Stringent restrictions to new housing supply lowered aggregate US growth by more than 50% from 1964 to 2009.

See The new Hsieh and Moretti paper on land use restrictions and economic growth. From Marginal Revolution.

"We quantify the amount of spatial misallocation of labor across US cities and its aggregate costs. Misallocation arises because high productivity cities like New York and the San Francisco Bay Area have adopted stringent restrictions to new housing supply, effectively limiting the number of workers who have access to such high productivity. Using a spatial equilibrium model and data from 220 metropolitan areas we find that these constraints lowered aggregate US growth by more than 50% from 1964 to 2009.

Here is the pdf, via the excellent LondonYIMBY.  Here is a related estimate from two days ago."

The Value of Access: How Closeness to the Obama White House Benefited Companies

By Guy Rolnik of the Stigler Center.

"Between January 2009 and December 2015, White House officials met with corporate CEOs 2,286 times. A new study, to be presented at the upcoming Stigler Center conference on the political economy of finance, shows that access to the White House has several economic benefits.

Since Donald Trump assumed office, there has been a dramatic increase in the reporting and discussion on crony capitalism in the U.S.: Trump’s conflicts of interest, his pro-business policies, his frequent meetings with business executives, and the assertion that, more than any other president, he is tuned in to the interests of big business.

But are all these issues unique to Trump? Was the Obama administration completely different?

 
A new paper by Jeffrey Brown and Jiekun Huang of the University of Illinois at Urbana-Champaign, “All the President’s Friends: Political Access and Firm Value,” is trying to answer that question using White House visitor logs from January 2009 through December 2015, when President Barack Obama was in office. The paper will be presented during the Stigler Center conference on the political economy of finance, which will be held between June 1-2.   

Before asking ourselves if the methodology and interpretation are convincing, it is worth starting with two anecdotes, both mentioned in the paper.

The first is about Google. The backdrop is an antitrust investigation against Google by the FTC that culminated in an August 2012 FTC document that recommended suing Google for certain practices. Immediately after that, Google executives had a series of meetings with FTC and White House officials: for example, Google CEO Larry Page (currently the CEO of Alphabet, Google’s parent company) met with FTC officials, and the company’s executive chairman Eric Schmidt met with Pete Rouse, a senior adviser to President Obama, in the White House. Following those meetings, the FTC closed its investigation after Google agreed to make some changes to its business practices.

The FTC decision to close the investigation was probably not a direct result of these meetings. After analyzing White House visitor logs, the Wall Street Journal found that Google possibly had unprecedented access to the White House: since Obama took office, Google employees have visited the White House for meetings with senior officials about 230 times—on average, roughly once a week.

The second anecdote is related to General Electric (GE). GE and the Obama White House seemed to be very close. In a July 1, 2010, piece in the Washington Examiner, Timothy Carney wrote:

“Except for maybe Google, no company has been closer and more in synch with the Obama administration than General Electric. First, there’s the policy overlap: Obama wants cap-and-trade, GE wants cap-and-trade. Obama subsidizes embryonic stem-cell research, GE launches an embryonic stem-cell business. Obama calls for rail subsidies, GE hires Linda Daschle as a rail lobbyist. Obama gives a speech, GE employee Chris Matthews feels a thrill up his leg. I could go on.”

Behind this, wrote Carney, is the close relationship between GE CEO Jeff Immelt and President Obama: Immelt sat on Obama’s Economic Recovery Advisory Board and was asked by Obama’s Export-Import Bank to be the opening act for the president at an Ex-Im conference. And this may be just the tip of the iceberg.

The most frequent visitors

The reason that the authors chose to focus on the Obama administration is that it was simply the only administration to voluntarily release its visitor logs. Previous administrations didn’t do so, and the Trump administration is unlikely to do so either.

Using the visitor logs, Brown and Huang were able to identify 2,286 meetings between corporate executives from members of the S&P 1500 stock index and White House officials during the seven-year period between January 2009 through December 2015. 

As can be clearly seen from panel A of Table 1 above, which includes all the executives that had at least 10 meetings in the period studied, the three most frequent visitors were Honeywell’s David Cote (30 visits), GE’s Immelt (22 visits) and EverCore’s Roger Altman (21 visits). On average, Cote had meetings in the Obama White House once every 2.8 months.

