Thinking about metrics comparing countries for both average living standards and equality of living standards.

A healthy debate is happening about whether the standard measure of national economic well-being--per capita GDP--is sufficient for that purpose.  One problem is that per capita GDP does nothing to take into account how broadly affluence is enjoyed.  If, to give an extreme example, a country of 1000 people had GDP of $1 billion (let's call it Witallia), its per capita GDP would be $1 million, which sounds great.  But if the country has one person who makes $1 billion and the remainder make nothing, it is not doing very well.

The standard measure of inequality is the GINI coefficient.  If a country has a GINI of 0, it means everyone makes exactly the same amount of money; if it has a GINI of 1, it is like Witallia. 

Clearly, no country is either, but the range of GINIs is large.  The GINI for Norway is 27, while in the US it is 41.   Norway in a sense dominates the US, in that it has both higher per capita GDP ($75,000) than the US ($62,000) and a lower GINI.  So it is easy to compare countries when one comes out ahead in both measures.

But often one country will have a higher per capita GDP and higher GINI than another.  A metric that seeks to compare countries in both dimensions needs to combine both into a single number.  A straightforward example would be to simply divide a measure of national income by GINI.  I did this using 2015 World Bank Data on PPP Per Capita Gross National Income and GINI (this is the most recent year with reasonably complete sets of both.  When one does this, the top countries for GNI/GINI are

1. Norway
2. Luxembourg
3. Switzerland
4. Denmark
5. Sweden
6. Ireland
7. Austria
8. Belgium
9. Finland
10. Germany

The US clocks in at number 11.  One could make a case that among large economies, it is number 2. 

This list looks reasonable to me, but that doesn't mean this measure is correct--anything that attempts to combine the two will be somewhat arbitrary.  One could try things like GDP/(GINI^1/2), for example.  (BTW, if someone has already done the exercise above, my apologies for not citing--I looked around the web for a while and couldn't find one).

  

Mortgage Spreads are Rising (although maybe it's a blip).

I check out mortgage rates at least once a week, because, well, it is my job to know what they are. 

Recently, I have been expecting to see mortgage rates fall a lot, because 10-year Treasury Yields have fallen a lot.  But they haven't.  Here is the spread of 30-year mortgages over 10-year Treasuries:

As you can see, the spread is at its highest level in at least five years (BTW, 10-year Treasuries are from Fridays, and the Freddie PMMS is from Thursdays, but still...). 

I am eagerly awaiting next week to see if this continues.

Robustness in Economics and Econometrics: Interview with William "Buz" B...

This took me back (with pleasure) to my graduate school days.  I have been privileged to learn from many amazing people, but I think I learned more from Professor Brock than anyone else (and I think I learned only about 1/3 of what he tried to teach me).

By world standards, the middle class in the US still does very well

After reading Biyamen Applebaum's thought-provoking piece in the NYT today, I thought about how economists measure well-being, and how measures other than GDP per capita better reflect social welfare.  One obvious measure is median disposable income--a good representation of middle-class affluence, in that it is at the middle, and is not skewed by the top end of the distribution.

After looking at OECD data that I myself adjusted for exchange rates, a Wikipedia article based on OECD data, a Mises report also based on OECD data, and World Population Review, the consensus ranking of the US for median income is fourth, after Luxembourg, Norway, and Switzerland.  The top five is rounded out by Australia.  Median income here is the disposable median, meaning after taxes and transfers.

This is not to say the US couldn't be doing better.  As I noted in an earlier post, median income is pretty stagnant here.  I would also be curious about the variance of disposable income at the household level.  If people have steadier incomes at the median in other places, they may feel more economically secure.

Nevertheless, if we were to list our most serious economic issues, failing the middle class, at least relative to other countries, would not be on the top of the list.

The median male earner--the top line overstates progress

Has the median man made progress economically since 1980?  Not really.  While male median income rose (in 2017 $) from $35,589 to $40,396, or 13.5 percent,  this modest increase masks the fact that the share of men in their peak earnings years has increased, and that earnings at the median within peak earnings years categories have decreased.

