Results for “housing” 707 found
Minimum wages and rents
This topic remains underdiscussed in the minimum wage debates, here are some recent results from Atsushi Yamagishi:
I analyze the effect of minimum wage hikes on housing rents using exogenous variation in minimum wages across local labor markets in Japan. I estimate that in low-quality rental housing market, a 10% minimum wage increase induces a 2.5%–4.5% increase in rents. Minimum wage hikes benefit workers in light of a spatial equilibrium model showing that changes in housing market rents work as a sufficient statistic for measuring utility changes arising from changes in minimum wages. The increase in housing rents also implies an unintended benefit for homeowners.
Atsushi Yamagishi is from Princeton economics, but that is not his job market paper, here is the whole portfolio, which looks quite interesting.
Denmark takes forceful measures to integrate immigrants
After they fled Iran decades ago, Nasrin Bahrampour and her husband settled in a bright public housing apartment overlooking the university city of Aarhus, Denmark. They filled it with potted plants, family photographs and Persian carpets, and raised two children there.
Now they are being forced to leave their home under a government program that effectively mandates integration in certain low-income neighborhoods where many “non-Western” immigrants live.
In practice, that means thousands of apartments will be demolished, sold to private investors or replaced with new housing catering to wealthier (and often nonimmigrant) residents, to increase the social mix.
The Danish news media has called the program “the biggest social experiment of this century.” Critics say it is “social policy with a bulldozer.”
The government says the plan is meant to dismantle “parallel societies” — which officials describe as segregated enclaves where immigrants do not participate in the wider society or learn Danish, even as they benefit from the country’s generous welfare system.
Here is more from the NYT, and do note that Singapore has its own version of this policy. I would make a few observations:
1. Putting aside the normative, analyzing the effects of such policies will be increasingly important. Economists are not especially well-suited to do this, nor is anyone else. I am well aware of the Chetty “Moving to Opportunity” results. That is good work, but a) it probably doesn’t apply to coercive Danish resettlements, and b) cultural context is likely important for the results. At least for the countries that migrants wish to move to, most will have their own versions of this dilemma.
2. “Open Borders” as a sustainable political equilibrium is looking much weaker than it did a month ago. The key question in immigration policy is not “how many migrants should we take in?” (a lot, I would say), but rather “how can we make continuing immigration a politically sustainable proposition?” Many immigration advocates are in a fog about their inability to offer better answers to that question.
3. Will this Danish action, once the entire political economy is worked through, increase or decrease the allowed number of migrants to the country? Looking at the demand side to migrate, will this policy end up attracting a higher or lower quality of migrants to Denmark? Is Denmark even attractive enough as a destination to get away with this? Or will it send a better signal to would-be migrants and thus raise quality?
I would not be too confident about my answers to those questions, nor should you be so confident.
What is it we do and do not know about macroeconomics?
That is the topic of my latest Bloomberg column, here is one excerpt:
Another episode frequently cited as evidence against economists is the Great Recession of 2007-2009. Economists did make some mistakes on that one — but they are not the ones you usually hear about.
When real estate prices started to slow down and then fall, many economists declared there was a real estate bubble. The theory quickly developed that the market crash was due to a real estate bubble bursting, followed by a sharp fall in aggregate demand, followed by a decline in employment and output.
The last part of that explanation is correct. In retrospect, however, it is not clear that the housing prices of 2006-2007 represented a bubble. By today’s metrics those prices appear prescient, if slightly premature. The market was suddenly realizing that a lot of real estate assets were going to be worth much more — and the recent evolution of real estate valuations seems to have confirmed that judgment.
In 2009, however — and following a lot of foreclosures and the emergence of troubled banks — the market was far from ready to accept that the high real estate prices had been justified. The market was too skeptical when it should have been less panicked. A lot of economists got this wrong too, along with many pundits. All of this made the resulting panic worse because the talk was so pessimistic about real estate valuations. Instead, the real problem was that the market had lost faith in a set of high real estate prices that has since been largely validated. Maybe not in Las Vegas and Orlando, but for the nation as a whole, most of all on the coasts.