Panel B, which includes the list of White House officials who had the most meetings with business executives, reveals that the most visited officials were Valerie Jarrett (Senior Advisor and Assistant to the President for Intergovernmental Affairs and Public Engagement), Jeff Zients (Assistant to the President for Economic Policy and Director of the National Economic Council) and President Obama himself. On average, Jarrett met with corporate executives once every 24 days.

In assessing the degree of access that S&P 1500 executives had to the White House during the period studied, Brown and Huang found that firm-years in which the executives visit the White House account for around 11.4 percent of the sample, suggesting that a non-trivial fraction of the firms have political access. Also, since firms with political access are typically larger, they account for about 40 percent of the total market capitalization of firms in the sample.

Campaign contributions and lobbying ‘buy’ access

As access to the White House is still a scarce resource, what are the factors related to better access to it?

Brown and Huang regressed access against a series of firm characteristics and found that, as defined by the model they used, an increase in campaign contributions increases the probability of gaining access to the White House by 2.4 percentage points. Since the unconditional probability (firm-years in which the executives visit the White House) is 11.4 percent, 2.4 percentage points is a significant increase. This, the authors write, is “consistent with the notion that campaign contributions ‘buy’ political access.”

Their model also indicates that firms that spend more on lobbying, receive more government contracts, and have a large market share are also associated with an increased probability of gaining access to the White House.

Economic gains from access

Access to the White House, Brown and Huang found, has several economic benefits.

One is a positive effect on government contracts: the average firm generates about $34 million in profits from incremental contract volume due to political access.

Another is regulatory relief. Using a dataset of news articles which were characterized as positive or negative (based on the relative fraction of positive and negative words in the articles), Brown and Huang matched the articles with White House visits and found that “treatment firms, relative to control firms, experience an increase of 0.036 in the number of positive regulatory news articles during the 12 months immediately following a White House visit relative to that during the 12 months immediately before the visit.”

These results, they write, are “in line with the hypothesis that political access enables firms to obtain regulatory relief.”

These and other access benefits are encapsulated in stock prices. Brown and Huang checked excess stock returns—specifically, cumulative abnormal returns (CARs) around corporate executives’ visits to the White House.

“What we find is that these meetings tend to be associated with significant increase in firms’ stock prices,” says Huang. “We also find that these companies are able to secure more favorable regulatory access after the meetings.”

Cumulative abnormal returns in the days around corporate executives’ White House visits

The results show positive and statistically significant CARs for four timeframes checked by the authors. The results also indicate that the highest CARs, 2.749 percent, occurred following a 70-day window around a meeting with Obama’s top aides—slightly higher than following a meeting with Obama himself. Since the average market capitalization of the firms included in the study’s sample is about $36 billion, a 2.749 percent CAR is, on average, equivalent to an almost $1 billion increase in market capitalization.

Cumulative abnormal returns in the days around corporate executives’ White House visits by year from 2009 through 2015. Source: Brown and Huang (2017).

The excess returns are related to election cycles: The CARs were significantly positive during the 2012 general election year, the first years after a general election (2009 and 2013), as well as 2014 (Figure 2). These results indicate that access to influential government officials is particularly beneficial during those years.

Indeed, confounding factors may be present, but they were largely treated by Brown and Huang. For example, they exclude White House visits that are associated with the president’s advisory board meetings and excluded follow-up visits.

To address possible concerns about omitted variables that drive both the timing of corporate executives’ meetings with federal officials and stock returns, Brown and Huang used the election of Donald Trump as a shock, as up until the very last moment, his Democratic opponent, Hillary Clinton, was widely expected to win.

Therefore, if the basic notion of their theory is correct, we would expect shares of the companies that had access to the Obama White House to underperform as soon as the election results were announced. And, indeed, that is what they found: in all four models that they constructed—in which they checked the cumulative market-adjusted abnormal returns of these stocks from November 9, 2016, to November 11, 2016—the stocks of the companies that had access to Obama’s White House showed statistically significant underperformance in a range that runs between 80 basis points and 130 basis points.

