Knowledge that Transforms

Murphy and Topel (2006, henceforth MT) develop methods for valuing health improvements based on individuals’ willingness to pay. Our results indicate that past health improvements have been enormously valuable. We estimate that gains in life expectancy over the twentieth century were worth more than $1.2 million per person to the current US population, and that rising longevity added about $3.2 trillion per year to national wealth between 1970 and 2000, as mortality rates among older adults fell sharply. Looking ahead, we estimate that even modest progress against major lifethreatening diseases would be extremely valuable. For example, the two most prominent causes of disease-related mortality in the United States are cardiovascular diseases (CVD) and cancer. We find that a permanent 10 percent reduction in mortality rates from CVD would be worth about $5.7 trillion to current and future Americans, while similar progress against cancer would be worth $4.7 trillion. A 10 percent reduction in overall mortality would be worth about $18 trillion. If past progress is an indication, there is little doubt that these or greater gains will eventually be realized. The questions are when and at what cost? In comparison to these prospective benefits of health progress, expenditures on basic and applied health research in the United States are modest. Public support for basic biomedical research—mainly through the National Institutes of Health (NIH) and associated grants to research universities—totals about $28 billion annually. Adding expenditures on health research and development (R&D) by private institutions and by pharmaceutical and medical products companies brings the total for basic and applied health research to about $60 billion Social Value and the Speed of Innovation

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Twenty-seven percent of the Union Army prisoners captured July 1863 or later died in captivity. At Andersonville, the death rate may have been as high as 40 percent. How did men survive such horrific conditions? Using two independent datasets, we find that friends had a statistically significant positive effect on survival probabilities and that the closer the ties between friends as measured by such identifiers as ethnicity, kinship, and the same hometown, the bigger was the impact of friends on survival probabilities.

Public Education Expenditures, Taxation, and Growth: Linking Data to Theory by William F. Blankenau, Nicole B. Simpson and Marc Tomljanovich. Published in volume 97, issue 2, pages 393-397 of American Economic Review, May 2007

Effects of Environmental and Land Use Regulation in the Oil and Gas Industry Using the Wyoming Checkerboard as a Natural Experiment: Retraction by Shelby Gerking and William E. Morgan. Published in volume 97, issue 3, pages 1032 of American Economic Review, June 2007

Among the thirteen original colonies, Pennsylvania was most successful at issuing paper money with only minimal effects on prices --so much so that the colony's experience is sometimes seen as violating the classical quantity theory of money. Quantity theorists usually attribute this apparent anomaly to mismeasurement of the money stock. In contrast, I use data on money, prices, and real activity in Pennsylvania from 1723 to 1774 and for the United States as a whole from 1790 to 1850 (when the money stock is better measured) to show that the long-run behavior of money and prices is well explained by the quantity theory in both periods, despite the differences in institutional arrangements, once growth in monetized transactions is taken into account.

How do investors respond to predictable shifts in profitability? We consider how demographic shifts affect profits and returns across industries. Cohort size fluctuations produce forecastable demand changes for age-sensitive sectors, such as toys, bicycles, beer, life insurance, and nursing homes. These demand changes are predictable once a specific cohort is born. We use lagged consumption and demographic data to forecast future consumption demand growth induced by changes in age structure. We find that demand forecasts predict profitability by industry. Moreover, forecast demand changes five to ten years in the future predict annual industry stock returns. One additional percentage point of annualized demand growth due to demographics predicts a 5 to 10 percentage point increase in annual abnormal industry stock returns. However, forecasted demand changes over shorter horizons do not predict stock returns. A trading strategy exploiting demographic information earns an annualized risk-adjusted return of approximately 6 percent. We present a model of inattention to information about the distant future that is consistent with the findings. We also discuss alternative explanations, including omitted risk-based factors.

Why Do Poor Children Lose Health Insurance in the SCHIP Era? The Role of Family Health by Anne Carroll, Hope Corman, Kelly Noonan and Nancy E. Reichman. Published in volume 97, issue 2, pages 398-401 of American Economic Review, May 2007

Following the recently dismissed antitrust lawsuit against the National Residency Matching Program (NRMP), Jeremy Bulow and Jonathan Levin (2006) propose a simple matching model in which firms set impersonal salaries simultaneously before matching with workers, which leads to lower aggregate wages than any competitive outcome. I model a feature of the NRMP, ordered contracts, that allows firms to set several contracts while determining the order in which they try to fill them, which has different properties than standard models with multiple contracts. Furthermore, the low wages of Bulow and Levin are no longer an equilibrium, but competitive wages are.

We develop a simple macroeconomic model of credit market imperfections with heterogeneous investment projects. The projects differ in productivity, the investment requirement, and the severity of agency problems behind the borrowing constraints. A movement in borrower net worth shifts the composition of the credit between projects with different productivity levels, thereby causing endogenous investment-specific technological change. Furthermore, such endogenous technological change in turn affects borrower net worth. These composition effects could give rise to credit traps, credit collapse, leapfrogging, credit cycles, and growth miracles in the dynamics of the aggregate investment and borrower net worth.