Disaster Data

Wes Longhofer came a cross a new database: The Centre for Research on the Epidemiology of Disaster’s International Disaster Database. Site: http://www.emdat.be/

The site has cross-national data on both natural and human-caused disasters since 1900.  Apparently, the most costly industrial accident in history was a chemical spill in Spain in 2002.  Didn’t know that…

The dataset will be useful for our papers on environmental associations/policy reform/etc. Our prior work has generally found that environmental degradation variables (e.g., pollution) don’t do a good job of accounting for environmental mobilization or policy reform.  Reviewers have then suggested, on more than one occasion, that people may respond to vivid disasters (Three Mile Island, Exxon Valdez, etc), rather than actual degradation.  So, at one time David Frank pulled together a simple measure of disasters… but now someone has assembled a much more systematic dataset.

Disasters might also be an interesting issue to analyze as a dependent variable.  For instance, one wonders if strong environmental/health/safety laws, strong unions, or other factors reduce industrial accidents…  Maybe INGOs help, too… they do everything.  (kidding…)

The MacroDataGuide

Katerina Vrablikova, a visiting fellow at the UCI Center for the Study of Democracy, pointed me to a data website that I hadn’t seen before.  It is called The MacroDataGuide:

http://www.nsd.uib.no/macrodataguide/index.html

It is maintained by the Norwegian Social Science Data Services (apparently a branch of the Norwegian Ministry of Education and Research) to organize “contextual” variables for use with the European Social Survey.

It is a nice, clean, website with descriptive information on lots of country-level datasets.  It has all the big ones, and a few that are new to me.

The site provides a wealth of summary information:  topics covered by the dataset, the number of countries and time period covered, relevant references, and mundane-but-useful information such as the file format(s) available, cost, and links to documentation and (usually) the actual dataset.  There is also commentary on data quality, which is rare to see.

Definitely worth a look.

More Globalization Indices

Wade Cole sent me a link to a useful data source, the KOF index of globalization:  http://globalization.kof.ethz.ch/

They create 3 measures of globalization, reflecting economic (trade, FDI, barriers), social (communication), and political (embassies, international orgs, treaties) dimensions.

They rely in standard measures that are pretty familiar.  A full list of the measures (and weights used to create the indices) can be found here:  http://globalization.kof.ethz.ch/static/pdf/variables_2010.pdf

Coverage looks pretty solid — from 1970 to the present.  Overall, worth checking out.

WDI Reshape do file

I got a request for my stata code for reshaping the wdi 2010.  There is also code to add variable labels.  It is an alternative to using “wdireshape“.  You can download it here:  WDI 2010 reshape stata code.doc

Notes:

1.  The stata code is in a word “doc” file, rather than a stata “do” file.  That is because WordPress limits the filetypes you can upload.  Rather than putting it on my other website, I just pasted it into a word document.  You can just paste it back into a stata do file…

2.  You should download the “csv” version of the WDI.

3.  You need a computer with quite a bit of memory to run the reshape.  If you are short on memory, you can manually select a subset of the file and reshape it in smaller chunks that fit into your computer’s memory.  You can then “merge” the pieces together.

4.  It takes a long time to run if you do the whole file at once (hours).

WDI Reshape

As I mentioned previously, the WDI comes in a cumbersome format.  So, I was going to post the Stata code used to “reshape” it into a more useful format.  But it turns out that someone already created a Stata add-on to do it.  It is called “wdireshape”: http://ideas.repec.org/c/boc/bocode/s456955.html

Also, another helpful web page:

http://dss.princeton.edu/online_help/analysis/reshape_wdi.htm

WDI 2010 Is Out — And Free!

The World Bank has released the World Development Indicators 2010 — and it is freely downloadable in multiple file formats.

http://data.worldbank.org/data-catalog

This is great news.  You can just download a spreadsheet (excel or .csv).  No more messing with a CDROM or MS Access databases!  (Those who have worked with older versions know what I mean.)

It is still a bit of a pain to work with.  It is too big for my (older) version of Excel.  And, the format remains quirky:  years are columns, countries are rows, with variables stacked long (a column contains a the variable identifier). Fortunately, Stata’s “reshape” command can get it into a more useful format.  I can post the syntax if people are interested.

