Every Monday, the National Bureau of Economic Research, a nonprofit organization made up of some of North America’s most respected economists, releases its latest batch of working papers. The papers aren’t peer-reviewed, so their conclusions are preliminary (and occasionally flat-out wrong), but they offer an early peek into some of the research that will shape economic thinking in the years ahead. Here are a few of this week’s most interesting papers.
Authors: Austan D. Goolsbee, Alan B. Krueger
What they found: Had the U.S. government not bailed out two of the Big Three automakers in 2009, the Great Recession would have been deeper and longer, and the automobile industry might have collapsed.
Why it matters: This paper assesses whether the 2009 bailout of General Motors and Chrysler was necessary and wise. The two economists behind this paper [which has a free version], Austan Goolsbee and Alan Krueger, both served in President Obama’s administration when the bailouts occurred. While they argue (unsurprising) that, overall, the auto bailouts were good decisions given the circumstances, their defense is worth reading. Saving Chrysler was questionable — it was far smaller than GM, and so the economic repercussions of its bankruptcy were, too. But the failure of GM would have triggered a cascade of bankruptcies of auto suppliers, as well as possibly have taken Ford down with it. While the authors are skeptical of some contemporary estimates that put potential job losses as high as 2.5 million to 3.3 million, they estimate at least 500,000 to 1 million jobs would have been lost without the bailout of GM. By December 2013, the government had fully exited its investments in GM and Chrysler and had received back about $70 billion of the initial $80 billion it invested. The companies were radically restructured and turning a profit. Since bottoming-out, employment in the auto industry is up by more 250,000 jobs.
Key quote: “Later, during the presidential election of 2012, critics of the rescue argued that private lenders should have been allowed to fund the GM and Chrysler restructurings in bankruptcy. In early 2009, however, such funding simply did not exist. At that moment, for better or for worse, it was government money or bust. Without government funds, GM and Chrysler were on a path to disorderly bankruptcy which would, by all accounts, take years to resolve the myriad disputes among thousands of creditors, suppliers, and so on, and likely meant liquidation.”
Data they used: Auto sales data from Automotive News; JD Power quality ratings.
Author: David C. Chan, Jr.
What he found: Emergency department physicians who take on new patients near the end of their shifts spend less time with them on average and are more likely to admit them for costly inpatient treatment. Patient-care costs rise by 21 percent in the last hour of a doctor’s shift.
Why it matters: A trove of economic research has examined how to make workers more productive — through financial incentives, better monitoring or social changes in the workplace (e.g. working from home). But the time schedule of work is often an overlooked component of boosting worker productivity. How workers’ shifts are staggered can have a huge impact on their performance. Emergency department (ED) physicians work long hours and have very little incentive to stay past their shifts. As a result, these doctors are less likely to accept new patients in the end-of-shift (EOS) zone; from the doctor’s perspective, the patient can be seen by another doctor, or she can wait until the next shift’s doctor starts. When ED doctors do take patients in their EOS zone, their behavior changes: They take down less information to pass on to the next doctor, and are more likely to admit patients for inpatient treatment. The researcher controlled for the length of the shift and found these changes were not the result of fatigue. But they do lead to higher costs: about 21 percent higher when a patient is seen in the last hour of a doctor’s shift.
Key quote: “Although scheduled availability begins and ends at set times, the true nature of work usually blurs across these constructed boundaries. … Workers who are nominally on duty are thus subject to behavioral incentives that may distort their acceptance and performance of work.”
Data he used: 442,244 patient visits from a “large, academic, tertiary-care” emergency department over the period from June 2005 to December 2012, totaling 23,990 shifts in 35 different shift types.
Authors: Lawrence Jin, Donald S. Kenkel, Feng Liu, Hua Wang
What they found: Anti-smoking policies from 1964 to 2010 reduced cigarette consumption by 28 percent, and the benefits were estimated to be $573 billion (in 2010 dollars), or about 12 percent of the GDP in 1964. A simulation of prospective anti-smoking FDA regulations registered benefits of about $100 billion.
Why it matters: Smoking kills an estimated 400,000 people in the U.S. each year, and is the leading cause of preventable death. While the decline in smoking since the 1950s has been hailed as an enormous public health achievement, 20 percent of American adults still smoke. The authors of this paper used a benefit-cost analysis (BCA) to retrospectively evaluate the Food and Drug Administration’s anti-smoking regulations since 1964 and found the benefits clearly outweighed the costs. They tweaked their analysis to incorporate what the field of behavioral economics calls “nudges” — slight psychological incentives, like requiring restaurants to post calorie counts as a way to encourage healthier eating. A recent law, the 2009 Family Smoking Prevention and Tobacco Control Act, empowered the FDA to introduce some anti-smoking nudges. It requires the FDA to enact graphic warning labels on cigarette packages aimed at preventing youth from starting to smoke. And it would allow the FDA to ban menthol in cigarettes, as well as to reduce their nicotine content. The authors of this paper calculate the prospective benefits of future anti-smoking regulations — both through these nudges and standard mass media campaigns — to be around $100 billion.
Key quote: “Like any BCA, our analysis involves a number of simplifying assumptions and faces data limitations. … Some key simplifying assumptions mean that the counterfactual simulations probably overstate the impact of the anti-smoking policies in both the retrospective and prospective analyses. Our estimates might be seen as upper bounds of the consumer benefits from the policies. … Despite these limitations, we believe our analysis provides a useful worked example of behavioral BCA of a major area of public health policy.”
Data they used: Population data and birth-rate projections from the census; estimates of mortality rates by smoking status from various public health literature; sex-specific birth cohort smoking initiation rates from the Tobacco Use Supplements to the Current Population Survey.