The birth rates in France decreased by nearly 50% during World War I. The amount of lives that were not born because of this decrease was equivalent to the estimated amount of the French that died during the war at 1.4 million. The article aims to analyze the consequences of World War I on various aspects of the population in France. They analyze the economic effects the war had on birth rates due to a decrease in income and how fertility was affected. Some methods this article used to gather data came from the French census for the years 1911 and 1921, this was collected from the Inter-University Consortium for Political and Social Research and the French National Institute for Statistics and Economic Studies. They were able to collect data for 87 regions in France to evaluate the population before, during, and after the war. Fertility decreased dramatically for those who were affected by the war directly. The research found that women who were in their 20’s during World War I gave birth to the least amount of children compare to the generations before and after the war. These women of childbearing age also postponed having children until the war was over. With over 8.7 million men fighting in the war over a 5 year span that significantly decreased the option for conception. A major result found was that the number of babies born out-of-wedlock increased. This study found that the women’s labor force participation did not change dramatically after the war. Major conclusions found were that the war triggered a 91% decline in birth rates. Birth rates declined for many other countries, not only France during World War I & II. The researcher predicts that future events of turmoil will cause a decline in birth rates again. This article was extremely difficult to follow along with. The pages did not seem to have any sequential flow to them and there were little to no headings that were helpful to describe the information to follow. The author included many figures and tables that all seemed to be similar to each other. Some of the graphs did not include keys or increments on the axises which made it difficult the information being displayed. This article included many complex equations that the author related his data to; however, they were not decipherable for me.
2014. “Fertility and Wars: The Case of World War I in France.” American Economic Journal: Macroeconomics, 6(2): 108-36.DOI: 10.1257/mac.6.2.108
The “Baby Boom” has been compared to an earthquake with many aftershocks that affected not only the United States but also many Western European countries. The “Baby Boom” ended as quickly as it started, very unexpectedly. This cycle of increases and decreases in births was referred to as pro cyclical fertility. This article hypothesizes about the timing, length, magnitude, and volumes of the baby boom in North America and Europe. The two main indicators in question are the crude birth rates and total fertility rates. Another factor that influences the increased fertility rates was the influx of women into the workforce during World War II. The increase in birth rates were not only limited to the countries that participated in World War II. To test their hypothesis they fitted a log-linear multilevel model to some of the variables. Another method data was extracted from was Coales index for marital fertility rates. The four main conclusions found: 1- The Baby Boom can not be seen as a post wartime fluke phenomenon, 2-Recuperation can explain the some of the increases in birth rates; it is partially due to the high number of conceptions after the Great Depression, 3- people started marrying at a younger age after the war which caused a marriage boom, 4- An increase in marriage fertility so that more children were born per woman. The main results were not disclosed, they were “available upon request”; however, they do confirm a significant effect of the level of marital fertility in 1930. This article was very interesting, it included many tables and graphs that were very complex and difficult to read. There were over 12 figures which was Figure 7, was a convoluted graph that is indecipherable for any person who does not look at graphs for a living. This was not a very easy article to read because they did not include titles for each of the sections. The whole paper did not seem to flow very well because it lacked structure. I also thought it was inconvenient for the authors to choose not to disclose the results; especially, in a public research article. I believe that the whole point of doing research on a topic and writing a report on it is for the benefit of society. By not publishing the results they are not bettering the scientific community.
Van Bavel, J. and Reher, D. S. (2013), The Baby Boom and Its Causes: What We Know and What We Need to Know. Population and Development Review, 39: 257–288. doi:10.1111/j.1728-4457.2013.00591.x
The two decades post World War II experienced a substantial increase in births. A 1.5 increase occurred from 1940 before the war to 1957 post-war. This boom only lasted for less than a decade when fertility rates fell and there was a sharp decrease in births. This article suggest that they believe the baby was a result of more women of child bearing age entering the working force during the war. They believe this was the main trigger for creating the increased birth rates. Most single women would work until they were married and then quit in order to have a family; however, the war caused many married women to go back into the workforce. Then when the war ended and then men returned home they returned to their work and there were not enough jobs for the younger women. These younger women then skipped joining the workforce, got married and started families thus creating the “Baby Boom”. Previously, married women with families would be frowned upon for joining the workforce, but the war gave the women no other choice. A similar trend in increased birth rates was seen when the Great Depression ended. The methods they used to determine this information came from the database, “1% Integrated Public Use Microdata Series”. They also used a variation in mobilization rates across the states from Acemoglu et al. (2004). “At the height of the baby boom older cohorts of women were having children late, while younger women were having them early” (Doepke et al. 2015). They were able to gather their main results from an individual-level regression equation. They were mainly interested in was the interaction of mobilization rates from different years. States that deployed the most amount of men which created a higher demand for women in the workforce, experienced the highest fertility rates post World War II. This also has to do with the age of women who were of age to marry and child bear once the war was over. The main conclusions they found supported their hypothesis that “that if female labour supply is persistent, a one-time demand shock for female labour leads to long-lasting, asymmetric effects on the labour supply of younger and older women” (Doepke et al. 2015). This study found multiple forces were at work when causing the “Baby Boom”.
