Wednesday, May 25, 2016

Interview with Matthew Gentzkow: Media, Brands, Persuasion

Douglas Clement has another of his thoughtful and revealing interviews with economists, this one with Matthew Gentzkow. It appeared online in The Region, a publication of the Federal Reserve Bank of Minneapolis, on May 23, 2016.  For a readable overview of Gentzkow's work, a useful starting point is an essay by Andrei Shleifer titled  "Matthew Gentzkow, Winner of the 2014 Clark Medal,"  and published in the Winter 2015 issue of the Journal of Economic Perspectives. The Clark medal, for those not familiar with it, is a prestigious award  given each year by the American Economoic Associstion "to that American economist under the age of forty who is judged to have made the most significant contribution to economic thought and knowledge." Here are some answers from Gentzkow in the interview with Clement that caught my eye.

It seems to me that many discussions of politics neglect the entertainment factor. Politics isn't just about 30-page position papers and carefully worded statements. For lots of citizens and voters--and yes, for lots of politicians, too--it's a fun activity for observers and participants. Thus, when you think about how the spread of television (or newer media) affect voting, it's not enough just to talk about how media affect the information available to voters. It also matters if the new media just give the voters an alternative and nonpolitical source of entertainment. Here's a comment from Gentzkow on his research in this area:
I started thinking about this huge, downward trend that we’ve seen since about the middle of the 20th century in voter turnout and political participation. It’s really around the time that TV was introduced that that trend in the time series changes sharply, so I thought TV could have played a role.
Now, a priori, you could easily imagine it going either way. There’s a lot of evidence before and since that in many contexts, giving people more information has a very robust positive effect on political participation and voting. So, if you think of TV as the new source of information, a new technology for delivering political information, you might expect the effect to be positive. And, indeed, many people at the time predicted that this would be a very good thing for political participation.
On the other hand, TV isn’t just political information; it’s also a lot of entertainment. And in that research, I found that what seemed to be true is that the more important effect of TV is to substitute for—crowd out—a lot of other media like newspapers and radio that on net had more political content. Although there was some political content on TV, it was much smaller, and particularly much smaller for local or state level politics, which obviously the national TV networks are not going to cover.
So, we see that when television is introduced, indeed, voter turnout starts to decline. We can use this variation across different places and see that that sharp drop in voter turnout coincides with the timing of when TV came in. The more important effect of TV is to substitute for media that on net had more political content. So, we see that when television is introduced, indeed, voter turnout starts to decline. That drop is especially big in local elections. A lot of new technologies … are pushing people toward paying less attention to local politics, local issues, local communities.
People in different geographic areas show on average different consumption patterns. For example, Coke is more popular in some place, and Pepsi in others. Or imagine that someone moves from an area with high average health care spending to low average health care spending. Gentzkow and co-authors looked at people who moved from one geographic area to another, and how certain aspects of their consumption changed. Were people's preferences firmly established based on their previous location? Or did their preferences shift when they were in a new location? Here's how Gentzkow describes the differences between shifts in consumption related to brand preferences and shifts related to health care:
Well, imagine watching somebody move, first looking at how their brand preferences change; say they move from a Coke place to a Pepsi place and you see how their soft drink preferences change. Then imagine somebody moving from a place where there’s low spending on health care to a place with high spending, and you see how things change. In what way are those patterns different?
The first thing you can look at is how big the jump is when somebody moves. That’s sort of a direct measure of how important is the stuff you are carrying with you relative to the factors that are specific to the places. How important is your brand capital relative to the prices and the advertising? Or in a health care context, how important are the fixed characteristics of people that are different across places, relative to the doctors, the hospitals and the treatment styles across places. It turns out the jumps are actually very similar. In both cases, you close about half the gap between the place you start and the place you’re going, and so the share due to stuff people carry with them—their preference capital or their individual health—is about the same.
What’s very different and was a huge surprise to me, not what I would have guessed, is that with brands, you see a slow-but-steady convergence after people move; so, movers steadily buy more and more Pepsi the longer they live there. But in a health care context, we don’t see that at all; your health care consumption changes a discrete amount when you first move, but the trend is totally flat thereafter—it doesn’t converge at all.
Gentzkow's results on shifts in health care patterns may have some special applicability to thinking about how people react to finding themselves in a different and lower-spending health care system. Say that the change to this new system wasn't the result of a geographic shift--say, moving from a high-cost metro area where average spending on health care might be triple what it is in a low-cost area--but instead involved a change in policy. These results might imply that the policy reform would bring down health spending in a one-time jump, but then spending for the group that was used to being at a higher level would not continue to fall, as might have been predicted. 