Economists should have been less quick to judge what is or is not a bubble. The real-estate-bubble explanation appeared to be correct in the short run, but economists should have been more modest about their ability to second-guess the market. The good news is that, with hindsight, we can piece together what happened. Policymakers and market participants made a series of overlapping mistakes related to monetary policy, the shadow banking system and panic about real estate.
There is a good picture of trends in real estate prices at the link, or ungated here.
Upzoning with Strings Attached
The subtitle of this paper is: “Evidence from Seattle’s Affordable Housing Mandate.” Here is the abstract:
This paper analyzes the effects of a major municipal residential land use reform on new home construction and developer behavior. We examine Seattle’s Mandatory Housing Affordability (MHA) program, which relaxed zoning regulations while also encouraging affordable housing construction in 33 neighborhoods in 2017 and 2019. The reforms allowed for more dense new development (‘upzoning’), but they also required developers to either reserve some units of each project as below market rate rentals or pay into a citywide affordable housing fund. Using a difference-in-differences estimation comparing areas the reforms affected versus those not affected, we show new construction differentially fell in the upzoned, affordability-mandated census blocks. Our quasi-experimental border design finds strong evidence of developers strategically siting projects away from MHA-zoned plots – despite their upzoning – and instead to nearby blocks and parcels not subject to the program’s affordability requirements. The differential reduction from MHA to non-MHA zones could be as large as 70% of average permitting activity at the border. Lowrise multifamily and mixed-use development. Our findings speak to the mixed results of allowing for more density while simultaneously mandating affordable housing for the same project.
That is by Betty Xiao Wang and Jacob Krimmel. Via the excellent Kevin Lewis.
Sort of Middlebury markets in everything
Middlebury lacks sufficient housing for all the students planning to attend this fall. After exhausting other options, the college plans to pay 30 students $10,000 each to stay away.
Clever idea, but I’m sure you all noticed the “After exhausting other options” clause in there. Here is from the rest of the story:
But the nonresidential buildings could not be renovated in time to add necessary safety features, and the college decided not to house students at Bread Loaf due to the logistics of running a satellite operation, as well as negative feedback from students who had lived there earlier in the pandemic and said they’d felt isolated from the main campus.
I say Granny Flats and beans! It is not for long, so let the learning continue. The article does not discuss the stance of the town of Middlebury, but as it is an exclusive village of about 9,000 I can take a wild guess…
Thursday assorted links
1. Hawaii is going to build more homes.
2. When did people stop being drunk all the time?
3. “Tom Sowell himself designs the cover jacket of just about every one of his books (and often uses just 3 colors: black, white, and red)” Link here. With a photo.
4. Over the last year, Japan’s population fell by about 800,000.
5. Okie-dokie!
6. Sinead O’Connor obituary RIP (NYT).
On white flight (from the comments)
Are whites fleeing from Asian-heavy California public schools? One recent paper suggested maybe so, but abc raises some doubts:
I don’t want to dismiss the paper out of hand, as I have seen time and again the challenges communities face both in and outside of the school setting in accommodating demographic change.
However, I don’t think the headline result in this paper is particularly credible. First, there isn’t a well-articulated research question to guide the choice of regression. Second, the authors implicitly rely on the “an instrument is always better” fallacy rather than explaining why their instrument yields more reliable estimates than naive OLS for the (unstated) question of interest. Taken together, the paper is undergrad-thesis level material elevated only by a click bait topic and result. If we want to make bold claims about White animosity towards Asians (a claim that also constructive of such animosity and counter-animosity from Asians towards Whites) we should demand substantive evidence. This paper does not present such evidence.
Some key takeaways:
(1) The authors note that a mechanical housing market replacement would suggest a one-for-one effect, but say that their -1.47 effect is above that threshold. However, if we check the confidence interval using a conservative 1.96 critical value and the estimated standard error of the coefficient estimate, we have -1.47 + 1.96*0.268 = -0.96 so that we are not statistically significantly different from -1 by this measure.