	Share in Age Category		Median Earnings (2017 $)
	1980	2017	1980	2017
15-24	0.216	0.120	$13,057	$13,734
25-34	0.232	0.183	$44,252	$40,575
35-44	0.161	0.167	$56,911	$52,403
45-54	0.136	0.169	$56,732	$53,985
55-64	0.127	0.165	$45,200	$48,863
65+	0.127	0.196	$20,845	$32,654

Note that population share for 35-64, prime earnings years, rose from 1980 to 2017; earnings fell for every population group between 25 and 54.  The median 30 year old is making less than their counterpart from 27 years earlier, as is the median 40 year old, as is the median 50 year old.

Had income within each age category remained constant at 1980 levels, current median income for men could be $40,306, or almost exactly where it us now.  On an age adjusted basis, there was no median income growth.  But that probably overstates economic well being at the middle--the one category where income has risen rapidly is the 65+ group, which may reflect the fact that 65 year olds no longer feel that they can retire.  So when current generations think they are not keeping up with the past, they are on to something.

Some notes: (1) I use 1980 as the base year, because how median income was measured changed that year, and so previous years are not as comparable.  (2) I look only at men, because the labor force participation rate among women has changed so much that 1980 and 2017 data are not comparable (although it is no doubt the case that women are far more economically independent now than in 1980). 

Source: US Census Bureau: Current Population Survey, Annual Social and Population Supplements.  Table P8.   

1984: Something happened to Rent CPI

Using one of the world's most useful websites, FRED, I drew a graph of rent CPI and all CPI going back to the beginning of the series.

Until 1984, rent growth and CPI growth pretty much matched each other, meaning inflation adjusted rents stayed nearly constant.  And then, a departure began between the two: rents have been rising faster than inflation, and the difference between he two is accelerating.

In a well functioning housing market, rents should stay fairly constant across time.  If rents rise above inflation, builders have incentive to build, until they create enough vacancy that real rents fall again (in the old days, this would usually entail a little bit of overshooting).

We do not, alas, have a well functioning housing market in the US.  My hypothesis is that this is because builders, unlike, say, auto manufacturers or farmers, need to get permission from governments to respond to demand pressures, and often do not get it.     

Should young people borrow to get their 401(k) match?

I think the answer is yes.  Suppose you are a young person, early in your earnings years.    Your employer offers you a one to one 401(k) match on, say, 5 percent of your income.  The employer match gives you a guaranteed 100 percent immediate return on your investment (I know of no other deal like this).  But after paying rent, college (or other school) debt, utilities and food, you haven't got five percent of your income left over.  Should you take on credit card debt to finance the 401(k) contribution?

If (and that is a big if) you are a prime borrower, the answer is likely yes.  Suppose your investments earn an eight percent return and, as a prime borrower, you pay 15 percent interest on your credit card.  You are creating a $200 asset for every $100 of debt you take on.  The asset grows by 8 percent, compounded, per year, and your debt grows by 15 percent, meaning that in year 11 the value of your debt will exceed the value of your assets.  (Clearly, if credit card interest is in the 20s, it is a completely different story.

But, one expects income to increase over the early part of the life-cycle, making it possible to amortize the credit card debt over time.  It is important to be disciplined, and not use any more credit card debt than necessary, and to pay it off as soon as possible, but it also makes sense not to leave money on the table.  

I host a podcast.

It's a chat about Robert Galbraith's Career of Evil.  Panelists Lisa Schweitzer and Aubrey Hicks made is work.

Eight double spaced pages that might change the world.

Geoffrey Heal computes the cost of going entirely to renewables by the year 2050.  The paper is short and to the point.  His computations are:

US GDP is currently a shade under $20 trillion.  If Heal is correct, this means the cost of going to all renewables is ~ 11 basis points per year over the next 31 years.  It is hard to imagine that the negative externalities of fossil fuel are less than 11 bps.  Heal also argues that costs will, if anything, be lower than the computed costs.

Imagine--it is possible to stop greenhouse gas emission while improving the economy.  

