Interested in China's regional economic diversification ?
In this new paper in Regional Studies, we explore the role of relatedness, & high-speed rail, in China's regional diversification. The paper was led by lead @gaojian08
(1/n) 🧵
Paper: tandfonline.com/eprint/GRXBNTC…
We start by verifying that Chinese provinces are more likely to (i) enter related activities & (ii) enter activities present in geographic neighbors. These are classic findings in economic geography that we reproduce using Chinese enterprise data & firm financial data. (2/N)
Then, we compare these spillover channels. What matters more? Having related industries? Or a geographic neighbor that is already in that industry? We find that these two channels work as substitutes. (3/N)
Having many related industries, or many geographic neighbors where the industry is present, predicts entries. But having both is not more predictive than having one. As long as you have one source of spillovers (relatedness or geography) the other one is less relevant. (4/N)
Finally we look at the role of high-speed rail in accelerating regional spillovers. During the last decades, China's high-speed rail went through several acceleration campaigns, which should facilitate spillovers among nearby regions. (5/N)
These acceleration campaigns followed existing roads and rail lines (connecting cities which have been connected for thousands of years). So they were not designed to connect a particular industries (e.g. to connect advertisement companies in Shanghai & Wuhan) (6/N)
We find that regions connected by rail grew more similar in terms of their industrial structure. These findings, suggest that high speed rail contributes to spillovers among neighboring regions. (7/N). You can get the paper at: centerforcollectivelearning.org/papers
&
tandfonline.com/eprint/GRXBNTC…

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More from @cesifoti

24 Feb
There is a lot of discussion of bias in economics. This discussion is justified & needed. What I can add to this is some stories on how economists treat people from outside the field. Let me share with you a few bone chilling stories of what I’ve been through 🧵/1 #EconTwitter
I begun working in economics as a physics PhD student (mid 2000s). In 2007, I published a first author paper in Science, and was asked to present it in a seminar series at Harvard. /2
Right after the seminar, a professor from the other Cambridge MA university approached me. After some small talk, he leaned towards me and whispered into my ear: /3
Read 21 tweets
25 Jan
What is economic complexity? And how it is helping us understand the economy? More than a decade ago, two papers helped ignite the field. Today, I am publishing the first comprehensive review of Economic Complexity in Nature Review Physics (thread) 1/N
nature.com/articles/s4225…
I start from two findings: relatedness and complexity. Relatedness measures the overall affinity between an activity and a location, and can explain path dependencies and the activities that will grow or decline. /2
Complexity metrics are dimensionality reduction techniques (common in machine learning) that can identify the combinations of factors that best explain the geography of multiple economic activities. /3
Read 15 tweets
9 Dec 20
This semester I had the pleasure to teach data visualization studio at an elite US university. Many students were interested in social justice (being 2020 in the US). Yet, many approached the topic in a way that was a bit naive ... (thread🧵) /1
Their instincts were to create projects that "brought attention to the issue." But since this was a hands-on class, where students had to build instead of arguing, we had to push them beyond these first instincts. /2
The class required them to go beyond stating the problem, or assigning blame. They not only had to suggest a solution, they had to implement it. And in that act of making, is where the deepest lessons took place. /3
Read 14 tweets
7 Nov 20
Map Time!
So you’ve seen a lot of maps in the last few days. What maps work, which ones don’t, and how to think about them? Time for a thread ! /1
To begin, let’s go through some data visualization basics. Data visualization, is the use of graphical metaphors to represent quantities. The fact that visualization are metaphors, however, is often forgotten. 2/
Think of a scatter plot showing age vs income. Age is measured in years. Income in dollars, but in a scatter plot they are both represented in inches (a spatial metaphor!). 3/
Read 17 tweets
5 Nov 20
Biden squeezing by to win the 2020 election like...

But in all earnest there are a few lessons we all need to reflect on (thread). 1/
1. The election will leave many people unsatisfied. With 71+ million votes for Biden, and 68+ million votes for Trump, this is the largest number of votes casted in a US presidential election (Biden is the most voted ever). Yet, a 270-268 victory is unsatisfying in two accounts:
It will of course be unsatisfying to the 68+ million Americans who voted for Trump. But those who voted for Biden expected a repudiation of Trump’s government & a landslide win. That didn’t happen. This is America.
Read 9 tweets
17 Oct 20
Today I am leaving the US.
With my family we are exploring a new life in the south of France.
I’ve been in the US for more than 16 years. I earned my citizenship & experienced many ups & downs. But I am grateful. The US was good to me in many ways ...
/1
I published 3 books & about 60 academic papers. I started a company that employs dozens of people & has clients throughout the world. I ran a lab for 9 years at one of the countries top universities. I was invited to the main stage of Ted and to Davos.
/2
I met millionaires, billionaires, movie stars, & rock stars. I had my work published in “The Times.” I hanged out with Nobel prize winners in their darkest moments. I experienced hype & betrayal. I saw the belly of the beast, from the inside, as I rose, fell, & stood up again. /3
Read 24 tweets

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