Finally, here's an observation in passing from Gentzkow about social media. Are the new media a source of concern because they are not interactive enough (say, as compared to personal communication) or because they are too interactive and therefore addicting (say, as compared to television? Here's Gentzkow"
A lot of people are complaining about social media now. But think back to what they were saying back when kids were all watching TV: “It’s this passive thing where kids sit there and zone out, and they’re not thinking, they’re alone, they’re not communicating!” Now, suddenly, a thing that kids are spending lots of their time doing is interacting with other kids. They’re writing text messages and posts and creating pictures and editing them on Instagram. It’s certainly not passive; it’s certainly not solitary. It has its own risks perhaps, but not the risks that worried people about TV. I think there’s a tendency, no matter what the new technology is, to wring our hands about its terrible implications. Kind of amazing how people have turned on a dime from worrying about one thing to worrying about its exact opposite.

Tuesday, May 24, 2016

The Tradeoffs of Parking Spots

Sometimes it seems as if every proposal for a new residential or commercial building in an urban or suburban area is neatly packaged with a dispute over parking. Will the new development provide  a minimum number of parking spaces? Will it be harder for those already in the are to find parking? How should the flow of drivers in and out of the parking area be arranged? Of course, all of these questions presume the cars and drivers need and deserve to be placed front and center of development decisions.

Donald Shoup, an urban economist who focuses on parking issues, discusses this focus on parking in
"Cutting the Cost of Parking Requirements," an essay in the Spring 2016 issue of Access, a research center on surface transportation issues run by a number of University of California schools. Shoup starts this way:

At the dawn of the automobile age, suppose Henry Ford and John D. Rockefeller had hired you to devise policies to increase the demand for cars and gasoline. What planning regulations would make a car the obvious choice for most travel? First, segregate land uses (housing here, jobs there, shopping somewhere else) to increase travel demand. Second, limit density at every site to spread the city, further increasing travel demand. Third, require ample off-street parking everywhere, making cars the default way to travel.
American cities have unwisely embraced each of these car-friendly policies, luring people into cars for 87 percent of their daily trips. Zoning ordinances that segregate land uses, limit density, and require lots of parking create drivable cities but prevent walkable neighborhoods. Urban historians often say that cars have changed cities, but planning policies have also changed cities to favor cars over other forms of transportation.
Minimum parking requirements create especially severe problems. In The High Cost of Free Parking, I argued that parking requirements subsidize cars, increase traffic congestion and carbon emissions, pollute the air and water, encourage sprawl, raise housing costs, degrade urban design, reduce walkability, damage the economy, and exclude poor people. To my knowledge, no city planner has argued that parking requirements do not have these harmful effects. Instead, a flood of recent research has shown they do have these effects. We are poisoning our cities with too much parking. ...
Parking requirements reduce the cost of owning a car but raise the cost of everything else. Recently, I estimated that the parking spaces required for shopping centers in Los Angeles increase the cost of building a shopping center by 67 percent if the parking is in an aboveground structure and by 93 percent if the parking is underground.

Developers would provide some parking even if cities did not require it, but parking requirements would be superfluous if they did not increase the parking supply. This increased cost is then passed on to all shoppers. For example, parking requirements raise the price of food at a grocery store for everyone, regardless of how they travel. People who are too poor to own a car pay more for their groceries to ensure that richer people can park free when they drive to the store. ...
A single parking space, however, can cost far more to build than the net worth of many American households. In recent research, I estimated that the average construction cost (excluding land cost) for parking structures in 12 American cities in 2012 was $24,000 per space for aboveground parking, and $34,000 per space for underground parking
Shoup discusses California legislation that seeks to put a cap on minimum parking requirements. You can imagine how welcome this idea is. Another one of Shoup's parking projects is discussed by Helen Fessenden in "Getting Unstuck," which asks "Can smarter pricing provide a way out of clogged highways, packed parking, and overburdened mass transit?" Fessenden's article appears in the Fourth Quarter 2015 issue of Econ Focus, which is published by the Federal Reserve Bank of Richmond. On the subject of parking, she writes:

Economist Don Shoup at the University of California, Los Angeles has spent decades researching the inefficiencies of the parking market — including the high cost of minimum parking requirements — but he is probably best known for his work on street parking. In 2011, San Francisco applied his ideas in a pilot project to set up "performance pricing" zones in its crowded downtown, and similar projects are now underway in numerous other cities — including, later this spring, in D.C. ...
"I had always thought parking was an unusual case because meter prices deviated so much from the market prices," says Shoup. "The government was practically giving away valuable land for free. Why not set the price for on-street parking according to demand, and then use the money for public services?"
Taking a cue from this argument, San Francisco converted its fixed-price system for on-street parking in certain zones into "performance parking," in which rates varied by the time of day according to demand. In its initial run, the project, dubbed SFpark, equipped its meters with sensors and divided the day into three different price periods, with the option to adjust the rate in 25-cent increments, with a maximum price of $6 an hour. The sensors then gathered data on the occupancy rates on each block, which the city analyzed to see whether and how those rates should be adjusted. Its goal was to set prices to achieve target occupancy — in this case, between 60 percent and 80 percent — at all times. There was no formal model to predict pricing; instead, the city adjusted prices every few months in response to the observed occupancy to find the optimal rates.
The results: In the first two years of the project, the time it took to find a spot fell by 43 percent in the pilot areas, compared with a 13 percent fall on the control blocks. Pilot areas also saw less "circling," as vehicle miles traveled dropped by 30 percent, compared with 6 percent on the control blocks. Perhaps most surprising was that the experiment didn't wind up costing drivers more, on net, because demand was more efficiently dispersed. Parking rates went up 31 percent of the time, dropped in another 30 percent of cases, and stayed flat for the remaining 39 percent. The overall average rate actually dropped by 4 percent.
A summary of the 2014 evaluation report for the SFPark pilot study is available here.

For many of us, parking spots are just a taken-for-granted part of the scenery. Shoup makes you see parking in a different way. Space is scarce in urban areas, and in many parts of suburban areas, too. Parking uses space. Next time you are cycling a block, looking for parking, or navigating a city street that is made narrower because cars are parked on both sides, or walking down a sidewalk corridor between buildings on one side and parked cars on the other, or wending your way in and out of a parking ramp, it's worth recognizing the tradeoffs of requiring and underpricing parking spaces.

Monday, May 23, 2016


The American College of Physicians has officially endorsed "telemedicine," which refers to using technology to connect a health care provider and a patient who aren't in the same place. An official statement of the ACP policy recommendations and a background position paper, written by Hilary Daniel and Lois Snyder Sulmasy, appear in the Annals of Internal Medicine (November 17, 2015, volume 163, number 10). The same issue includes an editorial on "The Hidden Economics of Telemedicine," by David Asch, emphasizing that some of the most important costs and benefits of telemedicine are not about delivering the same care in an alternative way.  For starters, here's are some comments from the background paper (with footnotes and references omitted for readability):
Telemedicine can be an efficient, cost-effective alternative to traditional health care delivery that increases the patient's overall quality of life and satisfaction with their health care. Data estimates on the growth of telemedicine suggest a considerable increase in use over the next decade, increasing from approximately 350 000 to 7 million by 2018. Research analysis also shows that the global telemedicine market is expected to grow at an annual rate of 18.5% between 2012 and 2018. ... [B]y the end of 2014, an estimated 100 million e-visits across the world will result in as much as $5 billion in savings for the health care system. As many as three quarters of those visits could be from North American patients. ...