Shopping

I just had a major home repair that illustrated (1) that law of one price doesn't always hold and (2) people should shop for expensive things.

The expensive thing was a new roof on my vintage 1911 house.  That the place needed a new roof (including a tear-off of the old roof) was not a question. 

I call up a handyman I know and like, and I got a quote of X.  His work is good, but it turns out he is not bonded and doesn't always see the need for permits.  So I decided to investigate further.

I call up roofing company A, and I get a quote of 3X.  But, as the salesman told me, "if I act now!" The price would be 2.5X.  I passed.

I call up roofing company B, and I get a quote of 2X.  I think I may be stuck with this, but I decide to call one more.

Company C gives me a price of 1.1X, with bonding and permitting included.  The new roof is beautiful too (and uses the same shingles offered by A and B).  It was very much worth the bother of shopping.

So roof shopping is like car shopping, mattress shopping and mortgage shopping--some people selling the products take advantage of the fact that there are people who don't have the ability to fend for themselves.  The sad thing is that those least able to afford absurd mark-ups are those most victimized by those mark-ups.  And that is why we need consumer protection.

Is the increasing cost of housing about productivity?

Construction productivity has long lagged productivity in other sectors.  For example, a McKinsey report has manufacturing productivity in several OECD countries increasing by 70 percent, while construction productivity has been flat.

Microeconomic theory holds that in a competitive economy, in equilibrium, the Marginal Rate of Physical Transformation between goods must equal the Marginal Rate of Substitution (that is, the tradeoff on the production side must equal the trade-off on the consumption side).  Prices equilibrate both.  So let's say in the case above, one could in 1994 trade one house for one bundle of manufactured products. By 2012, one could trade one house for 1.7 bundles.  For this to equilibrate, this means that the price of housing must rise to 1.7X the price of manufactured goods.  This might, in the end, lead people to consumer more housing (because increasing productivity in the manufacturing sector could raise incomes), or less housing (because its relative cost is housing).

The world is more complicated than this--for example, we have not seen overall productivity spill over anything like completely into wages.  But if you wonder why the rent is to damn high, the productivity story could well be a large part of the reason. 

What is it about LA?

Cities will make the following deal with developers: we'll give you more density, if you provide units that are deed restricted to be "permanently affordable," meaning will have rents below some ceiling that is tied to area median income.

I have now talked to developers who say the deal works in Seattle and New York, but not in Los Angeles, because city governments around LA specify so much of what must be done during the development process.

This argues (again) for the need for performance based regulation.  For instance, when the EPA requires auto makers to have a minimum MPG for their fleet, it doesn't tell the auto makers how to get there--it just says, "get there."  

Housing really is harder to afford

I have enjoyed reading Michael Kinsley's stuff for as long as I can remember.  The problem is that he inspired a group of young people to value cleverness and contrariness, and so we get stuff like Kevin Drum in Mother Jones saying that housing costs are not rising at an alarming rate.

Allow me to present two pictures (and again, let me acknowledge the people at IPUMS for making it easy to use census and American Community Survey Data).  The first is median rent to median renter income for about 225 MSAs in 2000.

The next is the same picture, but for 2016.

Notice how in 2000,  in the vast majority of MSAs, the median renter would spend less than 30 percent of income on the median rental unit.  By 2016, that had reversed: the median income renter pays more than 30 percent of income in rent in the majority of cities.  And while the 30 percent number is somewhat arbitrary, that fact that rents relative to incomes rose nearly everywhere is not.  It is easy to see why renters are upset.

Joel Kotkin, Housing Affordability, and the Fringe

Joel Kotkin notes quite correctly that housing is expensive relative to incomes in California--he is certainly not alone in this view.  His cure for this particular illness--make it easier to develop on California's metropolitan fringe.

At first glance, he has a point.  The median price of a house in Banning, California (which I think counts as the fringe), is $257,000, which seems pretty affordable.  Here is where Banning is:

There is not a lot of, um, public transit available in Banning.  The nearest job centers are in Riverside and Palm Springs, which are 31 and 23 miles away.  Riverside has about 170,000 jobs; Palm Springs has about 26,000 jobs.  So let's say average distance to jobs is about 30 miles.

