The Rust Belt Is Right to Blame Obama | Wall Street Journal | 12.18.2016

Donald Trump hasn’t wasted time moving to revive America’s economic growth, with an emphasis on manufacturing. Critics may say the recent Carrier deal, which will save 800 American jobs, is small potatoes, but Mr. Trump’s pledge to reduce regulation is decidedly not. A new analysis confirms that the average industry’s regulatory risk has increased nearly 80% from 2010—and that this burden particularly hurts manufacturing and heavy industry.

The analysis was developed by a small group of quantitative hotshots under the guidance of Alex Vogel, an old Washington hand, and Jeff Hood, a 30-year finance veteran. Instead of considering the question of regulatory risk like D.C. think tankers, they approached it like Wall Street analysts.

Their most inventive technique involved natural-language processing, an essential tool of the big-data era that has been used to analyze Shakespeare and fight spam email. Messrs. Vogel and Hood used the technology to analyze the language in the 10K reports that companies file with the Securities and Exchange Commission.

Every 10K report includes a formal assessment of the company’s vulnerabilities. Messrs. Vogel and Hood flagged any words and phrases that signaled regulatory exposure. They included general terms like “regulation” and “Congress” as well as specific ones like “fraud,” “inversions” and “Dodd-Frank.” They did something similar with the Federal Register to capture economically significant rule-making.

Then, firing up a suite of algorithms and formulas, they generated a regulatory-risk score for every company in the Fortune 500. Hedge funds are using the findings to gauge how potential investments could be affected by new regulations, court filings and other breaking events.

But the news here is in the next steps. The Vogel and Hood team analyzed corporate lobbying and turned out company-by-company ratings of its effectiveness. They put into the calculations the amounts that firms spend on government relations, the size of government-relations staffs, the expertise of the outside lobbyists hired, and the number of lobbying registration reports filed. Each company can then be ranked in the hierarchy of Washington influence.

Messrs. Vogel and Hood say their method is like a capital asset pricing model with one exception: In place of the standard measure for market risk, they substituted their metrics for regulatory risk and corporate response. What were the results?

First, and no surprise here: From 2010-15 regulatory risk jumped—an average increase across all industries of 79%.

Second, and more surprising: As regulatory risk climbed, annual capital expenditures fell, a total drop of nearly $32 billion when comparing 2010 to 2015. This negative relationship was strong across the board, but it was statistically tightest for “industrials” (heavy manufacturing plus railroads and airlines).

Third, as regulatory risks grew and capital expenditures shrank, major corporations also cut jobs by more than 1.1 million. Among the biggest losers were heavy manufacturing, airlines, railroads, information technology and consumer products—America’s industrial core.

Fourth, while the business of making things and moving them to market was eroding, the value of gaming the government increased. The Vogel and Hood team constructed two trial portfolios composed solely of companies that ranked high in lobbying strength. From 2010-16 these portfolios outperformed the S&P 500 by 22% and 27%.

In other words, Trump voters were right to see the Obama administration and its designated heir, Hillary Clinton, as hostile to industry. That makes what happened on Nov. 8 less of a mystery. Under Mrs. Clinton, regulatory risk would have only increased further. Mr. Trump pledged to reverse course. Voters in manufacturing and agricultural states heard both messages loud and clear.