Abstract:

We consider the causes of international capital flows. Since capital flows are extremely persistent, we argue that their drivers must be persistent, too. We think the most compelling candidates are demographic trends, tfp differences and financial frictions. In this paper we focus primarily on the role of demography in a multi-country overlapping generations model in which saving decisions are tied to agents’ life expectancy. Capital flows reflect differences between saving and investment across countries. Demographic changes affect the aggregate accumulation of assets in two ways: by changing life expectancy which changes individual household saving behavior, and by changing the age distribution of the population by which individual household decisions are aggregated. The most important drivers turn out to be increases in life expectancy caused by decreases in adult mortality.We use a quantitative version of the model to illustrate the impact of demography on capital flows and net foreign assets in China, Germany, Japan, and the United States.

www.nber.org/papers/w19465

www.ons.gov.uk/ons/rel/disability-and-health-measurement/healthy-life-expectancy-at-birth-for-upper-tier-local-authorities–england/2009-11/stb-hle–at-birth-for-upper-tier-local-authorities–england-2009-11.html

www.ons.gov.uk/ons/rel/subnational-health4/life-expectancy-at-birth-and-at-age-65-by-local-areas-in-england-and-wales/2009-11/stb.html

www.cdhowe.org/the-main-challenge-of-our-times-a-population-growing-younger/22311

www.cdc.gov/nchs/data/databriefs/db125.htm

HTML:

www.cdc.gov/mmwr/preview/mmwrhtml/mm6228a1.htm

PDF (full issue):

www.cdc.gov/mmwr/pdf/wk/mm6228.pdf

www.prb.org/Articles/2013/us-hispanics-life-expectancy.aspx

www.ssc.wisc.edu/cde/cdewp/2013-07.pdf

www.prb.org/Reports/2013/life-expectancy-blacks-hispanics.aspx

www.cdc.gov/nchs/hus.htm

B. “United States Life Tables Eliminating Certain Causes of Death, 1999-2001,” by Elizabeth Arias, Melonie Heron, and Betzaida Tejada-Vera (National Vital Statistics Reports, Vol. 61, No. 9, May 2013, .pdf format, 128p.).

www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_09.pdf

www.demographic-research.org/volumes/vol28/26/

www.ons.gov.uk/ons/rel/lifetables/interim-life-tables/2009-2011/stb-2009-2011.html

www.demographic-research.org/volumes/vol28/9/

cbe.anu.edu.au/research-papers/dpcepr/harsh-occupations,-life-expectancy-and-social-security/

www.nap.edu/catalog.php?record_id=13497

A. “Age-specific and sex-specific mortality in 187 countries, 1970-2010: a systematic analysis for the Global Burden of Disease Study 2010,” by Haidong Wang, Laura Dwyer-Lindgren, Katherine T. Lofgren, Julie Knoll Rajaratnam, Jacob R. Marcus, Alison Levin-Rector, Carly E. Levitz, Alan D. Lopez, and Christopher J.L. Murray (Vol. 380, No. 9859, December 15, 2012, p. 2071-2094).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961728-0/abstract

B. “Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010,” by Rafael Lozano, Mohsen Naghavi, Kyle Foreman, et al. (Vol. 380, No. 9859, December 15, 2012, p. 2095-2128).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961728-0/abstract

C. “Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010,” by Joshua A. Salomon, Theo Vos, Daniel R. Hogan, Michael Gagnon, Mohsen Naghavi, Ali Mokdad, Nazma Begum, Razibuzzaman Shah, et al. (Vol. 380, No. 9859, December 15, 2012, p. 2129-2143).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961680-8/abstract

D. “Healthy life expectancy for 187 countries, 1990-2010: a systematic analysis for the Global Burden Disease Study 2010,” by Joshua A. Salomon, Haidong Wang, Michael K. Freeman, Theo Vos, Abraham D. Flaxman, Alan D. Lopez, and Christopher J.L. Murray (Vol. 380, No. 9859, December 15, 2012, p. 2144-2162).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961690-0/abstract

E. “Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010,” by Theo Vos, Abraham D. Flaxman, Mohsen Naghavi, Rafael Lozano, Catherine Michaud, Majid Ezzati, Kenji Shibuya, Joshua A. Salomon, Safa Abdalla, et al. (Vol. 380, No. 9859, December 15, 2012, p. 2163-2196).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961729-2/abstract

