Showing posts with label History. Show all posts
Showing posts with label History. Show all posts

Friday, December 13, 2019

The mobility patterns of historically notable individuals

A new study using Natural Language Processing techniques to retrieve historical information from Wikipedia and analyze the spatial mobility patterns of historically notable individuals. A nice and inventive method to study historical mobility patterns. Science can be incredible and fun. (HT Marco De Nadai)



image credit: Lucchini et al 2019

Friday, November 29, 2019

Awarded research on historical inequality in Brazil


I am very proud to share that my friend and colleague at Ipea Pedro Souza has been awarded the Prêmio Jabuti for his book 'A History of Inequality: the concentration of top incomes in Brazil between 1926-2013'. The Prêmio Jabuti (the "Tortoise Prize") is the most prestigious literary award in the country. The book is based on his PhD thesis, which has already received two national awards btw.

If you read Portuguese, you can buy Pedro's book here, or download his PhD thesis here. There is a paper in English summarizing some of the key findings of his research. I've also posted the English abstract of his thesis below.






Souza, Pedro H. G. F. de. “A desigualdade vista do topo : a concentração de renda entre os ricos no Brasil, 1926-2013”, 12 de setembro de 2016. https://repositorio.unb.br/handle/10482/22005.

Abstract:
This dissertation uses income tax tabulations to estimate top income shares over the long-run for Brazil. Between 1926 and 2013, the concentration of income at the top of the distribution combined stability and change, diverging from the European and American patterns in the 20th century. Contrary to benign industrialization and modernization theories, there was no overarching, long-term trend. Most of the time the income share of the top 1% of the adult population fluctuated within a 20%--25% range, even in recent years. Still, top income shares had temporary yet significant ups and downs which largely coincided with the country's most important political cycles. The top 1% income share increased during the Estado Novo and World War II, then declined in the early post-war years and even more so in the second half of the 1950s. The 1964 coup d'état reversed that trend and income inequality rose back to post-war levels after a few years of military rule. The 1970s were marked by instability, but top income shares surged again in the 1980s. The share of the 1% then decreased somewhat in the 1990s and perhaps the mid-2000s. There were no real changes since then. In addition, this dissertation analyzes the concentration of income among the rich, provides international comparisons of top income shares, and contrasts the income tax series with estimates from household surveys. The income tax series are also used to compute “corrected” Gini coefficients which take into account the underestimation of top incomes in household surveys. The major research questions are comparative and historically oriented, and I argue in favor of an institutional interpretation of the results. The motivation for and implications of this approach are presented in the more theoretical chapters that precede the empirical analysis. In these chapters, I engage with the history of ideas about inequality and social stratification and highlight the long and heterogeneous tradition of studies about the rich and the wealthy. My main argument is that the academic and political concern with distributional issues flourishes when inequality is conceived in binary or dichotomous terms.

Friday, October 11, 2019

How many people have ever lived on Earth?

Have a guess. I can only say I was wrong by a lot :) Now select this back box to see how close your guess was. 109 billion  There is a nice article by PRB on this question and how one arrived at this estimate. HT Sergei Soares.


Monday, September 23, 2019

Coloring slavery history in Brazil

Marina Amaral (Twittter) is a renowned digital colorist. Marina has an incredible portfolio, coloring photographs of Marie Curie, Abraham Lincoln, Albert Einstein, tragic moments in the WWII and victims of Auschwitz concentration camp.



credit: Marina Amaral

Tuesday, March 19, 2019

The race for the largest city in the world over the past 500 years

In previous posts, I've pointed out to an incredible open dataset with comprehensive population estimates of human settlements and cities for the past 6,000 years. The talented John Burn-Murdoch used some of these data to create this nice animation showing the changing ranks of the 10 largest cities in the world since 1500. The full code for the animation is available here.

Tuesday, October 3, 2017

The long-term effect of slavery on inequality today

According to a new working paper, 1800s slavery explains approximately 20% of income inequality in Brazil today. While the direction of the impact is not surprising, I'm impressed by its magnitude. I wonder how much investment in cash transfer programs would be necessary to achieve an effect of similar magnitude. Thanks John B. Holbein‏ for pointing to this study on Twitter.


Fujiwara, T., Laudares, H., & Caicedo, F. V. (2017). Tordesillas, Slavery and the Origins of Brazilian Inequality.