Matthias Doepke, Moshe Hazan, Yishay D. Maoz; The Baby Boom and World War II: A Macroeconomic Analysis, The Review of Economic Studies, Volume 82, Issue 3, 1 July 2015, Pages 1031–1073, https://doi.org/10.1093/restud/rdv010
The research article “Effects of the Fertility Transition on Birth Seasonality in the Netherlands” was an interesting article that analyzed the seasonal patterns of births in the Netherlands compared to different demographic regions in the world. There is a relatively large variation in patterns of births for the different geographic regions. The methods they used to analyze their hypothesis included gathering the data from a register-based data system for all births in the Netherlands from the years 1952-2005. They also decided to split the patterns by parity and maternal age. Previously, seasonal birthing patterns were not affected by parity; however, after a war the seasonal patterns shifted because of the difference in parities. Rationale for this research was to either support or negate many theories that discussed the effects contraceptives, extreme temperature and holiday seasons had on seasonal birthing patterns. For example, “The September peak, observed in both the European and the American pattern, has been related to the ‘holiday theory’, or the increase in conceptions around Christmas and New Year, related to increased time spent together around these holidays” (Haandrikman and Van Wissen, 2008). The major results included a steady birthrate from March through April, with a peak in September. For the first 2 decades of the study, springtime was the favorable time to have give birth; however, in the most recent decades, the summer shows the highest birthrates. Another major result was how greatly the seasonality of births was affected by maternal age. Younger mothers were more likely to give birth in the last few months in the year, while older mothers favored to give birth at the beginning of the year. The main conclusions include the fact that the peak of conceptions changed from summer months to winter months. The least amount of births occur in the wintertime. The current pattern for seasonal births in the Netherlands ins very similar to that of The United States. For parities, the main results included a peak for higher incomes in the spring and deep winter months. All of the changes in seasonal birth patterns from the earlier decades to the most recent decades in the study are somewhat linked to the introduction of contraceptives. The fluctuations are also attributed to a change in seasonal environmental light intensity. This was an interesting research article that analyzed many different factors that have an effect on seasonal birth patterns.
HAANDRIKMAN, K., & VAN WISSEN, L. (2008). EFFECTS OF THE FERTILITY TRANSITION ON BIRTH SEASONALITY IN THE NETHERLANDS. Journal of Biosocial Science, 40(5), 655-672. doi:10.1017/S0021932008002733
Shortly after Greece joined the European Union and switch to the single European currency, they suffered a tremendous financial crisis. In 2010, Greece increased it’s public debt significantly causing a recession. This large amount of debt incurred by the Greece created a decrease in their country’s birthrates. In order to properly depict this decline, researchers gathered data for the economy from the statistical program SPSS and based the research on the factors of GDP, fiscal deficit, public debt and unemployment. They took the birth rate statistics from Euro Stat reports during the years 2000 to 2013. Their research supported the hypothesis that the economic crisis did indeed cause a fall in birth rates. The results include a number of factors that correlate with declining birth rates; from 2008 to 2013 the unemployment rate rose 19.8%. During those same years, birth rates decreased by 24.168, this depicts the direct negative correlation between unemployment and birth rates, that they both generated a negative slope. A graph of similar data represents the difference in unemployment rates in men versus women. Women in Greece have a significantly higher unemployment rate than men; therefore, it is logical that unemployed women are less likely to bear children because they lack the financial stability necessary to support a child. Next they analyzed the GDP taken from the measured six years which showed a significant decrease over the first four years, but in year five the GDP began to rise again. This data does not correlate with the declination of birth rates as well as what the unemployment rates show. Fiscal deficits also followed this trend; thus, the results do not display a constant decrease. In the year of 2014, the fiscal deficit significantly decreased, GDP increased and unemployment decreased; hence, the economy was beginning to recover from their economic downfall. The data gathered for birthrates in Greece correspond with the data found for birthrates in other countries experiencing a recession. Birthrates were more commonly affected in countries with lower economic status. An example of these trends were recorded when the USSR was divided and these new countries saw a notable reduction in the amount of children born per woman. However, the study found that unemployment had the greatest influence upon the birthrate because women are less likely to bear children without a steady form of income. It also found that unemployed women were more likely to have abortions. The factors of decreased GDP, higher unemployment rates, fiscal deficits and large public debt all lead to a diminishing birthrate in Greece.