A similar test of Republican administrations, says Huang, will likely yield similar results. “Before Donald Trump took office, he had a meeting with the CEO and founder of Alibaba, Jack Ma. Upon the release of the news that Trump was meeting with Jack Ma, Alibaba’s stock price increased by 1.5 percent, which is very much consistent with what we observe.”

The Trump administration could be worse in this respect than that of Obama. One reason is his policies so far. Another is that, just recently, the White House announced that it would no longer make its visitor logs available to the public. The White House is not obligated to make the logs public, but the move broke with Obama’s practice. The White House cited privacy and national security concerns. In fact, those issues were already addressed by the Obama White House by redacting visits that were tied to national security issues, other particularly sensitive issues, and private visits that were not related to the business of governing."

Government Can’t Even Plan for Its Own Survival

By David Boaz of Cato.

"Economists and (classical) liberals have long criticized the failures of government planning, from Hayek and Mises and John Jewkes to even Robert Heilbroner. Ron Bailey wrote about centralized scientific planning, Randal O’Toole about urban planning, Jim Dorn about the 1980s enthusiasm for industrial planning, and I noted the absurdities of green energy planning.

One concern about planning is that it will lead government to engage in favoritism and cronyism. So who would have guessed that when the leaders of the federal government set out to plan for their own survival—if no one else’s—in the event of nuclear attack, they failed?

That’s the story journalist and author Garrett Graff tells in his new book Raven Rock: The Story of the U.S. Government’s Secret Plan to Save Itself—While the Rest of Us Die. As the Wall Street Journal summarizes:

COG—continuity of government—is the acronymic idée fixe that has underpinned these doomsday preparations. A bunker was installed in the White House after Pearl Harbor, but the nuclear age (particularly after the Soviet Union successfully tested an atomic bomb in September 1949) introduced a nationwide system of protected hideaways, communications systems, evacuation procedures and much else of a sophistication and ingenuity—and expense—never before conceived….
Strategies for evacuating government VIPs began in earnest in the early 1950s with the construction of Raven Rock, an “alternate Pentagon” in Pennsylvania near what would become known as Camp David, and Mount Weather, a nuclear-war sanctuary in Virginia for civilian officials….
In 1959, construction began on a secret refuge for Congress underneath the Greenbrier, a resort in West Virginia. In the event of an attack, members of Congress would have been delivered by special train and housed in dormitories with nameplated bunk beds.
The most important COG-related activities during the Kennedy administration came during the Cuban Missile Crisis in October 1962, the closest this country has come to a nuclear war. Not only was the military mobilization chaotic—“one pilot bought fuel for his bomber with his personal credit card”—but VIP evacuation measures were, for the most part, a debacle: “In many cases, the plans for what would happen after [a nuclear attack on the U.S.] were so secret and so closely held that they were almost useless.” …
The Air Force also acquired, for the president’s use, four Boeing 747 “Doomsday planes” with state-of-the-art communications technology, which were nicknamed “Air Force One When It Counts.”…
Probably the most fraught 24 hours in the history of COG worrying occurred on Sept. 11, 2001, when al Qaeda terrorists attacked the World Trade Center and the Pentagon. COG projects and training had been ceaselessly initiated and honed for a half-century; but, as Mr. Graff writes with impressive understatement, “the U.S. government [wasn’t] prepared very well at all.”…
While Vice President Dick Cheney had been swiftly hustled to the White House bunker, “those officials outside the bunker, even high-ranking ones, had little sense of where to go, whom to call, or how to connect back to the government,” Mr. Graff writes. But there were enough people in the bunker to deplete the oxygen supply and raise the carbon-dioxide level, and so “nonessential staff” were ordered to leave. When House Speaker Dennis Hastert tried to call Mr. Cheney on a secure phone, he couldn’t get through….
When President George W. Bush heard the news about the attacks that morning, he was in Florida. He was whisked into Air Force One, which, Mr. Graff notes, “took off at 9:54 a.m., with no specific destination in mind.” It would eventually land, and the president would address the country. But “Air Force One’s limitations”—it wasn’t one of the Doomsday planes—“came into stark relief.” For one thing the plane’s communications systems were woefully inadequate for what was required on 9/11. “On the worst day in modern U. S. history,” Mr. Graff writes near the end of his exhaustingly detailed account (I sometimes felt buried alive under its mass of data), “the president of the United States was, unbelievably, often less informed than a normal civilian sitting at home watching cable news.”

