Equity Volatility and Corporate Bond Yields

This paper explores the effect of equity volatility on corporate bond yields. Panel data for the late 1990's show that idiosyncratic firm-level volatility can explain as much cross-sectional variation in yields as can credit ratings. This finding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001), helps to explain recent increases in corporate bond yields.

Equity Volatility and Corporate Bond Yields

This paper explores the effect of equity volatility on corporate bond yields. Panel data for the late 1990's show that idiosyncratic firm-level volatility can explain as much cross-sectional variation in yields as can credit ratings. This finding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001), helps to explain recent increases in corporate bond yields.

Equity volatility and corporate bond yields

This paper explores the e¡ect of equity volatility on corporate bond yields. Panel data for the late 1990s show that idiosyncratic ¢rm-level volatility can explain as much cross-sectional variation in yields as can credit ratings. This ¢nding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001), helps to explain recent increases in corporate bond yields. DURING THE LATE 1990s, THE U.S. EQUITY and corporate bond markets behaved very di¡erently. As displayed in Figure 1, stock prices rose strongly, while at the same time, corporate bonds performed poorly. The proximate cause of the low returns on corporate bonds was a tendency for the yields on both seasoned and newly issued corporate bonds to increase relative to the yields of U.S.Treasury securities. These increases in corporate^Treasury yield spreads are striking because they occurred at a time when stock prices were rising; the optimism of stock market investors did not seem to be shared by investors in the corporate bond market

calories purchased

Background: Studies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation. Findings: Researchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories. Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216–409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p = 0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by>100 calories was 0.90 (p = 0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR = 0.25, p < 0.001) and for individuals ordering small meals (AOR = 0.54, p = 0.001). Accuracy worsened for females (AOR = 1.38, p < 0.001) and for individuals ordering large meals (AOR = 1.27, p = 0.028). Conclusions: We concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information

Vitamin D deficiency in minority populations

Objective Black and Hispanic individuals synthesize less vitamin D per unit of sun exposure than white individuals. The relationship between UV radiation and vitamin D insufficiency in minorities has not been well explored. Design Prospective cohort study. Setting Using the National Health and Nutrition Examination Survey, we obtained serum vitamin D levels for non-Hispanic Whites, Hispanics and non-Hispanic Blacks aged ≥18 years from 2000–2006. We linked these data with the average monthly solar UV index by census tract and data on sun exposure, vitamin D supplementation, health and demographics. We used multivariable regression analyses to assess vitamin D deficiency (<15 ng/ml) and insufficiency (<20 ng/ml) in January (when the UV index was lowest) by race/ethnicity and geography. Subjects Adults (n 14 319) aged ≥18 years. Results A 1-point increase in the UV index was associated with a 0·51 ng/ml increase in vitamin D (95 % CI 0·35, 0·67 ng/ml; P<0·001). Non-Hispanic Black race and Hispanic ethnicity were associated with a 7·47 and 3·41 ng/ml decrease in vitamin D, respectively (both P<0·001). In January, an estimated 65·4 % of non-Hispanic Blacks were deficient in vitamin D, compared with 28·9 % of Hispanics and 14·0 % of non-Hispanic Whites. An estimated 84·2 % of non-Hispanic Blacks were insufficient in vitamin D v. 56·3 % of Hispanics and 34·8 % of non-Hispanic Whites. More non-Hispanic Blacks were estimated to be deficient in vitamin D in January in the highest UV index quartile than were non-Hispanic Whites in the lowest UV index quartile (60·2 % v. 25·7 %). Conclusions Wintertime vitamin D insufficiency is pervasive among minority populations, and not uncommon among non-Hispanic Whites.Economic

An Alternative Mathematical Modeling Approach to Estimating a Reference Life Expectancy

Background. Reference life expectancies inform frequently used health metrics, which play an integral role in determining resource allocation and health policy decision making. Existing reference life expectancies are not able to account for variation in geographies, populations, and disease states. Using a computer simulation, we developed a reference life expectancy estimation that considers competing causes of mortality, and is tailored to population characteristics. Methods. We developed a Monte Carlo microsimulation model that explicitly represented the top causes of US mortality in 2014 and the risk factors associated with their onset. The microsimulation follows a birth cohort of hypothetical individuals resembling the population of the United States. To estimate a reference life expectancy, we compared current circumstances with an idealized scenario in which all modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect. We compared estimations of years of potential years life lost with alternative approaches. Results. In the idealized scenario, we estimated that overall life expectancy in the United States would increase by 5.9 years to 84.7 years. Life expectancy for men would increase from 76.4 years to 82.5 years, and life expectancy for women would increase from 81.3 years to 86.8 years. Using age-75 truncation to estimate potential years life lost compared to using the idealized life expectancy underestimated potential health gains overall (38%), disproportionately underestimated potential health gains for women (by 70%) compared to men (by 40%), and disproportionately underestimated the importance of heart disease for white women and black men. Conclusion. Mathematical simulations can be used to estimate an idealized reference life expectancy among a population to better inform and assess progress toward targets to improve population health