Let me know what you think of the new design. The only substantive change so far is that I have added a way to subscribe to posts by email. Thanks to the reader who suggested this.
One of these days, I might get my entire web site into the 21st century.
UPDATE: I went back to the old design, until I can figure out how to configure a new one. I tried editing the .css file by hand, and it did nothing to change the font-size on blockquotes, which was large and annoying.
about this reported study, which
found that the employees who complained about work were pretty bummed out as a result. In diary entries, they reported feeling crummy and dissatisfied with their work.
The study makes it sound as if the causal variable is how much you complain, and that more complaining leads to more misery. I can think of some alternatives.
1. The causal variable could be something about your job. If you have a bad relationship with your boss, you will have reason to complain and you will be unhappy.
2. The causal variable could be something about you. When I used to hire people, I was convinced that the easiest way to know that Joe will be a malcontent if I hire him is if he is a malcontent in the job that he would leave to come to work for me. In my hiring interview, I would always ask the applicants what they liked and did not like about their most recent job. If they put most of the emphasis on what they disliked, then that was a red flag.
My point here is that the methods of the study leave me doubtful about the inferences that were drawn. Particularly because I am a big believer in (2), that some people are intrinsically less happy than others.
One way to improve government operations would be through re-organization. I once wrote,
the total number of executive entities is 157. I cannot think of any corporation in which the CEO has so many direct reports. This number ought to be fewer than ten.
I proposed consolidation. Ideally, this would be done through legislation. However, if Congress balks, the President could informally choose to make some Cabinet officials and agency heads subordinate to others. My ideas for agencies:
1. Defense. With NSA and CIA incorporated into it. In today’s world, intelligence is as important as any branch of the military.
2. State Department.
3. Financial Operations. This would include Treasury and OMB and would administer Social Security, Medicare, and all government financial guarantee programs.
4. Infrastructure. This would include the electric grid and communications spectrum
5. Economic opportunity. Attempt to coordinate and rationalize all of the many means-tested government transfer programs. Maybe someone would figure out that a Basic Income Grant would be less bad than what we have now.
6. Science and Statistics. Some functions of Commerce, Labor, and Agriculture go here. Many of their other functions disappear.
7. Consumer safety. This would include consumer protection in the financial arena.
8. Homeland Security. Smaller than it is now, with more resemblance to the old FBI.
President Trump plans to unveil a new White House office on Monday with sweeping authority to overhaul the federal bureaucracy and fulfill key campaign promises — such as reforming care for veterans and fighting opioid addiction — by harvesting ideas from the business world and, potentially, privatizing some government functions.
For a government agency, the incentives are perverse. Problems generate rewards, and solutions don’t. I once wrote,
In a government agency, each worker is paid more the longer the problem persists. In contrast, no one gets paid to work on an IETF task force. Instead, businesses and universities lend experts to work with the IETF. This represents a cost to the employers and perhaps also to the employees, who are kept from research or other activities that could advance their careers. Everyone involved in the process has an incentive to get the problem solved as expeditiously as possible.
An IETF is an Internet Engineering Task Force. My recommendation is to create temporary task forces to solve problems. Meanwhile, shrink agencies whose natural interest is in perpetuating problems.
In an interview format with Aaron Steelman. Pointer from Timothy Taylor. Interesting throughout. A few tidbits:
people don’t spend the money the week before it shows up — they spend it the week it shows up. And it seems like you’re going to have a lot of difficulty quantitatively fitting that little foresight into a life cycle model unless people are often literally liquidity constrained, absolutely at their debt limits.
…
What equilibrium supports high-fee mutual funds, index funds, and so on, and how does that change the flow of funds between the corporate and household sector and the pricing of risk?
a high propensity to consume correlates with low liquidity, which is useful for theorizing but also presents a little bit of a chicken-and-egg problem. Is it different preferences, objectives, or behavioral constraints that are causing both the low liquidity and the propensity to spend, or is it the low liquidity that is causing the lack of planning and high spending responses? So for many purposes, what I take my findings to mean is that the buffer-stock model is a quite reasonable model with one critical ingredient. The critical difference relative to the way I modeled households in the 2002 paper with Gourinchas is that I think there’s much more heterogeneity in preferences across households. While in that paper we looked at differences in preferences across occupation and industry, I think there’s just much more persistence in heterogeneity in behavior, consistent in the buffer-stock model with differences in impatience.
There is a significant portion of the population with above-median income and close to zero saving. I think it is hard to tell a story that explains that in terms of rational behavior. Remember, we are talking about a lot of people, not just a few random exceptions.
1. The American middle class does not believe in saving up for health care expenses. The idea that you should have $10,000 – $15,000 set aside for the occasional acute medical episode is abhorrent. The idea that you should save up for the inevitable medical expenses of old age is abhorrent. We are not Singapore.
2. The American middle class does not believe in paying taxes in order to support people who are very poor or very sick. We are not Denmark.