Telemedicine has been used for over a decade by Veterans Affairs; in fiscal year 2013, more than 600 000 veterans received nearly 1.8 million episodes of remote care from 150 VHA medical centers and 750 outpatient clinics. ... The VHA's Care Coordination/Home Telehealth program, with the purpose of coordinating care of veteran patients with chronic conditions, grew 1500% over 4 years and saw a 25% reduction in the number of bed days, a 19% reduction in numbers of hospital readmissions, and a patient mean satisfaction score of 86% ... 
The Mayo Clinic telestroke program uses a “hub-and-spoke” system that allows stroke patients to remain in their home communities, considered a “spoke” site, while a team of physicians, neurologists, and health professionals consult from a larger medical center that serves as the “hub” site. A study on this program found that a patient treated in a telestroke network, consisting of 1 hub hospital and 7 spoke hospitals, reduced costs by $1436 and gained 0.02 years of quality-adjusted life-years over a lifetime compared with a patient receiving care at a rural community hospital ... 
The Antenatal and Neonatal Guidelines, Education and Learning System program at the University of Arkansas for Medical Sciences used telemedicine technologies to provide rural women with high-risk pregnancies access to physicians and subspecialists at the University of Arkansas. In addition, the program operated a call center 24 hours a day to answer questions or help coordinate care for these women and created evidence-based guidelines on common issues that arise during high-risk pregnancies. The program is widely considered to be successful and has reduced infant mortality rates in the state. ...
An analysis of cost savings during a telehealth project at the University of Arkansas for Medical Sciences between 1998 and 2002 suggested that 94% of participants would have to travel more than 70 miles for medical care. ...  Beyond the rural setting, telemedicine may aid in facilitating care for underserved patients in both rural and urban settings. Two thirds of the patients who participated in the Extension for Community Healthcare Outcomes program were part of minority groups, suggesting that telemedicine could be beneficial in helping underserved patients connect with subspecialists they would not have had access to before, either through direct connections or training for primary care physicians in their communities, regardless of geographic location.
Most of this seems reasonable enough, except for that pesky estimate up in the first paragraph that the global savings from telemedicine will amount to $5 billion per year on a global basis. The US health care system alone has average spending of more than $8 billion per day, every day of the years. Thus, this vision of telemedicine is that it will mostly just rearrange existing care--reach out to bring some additional people into the system, help reduce health care expenditures on certain conditions with better follow-up--but not be a truly disruptive force.

In his editorial essay in the same issue, David Asch points out: "If there is something fundamentally different about telemedicine, it is that many of the costs it increases or decreases have been off the books." He offers a number of examples:

"Some patients who would have visited the physician face to face instead have a telemedicine "visit." They potentially gain a lot. There are no travel costs or parking fees. They might have to wait, but presumably they wait at home or at work where they can do something else (like many of us do when placed on hold). There is no waiting at all in asynchronous settings (the photograph of your rash is sent to your dermatologist, but you do not need a response right away). The costs avoided do not appear on the balance sheets of insurance companies or providers ...  However, the costs avoided are meaningful even if they are not counted in official ways. There are the patients who would have forgone care entirely because the alternative was not a face-to-face visit but no visit. There are no neurologists who treat movement disorders in your region. The emergency department in your area could not possibly have a stroke specialist available at all times. ...  We leave patients out when we ask how telemedicine visits compare with face-to-face visits: all of the patients who, without telemedicine, get no visit at all.
Savings for physicians, hospitals, and other providers are potentially enormous. Clinician-patient time in telemedicine is almost certainly shorter, requiring less of the chitchat that is hard to avoid in face-to-face interactions. There is no check-in at the desk. There is no need to devote space to waiting rooms (in some facilities, waiting rooms occupy nearly one half of usable space). No one needs to clean a room; heat it; or, in the long run, build it. That is the real opportunity of telemedicine. ...

On the other hand, payers worry that if they reimburse for telemedicine, then every skin blemish that can be photographed risks turning from something that patients used to ignore into a payable insurance claim. Indeed, it is almost certainly true that if you make it easy to access care by telemedicine, telemedicine will promote too much care. However, the same concern could be reframed this way: An advantage of requiring face-to-face visits is that their inconvenience limits their use. Do we really want to ration care by inconvenience, or do we want to find ways to deliver valuable care as conveniently and inexpensively as possible?
I find myself wondering about ways in which telemedicine will be more disruptive. For example, consider the combination of telemedicine with technologies that enable remote monitoring of blood pressure, or blood sugar, or whether medications are being taken on schedule. Or consider telemedicine not just as a method of communicating with members of the American College of Physicians, but also as a way of communicating with nursing professionals, those who know about providing at-home care, various kinds of physical and mental therapists, along with social workers and others. There will be a wave of jobs in being the "telemedicine gatekeeper" who can answer the first wave of questions that most people ask, and then have access to resources for follow-up concerns. My guess is that these kinds of changes will be considerably more disruptive to traditional medical practice than a worldwide cost savings of $5 billion would seem to imply.

