LONG-TERM TRENDS IN THE U.S. STANDARD OF LIVING

2008 ◽  
Vol 22 (1) ◽  
pp. 129-152 ◽  
Author(s):  
Richard H Steckel

When economists investigate long-term trends and socioeconomic differences in the standard of living or quality of life, they have traditionally focused on monetary measures such as gross domestic product—which has occupied center stage for over 50 years. In recent decades, however, scholars have increasingly recognized the limitations of monetary measures while seeking useful alternatives. This essay examines the unique and valuable contributions of four biological measures—life expectancy, morbidity, stature, and certain features of skeletal remains—to understand levels and changes in human well-being. People desire far more than material goods and in fact they are quite willing to trade or give up material things in return for better physical or psychological health. For most people, health is so important to their quality of life that it is useful to refer to the “biological standard of living.” Biological measures may be especially valuable for historical studies and for other research circumstances where monetary measures are thin or lacking. A concluding section ruminates on the future evolution of biological approaches in measuring happiness.


2011 ◽  
Vol 24 (18) ◽  
pp. 4831-4843 ◽  
Author(s):  
P. Jonathan Gero ◽  
David D. Turner

Abstract A trend analysis was applied to a 14-yr time series of downwelling spectral infrared radiance observations from the Atmospheric Emitted Radiance Interferometer (AERI) located at the Atmospheric Radiation Measurement Program (ARM) site in the U.S. Southern Great Plains. The highly accurate calibration of the AERI instrument, performed every 10 min, ensures that any statistically significant trend in the observed data over this time can be attributed to changes in the atmospheric properties and composition, and not to changes in the sensitivity or responsivity of the instrument. The measured infrared spectra, numbering more than 800 000, were classified as clear-sky, thin cloud, and thick cloud scenes using a neural network method. The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. The AERI data also show many statistically significant trends on annual, seasonal, and diurnal time scales, with different trend signatures identified in the separate scene classifications. Given the decadal time span of the dataset, effects from natural variability should be considered in drawing broader conclusions. Nevertheless, this dataset has high value owing to the ability to infer possible mechanisms for any trends from the observations themselves and to test the performance of climate models.


Diabetes Care ◽  
2017 ◽  
Vol 41 (1) ◽  
pp. 69-78 ◽  
Author(s):  
Olga Montvida ◽  
Jonathan Shaw ◽  
John J. Atherton ◽  
Frances Stringer ◽  
Sanjoy K. Paul

2014 ◽  
Author(s):  
Juan Antonio Montecino ◽  
Iren Levina ◽  
Gerald Epstein

2017 ◽  
Vol 122 (12) ◽  
pp. 6152-6169 ◽  
Author(s):  
Tingting Xue ◽  
Guoping Tang ◽  
Lin Sun ◽  
Yuzhen Wu ◽  
Yonglin Liu ◽  
...  

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