Monday, October 23, 2017

Quote of they day: programming

"In programming the hard part isn’t solving problems, but deciding what problems to solve."

ps. a timely quote that reflects my struggle working on the 4th paper of my doctoral research.

Tuesday, October 17, 2017

Migrating researchers are cited the most

This is according to a recent paper published in Nature. The authors analyzed 14 million papers published between 2008 and 2015 by nearly 16 million individual authors. Around 4% of those authors - more than 595K were considered to be “mobile,” meaning they had affiliations with academic institutions in more than one nation between 2008 and 2015. 

The study looks very interesting throughout. Here are only two of the main results:
  • "[...] mobile scholars have about 40% higher citation rates, on average, than non-mobile ones"
  • "Regardless of region, mobility pays in terms of citations. Across all regions, mobile scholars are more highly cited than their non-mobile counterparts. The advantage varies by region. Mobile North Americans see only a 10.8% boost in citations over their non-mobile colleagues. For Eastern European scholars, the gulf is 172.8%."
I thank Tim Schwanen for the pointer.

Monday, October 16, 2017

Two positions open at Oxford

Just a heads up to job seekers. There are currently two positions open at Oxford University. Perhaps some of you could be interested.

Tuesday, October 10, 2017

Insights from behavioural economics into transport planning and design

Yesterday, Richard Thaler was awarded the 2017 Prize in Economic Sciences "for his contributions to behavioural economics". In case you're interested on the topic, Erel Avineri has published a paper a few years ago where he discusses some of the insights that research in behavioural sciences can bring into the planning and design of transport systems to make them safer, sustainable and more efficient.

Avineri, E. (2012). On the use and potential of behavioural economics from the perspective of transport and climate change. Journal of Transport Geography, 24, 512-521.

It can be argued that the main thinking in transport planning and policy making stem from neoclassical economics in which individuals are largely assumed to make rational, consistent, and efficient choices, and apply cognitive processes of decision making that maximise their economic utility. Research in behavioural sciences indicates that individuals’ choices in a wide range of contexts deviate from the predictions of the rational man paradigm inspired the research agenda in the field of travel behaviour. New concepts and practices of government aim to apply some behavioural economics insights in the design of behavioural change initiatives and measures, an approach recently advocated in the US and the UK. This paper provides a brief review on the use and potential of behavioural economics from the perspective of transport and climate change, in two main contexts: travel demand modelling and design of behaviour change measures. The discussion of limitations and knowledge gaps associated with the implementation of behavioural economics to a travel behaviour context might contribute to the debate and help in defining research agenda in this area.

Why you should always visualize your data

In 1973, the statistician Francis Anscombe published a paper demonstrating the importance of plotting the data before analyzing it. That paper introduced what latter became known as the Anscombe's Quartet, which comprises four datasets that have almost identical descriptive statistics including means, variances and correlation and yet look completely different when you plot them.

This is how the Anscombe's Quartet look like.

This year, this idea has been taken to a whole new level. A couple of researchers took this idea very seriously and they developed a method to relocate the points in a scatterplot towards a given shape and still keep descriptive summaries seemingly identical. The authors published the method here. They've also developed an R library {datasauRus} so you can   procrastinate the whole afternoon  learn more about statistics.

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)

Friday, September 29, 2017

Urban Picture

Few cities are as photogenic as Barcelona from above #CatalanReferendum

Photo via City Describer

Wednesday, September 27, 2017

Uber ban in London

This week, it was on the news that Uber will soon lose its license to operate in London since the local transport regulator ruled that Uber is "not fit and proper" to operate in city. This decision is not settled yet and it's probably  hopefully  going to be negotiated along the appeal process towards a middle-ground regulation. 

In the meantime, Tyler Cowen's has shared his views on why this is "a big brexit mistake". This is part of a much larger debate on whether/how governments should regulate the 'sharing economy', a debate which would need a careful discussion on transport regulation. A paper on this very topic just got recently published and it does a really good job at tackling the most important points in this debate. The paper is coauthored by top researchers from the Transport Studies Unit TSU/Oxford   I'm biased . This is a very timely discussion in Brazil, where the Congress will be creating a national regulation  scheme for ride hailing apps in the coming months (link in Portuguese).

Dudley, G., Banister, D., & Schwanen, T. (2017). The Rise of Uber and Regulating the Disruptive Innovator. The Political Quarterly.

The ride-hailing company Uber has achieved extremely rapid global expansion by means of outmanoeuvring governments, regulators and competitors. The rise of the company has been based on a deliberate strategy of acting as a market disruptive innovator through a user friendly technology and making use of the ‘sharing economy’. These attributes are not unique, but are distinctively augmented by a relentless expansionary ambition and an ability to maintain the capacity to innovate. Uber has generated great political controversy, but the challenge for governments and regulators is to embrace the benefits of the disruptive innovator, while adopting an approach that takes into account the full range of impacts. For Uber, the challenge is to maintain its expansionary style as a disruptive innovator, while also redefining on its terms the political and public debate. The case study of London provides important insights into the dynamics of these processes.

image credit: DANIEL LEAL-OLIVAS/AFP/Getty Images