Homage: I ran across a mention of these reports at the always-interesting Marginal Revolution website.

Saturday, May 21, 2016

Rising Tuition Discount Rates at Private Colleges

Colleges and universities announce a certain price for tuition, but based on financial aid calculations, they often charge a lot less. The difference is the "institutional tuition discount rate." The National Association of College and University Business Officers (NACUBO) has just released a report with the average discount rate for 2015-16 based on a survey of 401 private nonprofit colleges (that is, not including branches of state university systems and not including for-profit colleges and universities), along with and how that rate has been evolving over time.

The two lines in the figure imply that the level financial help a student receives as a freshman, when making a choice between colleges, is going to be more than the financial help received in later years. Beware! More broadly, a strategy of charging ever-more to parents who can afford it, while offering ever-larger discounts to those who can't, does not seem like a sustainable long-run approach.

Friday, May 20, 2016

Inequalities of Crime Victimization and Criminal Justice

Many Americans worry about high incarceration rates and a police presence that can be heavy-handed or worse in some communities. Many Americans also are worrying about crime. For example, here's a Gallup poll result from early March:


And law-abiding people in some communities, many of them predominantly low-income and African-American, can end up facing an emotionally crucifying choice. One one side, crime rates in their community are high, which is a terrible and sometimes tragic and fatal burden on everyday life. On the other side, they are watching a large share of their community, mainly men, becoming involved with the criminal justice system through fines, probation, fines, or incarceration. Although those who are convicted of crimes are the ones who officially bear the costs, in fact the costs when someone needs to pay fines, or can't earn much or any income, or can only be visited by making a trip to a correctional facility are also shared with families, mothers, and children. Magnus Lofstrom and Steven Raphael explore these questions of "Crime, the Criminal Justice System, and Socioeconomic Inequality" in the Spring 2016 issue of the Journal of Economic Perspectives.

(Full disclosure: I've worked as the Managing Editor of the Journal of Economic Perspectives for 30 years. All papers appearing in the journal, back to the first issue in Summer 1987, are freely available online, compliments of the American Economic Association.)

It's well-known that rates of violent and property crime have fallen substantially in the US in the last 25 years or so. What is less well-recognized is that the biggest reductions in crime have happened in the often predominantly low-income and African-American communities that were most plagued by crime. Loftrom and Raphael look at crime rates across cities with lower and higher rates of  poverty in 1990 and 2008:
"However, the inequality between cities with the highest and lower poverty rates narrows considerably over this 18-year period. Here we observe a narrowing of both the ratio of crime rates as well as the absolute difference. Expressed as a ratio, the 1990 violent crime rate among the cities in the top poverty decile was 15.8 times the rate for the cities in the lowest poverty decile. By 2008, the ratio falls to 11.9. When expressed in levels, in 1990 the violent crime rate in the cities in the upper decile for poverty rates exceeds the violent crime rate in cities in the lowest decile for poverty rates by 1,860 incidents per 100,000. By 2008, the absolute difference in violent crime rates shrinks to 941 per 100,000. We see comparable narrowing in the differences between poorer and less-poor cities in property crime rates."
As another example, Lofstrom and Raphael refer to a study which broke down crime rates in Pittsburgh across the "tracts" used in compiling the US census. As overall rates of crime fell in Pittsburgh, predominantly African-American areas saw the biggest gains:
"The decline in violent crime in the 20 percent of tracts with the highest proportion black amounts to 54 percent of the overall decline in violent crime citywide. These tracts account for 23 percent of the city’s population, have an average proportion black among tract residents of 0.78 and an average proportion poor of 0.32. Similarly, the decline in violent crime in the poorest quintile of tracts amounts to 60 percent of the citywide decline in violent crime incidents, despite these tracts being home to only 17 percent of the city’s population."
It remains true that one of the common penalties for being poor in the United States is that you are more likely to live in a neighborhood with a much higher crime rate. But as overall rates of crime have fallen, the inequality of greater vulnerability to crime has diminished.