What are the implications of this for affordability?  First, the cost of driving is, according to the Federal Government, about 58 cents per mile.  This means driving cost is about $35 per day.  Let's say people can work from home one day a week, so they drive to work 16 days per month.  Living in Banning adds $560 per month relative to living next to a job.

Now let's say you're a parent and need to pay for daycare.  As best as I can tell searching daycare websites, the least expensive late afternoon care costs about $8 per hour (feel free to correct me if I have this wrong).  Assuming an afternoon drive of 45 minutes to Banning, that is another $128 per month per kid.

We have now added $688 per month for a household with one young child in living costs by living at the fringe.  At a 4 percent interest rate, this "payment" translates into a $144,000 mortgage--that $260k house is similar in cost to a $400K house near jobs.

Note I haven't taken into account the opportunity cost of time, and I am only talking abou private costs.  Surely there are social costs to having people drive longer distances--particularly with respect to greenhouse gas emissions. 

Where are the half-million units?

One of the many useful things the people at the St. Louis Fed do is maintain the FRED page, which has a cornucopia of economic data that is easy to download and graph.   Tonight I just happened to be curious about this picture:

The red line is permitted housing units; the blue line is completed unit.  Let's assume that there is a lag of one year between permitting and completion (the length of the time series means that any reasonable lag assumption should be innocuous.  If we look at permits going back to 1967 and ending one year ago, we find that slightly more units were completed than permitted (this is OK, because small places do not necessarily report building permit data to the Commerce Department).  But since 2008, about 500,000 fewer units have been completed than permitted.  This is about a six percent melt from permitting to completion.

So the question is: why?  Very curious about this.

E.B. White on the definition of democracy (h/t Leslie Appleton-Young)

E.B. White in the New Yorker in 1943:

We received a letter from the Writers’ War Board the other day asking for a statement on “The Meaning of Democracy.” It presumably is our duty to comply with such a request, and it is certainly our pleasure.

Surely the Board knows what democracy is. It is the line that forms on the right. It is the don’t in don’t shove. It is the hole in the stuffed shirt through which the sawdust slowly trickles; it is the dent in the high hat. Democracy is the recurrent suspicion that more than half of the people are right more than half of the time. It is the feeling of privacy in the voting booths, the feeling of communion in the libraries, the feeling of vitality everywhere. Democracy is a letter to the editor. Democracy is the score at the beginning of the ninth. It is an idea which hasn’t been disproved yet, a song the words of which have not gone bad. It’s the mustard on the hot dog and the cream in the rationed coffee. Democracy is a request from a War Board, in the middle of a morning in the middle of a war, wanting to know what democracy is.

Lots of folks over 65 are spending a lot on housing.

The Census has a nice tool that allows one to map American Community Survey data by counties (at least counties with sufficient population to develop estimates based on samples).  I drew two today.  This first one is the share of those renters over the age of 65 who pay more than 30 percent of their income on rent.

The second one is the share of those owners over the age of 65 who spend more than 30 percent of their income on homeowning.

The picture for elderly renters is pretty grim: in most counties that are mapped 45 percent or more are spending more than 30 percent of their income on rent.  So one may take a small amount of comfort in the fact that the 78 percent of those over 65 are homeowners.  But in the median county mapped here,  a quarter of those over the age of 65 pay more than 30 percent on housing cost.  This is because such people have either not paid off their mortgage, or have high property taxes.

Altogether, about 55 percent of those 22 percent of the 65+ households who rent pay more than 30 percent of their income in rent, and 26 percent of the 78 percent who own pay more.  This means nearly 1/3 of those over the age of 65 live in an unaffordable house.

It is hard to imagine things getting better.  The old population is growing quickly--the very old population is growing even more quickly.  As people age, their incomes fall, so absent falling housing costs, the share that will be pressured by housing costs will increase in the years to come.     

Is it reasonable for Angelinos to expect a shorter commute?

