Data

For inquiries about either dataset, please contact me directly via email.

I. Global Menarche and Menopause Dataset

This meta dataset is composed of country -time specific ages of menopause and menarche, complied via a standardized review of the medical literature using Google scholar. The terms queried were “Climactic”/or “menopause”/“menarche”/or “perimenopause”. Since the goal was to construct a country-specific natural age of menopause and menarche time series, only medical articles with natural age were recorded. The recorded age of menopause is the menopause transition age also known as perimenopause. It refers to the age at which a woman’s body makes the natural transition to the end of reproductive years via a decline in ovarian function (Harvard Health, 2009).

The constructed corpus has a combination of cross-section and observational studies that sample from community and hospital/clinic settings. The number of participants ranges between 50 to 1000 respondents. The variable of interest is specified as the mean and median age at natural menopause. There are 66 countries in the sample, ranging from 1970 to 2016. There are 576 country time-specific observations for menopause. The sample mean of menopause age is 49.433 years with a standard error of 0.081. Figure 1 gives a general snapshot one aspect of the data- evolution of global menopause age over time.

Figure 1: Global trends in Age of Menopause and GDP.

II. The Intrepid Project Dataset ⧉

The Intrepid Project, funded by the Swiss National Science Foundation, aims to develop a general understanding of how policy announcements by state agencies are interpreted by journalists in ways that send signals, indicate intent, and otherwise provoke economic and political reactions.

To do this, journalistic accounts of policy announcements on central bank monetary policy and on foreign policy are hand-annotated to capture particular features. We then use machine learning techniques on semantic and syntactic properties of announcement texts that differ on issue domains (monetary vs. foreign policy), country studied (the United States, France, and Canada), and time period (when archival materials are available, from the late 1960s to 2018), matching those announcement texts to hand-coded journalistic texts. In this way, we aim to develop models of the announcement interpretation process.

Figure 2 gives a snapshot of the data complied. The figure generates year wise word cloud of most frequently used words in New York Times coverage of FOMC communications between 1985–2015.

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Figure 1: Most Frequently Used Words in New York Times Coverage of FOMC Communications (1985–2015) .

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