World economic plants a standard reference second edition

The evolutionary record and methods of reconstruction 2. Earliest forms of plant life 3. The colonization of land 4. The first forests 5. Major emergence of the seed plants 6. Flowering plant origins 7. The past 65 million years 8. Mass extinctions and persistent populations 9.

Ancient DNA and the biomolecular record Evolutionary theories and the plant fossil record. Jennifer C McElwain received her B. Oxford University Press is a department of the University of Oxford.

It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Academic Skip to main content. Search Start Search. In , the risk of a pandemic became reality. As governments, businesses, and societies grapple with COVID, societal cohesion is more important than ever. If we are to prevent the pandemic from sapping the potential of an entire generation, it's time to teach resilience to Gen Z as a core skill.

COVID exposed vulnerabilities and deep-rooted inequalities in cities, but with careful planning and investment they can become the new sustainability hubs. Industry is facing disruption from all sides. And leaders need to closely watch three critical drivers of risk — political, technological and societal. The middle childhood SES group consistently lies between the bottom and top in terms of these adult health outcomes. These results conform to the general finding in the literature that childhood economic circumstances are very predictive of later-life adult economic and health outcomes Currie, ; Case et al.

Similarly, in accordance with the literature, higher childhood SES is associated with much higher levels of adult education, net worth, and life satisfaction, another indication of the strong economic transmission across generations in these outcomes.

The more novel results are in the third panel of table 8 which deals with the channels of war. The probability of being dispossessed was highest in the high childhood SES group, not surprising as there was more to capture. Persecution was also highest in the high SES category, while obtaining childhood immunizations was highest in the lowest SES category.

Absent fathers were not strongly differentiated across SES categories. Finally, we examine differences in associations with war by childhood SES categories. For childhood SES by WWII interactions among the health variables, we find the negative health effects to be either neutral by SES categories or that the negative health effects are concentrated on the middle class as in the summary measure of self-reported health or concentrated in the middle and lower class as with heart disease, possibly reflecting the role of lifetime stress with that disease.

In contrast, we find very strong interactions of a negative middle class war interaction for many of our adult SES outcomes—education, and ln net worth. Life satisfaction decrements associated with the war were concentrated on the lower and middle class.

In terms of being ever married, the negative effects of the war were highest on the highest SES women and the lowest SES men. A summary of health and SES outcomes does suggest that the middle class suffered more due to the war with the lower class next in line. Finally, the length of time it takes to achieve a given level of education due to war expands the most for the low and middle class compared to the upper class.

The bottom panel of table 8 shows that some pathways through which war operates are concentrated among the poorest households hunger and immunizations present for the middle class , some are concentrated among middle class dad absent , or the highest SES households dispossession.

Persecution was focused on the middle and upper classes. To conduct this analysis we use new data—SHARELIFE—that records not only adult outcomes in , but also contains retrospective data for salient aspects of the wartime experiences of respondents.

We augment these data with historical information on how WWII affected individuals differently over time and across regions. Our data allow us to analyze which type of individuals were most affected, and by which channels. Our analysis shows that experiencing war increased the probability of suffering from diabetes, depression, and with less certainty heart disease so that those experiencing war or combat have significantly lower self-rated health as adults. Experiencing war is also associated with less education and life satisfaction, and decreases the probability of ever being married for women, while increasing it for men.

We also analyze pathways through which these wartime effects took place and found strong effects for hunger, dispossession, persecution, childhood immunizations, and having an absent father. While a war of the magnitude of WWII affected all social classes to some degree, our evidence does suggest that the more severe effects were on the middle class with the lower class right below them in size of impact.

Population-based economic panels are relatively recent, but combining them with life-histories covering salient past personal and macro events opens up many new research opportunities of which WWII is only one illustration.

This is especially so in Western Europe where the political and economic history of the past four decades is particularly rich and varied. Sarah Lehner and Johanna Sophie Quis provided excellent research assistance.