(2) The naive OLS estimate in high-SES regions is -0.6, well below the fixed enrollment effect of -1. The authors speculate that OLS may be biased downward because the error term include unmeasured district quality changes that draw in both Asians and Whites. (Note such a correlation only operates if enrollment is not capped, so inconsistent with that model.) The authors don’t document any of these omitted variable issues, however, and just assert that their instrument will be better.
(3) Authors do not substantively engage issues with their IV. First, the IV doesn’t account for changes in composition of immigrants over time (increasing wealth and education of Asian arrivals relative to earlier waves) nor does it account for movement of second-generation Asian families. If there is no omitted variable bias but the instrumented entry is lower than the actual entry, then mechanically the coefficient will have to be higher to offset this effect and restore least-squares minimization.
(4) The instrumented Asian inflows coefficient could pick up effects from Asian-agglomeration effects. A one unit increase in Asian enrollment from pure fixed-pattern immigration flows made lead to shifts of previously settled Asians or shift the direction of subsequent immigration. For example, a settled Korean in Riverside who sees large increases in Korean population in Orange County may see OC as being more attractive than before and move into the area. This induced shift may be only partially captured by the first-stage prediction, leaving the 2nd stage coefficient of interest to increase in magnitude.
(5) Various sensitivities lead to surprising results. First, the instrument behaves poorly in some subsamples, e.g. the bottom-half of the SES scale. Why should we believe an instrument in one data subset when it plainly fails in the complement? Second, the instrument is insignificant in the Bottom Tercile of the above-median SES group (appendix table 2). Third, the IV estimate is only -0.841 in the top tercile of the above-median SES group, again below the key -1 threshold if enrollment caps are binding. Taken together, are we to think that we can identify white flight using this instrument only for the 66.6th to 83.3th percentile bucket?
(6) There’s just a big background trend issue that one has to worry about here. The theory of white flight begs the question of “flight to where?” However if we just look at Appendix Figure 2 during this time period there is a big drop in total White enrollment (and a small decline in Black enrollment) while Asian and Hispanic enrollment see big increases. To what extent are we just finding that aging out of whites in high-SES regions is being replaced disproportionately by Asians?
(7) A couple other wrinkles: how are mixed-race students handled? how would demographic shifts in total enrollment by district affect the 1-to-1 threshold? If child population is shrinking over time (e.g. because families are leaving CA, children per family is declining) then normal churn would predict more than 1-to-1 replacement of new-cohort race versus previous-cohort race.
So perhaps the right answer is “no”?
White Flight from Asian Immigration: Evidence from California Public Schools
Asian Americans are the fastest-growing racial group in the US but we know little about how Asian immigration has affected cities, neighborhoods and schools. This paper studies white flight from Asian arrivals in high-socioeconomic-status Californian school districts from 2000-2016 using initial settlement patterns and national immigrant flows to instrument for entry. We find that, as Asian students arrive, white student enrollment declines in higher-income suburbs. These patterns cannot be fully explained by racial animus, housing prices, or correlations with Black/Hispanic arrivals. Parental fears of academic competition may play a role.
That is from a new NBER working paper by Leah Platt Boustan, Christine Cai, and Tammy Tseng. Nut unrelated to recent issues surrounding Harvard admissions policies, of course, and also not unrelated to the somewhat uncomfortable role that successful Asian students play in the political discourse of the Left.
Singapore facts of the day, shareholder state edition
The government (through holding company Temasek) has a minority stake in DBS Bank which is the largest company on the Singapore Exchange. The government has a majority stake in the two largest telecom companies: Singtel and Starhub, it has a majority stake in the flag carrier Singapore Airlines and it is the owner of CapitaLand (the largest real estate company in Singapore).
Out of the 25 largest companies listed on the Singapore Exchange (as of 26th June 2023, excluding real estate investment trusts) 9 companies were started by the government. It still maintains at least a minority stake in all of them and a majority stake in Singapore Airlines and ST Engineering. For most of them, it is still the largest shareholder.