Fifty years of planning for a single event, the most important task imaginable—the survival of the republic and their own personal survival—and top government officials still didn’t get it right. A good lesson to keep in mind when we contemplate having less-motivated government officials plan our cities, our energy production, our health care system, or our entire economy."

Stolper-Samuelson predicts that the wages in America that will disproportionately rise when trade becomes freer are chiefly those earned by middle-income workers

Here I Take a Minority Position on the Prediction of Stolper-Samuelson by Don Boudreaux. See also Clarification and Elaboration on Stolper-Samuelson.

Here’s a letter to the Wall Street Journal:

Reviewing Roger Backhouse’s biography of the economist Paul Samuelson, Eric Maskin writes that “The Stolper-Samuelson Theorem implies that international trade causes inequality between high-skilled and less-skilled workers to grow in rich countries.  The theorem was derived in 1941 but clearly remains relevant in today’s America of rising inequality” (“An Einstein of the Dismal Science,” May 20).

Not so fast.

When applied to labor, the Stolper-Samuelson Theorem predicts that the workers whose wages fall as a result of freer trade are (in econ jargon) the relatively more scarce factor of production – which, in America, is less-skilled workers – and that the workers whose wages rise are the relatively more abundant factor of production.  In plain language, while the workers in America whose wages are reduced by freer trade are indeed the lowest paid, they also are a minority of workers.  Freer trade raises the wages of those workers whose skill-levels are relatively most abundant.  Because the workers in America whose skill-levels are most abundant likely are those whose incomes are in or near the middle of the income distribution for workers, Stolper-Samuelson predicts that the wages in America that will disproportionately rise when trade becomes freer are chiefly those earned by middle-income workers.

Yet it is difficult to see how a change in the wages distribution with a disproportionate amount of the gains going to middle-income workers increases income inequality.

 Therefore, to the extent that the Stolper-Samuelson Theorem applies in reality, it tells us that whatever increase in income inequality has occurred over the past several decades is likely not due to the effect that freer trade has on the distribution of workers’ wages.
Sincerely,

Donald J. Boudreaux
Professor of Economics
and
Martha and Nelson Getchell Chair for the Study of Free Market Capitalism at the Mercatus Center
George Mason University
Fairfax, VA  22030

Note that in this letter I do not argue that income inequality has not increased in the United States.  Instead, I argue that whatever increase in income inequality there might have been in the U.S. is not as straightforwardly explained by – or even consistent with – the Stopler-Samuelson Theorem as many people today (such as Eric Maskin) presume."

Causation clearly runs from tight money to falling NGDP to financial distress

See Financial crisis or monetary policy failure? by Scott Sumner.

"I often debate the question of whether severe slumps are caused by financial crisis or tight money. In my view it's usually tight money, with financial stress being a symptom of falling NGDP. So how would we test my hypothesis?

While cleaning out my office at Bentley, I came across an old NYT article from June 11, 1933:

Wall Street notes a remarkable contrast between the attitude toward the war debt question last December and that of the present time. Last year, financial circles began to become apprehensive about the war debt question long before December 15. By late November the pound sterling had fallen to a record low of $3.14 1/2 and the financial markets were severely depressed. At the present time, although the war debts payments are due by next Thursday, there has been almost no discussion of the subject in financial circles, and the possibilities of wholesale default have left the markets unperturbed.

Why did the markets suddenly stop caring about the war debts issue in June 1933? For the same reason they suddenly started caring about the war debts issue in mid-1931. War debts disturbed the financial markets when they led to devaluation fears, which triggered massive gold hoarding. By June 1933, the US was off the gold standard, and hence gold hoarding no longer exerted a deflationary impact on the US. However, gold hoarding continued to be a problem for countries still on the gold standard, such as France. 

