enable self-replication? They’d have to purchase them (or conquer the world sci-fi style). Where would a machine get the resources to make purchases of necessary inputs? The same place that everyone else gets them.

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Why Have Economists Continually Underestimated Projected Inflation?

Scott Buchanan5 Comments

I keep reading about how inflation has peaked (even peaked many months ago) and so any minute now the Fed will relent on raising interest rates, and will in fact start reducing them. Every data point that seems to support an early Fed pivot and a gentle “soft landing” for the economy is greeted with optimistic verbiage and a rip higher in stocks.

Except – – other meaningful data points regularly appear which show that inflation (especially core inflation) is remaining stubbornly high. The Personal Consumption Expenditures (PCE) Index is the Fed’s preferred way to track core inflation. It did peak in early 2022, and is falling, but very slowly and fitfully. Just when it seems like it is about to cascade downward, along comes another uptick.  The latest report for 02/24/23 showed the PCE index (excluding the volatile categories of food and energy) increasing 0.6 percent during the month of January, which translated to a 4.7 percent year-on-year gain. That was considerably higher than the 0.4 percent monthly gain (4.3 percent year-on-year) that economists expected.

Source: MV Financial

The chart below illustrates the chronic tendency of the economists at the Fed to lowball the estimates of future inflation. Each of the ten bars depicts quarterly projections of what inflation would be for 2023, starting back in September 2020 (first, green bar).  No one in the craziness of 2020 could be held particularly responsible back then for accurately projecting 2023 conditions. But the Fed embarrassed themselves badly into late 2021 by airily dismissing inflation as “transitory”, due mainly to supply chain constraints that would quickly pass. (See towards the middle of the chart, yellow Sept 2021 and blue Dec 2021 bars projecting a mere 2.2% inflation for 2023.)

Source: Jeremy LaKosh

Only as of December 2022 did estimates of inflation jump up to 3.1% for 2023, and that estimate will surely get revised upward even further.

Many factors probably went into this systematic failure on the part of the Fed economists. There are probably political reasons for erring on the rosy optimistic side, which I will not speculate on here.

One factor in particular was mentioned in the Minutes of the Jan 31/Feb 1 Fed meeting that I thought was significant:

A few participants remarked that some business contacts appeared keen to retain workers even in the face of slowing demand for output because of their recent experiences of labor shortages and hiring challenges.

Jeremy LaKosh notes regarding this feature, “If true across the economy, the idea of keeping employees for fear of facing the labor force shortage would represent a fundamental shift in the employment market. This shift would make it harder for wage increases to mitigate towards historical norms and keep upward pressure on prices.”

This all rings true to my anecdotal observations. In bygone days, when business slowed down, factories would lay off or furlough workers, with the expectation on all sides that they would call the workers back (and the workers would come back) when conditions improved. However, employers have had to struggle so hard this past year to find willing/able workers, that employers are loath to let them go, lest they never get them back. I have read that even though homebuilders are not sure they can sell the houses they are building, they are so worried about losing workers that they are keeping them on the payroll, building away.

Other inflation data points show big decreases in prices for goods (and energy), but not for services. Wages, of course, are the big driver for service costs.

So the inflation story in 2023 seems to come down largely to a labor shortage. This is a large topic cannot be fully addressed here. I will mention one factor for which I have anecdotal support, that the enormous benefits (stimulus money plus enhanced unemployment) paid out during 2020-2021 set up a large number of baby boomers to leave the workforce early and permanently. Studies show that this is a major factor in the drop in workforce participation rate post-Covid. Maybe some of those folks had not planned ahead of time for such early retirement, but they got a taste of the good life (NOT getting up and going to work every day) in 2020-2021 along with the extra cash to pad their savings, and so they decided to just not return to work. That exodus of trained and presumably productive workers has left a hole in the labor force which now manifests as a labor shortage, which drives up wages and therefore inflation and therefore interest rates, which will eventually crater the economy enough that struggling firms will finally lay off enough workers to mitigate wage gains.

I wonder if this unhappy scenario could be staved off with increased legal migration of targeted skilled workers from other countries to alleviate the labor shortage. Dunno, just a thought.