From the abstract:
"...To deal with the endogeneity of slavery placing, we use a spatial Regression Discontinuity framework, exploiting the colonial boundaries between the Portuguese and Spanish empires in current day Brazil. We find that the number of slaves in 1872 is discontinuously higher in the Portuguese side of the border, consistent with this power’s comparative advantage in this trade. We then show how this differential slave rate has led to higher income inequality of 0.103 points (Gini coefficient), approximately 20% of average income inequality in Brazil. To further investigate the role of slavery on economic development, we use the division of the Portuguese colony into Donatary Captancies. We find that a 1% increase in slavery in 1872 leads to an increase in inequality of 0.112. Aside from the general effect on inequality, we find that more slave intensive areas have higher income and educational racial imbalances and worse public institutions today"

ps. This paper also reminds me of this post on how presidential elections are impacted by a 100 million year old coastline in the USA. Hint: geology determined the distribution of productive land, which influenced the spatial distribution of African slaves which in turn influenced the electoral distribution. I'm not saying I'm convinced by this argument but I have to recognize it uses a quite inventive identification strategy.
image credit: Fujiwara et al (2017)

Sunday, October 1, 2017

Our biggest cities have existed and died before

Ta-Prohm, Cambodia, used to be the largest population settlement before the industrial revolution. Nowadays it is one of the most impressive ruins in the world.

"In reality, our biggest cities have existed and died before. This one did. It just happens over a longer period of time - the rain falls, the roots grow and nature eats what we built. The best technology of that time wasn't enough." Geat video by Joe Posner (Vox)


Saturday, August 12, 2017

An R library to analyze and map John Snow's 1854 Cholera data

As many of you will know, an English physician called John Snow mapped the cholera outbreak in the Soho district of London in 1854. That map would later be a key element in the discovery that cholera was caused by contaminated water, not air. It's fair to say this map somehow changed history not only because of the lives it helped save, but perhaps more importantly because of the ways it opened human imagination to the role of spatial analysis in science and human development. Steven Johnson has written a book about the story of this map and its influence on modern science and cities. If you are short in time, there is a great 9-minute video summary of the book here.

All this introduction to say that now there is an R library that allows you to analyze and map John Snow's 1854 Cholera data yourself. Thanks Bob Rudis for calling attention to this library on twitter. Dani Arribas-Bel also pointed out to this chapter / online notebook that presents the documented code for a reproducible spatial analysis of John Snow’s map using mostly Python. This is great material for teaching.

update 16 Aug 2017: RJ Andrews has also pointed me to this paper analyzing the mortality rates and the space-time patterns of John Snow’s cholera epidemic map.



Sunday, August 6, 2017

Urban Picture

New York parking lot, 1930 via History in Pics


Tuesday, June 20, 2017

Assorted links

  1. Personal details of ~200 million US citizens exposed. A 1.1 terabyte data set with names, home addresses, phone numbers, political views etc. This is approx. 2/3 of the american population. Probably the largest data leak in history  thus far 






  2. I've recently found out that the principal scientist at Amazon‘s Modeling and Optimization team is Renato Werneck, a Brazilian researcher who is also one of the authors of Raptor, the Round-Based Public Transit Routing algorithm






  3. In the USA, both Democrats and Republicans agree there is a lot of discrimination against certain social groups. They just disagree which groups are discriminated against


  4. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. Since 1980, obesity rates doubled in more than 70 countries and continuously increased in other countries

Prevalence of Obesity at the Global Level, According to Sociodemographic Index (SDI)

[click on the image to enlarge it]


Friday, December 23, 2016

A history of global living conditions: a big picture of human development in 6 charts

It is hard not to be a pessimist these days. As 2016 comes to an end, it leaves us with that bitter feeling of "WTF world!". In gloomy days like these, having a long term perspective on human development can help us alleviate this feeling.

The image below brings 6 charts that give a historical perspective on human development (detailed and interactive charts here). They show the big picture of some of the remarkable improvements we have seen in the world in the last 200 years, with less poverty and tyranny and with more education and better health conditions.

This image comes from Our World in Data (OWID), a fantastic online publication that shows how living conditions are changing in the world with the best available on wide range of topics including health, food, energy, institutions, culture, education, technology, war and peace, etc. I am proud that OWID is produced at the University of Oxford. It was created by  Max RoserEsteban Ortiz Ospina and Jaiden Mispy

The OWID website is a great source of information, particularly if you're feeling too pessimistic about the world  or if you feel like procrastinating a bit, like me 

"One reason why we do not see progress is that we are unaware of how bad the past was." (Roser et al, OWID)