I have lived in LA for 11 years now, and I think it is safe to say that among the top topics of conversation is traffic and the misery of commuting.  And in a sense, people are right about
the fact that they have long commutes:  LA-OC Metro 2017 American Community self-reported average travel time to work ranks 246 among the 260 largest Metropolitan Areas, and share of people with a commute of an hour or longer ranks 231 (we will get to who does worse in a bit).  Thanks to Steven Ruggles, Sarah Flood, Ronald Goeken, Josiah Grover, Erin Meyer, Jose Pacas and Matthew Sobek, IPUMS USA: Version 9.0 [dataset]. Minneapolis, MN: IPUMS, 2019, who make it easy to download various data sets and play with them.

But should people reasonably expect LA to do any better than this?  Consider this plot of number of commuters in an MSA against average travel time (I looked to see if someone else had done this particular plot, and couldn't find anyone who has.  If I have failed to cite work already done on this, I apologize).

Two things are pretty clear: larger cities have worse commuting times, and Los Angeles has shorter commutes than New York, but also shorter commutes than some places with smaller numbers of commuters.

How does it do in context?  If we run a simple bivariate regression of number of commuters explaining travel time, we get this:

That is a lot of explaining for one variable--the t-statistic is 11 and the R2 is .32.  And I don't worry too much about getting the direction of causality wrong here.  The regression predicts that LA's commute should, given its size, be six minutes, or about 20 percent, longer than it actually is.  So it appears that people who live in Los Angeles and Orange Counties have shorter commutes than they should expect, given the very large size of their employment market (and there are large benefits to living in such large employment markets).  

I should note that the scatter plot above looks quadratic, and so I also did the quadratic regression:

The addition of the squared term improves the fit, and so now we can explain almost 38 percent of the variation in commuting time with one variable.  It doesn't change the basic result, however, that LA's commute times are considerably shorter than its size would predict (although its commutes are five, rather than six, minutes shorter than the model would forecast).

So we who live in LA really have nothing to complain about with respect to congestion--we get agglomeration benefits from living in a very large city (Ed Glaeser, Enrico Moretti, Vernon Henderson, Stuart Rosenthal, Will Strange, Jane Jacobs, Alfred Marshall, and many, many others have written about the productivity and consumption benefits of living in a large MSA), and the congestion costs, while real, are relatively low.   

But....this doesn't tell the whole story.  Look again at the scatterplot above, and one sees that the MSA with the longest commute is the relatively small Easton, Pennsylvania.  What is going on here?  Easton is a town immediately to the west of the Delaware River from New Jersey.  It is on Interstate 78, 68 miles to the west of the Holland Tunnel.  It is an inexpensive housing market.  And people commute from there to metro New York.

And so it is with Los Angeles. One place with fewer commuters than metro LA, but a longer commute, is Riverside-San Bernardino, the Inland Empire.  The Census counts people who live there as living in a separate metropolitan area, but they are in fact very much part of the Los Angeles regional economy.  And the people who live there have commutes that are more than 20 percent longer than the model predicts.  People who live out east may get some of the production externalities of the region, but I am not sure, after their exhausting commutes, that they benefit that much from the consumption externalities.

So I, and my neighbors, who live in Pasadena have no reason to complain about our commutes (cost of housing is a different issue).  Those who live in Ontario, on the other hand, have a point.

California is getting richer..because it is becoming clubbier.

Jung Choi, Eul Noh and I have a paper that shows that when high skill people move to high skill cities, rents for low skill people rise more rapidly than their incomes (high skill people generally see their incomes rise more than rents).  One manifestation of this is that high skill places are pushing out low skill workers.

And so we see this currently in California.  Adam Fowler and Hoyu Chong of Beacon Economics looks at American Community Survey Data to look at net domestic migration in California.  More people are moving out than moving in, but it is the lowest income people who are doing the moving.  High income households are actually moving in.

There is some irony here, because I often hear people authoritatively say that California's taxes and regulations are pushing wealthy people away.   We will have to see the impact of the curb on the state and local tax deduction on migration (that federal tax law change does increase the relative tax burden for income income people in California), but up to this point, the wealthy seem willing to pay the costs of California's access to labor markets and beaches.