 

In my book entitled "The Midas Paradox", I did a very extensive empirical study of this question. The price of German war debt bonds suddenly become highly correlated with US stock indices in mid-1931 (when Germany got into financial trouble), and this continued through 1932. Fears of German default were triggering a loss of confidence in the international gold standard. That loss of confidence was justified, as Germany adopted exchange controls in July 1931 and the UK devalued in September 1931. At that point people started worrying about a US devaluation, and gold hoarding rose sharply.

Because the supply of newly mined gold doesn't change very much from year to year, big changes in the value of gold are primarily caused by shifts in gold demand. But once the US began devaluing the dollar in April 1933, increases in gold demand no longer had a significant deflationary impact on the US. Gold kept getting more valuable, but now the dollar was losing value. (Recall that price deflation means that money is getting more valuable.)

Back in 1932, the vast majority of serious people rejected my "tight money" explanation of the Depression. It was "obviously" caused by financial turmoil, both domestic and international. Falling NGDP was seen as a symptom. Only a few lonely exceptions like Irving Fisher and George Warren took a "market monetarist" perspective, urging a shift toward expansionary monetary policy. Because we were near the zero bound, they recommended a depreciation of the dollar against gold. In 1933, FDR adopted their suggestion, and it worked just as Warren and Fisher predicted---prices and output immediately began rising sharply. The policy would have been even more effective if not offset by the NIRA, which sharply reduced aggregate supply.

And there is lots more evidence for the tight money--->falling NGDP---> financial distress chain of causation. After the dollar started depreciating against gold in April 1933, domestic bank failures ceased almost immediately.

Some people claim that tight money did not cause the Great Recession, because there was no alternative monetary policy at the zero bound of interest rates. But something similar occurred in the 1980s, when we were not at the zero bound. Between 1934 and 1980, there was a period of calm in the banking system. Some people wrongly attribute that to regulation, but in fact it was caused by higher rates of inflation and NGDP growth during 1934-80, which made it easier for debts to be repaid. As soon as the Fed adopted a tight money policy in 1981, and NGDP growth began slowing sharply, we experienced a bout of bank failures (mostly S&Ls). The causation in this case clearly went from tight money to sharply slower NGDP growth to banking distress, as we were not even close to the zero lower bound on interest rates.


To summarize, the question of whether tight money or financial distress causes deep slumps might seem almost unsolvable, if you simply focus on the Great Recession. But those with a deep knowledge of economic history know that causation clearly runs from tight money to falling NGDP to financial distress. Unfortunately, economic history is no longer widely taught in our graduate programs, so we now have an entire generation of economists who are ignorant of this subject, and who keep developing business cycle models that are easily refuted by the historical record."

Subsidizing sports teams is a bad play

See What Prince William County can learn from the Oakland Raiders by Tyler Muench in The Washington Post. Tyler Muench is Northern Virginia director with Americans for Prosperity. Excerpts:

"Professional sports teams have been relocating to new cities when they fail to acquire public funding for stadiums. Last year, the Rams stuck St. Louis with a $144 million bill after the team decided to move to Los Angeles. And earlier this year, San Diego taxpayers were left with a $50 million tab after the Chargers joined the Rams in L.A.

This time around is no different. The Oakland Raiders’ move to Las Vegas will leave Oakland taxpayers stuck with a $163 million bill. Teams constantly ask taxpayers for handouts despite generating vast revenues. Billionaire owners get publicly financed stadiums and the working-class citizens pick up the tab — corporate welfare at its worst.

It’s understandable that cities want to attract professional sports teams. People of all ages love sports, and teams often define a community’s identity. But local governments can’t abandon all logic and principle to secure a team. That’s what Oakland did, and it didn’t work out.

The San Francisco Chronicle reports that the original $200 million bond that brought the Raiders to Oakland will cost $350 million. When asked about the bond, Oakland City Council President Larry Reid acknowledged it was a bad deal. “The projections were off, but everyone was just caught up in the emotions of having the Raiders return.”"

"Proponents of taxpayer-funded stadiums insist that stadiums are economic engines for communities and a wise investment for taxpayers. But economists from around the country disagree. A 2015 study from the Mercatus Center at George Mason University found these projects provide little to no economic benefit for their communities.

