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

Thursday, December 5, 2019

How much time do we spend with other people as we grow old?

A couple of years ago, I posted this chart showing how much time we spend with other people as we grow old. The chart was created by Henrik Lindberg using data from the America Time Use Survey, and the code to recreate this chart in R is available here.

p.s It's my birthday today and birthdays are always a good moment to reflect about life :)

Tuesday, December 3, 2019

geobr v1.1 is on CRAN

Good news! The new version of geobr v1.1 has been published on CRAN.

The geobr package in R is probably the easiest and fastest way to download shapefiles and official spatial data sets of Brazil. The package includes a wide range of geospatial data available at various geographic scales and for various years with harmonized attributes, projection and topology.

You can find a simple tutorial on how to use the package here.

The new release of geobr v1.1 includes 19 data sets:
  1. country
  2. region
  3. state
  4. meso region
  5. micro region
  6. intermediate region
  7. immediate region 
  8. municipality
  9. weighting area 
  10. census tract 
  11. statistical grid
  12. urban areas
  13. health facilities
  14. indigenous land
  15. conservation units 
  16. biomes
  17. legal Amazon 
  18. semiarid
  19.  disaster risk areas

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.

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.

Wednesday, November 27, 2019

An open-source framework for segregation measures

New paper by Renan Cortes and the Python Spatial Analysis Library (PySAL) team, giving a great contribution to the study of segregation. Eli Knap, one of the co-authors of the paper, has a great blog post summarizing some of the key contributions of the package.

Cortes, R. X., Rey, S., Knaap, E., & Wolf, L. J. (2019). An open-source framework for non-spatial and spatial segregation measures: the PySAL segregation module. Journal of Computational Social Science, 1-32.

In human geography and the urban social sciences, the segregation literature typically engages with five conceptual dimensions along which a given society may be considered segregated: evenness, isolation, clustering, concentration and centralization (all of which can incorporate or omit spatial context). Over the last several decades, dozens of segregation indices have been proposed and studied in the literature, each of which is designed to focus on the nuances of a particular dimension, or correct an oversight in earlier work. Despite their increasing proliferation, however, few of these indices remain used in practice beyond their original conception, due in part to complex formulae and data requirements, particularly for indices that incorporate spatial context. Furthermore, existing segregation software typically fails to provide inferential frameworks for either single-value or comparative hypothesis testing. To fill this gap, we develop an open-source Python package designed as a submodule for the Python Spatial Analysis Library, PySAL. This new module tackles the problem of segregation point estimation for a wide variety of spatial and aspatial segregation indices, while providing a computationally based hypothesis testing framework that relies on simulations under the null hypothesis. We illustrate the use of this new library using tract-level census data in two American cities.

image credit: Cortes et al 2019

Tuesday, November 19, 2019

What do we know about Transit Oriented Development (TOD)?

Author links open overlay
For those interested in what Transit Oriented Development (TOD) can and cannot do to promote more sustainable and inclusive cities, there are two brand new papers reviwing decades of TOD reseach and policy. These papers should probably be added to that neverending reading pile.

The TOD of Curitiba, Brazil

credit: Rafael Pereira via Google Maps

Tuesday, November 12, 2019

Monday, November 11, 2019

A glimpse into the accessibility landscape of São Paulo

These maps show the proportion of jobs and elementary schools accessible by public transport in under one hour in São Paulo. These are some of the results of the Access to Opportunities Project I'll be presenting this week at the Brazilian Conference on Transport Research ANPET 2019. I hope to see some of you there.

Thursday, November 7, 2019

New paper out: Distributional effects of transport policies on inequalities in access to opportunities

Glad to share our paper on "Distributional effects of transport policies on inequalities in access to opportunities in Rio de Janeiro" is now out the Journal of Transport and Land Use. I summarize the paper findings and contributions in this short thread here, but please feel free to read the full paper. The journal is open access!

Pereira, R. H. M., Banister, D., Schwanen, T., & Wessel, N. (2019). Distributional effects of transport policies on inequalities in access to opportunities in Rio de Janeiro. Journal of Transport and Land Use, 12(1). doi:10.5198/jtlu.2019.1523

The evaluation of social impacts of transport policies has been attracting growing attention in recent years. Yet studies thus far have predominately focused on developed countries and overlooked whether equity assessment of transport projects is sensitive to the modifiable areal unit problem (MAUP). This paper investigates how investments in public transport can reshape socio-spatial inequalities in access to opportunities, and it examines how MAUP can influence the distributional effects of transport project evaluations. The study looks at Rio de Janeiro (Brazil) and the transformations carried out in the city in preparation for the 2014 World Cup and the 2016 Olympics, which involved substantial expansion in public transport infrastructure followed by cuts in service levels. The paper uses before-and-after comparison of Rio's transport network (2014-2017) and quasi-counterfactual analysis to examine how those policies affect access to schools and jobs for different income groups and whether the results are robust when the data is analyzed at different spatial scales and zoning schemes. Results show that subsequent cuts in service levels have offset the accessibility benefits of transport investments in a way that particularly penalizes the poor, and that those investments alone would still have generated larger accessibility gains for higher-income groups. These findings suggest that, contrary to Brazil’s official discourse of transport legacy, recent policies in Rio have exacerbated rather than reduced socio-spatial inequalities in access to opportunities. The study also shows that MAUP can influence the equity assessment of transport projects, suggesting that this issue should be addressed in future research.

Wednesday, November 6, 2019

Positive thinking

Induced demand and the Black Hole Theory of Highway Investment