What is disturbing, though, is that low income people are moving out at the same rate they are leaving during the great recession, despite the fact that unlike in 2008, the unemployment rate here is at historic lows.  For economies to function, they need people like home health care workers and cooks, people who do important work but don't make a lot of money doing it.  The culprit for the exodus of lower income people from California is almost surely that there isn't enough housing here (the only state with fewer units per person is Utah, whose fertility rate is 30 percent higher than California's).  It is no longer the case that scarcity in housing is limited to Malibu and Beverly Hills--it is reaching San Bernardino and Riverside Counties, the traditional safety valves for inexpensive housing here.  When higher income people compete with lower income people for the same resources, the higher income people tend to win. 

Ads that amuse

I was browsing the web, and an add popped up up for a beautiful Porsche, with the tag-line, "a slice of the Autobahn on the 405."

I am sure the car is lovely to sit in, but that is about all one does on the 405.

For those that think homeless people migrate to warmer climates....

....here is a scatterplot of the Census 2017 homeless count per capita against mean January temperature by state:

See a correlation?  No?  That's because there isn't one.

(Note: y-axis was previously mislabeled).

Update: David Albouy asked me to look after controlling for urbanization.  Here is what I got:

Homeless people do tend to congregate in more urbanized states.  But again, climate has nothing to do with propensity for homelessness.

Is California a Big Spender?

People say so.  But what people say is sometimes not true.

I did the following exercise.  I took Census of Government Data on State and Local Spending for 2016 (the most recent available year) and divided it by State GDP for 2016.  This is what I got:

California is right in the middle, ranking 23rd, and sitting next to that well-known hotbed of socialism, Utah.

Two Moral Dilemmas for Housing Policy

Of course there are far more than two, but two seem particularly all encompassing to me. They are

(1) Should everyone, regardless of income, have access to housing in every neighborhood?

(2) What is the minimum acceptable quality of a house?

These are questions whose answers come with tradeoffs.  With respect to (1): suppose we decide that everyone should, if they wish, be able to live in a house on a beach in Laguna (as it happens, the Southern California beach town I most enjoy visiting).  Such a policy would be costly, and has implications for the distribution of other goods.  But there are reasons to think it is socially desirable for people of mixed income to live together.  The correct answer will involve normative judgments we make as a society, but we need to make these judgments explicitly.  I don't know that we do that.  Personally, I think everyone should be able to live in a safe neighborhood, be in a place where they can send their kids to a decent, publicly funded, school, and have a reasonable commute to work (30 minutes or less?  45?) within their choice set.  If people choose to live further away, that is their business.

As for (2), in the US context, I would think the minimum acceptable house would have indoor plumbing, clean water (I wish I could say this was a given),  good sanitation, reliable electricity,  a minimum amount of floor space per person (although I am not sure what that is), and be very, very fire resistant.  I am perhaps leaving something out, but anything beyond an agreed upon minimum adds to the cost of providing housing.  Again, I don't think when we discuss housing we discuss the tradeoffs enough.   

Rent Control

New York state is about to pass a suite of the most restrictive rent control laws in many years.  Among other things, the laws would restrict vacancy decontrol, and limit the ability to pass the cost of improvements through to tenants.  As such, it is moving New York away from second generation rent control toward first generation rent control.  Richard Arnott gives some examples of second generation control:

Second-generation rent controls commonly permit automatic percentage rent increases related to the rate of inflation. They also often contain provisions for other rent increases: cost pass-through provisions which permit landlords to apply for rent increases above the automatic rent increase, if justified by cost increases; hardship provisions, which allow discretionary increases to assure that landlords do not have cash-flow problems; and rate-of-return provisions, which permit discretionary rent increases to ensure landlords a "fair" or "reasonable" rate of return. Second-generation controls commonly exempt rental housing constructed after the application of controls, although new housing may be brought under the controls at a later time.  