Economist Victor Matheson of Holy Cross was more to the point: “Whatever number the sports promoter says, take it and move the decimal one place to the left. Divide it by 10, and that’s a pretty good estimate of the actual economic impact.”"

Here are the key findings from the Mercatus study:

• Professional sports can have some impact on the economy. Looking at all the sports variables, including presence of franchises, arrival and departure of clubs in a metropolitan area, and stadium and arena construction, the study finds that the presence of a franchise is a statistically significant factor in explaining personal income per capita, wage and salary disbursements, and wages per job.
• But this impact tends to be negative. Individual coefficients, such as stadium or arena construction, sometimes have no impact, but frequently indicate harmful effects of sports on per capita income, wage and salary disbursements, and wages per job. When the effect of these coefficients appears to be positive, it is generally so small as to be insignificant.
• At most, sports account for less than 5 percent of the local economy. Though sports are often perceived as a major economic force, sports at most account for less than 5 percent of the local economy, with the majority of estimates putting that number under 1.5 percent. Simply stated, sports teams are not the star players in local economies.

How Banks Game The Community Reinvestment Act By Putting Branches In Neighborhoods That Only Look Low Income

See Never Mind the Ferrari Showroom, Bank Regulators Call This a Poor Neighborhood: Branches in business districts are given low-income designation by a quirk in federal law by Rachel Louise Ensign and AnnaMaria Andriotis of the WSJ. Banks need to pass a test that they are in compliance or they might not be allowed to engage in mergers. Excerpts:

"To any casual observer, the area just south of Trump Tower in Midtown Manhattan is obviously wealthy: The blocks are crowded with skyscrapers, and stores include Versace and Ferrari. Diners can pick at the foie gras and caviar on La Grenouille’s $172 prix-fixe dinner menu.

In the eyes of federal-bank regulations, though, that sliver of New York City is a poor neighborhood where median incomes are relatively low.

The anomaly has yielded a hidden benefit for banks such as J.P. Morgan Chase & Co. and Wells Fargo WFC 1.30% & Co. that have crowded branches into the area. Having robust branch representation in supposedly low-income areas gives them a better score on a key regulatory test that can help determine how fast they expand.

"Neighborhoods like the one in Midtown Manhattan could add a new dimension to the debate, even though branch analysis is only one part of regulators’ broader CRA evaluations. Its quirky treatment under the CRA is due to the fact that regulators who enforce the act rely on older, sometimes unreliable, Census Bureau data to determine an area’s income level.

New York isn’t an isolated example. Six of the 10 most popular poor areas for banks to have branches, including the Manhattan tract, are slated to lose that classification when more recent census data go into effect this year, according to regulators and data from fair-lending software company ComplianceTech. But bank regulators have been using the older data because they stick to a preset schedule of switching every five years.

In one of these census tracts, a “low income” area in downtown San Francisco, one of the most expensive cities in the country, 53 branches pack into an area that census data indicate has only 1,783 residents. That’s 52 more branches than the average poor district in the U.S. has, despite the fact the San Francisco tract has far fewer residents than average.

About 30 miles away in Menlo Park, Calif., a First Republic Bank branch on Facebook Inc.’s corporate campus is classified as lower income because the surrounding areas have lower incomes than the median of the broader area. But the only people with access to the branch are employees and guests of Facebook"

"Then there is Manhattan’s census tract 102, the bustling Midtown blocks with the most lower-income bank branches per capita in the U.S., according to a Wall Street Journal analysis of data from ComplianceTech’s LendingPatterns.com. Due to a paucity of residential buildings in the area, the district bordered by Park and Fifth avenues, 49th and 56th streets has only 230 residents, or about 10 for each of the 22 bank branches that call the tract home, according to the census data used by banking regulators."

"But the areas often have few residential buildings, one reason that can explain the lower-income CRA designation. The fact that banks get credit for branches in these areas, though, has prompted some criticism.

“Banks can conform to the letter of the law, but not meet the purpose of CRA,” says John Vogel, an adjunct professor at Dartmouth’s Tuck School of Business. This is especially the case, he says, in the classification of “low- and moderate-income neighborhoods.”"