F. “Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010,” by Christopher J. L. Murray, Theo Vos, Rafael Lozano, Mohsen Naghavi, Abraham D. Flaxman, Catherine Michaud, Majid Ezzati, Kenji Shibuya, Joshua A. Salomon, et al. (Vol. 380, No. 9859, December 15, 2012, p. 2197-2223).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961689-4/abstract

G. “A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010,” by Stephen S. Lim, Theo Vos, Abraham D. Flaxman, Goodarz Danaei, Kenji Shibuya, Heather Adair-Rohani, Markus Amann, H. Ross Anderson, Kathryn G. Andrews, et al. (Vol. 380, No. 9859, December 15, 2012, p. 2224-2260).

www.thelancet.com/journals/lancet/article/PIIS0140-6736%2812%2961766-8/abstract

Abstract:

We investigate the effect of the vintage (year of FDA approval) of the prescription drugs used by an individual on his or her survival and medical expenditure. When we only control for age, sex, and interview year, we estimate that a one-year increase in drug vintage increases life expectancy by 0.52%. Controlling for other variables including activity limitations, race, education, family income as a percent of the poverty line, insurance coverage, Census region, BMI, smoking and over 100 medical conditions has virtually no effect on the estimate of the effect of drug vintage on life expectancy.

Between 1996 and 2003, the mean vintage of prescription drugs increased by 6.6 years. This is estimated to have increased life expectancy of elderly Americans by 0.41-0.47 years. This suggests that not less than two-thirds of the 0.6-year increase in the life expectancy of elderly Americans during 1996-2003 was due to the increase in drug vintage. The 1996-2003 increase in drug vintage is also estimated to have increased annual drug expenditure per elderly American by $207, and annual total medical expenditure per elderly American by $218. This implies that the incremental cost-effectiveness ratio (cost per life-year gained) of pharmaceutical innovation was about $12,900

papers.nber.org/papers/w18552

B. “The Asset Price Meltdown and the Wealth of the Middle Class,” by Edward N. Wolff (w18559, November 2012, .pdf format, 74p.).

Abstract:

I find that median wealth plummeted over the years 2007 to 2010, and by 2010 was at its lowest level since 1969. The inequality of net worth, after almost two decades of little movement, was up sharply from 2007 to 2010. Relative indebtedness continued to expand from 2007 to 2010, particularly for the middle class, though the proximate causes were declining net worth and income rather than an increase in absolute indebtedness. In fact, the average debt of the middle class actually fell in real terms by 25 percent. The sharp fall in median wealth and the rise in inequality in the late 2000s are traceable to the high leverage of middle class families in 2007 and the high share of homes in their portfolio. The racial and ethnic disparity in wealth holdings, after remaining more or less stable from 1983 to 2007, widened considerably between 2007 and 2010. Hispanics, in particular, got hammered by the Great Recession in terms of net worth and net equity in their homes. Households under age 45 also got pummeled by the Great Recession, as their relative and absolute wealth declined sharply from 2007 to 2010.

papers.nber.org/papers/w18559

www.aihw.gov.au/publication-detail/?id=60129542187

www.demographic-research.org/Volumes/Vol27/21/default.htm

aje.oxfordjournals.org/content/176/10?etoc

B. American Journal of Public Health (Vol. 102, No. 12, December 2012).

ajph.aphapublications.org/toc/ajph/102/12

www.nih.gov/news/health/nov2012/nci-06.htm

www.oenb.at/en/presse_pub/research/020_workingpapers/_2012/working_paper_179.jsp

www.demographic-research.org/volumes/vol27/20/

www.stat.fi/til/vaenn/2012/vaenn_2012_2012-09-28_tie_001_en.html

www.bmj.com/content/345/bmj.e5568

B. “Mortality and implant revision rates of hip arthroplasty in patients with osteoarthritis: registry based cohort study,” by D. J. W. McMinn, K. I. E. Snell, J. Daniel, R. B. C. Treacy, P. B. Pynsent, and R. D. Riley ( BMJ 2012;344:e3319, HTML and .pdf format).

www.bmj.com/content/344/bmj.e3319

Abstract:

