The recent increase in inequality in the U.S. and other developed countries has stimulated debate among economists. This debate is best exemplified by Thomas Piketty’s Capital in the twenty-first century and his critics. Taking aside the predictions for the future and the role that capital gains play in this debate, a deeper question is: what is a “normal” level of inequality in historical terms? In other words, if we take the estimates at face value, and inequality today is similar to that of the 19th century and higher than most of the middle of the 20th century, which one is the historical anomaly? Is it normal to have high levels of inequality, and the 20th century was an exception, or is it normal to have low levels of inequality and the 19th century was an exception? Without information on inequality before the 19th century, it is hard to answer the above questions.
A second question, which might be even more important than the first one, is the role of vertical mobility, especially over the very long run. Recent work by Gregory Clark (The Son Also Rises) advanced the idea that there is a magic rule/number in all societies and at all times. This rule implies a vertical mobility that is neither specially slow nor high, and is universal to the human race. This work and the notion of universality of this force are receiving fierce criticism. The main criticism is the source of the data and its inherent bias. Although the data in the book and related works comes from different sources, they share important shortcomings.
Finally, the role of women in mobility studies has been underplayed due to the lack of information on women’s income. Moreover, since most of the studies are focused on Anglo-Saxon countries, where it is customary for the bride to take the last name of the groom, it is not possible to construct matrilineal family trees. In contrast, this was not the case in Spain, even in the pre-modern era. Therefore the study could shed new light on the role of women on inequality and social mobility.
Requisite Skills and Qualifications:
The RA will help analyze the dataset and help creating a literature review in specific topics related to inequality and mobility. Knowledge of econometric software such as STATA or R is required. The RA should also be familiar with OCR software or willing to learn it.