3. Americans are not willing to say, “The proposed treatment for this problem is not worth the cost. The individual should accept lower-cost treatments and live (or perhaps not live) with the consequences.”
4. Americans, and especially health care providers, do not want to think of health care as a commodity. The providers want to be paid, but they do not want to think of themselves as selling their services, so the payment comes from third parties and the price is hidden to consumers.
5. Americans are not willing to give up being the “early adopters” of new treatments, which are often much more expensive when they first appear than when they have been available for many years.
This was not as big a problem 40 years ago, when health care was a smaller share of the economy. It has grown larger because of new treatment options available. These often involve medical procedures that require expensive equipment and highly trained specialists. That is why I called my health care book Crisis of Abundance. As an example, I know someone with Parkinson’s who is getting “deep brain stimulation.” This is an incredibly exotic procedure, requiring a very powerful MRI machine, a highly skilled surgeon, and uniquely trained technicians. But it is a very promising treatment for a very difficult disease.
6. Americans seem to be more willing to spend public money on medical services than on public health. But I would think that there is more bang for the buck in getting people to change unhealthy lifestyles than there is in trying to treat the consequences of those lifestyles.
Put together these cultural traits and you end up, in Josh Barro’s words, with an economy that spends 1/6th of GDP on health care with nobody wanting to spend 1/6th of their income on it.
if you can’t decide who is going to pay for the chronically ill, then the number one game in town is the selection game. It is way more important to make sure that “the other guy” pays for the chronically ill. You even end up in situations where you don’t want to be too good at treating the chronically ill, lest all the chronically ill select your plan which is still a net negative.
I think the libertarian reluctance to admit these are going to be socialized costs has led to a patchwork of payers with more interest in playing the selection game then playing the cost control game. It’s also the case that their opponents in the cost control game, providers, have a lot more leverage over a divided foe then a unified foe (either single payer or strong government regulations on cost/utilization).
I think it is fair to point out that our health insurance market as it has emerged gives health insurance companies stronger incentives to hide from costs than to reduce costs.
Another point is that the politics of health care make it more attractive for politicians to help many people who are relatively healthy to handle routine low-cost illnesses, obtain birth control, etc., than it is to try to target support for the people who really need it. Hence, you get the shell game of Obamacare, where you try to give healthy people the sort of benefits that seem to help them, but stick them with premiums that include the cost of subsidizing the people with chronic illnesses.
Politically, what you want are policies with lots of beneficiaries. But the requirement of compassionate health care policy is a policy with few beneficiaries. (For a determined libertarian, this means placing very high expectations on charity.)
Hence, we play shell games. One of them we call “employer-provided” health insurance, as if employers simply give it away. In fact, if an employee is worth $40,000 a year to the company and health insurance costs $10,000, that means that the rest of the paycheck has to be worth no more than $30,000 a year. The cost of health insurance is borne by workers. That means that the workers with illnesses that require expensive treatment are subsidized by workers who are generally healthy.
Another shell game is Medicare. Old people undergo a lot of expensive medical treatments. This cost is borne partly by taxes on the young. It is increasingly being deferred to taxes on people in the future. This Ponzi scheme faces a day of reckoning, which is likely to come within a decade. That is, if you believe the CBO analysis of Medicare, and I thought that fact-based people were supposed to believe in the CBO.
Relative to a policy of honestly taxing the healthy to pay for the sick, these shell games are inefficient. They cost more in terms of lost economic output. The labor market is distorted by “employer-provided” health insurance, leading to less employment and output. The health insurance market is distorted by Obamacare, and in fact that market is in trouble. Subsidized health insurance under Obamacare is sort of working. Mandated health insurance on the exchanges is imploding.
Well, “we all know” that conservatives hold university scientists in contempt for their effemenate [sic], elitist ways & that liberals regard industry scientists as shills. But here’s what GSS says about partisanship & industry vs. university scientists . . . .
He may be fair to liberals, but I do not think that his characterization of conservatives would pass an ideological Turing test.
If I may attempt to speak for those of us on the right, my views would be:
1. When it comes to public relations, industry scientists have an incentive to twist the truth. However, when business decisions are affected by scientific analysis, the incentive leans much more toward aiming for truth.
2. In academics, the incentive is to increase one’s prestige. Aiming for truth is not always the best strategy. In fact, based on my own bitter experience, in economics the best strategy is to surf the latest fads. In my day, it was rational expectations, and I was not on board (pun intended). More recently, we have had behavioral economics, natural experiments, and such. There are probably some current fads that I could willingly join, but not at this stage of my life.
3. In the particular area that most interests Kahan, which is climate change, I trust neither the incentives in industry nor in academics. Obviously, if you work for the coal industry, your incentive is to find low estimates for the environmental impact of carbon dioxide emissions. But if you work in academia and you happen to find low estimates for the environmental impact of carbon dioxide emissions, good luck to you if you hope to win prestige.
A recent survey of leading economists, called the IGM forum, asked two questions about CBO forecasts.