Growth of Commonwealth Universities

Danielle Logue has put together a really neat visualization of the historical proliferation of universities in the British Commonwealth.  As someone who thinks a lot about the growth of universities, I found it really interesting.

http://timothyhannigan.com/danielleMaps/dmap.php

Here’s a description with some of the context:

“This map is part of a larger doctoral research project by Danielle Logue, Said Business School, University of Oxford.  This project examines the changing composition of top management teams in over 500 universities across 37 countries of the British Commonwealth.  By conceptualising these leadership positions as constitutive of particular conceptions of control, it asks the question:  how do such conceptions of control spread in global, loosely structured fields, where there are not the usual suspects of organisational diffusion?  Amongst other findings, the research reveals the global diffusion of a finance ‘conception of control’, which will be demonstrated in an upcoming animated map.  Danielle is working with her DPhil colleague, Tim Hannigan at the Oxford Centre for Entrepreneurship and Innovation,  who provides the sophisticated technical expertise to produce such visualisations.  For further details, contact Danielle Logue (danielle.logue@sbs.ox.ac.uk) or Tim Hannigan (timothy.hannigan@sbs.ox.ac.uk).”

Development Finance Data

Wes sent me a link to the latest/greatest new source of data on international aid/development finance:

http://www.aiddata.org/home/index

They compile information on development finance (i.e., grants and loans) from governments and IGOs to developing countries for the period 1947-2009.

We are using it to expand on a paper, which we presented at ASA last August, that looked at the impact of World Bank “structural adjustment” loans on national income inequality. (We found that loans are associated with generally higher inequality in the 1980s; but not in the 1990s and not in Asia.)  This database will allow us to look at IMF loans, and other sources as well.

Also:  In the future, they plan to add data on aid from NGOs and private groups.  That will be really useful.

Updated IGO / INGO Membership Data

Allwyn Lim, working with Kiyo, has coded country IGO and INGO membership data from 2000-2007.  We hope to use this to extend our existing datasets.  However, we’ll need to do some checking (to watch out for discontinuities) first.

Allwyn’s coded disaggregated data on all UIA sub-types allowing for more nuanced analyses than in the past (e.g., separating ‘regional’ from truly ‘international’ INGOs).

The new dataset is on the password-protected part of the data archive at UC Irvine.

Substantively, the new data are quite interesting.  It looks like INGO memberships continue to grow incredibly quickly between 2000 and 2007.  My eyeball estimate is that the typical country grows by 20% in that period.  Wow.

> I’m attaching updated UIA NGO/IGO data for 2000-2007 in Excel. These
> are NGO/IGO memberships and not secretariats. There are two files:
>
> (1) “UIA 2000-2007″ has separate worksheets that replicate the tables
> from the respective yearbooks. I’ve retained all categories since
> people may want to use different combinations for their analyses.
>
> (2) “UIA Totals 2000-2007″ has NGO and IGO totals (sum of all
> categories A-U) in country-year format plus “newid3″ and “gurrid”
> where I could identify them.

International Communication and Global Culture

John Meyer emailed me about an interesting paper at ASA:

Rob Clark and Jason Hall presented a paper entitled “The International Telecommunications Network and Human Rights.”  The paper explores the idea that global telecommunication may be a useful measure of global cultural embeddedness, similar to “INGO membership”.  It turns out that their measure predicts human rights scores.

It is really important to keep developing measures of global embeddedness, going beyond what we have — which is pretty much just measures of international association (INGOs).

Obviously, INGOs are great.  John Boli & George Thomas’s book (Constructing World Culture) does a great job of explaining how INGOs are an important embodiment of world culture.  And, INGOs work really well in predicting a lot of things.  AND, people have largely come to accept INGOs as the “standard” way to test world polity effects.  But, it isn’t great to be wholly dependent on a single measure which, like all cross-national data, has its quirks.  Moreover, there’s a tendency to reify measures — to start thinking that INGOs = world culture, and to forget about other interesting stuff, like communication, media, movement of people/students, etc.