Behavioral Risk Factor Surveillance System Survey: Now in Stata and CSV formats

James Bailey1 Comment

The BRFSS Annual Survey is now available in Stata DTA and Excel-friendly CSV formats at my Open Science Foundation page.

The US government is great at collecting data, but not so good at sharing it in easy-to-use ways. When people try to access these datasets they either get discouraged and give up, or spend hours getting the data into a usable form. One of the crazy things about this is all the duplicated effort- hundreds of people might end up spending hours cleaning the data in mostly the same way. Ideally the government would just post a better version of the data on their official page. But barring that, researchers and other “data heroes” can provide a huge public service by publicly posting datasets that they have already cleaned up- and some have done so.

That’s what I said in December when I added a data page to my website that highlights some of these “most improved datasets”. Now I’m adding the Behavioral Risk Factor Surveillance Survey. The BRFSS has been collected by the Centers for Disease Control since the 1980s. It now surveys 400,000 Americans each year on health-related topics including alcohol and drug use, health status, chronic disease, health care use, height and weight, diet, and exercise, along with demographics and geography. It’s a great survey that is underused because the CDC only offers it in XPT and ASC formats. So I offer it in Stata DTA and Excel CSV formats here.

Let me know what dataset you’d like to see improved next.

“Five Talents” Microfinance NGO Helps the Poorest of the Poor to Start Their Own Businesses

Scott Buchanan1 Comment

It is a pleasure to be able to report on a successful microfinance outfit that helps the poorest of the poor. I heard a talk recently from Dale Stanton-Hoyle, CEO of the Five Talents organization. (He is as nice in person as he looks in this photo).

This group was birthed at Truro Anglican Church, in Fairfax, Virginia. An Anglican bishop from Tanzania noted that he had many thousands of people under his care who were suffering so much from hunger and other concomitants of poverty that they had little inclination or energy to listen to elevating spiritual messages.  As he put it, “An empty stomach has no ears.”

Inspired by Jesus’ parable of the talents, where servants were each entrusted with some large sum of money (expressed in “talents”) and were expected to multiply that money productively, a group was formed in 1998 to help people living in the most extreme poverty to build productive enterprises.

Their approach would be classified as micro-credit, which nowadays is well-known and well-regarded approach. The modern stream of micro-credit, which is a subset of microfinance, has its roots In the Grameen Bank of Bangladesh, founded by micro-finance pioneer Mohammed Yunus in the 1970s.

Five talents describes itself more specifically as:

A micro-enterprise development organization that helps the world’s most vulnerable families escape poverty. Partnering with local churches around the world, we train men and women, mostly women living in extreme poverty, to form savings groups, take out loans, and build their own businesses.    It may seem surprising, but even those living in extreme poverty can save a little each week, start a tiny business, and fulfill their God-given potential.

In general, Five Talents does not give handouts. They support a limited number of full-time trainers, who in turn train local volunteer trainers, who do most of the actual organizing and leading. They found that when Western sources provided the initial seed capital, the money was not valued as much, and the loan payback rates were unsustainably low, around 60% or so.

So their model is to form a group of 20 or more people, and have them save their own money for at least six months. This develops tremendous accountability for borrowed funds. You are borrowing precious money from your group of friends and associates, and they all have a stake in helping your business succeed so you can repay it.

During those initial 6 to 12 months, the organization provides training: first, basic literacy (many are illiterate) and math skills which are essential for running a small business. Then, they provide training for more specific business planning and operation. This graphic depicts the process:

A typical loan might be $30-$150. This might be used to buy a goat to raise, or some beans to sell in the market. The local people can be creative in coming up with enterprises. The speaker told of a woman who was stuck in a refugee camp, who had been beaten up by life and was bitter and hopeless. All she could see were wretched poor people, and not much else. But the trainer persisted in asking her, “But what has God blessed you with?”  The subsequent conversation went something like this: “Well there is this large river nearby. And…there are unemployed men in the camp who used to have skilled jobs. I could probably pay some of them to make me a dugout canoe, then I could ferry people across the river for a fee. And…there are all these ragged children running around underfoot… I could probably buy them some fishing gear and pay them to catch me fish in the river, that I could sell in the market.” So this insightful local person was able to identify two completely new business ideas that the trainer had not thought of.