In some jurisdictions, second-generation rent control has permitted full vacancy decontrol, whereby the unit becomes completely decontrolled when it is vacated. Other jurisdictions' programs permit inter-tenancy decontrol, whereby controls apply during successive tenancies but no restrictions are placed on inter-tenancy rent increases. Others contain alternative decontrol mechanisms; probably the most common has been rent level decontrol, whereby a unit is decontrolled when its controlled rent rises above a certain level. Yet others have no decontrol provisions.  

Such rent regulation often contains provisions which accord tenants improved security of tenure—rent increase appeal procedures, eviction procedures more favorable to the tenant, and so on—and it often includes restrictions to prevent cutbacks in maintenance, and on the conversion of controlled rental housing to owner-occupied housing.

Richard is one of the finest urban economists alive, and has taken the view that second generation rent control might do more good than harm.  This is certainly not Econ 101 gospel, but one one needs only to move onto Econ 201 to see where he is coming from.    If property owners have pricing power, the equilibrium rental rate could well be above the social optimum, and the quantity of housing produced could fall below the social optimum.  The idea that property owners might have pricing power goes back at least as far as David Ricardo, who worried about the corrosive effects of "economic rent" on social welfare.  It is certainly plausible to think that in a select few markets, such as New York and San Francisco, landowners do indeed have pricing power.  And this may argue for second generation rent control--but not the move toward first generation rent control, which puts tight caps on rent increases, eliminates vacancy decontrol, and imposes controls on new buildings.

Nevertheless, it is not clear to me that even second best rent control helps much with allocative inefficiency in markets where supply is inelastic--if there is a ceiling on the number of units builders can build, a price intervention is not going to bring about additional units.  So the issue is about redistribution.

Rajasekaran, 

Treskon and 

Greene 

have a nice white paper summarizing the literature on the winners and losers of rent control in the few jurisdictions where it exists in the US.  That literature shows that (1) rent control does indeed benefit incumbents; (2) does harm to those outside the rent control system (except, perhaps in Cambridge, MA); (3) probably reduces the stock of rental housing and (4) probably reduces the quality of the housing stock.  Diamond, McQuade and Qian find that the costs and benefits of San Francisco's second generation rent control (which has vacancy decontrol and no control of new buildings) are about equal.  This does not mean that this would be true for first generation rent control.

But even if second generation rent control is neutral in terms of costs and benefits, it doesn't necessarily lead to desirable distributional outcomes.  It is almost certainly true that the average property holder is wealthier than the average renter, and therefore that on average rent control redistributes income from higher to lower wealth people.  But rent control does not target the incomes/wealth of either property owners or renters.

We don't know much about the distribution of wealth among property owners.  We can turn to the US Census Rental Housing Finance Survey to see that nearly half of all units (and about 3/4 of all properties) are owned by individual investors.  Similar numbers are managed by either the owner herself or an unpaid agent of the owner.  So a substantial number of units are held by Mom and Pops.  According to the 2016 Survey of Consumer Finances, the median value of "equity in non-residential property (which includes residential properties with 5 or more units)" among those who hold such properties is about $70,000.  It is safe to say that a substantial number of owners of properties for rent do not have oodles of wealth.

As for the distribution of benefits to renters, consider the following graph:

Rent control in Los Angeles applied to buildings constructed through 1978.  I took data from the 2016 American Community Survey (I know, I need to update it) to look at the income distribution of those living in buildings built in the 1970s (the best I could do to get at the newest rent stabilized buildings) and those living in buildings built in the 1980s (i.e., the oldest non-rent stabilized buildings).  Do you see a difference in these distributions?  Neither do I.  And to me, good social welfare policy is targeted to those who need help.

The thing that bothers me most about rent control is that it allows elected officials to say they are tackling housing issues in our most expensive MSAs, while they continue to punt on the issue of supply elasticity.  I am waiting to see more of our great cities take up the example of Minneapolis, whose government eliminated single family zoning in that city.  I would even be OK with cities combining temporary rent control with Minneapolis style zoning, knowing that in the presence of sufficient supply, people would ultimately no longer feel the need for rent control.  Rent control alone, however, just gives electeds cover not to fix the fundamental problem.