Anyhow, John Meyer had an exchange with the authors of this new paper and learned how they created their measure.  They started with a matrix of calls to & from each country (separately for incoming and outgoing calls).  Then they dichotomized — essentially creating dummies of whether any dyad has a relationship.  Finally, they used degree centrality — calculating the total number of other countries a given country is linked to.  Also, since telecommunication was strongly correlated with INGOs, they residualized the telecom variable to reduce collinearity.

The authors found that (residualized) incoming telecommunication had a positive effect on human rights scores.  Outgoing calls didn’t.

Seems like a reasonable approach.  Of course, one could think of other good ways to do it — which would be worth trying — such as normalizing by country size in some way, or dealing with the actual density of calls.  Also, it wasn’t entirely clear whether the zeros were all real or might include missing data.  Finally, it would be useful to see which countries score high/how.  I wondered:  Are the paper’s findings general to all cases, or mainly due to a few extreme “basket case” countries like North Korea, which might be outliers?

Anyhow, I was really glad to learn of this interesting paper.  It suggests a new direction for thinking about and operationalizing world polity/world society processes.  We should definitely be exploring this type of data.

Participation in International Tests

Tricia also put up a measure of national participation in international educational tests.

It is a neat idea that Chiqui mentioned a while back.  We didn’t discuss it extensively, but I think the idea was that participation in the IEA testing regime might affect national educational policies.  Participating in testing activates a sense of competition — putting nations in more of a ‘horesrace’ mentality.  And, it stratifies nations, which facilitates copying/diffusion.  You know who is ‘winning’ and might choose to emulate them.

New Environment Treaty Data

Tricia just posted some new environmental treaty data from UNEP, in STATA format.  It doesn’t cover as many treaties as David Frank’s dataset, but it covers 12 important ones and is updated through 2009.   Here’s her description:

Time Series from 1960-2009

Data Downloaded from the UNEP GEO Data Portal at: http://geodata.grid.unep.ch/

For treaties, includes all 12 treaties listed on the UNEP GEO data portal, except the UN Framework.  Treaty data is listed as missing “.” for years before the treaty existed, coded as “0” before a country joined, and “1” for all years after joining.  Variable name is official treaty name, original source and years of treaty in dataset.

Interesting Data Site

Marion Fourcade sent me the link of this interesting site, the Government Indicators Database published by the Inter-American Development Bank:

http://www.iadb.org/datagob/

It mainly aggregates standard datasets, with a fancy interface.  But, it has some governance measures that I hadn’t seen before.  And, it is certainly nice for quickly looking up data on a specific country.

NOTE:  It does have longitudinal data on many variables, though it takes some clicking to find it.

Health and Education Expenditure Data

Minzee also shares some recent data on government health and education expenditures.  Again, an excerpt from her description:

“Data (variable name: healthpcgt3 & edupcgt3) are operationalized as % health expenditure in total central government outlay and % education expenditure in total central government outlay, respectively. Data come from IMF Government Financial Statistics. For 1990 and later years, data come from IMF GFS CD . For earlier years, data come from IMF GFS yearbooks. In both cases, central government data are used.”

Child Rights INGO Membership Data

Minzee Kim has generously shared her child rights INGO membership data.  I quote from her description of the data:

“Country membership in core child rights INGO data come from the Yearbook of International Organizations (various years), which reports country memberships annually from 1982 and periodically from 1967. Using the 2006-2007 version, all organizations under the following seven relevant subjects were examined.

1. Society/youth
2. Society/infants
3. Human Rights Organizations
4. Humanitarian Orgaizations
5. innovative change/Rights
6. Social Activity/Welfare
7. Society/Disadvantaged

595 child well-being related INGOs were indentified and 93 of those were identified as core child rights INGOs. Among the 93 core child rights INGOs, 53 had membership information. Based on the 53 child rights INGOs, country membership in child rights INGOs were constructed. County membership information in the 53 child rights INGOs were constructed using 1980, 1985, 1990, 1995, 2000 and 2005 versions of the Yearbook of International Organizations.”

Minzee:  Thanks for your hard work and your willingness to share the data!