Five principles for “How to Build a Successful Business Anywhere” are:

  1. Start Small and Dream Big
  2. Know Your Neighbors
  3. Plan for Success
  4. Manage Growth Wisely
  5. Let Your Business be a Blessing


Some 80% of their participants are women. These women get a huge boost in self-confidence and community status, as well as income and food for their families.

Five Talents typically operates in concert with the local Anglican church in a country, which gives them some credibility and support and structure to start with. They are currently active in nine countries, mainly in central and eastern Africa along with Bolivia and Myanmar. They aim for countries with largest numbers of people living in extreme poverty. There is a wide range of development among so-called Third World countries. Many African countries already have a nascent middle class economy, so Five Talents directs its effort elsewhere.

According to their tracking, they have developed some 95,000 businesses so far, with a total of 1.4 million family members supported. They currently train about 10,000 people a year, and hope to increase that to 20,000 people. As with most development NGOs, the ultimate holy grail is to have your development project become independent and self-sustaining. Happily, Five Talents reports a great deal of success in getting groups to become self-funding after about one and a half years.

Online Reading Onpaper

Zachary Bartsch4 Comments

We have six weekly contributors here at EWED and I try to read every single post. I don’t always read them the same day that they are published. Being subscribed is convenient because I can let my count of unread emails accumulate as a reminder of what I’ve yet to read.

Shortly after my fourth child was born over the summer, I understandably got quite behind in my reading. I think that I had as many as twelve unread posts. I would try to catchup on the days that I stayed home with the children. After all, they don’t require constant monitoring and often go do their own thing. Then, without fail, every time that I pull out my phone to catch up on some choice econ content, the kids would get needy. They’d start whining, fighting, or otherwise suddenly start accosting me for one thing or another – even if they were fine just moments before. It’s as if my phone was the signal that I clearly had nothing to do and that I should be interacting with them. Don’t get me wrong, I like interacting with my kids. But, don’t they know that I’m a professional living in the 21st century? Don’t they know that there is a lot of good educational and intellectually stimulating content on my phone and that I am not merely zoning out and wasting my time?

No. They do not.

I began to realize that it didn’t matter what I was doing on my phone, the kids were not happy about it.

I have fond childhood memories of my dad smoking a pipe and reading the newspaper. I remember how he’d cross his legs and I remember how he’d lift me up and down with them. I less well remember my dad playing his Game Boy. That was entertaining for a while, but I remember feeling more socially disconnected from him at those times. Maybe my kids feel the same way. It doesn’t matter to them that I try to read news articles on my phone (the same content as a newspaper). They see me on a 1-player device.

So, one day I printed out about a dozen accumulated EWED blog posts as double-sided and stapled articles on real-life paper.

The kids were copacetic, going about their business. They were fed, watered, changed, and had toys and drawing accoutrement. I sat down with my stack of papers in a prominent rocking chair and started reading. You know what my kids did in response? Not a darn thing! I had found the secret. I couldn’t comment on the posts or share them digitally. But that’s a small price to pay for getting some peaceful reading time. My kids didn’t care that I wasn’t giving them attention. Reading is something they know about. They read or are read to every day. ‘Dad’s reading’ is a totally understandable and sympathetic activity. ‘Dad’s on his phone’ is not a sympathetic activity. After all, they don’t have phones.

They even had a role to play. As I’d finish reading the blog posts, I’d toss the stapled pages across the room. It was their job to throw those away in the garbage can. It became a game where there were these sheets of paper that I cared about, then examined , and then discarded… like yesterday’s news. They’d even argue some over who got to run the next consumed story across the house to the garbage can (sorry fellow bloggers).

If you’re waiting for the other shoe to drop, then I’ve got nothing for you. It turns out that this works for us. My working hypothesis is that kids often don’t want parents to give them attention in particular. Rather, they want to feel a sense of connection by being involved, or sharing experiences. Even if it’s not at the same time. Our kids want to do the things that we do. They love to mimic. My kids are almost never allowed to play games or do nearly anything on our phones. So, me being on my phone in their presence serves to create distance between us. Reading a book or some paper in their presence? That puts us on the same page.