  

Is there in the US a necessity of life...

...other than housing, where governments impose supply ceilings?  Racking my brain on this, and I can't think of another product.  I could be wrong, though. 

Supply and Demand do explain why LA has a housing problem

The most recent homeless counts came in last week, and homelessness in Southern California is getting worse.  As my colleague Gary Painter has shown, this is not because LA "attracts homeless people," which is the view of the data-free opinionaters in the LA Times comments section.

The change in homelessness reflects how very expensive housing is here in LA, particularly as it attracts people with college degrees who outbid lower skilled workers for the housing stock that is here.  Many people without college degrees are leaving LA, but people with strong social or familial ties have reasons not to do so.

So why are things so bad here?  I would argue the problem arises from the fact that LA policymaker "solutions," which include bespoke zoning and some affordable units here and there, do not address the fundamental problem facing the LA housing market--that it has an inelastic supply curve.  As my friend and frequent co-author Steve Malpezzi taught me a long time ago, there is a big policy difference between nudging an inelastic supply curve to the right and making supply more elastic.

We may approximate the state of the LA housing market with the following supply and demand picture.  Albert Saiz showed in 2008 that Metro Los Angeles had the lowest supply elasticity of any American MSA, and given its small levels of construction in the face of large rent increases since then, it is hard to imagine how it has gotten any larger.

Now suppose municipalities relax the constraint on supply through a little up-zoning here and there.  The picture changes to this.

The relaxation of the constraint allows some housing price relief.  But there is a problem.

Housing demand for LA continues to increase, not (any longer) because of in-migration, but because of the age profile of the population.  Large numbers of kids are becoming adults, and, as Sarah Mawhorter shows, want to move out of the parental home (the parents want this too!), but don't want to leave the town where they grew up.

For LA to accommodate housing demand, it would need to have a supply curve that more closely resembles other cities--it would look like this:

The supply curve would still be upward sloping, but changes in demand would also lead to large increases in supply, and hence bring about milder price increases.  Policy can move this relatively elastic demand curve rightward, by reducing the requirements necessary to build (these include things like fees, and in LA's case, linkage fees and parking requirements).

I should note that LAs current vertical supply curve is not the result of topography alone.  In his excellent dissertation at UCLA, Greg Morrow showed that Los Angeles zoning contemplated a city of 10 million; various down-zonings since then have reduced the city's allowable density by 60 percent.  LAs current population of 4 million largely uses up its allowable zoning, and as affluent small households replace less affluent large households (something Hyojung Lee has documented), it will be able to hold even fewer people--unless land use policy is completely overturned.

For those who think LA is overcrowded, let me use Alain Bertaud's work to point out the LA's density is one-third of Krakow's, one-fourth of Paris' and one-fifth of Singapore.   I can testify that these are all very pleasant, livable cities.  If LA were to completely change its land-use policy, it could at once become considerably more affordable and have even more walkable neighborhoods than it currently has.  But incrementalism won't work.

California out-streaming

I was looking at Census estimates for 2018 this morning (I know, I know, but I also took a nice walk first), and saw that after seven years of positive in-migration of 50,000 per year, we in California had net outmigration of 38,000 between 2017 and 2018.  This reduces the pressure on the housing market by ~ 30,000 units, or 3-4 months of production at current levels.  Some thoughts:

(1) This doubtless explains why the housing market is slowing (and I am sticking with my call of a small price reduction over the next few years).

(2) Perhaps this reflects a tipping point--we have just become too expensive as a state, regardless of the economic productivity here.

(3) Perhaps also this reflects that policy hostility toward immigrants is really mattering.  California has long had domestic outmigration, but had more than enough foreign migration to make up for it.  This is no longer true.

It is particularly striking that this is happening at a time when there are lots of jobs in California.

Here is the site from which to download migration data. https://www.census.gov/data/tables/time-series/demo/popest/2010s-state-total.html …. Looks at annual components of changes and cumulative components of change.