Question A: Forecasting the effects of complex legislative actions is hard, so even competent, non-ideological and non-partisan projections could differ substantially from outcomes.
Question B: Adjusting for legal restrictions on what the CBO can assume about future legislation and events, the CBO has historically issued credible forecasts of the effects of both Democratic and Republican legislative proposals.
The answers were overwhelmingly affirmative for both. I have been following the IGM forum for years, and you rarely see such a strong consensus.
What does the term “credible” mean?
Does the affirmative answer to question B mean that the forecasts are accurate enough that policy makers should take them seriously? John Whitehead seems to think so. Pointer from Mark Thoma.
Or does the affirmative answer to question A mean that the forecasts are not accurate enough to reliably guide policy? Russ Roberts and I would tend to think so.
Anyone, including Russ or me, who criticizes economic methods faces the following argument.
1. Policy has to be based on some model and some forecast.
2. A formal model or a statistical forecast is more rigorous than intuition/opinion.
3. Therefore, the best approach is to use formal models and statistical forecasts.
I think that the problem comes in the way that one interprets point (1). Consider two possibilities:
1a. Policy has to be based on a “model” and a “forecast” which rule out any empirical analysis of how policy is formulated and implemented. Also, the “model” and the “forecast” can ignore the possible evolutionary responses of decentralized activity, including possible emergent market solutions to the problem that the policy is intended to solve, as well as innovations responding to the policy that mitigate its effects or that produce unintended adverse consequences.
1b. Policy has to be based on a “model” and a “forecast” which do take into account empirical public policy and dynamic market responses to the original problem and to the proposed solution.
If we interpret point 1 as “1b,” then I accept the logic that a model is better than no model and a forecast is better than no forecast.
If we interpret point 1 as “1a”, then the argument is a swindle. Models that ignore empirical public policy and dynamic market responses are not necessarily better than intuition/opinion, and they should not be regarded as credible.
Taking into account these requirements for credibility, CBO forecasts are not credible. Using them may very well do more harm than good.
The insightful Handle writes,
free YouTube videos combined with cheap and quick home delivery of tools and parts have made my own home, computer, and auto repairs much more worth my time than trying to arrange for an experienced professional.
I get it that having a YouTube video that tells me how to fix my toilet can lower the time it takes me to do it myself. But the Internet also makes it easier for me to find a cheap handyman. Overall, I think that my propensity to spend time fixing things myself has gone down rather than up over the past decade. Not that it was very high to begin with.
I think Prof. Kling misunderstood Prof. Cowen’s point. Less household production as share of GDP is not necessarily a bad thing and the best number may very well be 0%.
However, household production is generally not included in the GDP figures, even though it arguably should be. If actual GDP, including household production, used to be 37% higher than measured GDP, but now is only 20% higher than measured GDP, then the growth in actual GDP over the period has been even lower than the pretty dismal numbers we are observing.
Hence, this statistic supports Prof. Cowen’s hobby horse of the Great Stagnation, regardless of how one feels the ideal percentage of GDP household production ought to be. I think he is right on this point.
In a follow-up, the commenter writes,
My neighbor and I live in identical houses and we are equally messy. Initially, we both clean our own houses and nothing is added to measured GDP.
Then we decide to pay each other $100/week to clean each other’s house. Suddenly, measured GDP is $10k/year higher than it used to be. But economically nothing has changed. This suggests that we ought to include our cleaning labors in GDP regardless of whether we clean our own houses or each other’s.
I think this is misleading. I prefer to look at it this way:
1. Suppose you are willing to pay me $100 for 5 hours of cleaning services. Then that puts a value on my time of $20 an hour.
2. Now, suppose that I decide to spend 5 hours cleaning my own house. You want to say that I have produced $100 of output.
3. I would say instead that the 5 hours I spend cleaning my own house is a waste of time!
Maybe if you assume that the most valuable work I can do is cleaning houses, then you are sort of right. But if I am a surgeon, then you are pretty much wrong. And I claim that as an economy gets more efficient at using specialization, you become less and less right and more and more wrong.
In terms of comparing well-being now with well-being 50 years ago, suppose that most of the reduction in housework is due to the prevalence of permanent-press clothes rather than having to iron them. Suppose that our entire (market-based) GDP consists of shirt production. It would be really nice if the GDP calculation subtracted the need for ironing from the cost of today’s shirts. But it could only show up as a quality adjustment that I suspect is too sophisticated to be captured in the statistics.
Suppose that actual shirt production remains the same as it was 50 years ago. Then measured GDP might be the same, also (it could be a little higher, if the statisticians pick up some of the quality adjustment). But the alternative concept, of GDP + household production, has gone down from 50 years ago, because we have stopped ironing. To me, that makes GDP + household production a stupid concept. It has things exactly backwards.
If you are going to add anything household-related in GDP, it ought to be leisure, not housework. If you show me that leisure + GDP is not growing very much, then I would count that as an argument for a Great Stagnation. But I am not the least bit persuaded by a measure of GDP + housework.