This page serves as a guide for researchers and others
looking for the data we used for our paper on Polyarchy and Financial
Centre Competitiveness. We store the information on
GitHub,
Dataverse and
Datahub. In case of the sources becomes unavailable, please try the
others.
Special thanks
to the Hong Kong Research Grants Council's Theme-Based Research Scheme
for financial support for this work and the Europlace Institute of
Finance and Insti7programme Risk Management, Investment Strategies and
Financial Stability for their support -- though naturally errors remain
my/our own.
Interesting Variables to Have |
Z/Yen's IFC Ratings from 2005 to 2015 |
* |
Correlations between 'real' polyarchy and 'real'
eigencentrality |
* |
Correlations b/t all variables |
* |
Entropies in cross-border bank liabilities |
* |
VDem data |
* |
|
|
GEPHI
Network Data: Before and After Adjustment |
These are the
Gephi files for the
BIS
cross-border bank liabilities for the top 40 countries shown in
the
Z/Yen 2017 ranking of international financial centres (we
also provide a list in our paper in case this link does not
work). Once you open these files in Gephi, you will be able to
compute all the network statistics we did. Note that these links
go DIRECTLY to the Gephi files (and not the Github pages hosting
them). |
Before Adjustment |
After Adjustment |
2005 |
2011 |
2005 |
2011 |
2006 |
2012 |
2006 |
2012 |
2007 |
2013 |
2007 |
2013 |
2008 |
2014 |
2008 |
2014 |
2009 |
2015 |
2009 |
2015 |
2010 |
|
2010 |
|
The original
edges files show the sums in US dollars between countries from the BIS.
The modified edges show these values after we adjusted for them using
econometric methods (which we describe in our paper). The pre-adjustment
network statistics provide the eigenvalue centralities, along with all
the statisitcs that Gephi gives, but which we ended up not using (such
as PageRanks and modularities) -- applied to the original data the BIS
provides. The after adjustment statistics provide the numbers we
computed from the new data we calculated using regression.
Regression Panel |
This file provides the data for the variables for all the
jurisdictions we analysed in
cvs format and in
xls format. |
The variables includes in the regression panel
include: Country Name Year Polyarchy *100 Polyar Diff * 100
"Pure" Polyarchy Diff Pure Polyarchy Voice Diff Voice Largest
invest Exponential drop-off Diff in Invest Diff in Diff old
eigencentrality old clustering old pageranks old authority old
hub new authority new hub new pageranks new clustering new
eigencentrality CHANGE new authority CHANGE new hub CHANGE new
pageranks CHANGE new clustering CHANGE new eigencentrality
Invest Entropic Measure * 100 Invest Entropy Real effective
exchange rate index (2010 = 100) Diff REER * 100 Real interest
rate (%) Market cap. (% of GDP) Diff Market cap GDP per capita,
PPP (current thousands international $) Diff GDP thousands per
capita S&P Global Equity Indices (annual % change) Current
account balance (% of GDP) Commercial service exports (current
billion US$) Diff Commercial service exports (current billion
US$) Air transport, millions of passengers carried Diff air
passangers Central government debt, total (% of GDP) Diff
Central government debt, total (% of GDP) Gross capital
formation (% of GDP) Diff Gross capital formation (% of GDP)
Gross domestic savings (% of GDP) Diff Gross domestic savings (%
of GDP) FDI, net inflows (% of GDP) Diff FDI Broad money growth
(annual %) Rule of Law Change in rule of law times 100. |
Disclaimers: We provide these data 'as-is', as a first
attempt to put our working data online. We may have used better data for
our study, as I have rummaged through the files looking to put data
online without giving alot of attention to the contents (I am not paid
for this). Please contact me at
bryane.michael@eueconomics.org
if something looks wrong or you want better data. |