On the other side of the crime-and-punishment ledger, low-income and African-American men are more likely to end up in the criminal justice system. Lofstrom and Raphael give sources and studies for the statistics: "[N]nearly one-third of black males born in 2001 will serve prison time at some point in their lives. The comparable figure for Hispanic men is 17 percent ...  [F]or African-American men born between 1965 and 1969, 20.5 percent had been to prison by 1999. The comparable figures were 30.2 percent for black men without a college degree and approximately 59 percent for black men without a high school degree."

I'm not someone who sympathizes with or romanticizes those who commit crimes. But economics is about tradeoffs, and imposing costs on those who commit crimes has tradeoffs for the rest of society, too. For example, the cost to taxpayers is on the order of $350 billion per year, which in 2010 broke down as "$113 billion on police, $81 billion on corrections, $76 billion in expenditure by various federal agencies, and $84 billion devoted to combating drug trafficking." The question of whether those costs should be higher or lower, or reallocated between these categories, is a worthy one for economists.

But the costs explicitly imposed by the legal system are only part of the picture. For example, living in a community where it is common for you to experience or watch as people are regularly stopped and frisked is a cost, too. Lofstrom and Raphael discuss "collateral consequence studies: about how being in the criminal justice system affects employment prospects, health outcomes, and problem behaviors and and depression among children of the incarcerated. In addition, many local jurisdictions have dramatically increased their use of fines in the last couple of decades,, which can often end up being a high enough fraction of annual income for a low-income worker that they become nearly impossible to pay--then leading to additional fines or more jail time. The US Department of Justice Civil Rights Division report following up on practices in Ferguson, Missouri, noted an "aggressive use of fines and fees imposed for minor crimes, with this revenue accounting for roughly one-fifth of the city’s general fund sources." As Lofstrom and Raphael explain:
"Money is fungible. When fines and fees are imposed as part of a criminal prosecution, at least some of the financial burden will devolve on to the household of the person involved with the criminal justice system. When someone who is involved in the criminal justice system has reduced employment prospects, some of those financial costs will again be borne by others in their household. We have said nothing about the family resources devoted to replenishing inmate commissary accounts, the devotion of household resources to prison phone calls, time devoted to visiting family members, and the other manners by which a family member’s involvement with the criminal justice system may tax a household’s resources. To our knowledge, aggregate data on such costs do not exist."
I wrote a few weeks back about how the empirical evidence on "Crime and Incarceration: Correlation, Causation, and Policy" (April 29, 2016). Yes, there is a correlation that incarceration rates have risen in the US as crime has fallen. But a more careful look at the evidence strongly suggests that while the rise in incarceration rates probably did contribute to bringing down crime rates in the 1980s or into the early 1990s, but the continuing rise in incarceration rates since then seems to brought diminishing returns--and at this point, near-zero returns--in reducing crime further.

Lofstrom and Raphael conclude:
"Many of the same low-income predominantly African American communities have disproportionately experienced both the welcome reduction in inequality for crime victims and the less-welcome rise in inequality due to changes in criminal justice sanctioning. While it is tempting to consider whether these two changes in inequality can be weighed and balanced against each other, it seems to us that this temptation should be resisted on both theoretical and practical grounds. On theoretical grounds, the case for reducing inequality of any type is always rooted in claims about fairness and justice. In some situations, several different claims about inequality can be combined into a single scale—for example, when such claims can be monetized or measured in terms of income. But the inequality of the suffering of crime victims is fundamentally different from the inequality of disproportionate criminal justice sanctioning, and cannot be compared on the same scale. In practical terms, while higher rates of incarceration and other criminal justice sanctions may have had some effect in reducing crime back in the 1970s and through the 1980s, there is little evidence to believe that the higher rates have caused the reduction in crime in the last two decades. Thus, it is reasonable to pursue multiple policy goals, both seeking additional reductions in crime and in the continuing inequality of crime victimization and simultaneously seeking to reduce inequality of criminal justice sanctioning. If such policies are carried out sensibly, both kinds of inequality can be reduced without a meaningful tradeoff arising between them." 
While accusations of police brutality are often the flashpoint for public protests over the criminal justice system, my own suspicion is that some of the anger and despair focused on the police is because they are the visible front line of the criminal justice system. It would be interesting to watch the dynamics if protests of similar intensity were aimed at legislators who pass a cavalcade of seemingly small fines, which when imposed by judges add up to an insuperable burden for low-income families. Or if the protests were aimed at legislators, judges, and parole boards who make decisions about length of incarceration. Or if the protests were aimed at prisons and correctional officers. My own preference for the criminal justice system (for example, here and here) would be to rebalance the nation's criminal justice spending, with more going to police and less coming in  fines, and the offsetting funding to come from reducing the sky-high levels of US incarceration. The broad idea is to spend more on tamping down the chance that crime will occur or escalate in the first place, while spending less on years of severe punishments after the crime has already happened.