We develop a new methodology to compute differences in the expected longevity of individuals who are in different socioeconomic groups at age 50. We deal with the two main problems associated with the standard use of life expectancy: that people’s socioeconomic characteristics evolve over time and that there is a time trend that reduces mortality over time. Using HRS data for individuals from different cohorts, we estimate a hazard model for survival with time-varying stochastic endogenous covariates that yields the desired expected durations. We uncover an enormous amount of heterogeneity in expected longevities between individuals in different socioeconomic groups, albeit less than implied by a naive (static) use of socioeconomic characteristics. Our analysis allows us to decompose the longevity differentials into differences in health at age 50, differences in mortality conditional on health, and differences in the evolution of health with age. Remarkably, it is the latter that is the most important for most socioeconomic characteristics. For instance, education and wealth are health protecting but have little impact on two-year mortality rates conditional on health. Finally, we document an increasing time trend of all these differentials in the period 1992-2008, and a likely increase in the socioeconomic gradient in mortality rates in the near future. The mortality differences that we find have huge welfare implications that dwarf the differences in consumption accruing to people in different socioeconomic groups.

www.cemfi.es/ftp/wp/1210.pdf

Abstract:

Based on subjective survival probability questions in the Health and Retirement Study, we use an econometric model to estimate the determinants of individual-level uncertainty about personal longevity. This model is built around the Modal Response Hypothesis (MRH), a mathematical expression of the idea that survey responses of 0, 50 or 100 percent to probability questions indicate a high level of uncertainty about the relevant probability. We show that subjective survival expectations in 2002 line up very well with realized mortality of the HRS respondents between 2002 and 2010. We show that the MRH model performs better than typically used models in the literature of subjective probabilities. Our model gives more accurate estimates of low probability events and it is able to predict the unusually high fraction of focal 0, 50 and 100 answers observed in many datasets on subjective probabilities.

papers.nber.org/papers/w18258

www.statcan.gc.ca/pub/84f0211x/84f0211x2009000-eng.htm

www.cesifo-group.de/portal/page/portal/ifoHome/b-publ/b3publwp/_wp_abstract?p_file_id=18890599&category=

www.aihw.gov.au/publication-detail/?id=10737422286

Abstract:

This paper discusses a new pattern of mortality model which is built on the form and knowledge of the two-factor mortality model named after its designers Cairns, Blake and Dowd (2006). This model – the CBD model – is widely used and has been extended by the authors in a number of ways, including by the use of a cohort effect. In this paper, we propose a range of new parsimonious approaches to model the cohort effect. Instead of adding a cohort factor to an age-period model we model the effect by building discontinuities into the pattern of rates within each year. The fit of the resulting models is close to that available from the best of the CBD derivatives.

www.pensions-institute.org/workingpapers/wp1205.pdf

epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/3-19042012-AP/EN/3-19042012-AP-EN.PDF

www.pnas.org/content/109/15/5785.abstract?etoc

www.pnas.org/content/109/13/4916.abstract

Abstract:

Recent findings on limited financial literacy and exponential growth bias suggest saving decisions may not be optimal because such decisions require an accurate understanding of how current contributions can translate into income in retirement. This study uses a large-scale field experiment to measure how a low-cost, direct-mail intervention designed to inform subjects about this relationship affects their saving behavior. Using administrative data prior to and following the intervention, we measure its effect on participation and the level of contributions in retirement saving accounts. Those sent income projections along with enrollment information were more likely to change contribution levels and increase annual contributions relative to the control group. Among those who made a change in contribution, the increase in annual contributions was approximately $1,150. Results from a follow-up survey corroborate these findings and show heterogeneous effects of the intervention by rational and behavioral factors known to affect saving. Finally, we find evidence of behavioral influences on decision-making in that the assumptions used to generate the projections influence the saving response.

papers.nber.org/papers/w17927

B. “Financial Literacy and the Financial Crisis,” by Leora F. Klapper, Annamaria Lusardi, and Georgios A. Panos (w17930, March 2012, .pdf format, 54p.).

