Wednesday, June 21, 2017

Difference-in-differences for spatial data

It just came to my knowledge today that Raymond Florax passed away a couple of months ago (in memorian). Prof. Florax was very influential in the field of spatial econometrics. In one his latest papers, he co-authored with Delgado and proposed a difference-in-differences method for spatial data, controlling for spatial dependence. Here is the paper.

Delgado, M. S., & Florax, R. J. (2015). Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction. Economics Letters, 137, 123-126.


Abstract:
We consider treatment effect estimation via a difference-in-difference approach for spatial data with local spatial interaction such that the potential outcome of observed units depends on their own treatment as well as on the treatment status of proximate neighbors. We show that under standard assumptions (common trend and ignorability) a straightforward spatially explicit version of the benchmark difference-in-differences regression is capable of identifying both direct and indirect treatment effects. We demonstrate the finite sample performance of our spatial estimator via Monte Carlo simulations.

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]


Sunday, June 18, 2017

The effect of Uber on traffic congestion

Early this year, a paper in PNAS using a computer model estimated that car sharing services like Uber and Lyft could reduce the number of taxi vehicles on roads by ~76% without significantly impacting travel time. As Joe Cortright has said, the authors are overly optimistic. 

There is another study from last year that analyzed what actually happened to congestion levels when Uber entered the market in some US cities (abstract below). The results of this study are not really comparable to the the paper in PNAS, though. The methods are sound but I have the impression the authors pay too much attention to the statistical significance of the results and do not really discuss the magnitude of the effects of Uber entry on congestion. In any case, it's a good read. 


Li, Z., Hong, Y., & Zhang, Z. (2016). Do Ride-Sharing Services Affect Traffic Congestion? An Empirical Study of Uber Entry. Available at SSRN: https://ssrn.com/abstract=2838043

Abstract:
Sharing economy platform, which leverages information technology (IT) to re-distribute unused or underutilized assets to people who are willing to pay for the services, has received tremendous attention in the last few years. Its creative business models have disrupted many traditional industries (e.g., transportation, hotel) by fundamentally changing the mechanism to match demand with supply in real time. In this research, we investigate how Uber, a peer-to-peer mobile ride-sharing platform, affects traffic congestion and environment (carbon emissions) in the urban areas of the United States. Leveraging a unique data set combining data from Uber and the Urban Mobility Report, we examine whether the entry of Uber car services affects traffic congestion using a difference-in-difference framework. Our findings provide empirical evidence that ride-sharing services such as Uber significantly decrease the traffic congestion after entering an urban area. We perform further analysis including the use of instrumental variables, alternative measures, a relative time model using more granular data to assess the robustness of the results. A few plausible underlining mechanisms are discussed to help explain our findings.

A good-looking video of the computer simulation model of the PNAS paper.


Thursday, June 15, 2017

Mexicans didn’t cross the US border. The border crossed them


Carlos Goes pointed me to this short piece in The Economist:
"... communities have proved more durable than borders. The counties with the highest concentration of Mexicans (as defined by ethnicity, rather than citizenship) overlap closely with the area that belonged to Mexico before the great gringo land-grab of 1848."
For the most part, Mexicans didn’t cross the US border. The border crossed them.


Wednesday, June 14, 2017

Getting updates from Urban Demographics blog

This week we have crossed the milestone of 5000 followers on Twitter. If anything, this means there are a lot of procrastinators out there. If you're not on Twitter but you would like to  procrastinate  receive automatic updates when there is a new blog post, there are two options:

(1) You can subscribe to our RSS Feed in a reader . I'd recommend using Feedly. (2) Or you can get updates from our Facebook page.




if you like this blog, recommend it to your friends. If you don't like this blog, recommend it to your enemies. That's also fine.

Monday, June 12, 2017

The people who keep us company throughout our life cycle

Henrik Lindberg has put together this nice chart showing the people we spend the most time with throughout out life cycle. The data comes from the America Time Use Survey, and the the code to create this chart in R is available here. Thanks Steve Williams for the pointer.

This might be a good moment to reflect about life.

Friday, June 9, 2017

Time-lapse: Nightfall over Los Angeles

Nightfall, by Colin Rich. Remember to watch in high-definition full screen. Via Aaron Renn from Urbanphile.


NightFall from Colin Rich on Vimeo.

Wednesday, June 7, 2017

The Fundamental Law of Road Congestion

Duranton, G., & Turner, M. A. (2011). The fundamental law of road congestion: Evidence from US cities. The American Economic Review, 101(6), 2616-2652. Ungated version here.

Abstract:
We investigate the effect of lane kilometers of roads on vehicle-kilometers traveled (VKT) in US cities. VKT increases proportionately to roadway lane kilometers for interstate highways and probably slightly less rapidly for other types of roads. The sources for this extra VKT are increases in driving by current residents, increases in commercial traffic, and migration. Increasing lane kilometers for one type of road diverts little traffic from other types of road. We find no evidence that the provision of public transportation affects VKT. We conclude that increased provision of roads or public transit is unlikely to relieve congestion

This paper reminds of the Black Hole Theory of Highway Investment, which we posted about a while ago.


Monday, June 5, 2017

Making sense of smart cities

Last year (2016), Tim Schwanen, James Palmer and I put together a lecture series around the topic of "Urban Mobilities in the Smart City", hosted at the Transport Studies Unit (TSU) at Oxford University.

It was a great experience and I learned a lot from the speakers but also from the process of co-organizing the event. I would like to share here four papers that I've read back then and that I would recommend to anyone who wants to start a research on smart cities. These are quite influential papers so some of you might have read them already. Also, feel free to suggest in the comments some other publications you think have strongly contributed to the literature.


image credit : techcrunch