Thursday, May 19, 2016

Ray Fair: The Economy is Tilting Republican

Ray Fair is an eminent macroeconomist,  as well as  a well-known textbook writer (with Karl Case and Sharon Oster) who dabbles now and again in sports economics. Here I focus on one of Fair's other interests: the connection from macroeconomic to election outcomes, a topic where he has been publishing an occasional series of papers since 1978. With time and trial-and-error, Fair has developed a formula where anyone can plug in a few key economic statistics and obtain a prediction for the election. A quick overview of the calculations, along with links to some of Fair's recent papers on this subject, are available at Fair's website.

Fair's equation to predict the 2016 presidential election is
VP = 42.39 + .667*G - .690*P + 0.968*Z

On the left-hand side of the equation, VP is the Democratic share of the presidential vote. Given that a Democrat is in office, a legacy of economic growth should tend to favor the Democratic candidate, while inflation would tend to work against the Democrat. On the right-hand side, G is the growth rate of real per capita GDP in the first 3 quarters of the election year (at an annual rate); P is the growth rate of the GDP deflator (a measure of inflation based on everything in the GDP, rather than just on consumer spending as in the better-known Consumer Price Index); and Z is the number of quarters in the first 15 quarters of the second Obama administration in which the growth rate of real per capita GDP is greater than 3.2 percent at an annual rate.

Obviously, some of these variables aren't yet known, because the first three-quarters of 2016 haven't happened yet. But here are Fair's estimates of the variables as of late April: G=0.87; P=1.28; Z=3. Plug those numbers into the formula, and the prediction is that the Democratic share of the two-party presidential vote in 2016 will be 44.99%.

Fair offers a similar equation to predict the 2016 House elections. The formula is

VC = 44.09 + .372*G - .385*P + 0.540*Z

where VC is the Democratic share of the two-party vote in Congressional elections. Plugging in the values for G, P and Z, the prediction is 45.54% of the House vote for Democrats.

Of course, these formulas raise a number of questions. Where do these numbers and this formula come from? Why use these variables about economic growth rather than, say, the unemployment rate? Why measure inflation with the GDP deflator rather than with the Consumer Price Index? Where did the coefficient numbers come from?

The short answer to all these questions is that Fair's equations are chosen so that, if one looks back at historical election data from 1916 up through 2014, this equation is both fairly simple and does a pretty good job in predicting all the elections over time with the smallest possible error. The long answer to why these specific variables were chosen and how the equation is estimated is that you need to read the research papers at Fair's website.

Is there reason to believe that a correlation between the macroeconomy and election outcomes has existed during the last century or so of national elections, it will also hold true in 2016? Of course, Fair isn't making any claim that the macroeconomy fully determines election outcomes. Every election has lots of idiosyncratic factors related to the particular candidates and the events of the time. Correlations are just a way of describing or summarizing earlier patterns in the data. Fair's equation tell how macroeconomic factors have been correlated with election outcomes, based on the past historical record, but it doesn't have anything to say about all the other factors in a national election. For example, the predictions of the equation for the  Democratic vote were way low in 1992, when Bill Clinton was elected, and also  in 2004, when George W. Bush was re-elected. On the other side, predictions from the equation of the Democratic share of the vote were too high in 1984 and 1988, when Ronald Reagan was re-elected and then George Bush was elected.