Abstract:

The ability of consumers to make informed financial decisions improves their ability to develop sound personal finance. This paper uses a panel dataset from Russia, an economy in which consumer loans grew at an astounding rate – from about US$10 billion in 2003 to over US$170 billion in 2008 – to examine the importance of financial literacy and its effects on behavior. The survey contains questions on financial literacy, consumer borrowing (formal and informal), saving and spending behavior. The paper studies both the financial consequences and the real consequences of financial illiteracy. Even though consumer borrowing increased very rapidly in Russia, the authors find that only 41% of respondents demonstrate understanding of the workings of interest compounding and only 46% can answer a simple question about inflation. Financial literacy is positively related to participation in financial markets and negatively related to the use of informal sources of borrowing. Moreover, individuals with higher financial literacy are significantly more likely to report having greater availability of unspent income and higher spending capacity. The relationship between financial literacy and availability of unspent income is higher during the financial crisis, suggesting that financial literacy may better equip individuals to deal with macroeconomic shocks.

papers.nber.org/papers/w17930

C. “Limited Life Expectancy, Human Capital and Health Investments: Evidence from Huntington Disease,” by Emily Oster, Ira Shoulson, and E. Ray Dorsey (w17931, March 2012, .pdf format, 40p.).

Abstract:

One of the most basic predictions of human capital theory is that life expectancy should impact human capital investment. Limited exogenous variation in life expectancy makes this difficult to test, especially in the contexts most relevant to the macroeconomic applications. We estimate the relationship between life expectancy and human capital investments using genetic variation in life expectancy driven by Huntington disease (HD), an inherited degenerative neurological disorder with large impacts on mortality. We compare investment levels for individuals who have ex ante identical risks of HD but learn (through early symptom development or genetic testing) that they do or do not carry the genetic mutation which causes the disease. We find strong qualitative support: individuals with more limited life expectancy complete less education and less job training. We estimate the elasticity of demand for college completion with respect to years of life expectancy of 0.40. This figure implies that differences in life expectancy explain about 10% of cross-country differences in college enrollment. Finally, we use smoking and cancer screening data to test the corollary that health capital is responsive to life expectancy.

papers.nber.org/papers/w17931

A. “Telomere maintenance and telomerase activity are differentially regulated in asexual and sexual worms,” by Thomas C.J. Tan, Ruman Rahman, Farah Jaber-Hijazi, Daniel A. Felix, Chen Chen, Edward J. Louis, and Aziz Aboobaker (Vol. 109, No. 11, Mar. 13, 2012, HTML and .pdf format, p. 4209-4214). This article is available free of charge.

www.pnas.org/content/109/11/4209.full

B. ”ATM kinase inhibition in glial cells activates the innate immune response and causes neurodegeneration in Drosophila,” by Andrew J. Petersen, Stacey A. Rimkus, and David A. Wassarman (Vol. 109, No. 11, March 14, 2012, p. E656-E664).

www.pnas.org/content/109/11/E656.abstract

www.socialsecurity.gov/OACT/NOTES/ran6/index.html

- Chapter 2: Population Change.

www.ons.gov.uk/ons/rel/pensions/pension-trends/chapter-2–population-change–2012-edition-/index.html

- Chapter 3: Life expectancy and healthy ageing.

www.ons.gov.uk/ons/rel/pensions/pension-trends/chapter-3–life-expectancy-and-healthy-ageing–2012-edition-/index.html

- Chapter 4: The labour market and retirement.

www.ons.gov.uk/ons/rel/pensions/pension-trends/chapter-4–the-labour-market-and-retirement–2012-edition-/index.html

Abstract:

In this paper we analyze the effects of changes in longevity and the pace of technological progress on interest rates, savings behaviour and optimal retirement decisions. In so doing we embed the dynamic optimization problem of choosing a life-cycle consumption path and the retirement age into a general equilibrium setting. Thereby we assume that technology evolves exogenously and the production side of the economy can be described by means of a neoclassical production function. Our results show that (i) the aggregate capital to consumption ratio increases and interest rates decrease in response to increases in longevity; (ii) the response of the optimal retirement age to increases in longevity is ambiguous. However, for reasonable parameter values the optimal retirement age increases in longevity; (iii) the aggregate capital to consumption ratio decreases and interest rates increase in response to faster technological progress; (iv) the response of the optimal retirement age to faster technological progress is ambiguous. However, for reasonable parameter values the optimal retirement age increases in the pace of technological improvements.

www.hsph.harvard.edu/pgda/WorkingPapers/2012/PGDA_WP_91.pdf