Smith is supported by various grants from NIA. Additional funding from the U. National Institute on Aging as well as from various national sources is gratefully acknowledged. Putzger, F. Overman, R. Oldenburg Verlag. See table 1 for definitions of variables in first column and Appendix table A for definition of War combat variable. Adult respondents whose health deteriorated between PSID waves were no more likely than before to say their childhood health was not good or to cite additional childhood health problems Smith, b.

He shows that the productivity of those departments in Germany which lost a relatively high share of their professors was permanently lowered, while shocks to physical capital due to Allied bombing had returned to their old growth path by the s. More generally, to make up for investments in human capital takes years, while plants and factories can be repaired and replaced much more quickly.

In spite of deaths of large numbers of civilians in WWII, the existing evidence indicates that affected cities went back to old population growth paths in Western Germany and Japan Brakman et al. Most of the civilian deaths in WWI were due to famine and disease.

The two countries most directly affected in terms of number of causalities were Japan and China. They find that the loss of schooling is about a fifth of a year compared to the following cohort. They suggest that the mechanisms are closing down of religious schools, absence of teachers due to the war, absence of students due to escaping bombing, and actual destruction of schools.

She finds that destruction caused children to attain 0. Her estimates suggest that this schooling reduction is mainly due to physical destruction of schools and the absence of teachers. His suggested pathway is nutritional deprivation in utero. However, we include a different set of countries, and not all of them were equally strongly affected by WWII as Germany was. These types of estimations are possible for a smaller set of countries.

Van den Berg et al. For Germany, we collected data on monthly caloric rations in regions where respondents live. We see large drops in calories towards the end of the war and in occupation zones with the French and Soviet zone hit hardest. When we distinguish different age groups 0—4, 5—10, and 11—16 , we see strongest results for 0—4 group and impacts on adult depression.

This suggests that hunger analysis should not only be seen as operating through nutrition-related outcomes such as adult height, but also and equally through adult outcomes such as depression. Our effects on height are similar to Van den Berg et al. Iris Kesternich, University of Munich. Bettina Siflinger, University of Munich.

James P. Smith, RAND. Joachim K. Winter, University of Munich. National Center for Biotechnology Information , U.

Rev Econ Stat. Author manuscript; available in PMC May Smith , and Joachim K. Author information Copyright and License information Disclaimer. Iris Kesternich, University of Munich;. Copyright notice. See other articles in PMC that cite the published article. Abstract We investigate long-run effects of World War II on socio-economic status and health of older individuals in Europe.

Table 1 Variable Definitions. Open in a separate window. Per Capita Income Growth If wars alter long-term economic growth, they would permanently depress economic prospects of future generations. Country UK. Mortality In , there were about 2 billion people in the world.

Figure 2. Figure 3. Figure 4. Measures of War Exposure To analyze long-term impacts of WWII on health and economic outcomes, we use the fact that different countries in Europe and different people in those counties were differentially affected by WWII at different points in time. Figure 5. War variable War 0.

Combat variable War combat 0—2 months 0. Selection Effects As in any such analysis, there are issues of possible selection effects due to fertility, mortality, and migration that may have biased our estimates. Models of Channels of War We next turn to our estimates of how the micro pathway channels we highlighted above—hunger, dispossession, persecution, and the absence of father—are related to the experience of WWII. War Variable War 0. Combat Variable War combat 0—2 months 0.

OLS regressions include country dummies and year dummies. Appendix Table A. Columbia University Press. Target country Country to which people moved Time period Year in which people moved to target countries Number of combat operations War combat 0—2 months Respondent was living in a war country during the war period in a region within the country that experienced 0—2 months of combat Ellis, J.

Aurum Press. War combat 3 or more months Respondent was living in a war country during the war period in a region within the country that experienced 3—10 months of combat Gross domestic product Log GDP Country specific GDP Maddison, A.

Appendix Table B. Mean S. Background information Year of birth 0. Adult respondents whose health deteriorated between PSID waves were no more likely than before to say their childhood health was not good or to cite additional childhood health problems Smith, b 3 Waldinger demonstrated one micro channel on human capital, the loss of Jewish university professors in Germany due to WWII.

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