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Category: Bibliometry

Emigrants vs. Settlers

In his contribution to ‘Natural Experiments in History‘ James Belich  argues that shifting attitudes towards emigration in Britain and the US were essential for the settler explosions in the American West, Australia, Canada, New Zealand and South Africa. Belich puts the shift in attitudes between 1810 and 1820 and illustrates the transformation with the contest between the use of ’emigrant’ and ‘settler’ on the pages of the Times of London. Always on the lookout for potential application of the awesome power of Google N-gram, I checked whether the shift of attitudes and vocabulary is visible in the larger body of English-language literature indexed  by Google N-gram as well. Here is the graph: ‘Settler’ gets more popular than ’emigrant’ indeed! But the shift occurs a bit later with an initial catch-up around 1930 and the ultimate win of ‘settler’ around 1970. Interestingly, in the corpus of British books, ‘settler’ never surpasses ’emigrant’ in popularity, while in American books the two terms are practically even between 1830 and 1865 when ‘settler’ overtakes ’emigrant’ for good. Actually, it is ‘pioneer’ that rises in popularity beyond ’emigrant’ around 1810 and then surpasses both ’emigrant’ and ‘settler’ after 1845: Overall, Belich’s transformation in attitudes and vocabulary towards emigration seems reflected in literature, although the shift occurs later, and is much stronger for American English.

How to get more citations: red hot new evidence?

Wanna get more  citations to your papers? Start with the title. No colons, no question marks [evidence here  (gated); don’t look here]. More  acronyms [link]. And don’t even think about humorous and  amusing phrases [link]. Didn’t help? Don’t despair: “no more than 20% of citations of prominent papers involve the citer actually reading the papers in question” [link]

The ‘Nobel’ prize for Economics, VAR and Political Science

Yesterday the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel  was awarded to the economists Thomas J. Sargent and Christopher A. Sims “for their empirical research on cause and effect in the macroeconomy” (press-release here, Tyler Cowen presented the laureates here and here). The award for Christopher Sims in particular comes for the development of vector autoregression  – a method for analyzing ‘how the economy is affected by temporary changes in economic policy and other factors’. In fact, the application of vector autoregression (VAR) is not confined to economics and can be used for the analysis of any dynamic relationships. Unfortunately, despite being developed back in the 1970s, VAR remains somewhat unpopular in political science and public administration (as I learned the hard way trying to publish an analysis that uses VAR to explore the relationship between public opinion and policy output in the EU over time). A quick-and-dirty search for ‘VAR’/’vector autoregression’ in Web of Science [1980-2011] returns 1810 hits under the category Economics and only 52 under Political Science (of which 23 are also filed under Economics). This is the distribution over the last decades: Time period – Econ/ PolSci 1980-1989 –   13/1 1990-1999 – 406/15 2000-2011 – 1391/36 With all the disclaimers that go with using Web of Science as a data source, the discrepancy is clear. It remains to be seen whether the Nobel prize for Sims will serve to popularize VAR outside the field of economics.