Singapore’s Government Linked Companies do not appear to get any special advantages according to this 2003 study, and some of them – like SIA, Singtel, DBS and Keppel – have achieved success out of the home market.
Along with this, the government of Singapore owns the vast majority of land in Singapore. I’m not sure of the exact number (this 2021 article says over 80% while this OECD site says 90% without citing it), but it is likely to be above 80 or 90%. Nearly 80% of Singaporeans live in government built housing.
Here is more from Pradyumna Prasad, mostly about how to construct freedom indices properly.
Wednesday assorted links
1. The gender gap in commercializing science.
3. Jon Hartley is launching a de-dollarization facts website.
4. AI experimental church service in Germany, at least the first one drew a crowd.
5. Kenyan Luddites.
6. Claims about minimum wage and homelessness. I’ll say it again: the results on this question are swinging back in the neoclassical direction.
The Confederate Diaspora
This paper shows how white migration out of the postbellum South diffused and entrenched Confederate culture across the United States at a critical juncture of westward expansion and postwar reconciliation. These migrants laid the groundwork for Confederate symbols and racial norms to become pervasive nationally in the early 20th century. Occupying positions of authority, former slaveholders played an outsized role in this process. Beyond memorializing the Confederacy, migrants exacerbated racial violence, boosted novel forms of exclusion, and compounded Black disadvantage outside the South. Moving West, former Confederates had larger effects in frontier communities lacking established culture and institutions. Over time, they continued to transmit norms to their children and non-Southern neighbors. The diaspora legacy persists over the long run, shaping racial inequities in labor, housing, and policing. Together, our findings offer a new perspective on migration, elite influence, and the interplay between culture and institutions in the nation-building process.
That is a new NBER working paper by Samuel Bazzi, Andreas Ferrar, Martin Fiszbein, Thomas P. Pearson, and Patrick A. Testa. Deep Roots!
Wednesday assorted links
Sam Bowman on French success
But Ben Southwood has convinced me that France is rich because it gets the big things basically right. Housing supply there is freer: the overall geographic extent of Paris’s metropolitan area roughly tripled between 1945 and today, whereas London’s has grown only a few percent. Infrastructure is better: 29 French cities have trams, versus 11 here (likely one reason its second-tier cities are much more productive than Britain’s). It has nearly 12,000km of motorways versus around 4,000km here – and French motorways tend to be smoother and better kept (and three quarters are tolled, making congestion much less of a problem). Childcare is cheaper: about half the price per month, in part because they require half the staff. Energy is more abundant, as shown above. Because it gets those big four things right, it can afford to get a lot of other things wrong.
Here is the full essay, mostly on Coasean democracy.
Saturday assorted links
How D.C. densified
DC’s relative success can be traced to a few decisions made decades ago. In the 1970s, policymakers in Arlington County made a decision to adopt what’s known as ‘transit-oriented development planning’ ahead of the opening of DC’s Metro Orange Line, which runs between Arlington and Prince George County, Maryland (via DC). Arlington policymakers identified that zoning for apartment construction in commercial areas could bring in property taxes and help balance the budget without the level of controversy of changing zoning in existing residential areas. Some nearby jurisdictions followed suit, learning from Arlington’s example, helping the DC region stay more affordable than the country’s other superstar cities.
Here is the full essay by Emily Hamilton of Mercatus, serving up a very good short economic history of Arlington. And this on the District:
The District itself has permitted extensive redevelopment of formerly industrial neighborhoods when they received new Metro stations, including Navy Yard and NoMA. In the years since the 2010 financial crisis, DC has permitted thousands of apartments each year, a high rate compared to peer cities. As in Arlington, they’ve primarily been permitted on land that previously housed industrial or low-value commercial development where there are few or no existing residents to oppose new construction.
Interesting throughout. I am pleased to live in the land of partial YIMBY.
That is all from the new and excellent issue of Works in Progress.