Jesse M. Shapiro

Bio: Jesse M. Shapiro is an academic researcher from National Bureau of Economic Research. The author has contributed to research in topics: Newspaper & Consumption (economics). The author has an hindex of 47, co-authored 122 publications receiving 12471 citations. Previous affiliations of Jesse M. Shapiro include University of Chicago & Brown University.

Why Have Americans Become More Obese

Abstract: In the early 1960s, the average American adult male weighed 168 pounds. Today, he weighs nearly 180 pounds. Over the same time period, the average female adult weight rose from 143 pounds to over 155 pounds (U.S. Department of Health and Human Services, 1977, 1996). In the early 1970s, 14 percent of the population was classified as medically obese. Today, obesity rates are two times higher (Centers for Disease Control, 2003). Weights have been rising in the United States throughout the twentieth century, but the rise in obesity since 1980 is fundamentally different from past changes. For most of the twentieth century, weights were below levels recommended for maximum longevity (Fogel, 1994), and the increase in weight represented an increase in health, not a decrease. Today, Americans are fatter than medical science recommends, and weights are still increasing. While many other countries have experienced significant increases in obesity, no other developed country is quite as heavy as the United States. What explains this growth in obesity? Why is obesity higher in the United States than in any other developed country? The available evidence suggests that calories expended have not changed significantly since 1980, while calories consumed have risen markedly. But these facts just push the puzzle back a step: why has there been an increase in calories consumed? We propose a theory based on the division of labor in food preparation. In the 1960s, the bulk of food preparation was done by families that cooked their own food and ate it at home. Since then, there has been a revolution in the mass preparation of food that is roughly comparable to the mass

Smart Cities: Quality of Life, Productivity, and the Growth Effects of Human Capital

Abstract: From 1940 to 1990, a 10 percent increase in a metropolitan area's concentration of college-educated residents was associated with a .8 percent increase in subsequent employment growth. Instrumental variables estimates support a causal relationship between college graduates and employment growth, but show no evidence of an effect of high school graduates. Using data on growth in wages, rents and house values, I calibrate a neoclassical city growth model and find that roughly 60 percent of the employment growth effect of college graduates is due to enhanced productivity growth, the rest being caused by growth in the quality of life. This finding contrasts with the common argument that human capital generates employment growth in urban areas solely through changes in productivity.

Media Bias and Reputation

Abstract: A Bayesian consumer who is uncertain about the quality of an information source will infer that the source is of higher quality when its reports conform to the consumer's prior expectations. We use this fact to build a model of media bias in which firms slant their reports toward the prior beliefs of their customers in order to build a reputation for quality. Bias emerges in our model even though it can make all market participants worse off. The model predicts that bias will be less severe when consumers receive independent evidence on the true state of the world, and that competition between independently owned news outlets can reduce bias. We present a variety of empirical evidence consistent with these predictions.

Smart Cities: Quality of Life, Productivity, and the Growth Effects of Human Capital

Abstract: From 1940 to 1990, a 10% increase in a metropolitan area's concentration of college-educated residents was associated with a 0.8% increase in subsequent employment growth. Instrumental variables esti- mates support a causal relationship between college graduates and em- ployment growth, but show no evidence of an effect of high school graduates. Using data on growth in wages, rents, and house values, I calibrate a neoclassical city growth model and find that roughly 60% of the employment growth effect of college graduates is due to enhanced productivity growth, the rest being caused by growth in the quality of life. This finding contrasts with the common argument that human capital generates employment growth in urban areas solely through changes in productivity.

Ideological Segregation Online and Offline

Abstract: We use individual and aggregate data to ask how the Internet is changing the ideological segregation of the American electorate. Focusing on online news consumption, offline news consumption, and face-to-face social interactions, we define ideological segregation in each domain using standard indices from the literature on racial segregation. We find that ideological segregation of online news consumption is low in absolute terms, higher than the segregation of most offline news consumption, and significan tly lower than the segregation of face-to-face interactions with neighbors, co-workers, or family members. We find no evidence that the Internet is becoming more segregated over time.

Time Discounting and Time Preference: A Critical Review

Abstract: This paper discusses the discounted utility (DU) model: its historical development, underlying assumptions, and "anomalies" - the empirical regularities that are inconsistent with its theoretical predictions. We then summarize the alternate theoretical formulations that have been advanced to address these anomalies. We also review three decades of empirical research on intertemporal choice, and discuss reasons for the spectacular variation in implicit discount rates across studies. Throughout the paper, we stress the importance of distinguishing time preference, per se, from many other considerations that also influence intertemporal choices.

The Spread of Obesity in a Large Social Network over 32 Years

Abstract: Background The prevalence of obesity has increased substantially over the past 30 years. We performed a quantitative analysis of the nature and extent of the person-to-person spread of obesity as a possible factor contributing to the obesity epidemic. Methods We evaluated a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. The bodymass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings, spouse, and neighbors. Results Discernible clusters of obese persons (body-mass index [the weight in kilograms divided by the square of the height in meters], ≥30) were present in the network at all time points, and the clusters extended to three degrees of separation. These clusters did not appear to be solely attributable to the selective formation of social ties among obese persons. A person’s chances of becoming obese increased by 57% (95% confidence interval [CI], 6 to 123) if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% (95% CI, 21 to 60). If one spouse became obese, the likelihood that the other spouse would become obese increased by 37% (95% CI, 7 to 73). These effects were not seen among neighbors in the immediate geographic location. Persons of the same sex had relatively greater influence on each other than those of the opposite sex. The spread of smoking cessation did not account for the spread of obesity in the network. Conclusions Network phenomena appear to be relevant to the biologic and behavioral trait of obesity, and obesity appears to spread through social ties. These findings have implications for clinical and public health interventions.

Measuring Economic Policy Uncertainty

Abstract: We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency Several types of evidence – including human readings of 12,000 newspaper articles – indicate that our index proxies for movements in policy-related economic uncertainty Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s