At the most basic level, Fair's equation is just saying that a slow rate of economic growth during 2016, along with the fact that there haven't been many rapid quarters of economic growth during the Obama presidency, will tend to make it harder for Democrats to win in 2016. But correlation doesn't prove causation, as Fair knows as well as anyone and better than most, and he would be the last one to overstate how much weight to give to these kinds of formulas. Back in 1996, Fair provided a nontechnical overview of this work in "Econometrics and Presidential Elections," appearing in the Journal of Economic Perspectives (where I work as Managing Editor). He wrote there: 
"The main interest in this work from a social science perspective is how economic events affect the behavior of voters. But this work is also of interest from the perspective of learning (and teaching) econometrics. The subject matter is interesting; the voting equation is easy to understand; all the data can be put into a small table; and the econometrics offers many potential practical problems. ... Thus, this paper is aimed in part at students taking econometrics, with the hope that it may serve as an interesting example of how econometrics can be used (or misused?). Finally, this work is of interest to the news media, which every fourth year becomes fixated on the presidential election. Although I spend about one week every four years updating the voting equation, some in the media erroneously think that I am a political pundit—or at least they have a misleading view of how I spend most of my days."

Wednesday, May 18, 2016

What Was Different About Housing This Time?

Everyone knows that the Great Recession was tangled up with a housing boom that went bust. But more precisely, what was different about housing in the most recent business cycle? Burcu Eyigungor discusses "Housing’s Role in the Slow Recovery" in the Spring 2016 issue of Economic Insights, published by the Federal Reserve Bank of Philadelphia.

As a starting point, here's private residential fixed investment--basically, spending on home and apartment construction and major renovations--as a share of GDP going back to 1947. Notice that this category of investment falls during every recession (shown by the shaded areas) and then usually starts bouncing back just before the end of the recession--except for the period after 2009.
The most recent residential building cycle looks different. Eyigungor explains:
The housing boom from 1991 to 2005 was the longest uninterrupted expansion of home construction as a share of overall economic output since 1947 (Figure 1). During the 1991 recession, private home construction had constituted 3.5 percent of GDP, and it increased its share of GDP without any major interruptions to 6.7 percent in 2005. This share was the highest it had been since the 1950s. Just like the boom, the bust that followed was also different from earlier episodes. During the bust, private residential investment as a share of GDP fell to levels not seen since 1947 and has stayed low even after the end of the recession in 2009. In previous recessions, the decline in residential construction was not only much less severe, but the recovery in housing also led the recovery in GDP. As Federal Reserve Chair Janet Yellen has pointed out, in the first three years of this past recovery, homebuilding contributed almost zero to GDP growth.
There are two possible categories of reasons for the very low level of residential building since 2009. On the supply side, it may not seem profitable to build, given what was already built back before 2008 and the lower prices. On the demand side, one aftermath of the Great Recession could plausibly be that at least some people are feeling economically shaky and mistrustful of real estate markets. and so not eager to buy.

Both supply and demand presumably played some role. But housing prices have now been rising again for about three years, and the "vacancy" rates for owner-occupied housing and rental housing are back to the levels from before the Great Recession. In that sense, it doesn't look as if an overhang of empty dwellings or especially low prices are the big problem for the housing market. Instead, Eyigungor argues that the demand side of the housing market is holding back the housing market.

In particular, the demand for housing is tied up with the rate of "household formation"--that is, the number of people who are starting new households. The level of household formation was low for years after 2009 (and remember that these low levels are in the context of a larger population than several decades ago, so the rate of household formation would be lower still).
The rates of homeownership have now declined back to levels from the 1980s, and the share of renters has risen. "This decline has lowered overall housing expenditures, because homeowners on average spend more on housing than renters do because of the tax incentives of homeownership and holding a mortgage. Together, the declines in household formation and homeownership contributed to the decline in residential expenditures as a share of GDP."
Spending on housing usually helps lead the US economy out of recession, but not this time. The demand from new household formation hasn't been there. As I've pointed out in the past, both the Clinton administration with its National Homeownership Strategy and the Bush administration with its "ownership society" did a lot of bragging about that rise in homeownership rates from the mid-1990s up through about 2007. The gains to homeownership from those strategies has turned out to be evanescent, while some costs associated with those strategies have been all too real.