Master IPE Data ResourceOfficial CodebookBenjamin A.T. Graham

Version 1.3January 9, 2016

The following codebook describes the component datasets included in the Master

IPE Data Resource, Version 1.3. The dataset introduction paper for this version of

the dataset is available at SSRN: http://ssrn.com/abstract=2534067

The Nature of this Resource

This data resource merges together 73 of the most commonly used datasets related

to the field of international political economy (IPE). We attempt to draw all data

from its original source – i.e. downloading the data directly from the scholar or

institution that produced the data. For some of the broader datasets included, such

as the World Development Indicators, only those variables deemed relevant to IPE

were retained. In cases where I draw data from replication datasets, we retain only

those variables that are newly created by the study in question; we drop control

variables that are necessary to the replication file but are drawn from other sources.

The unit of analysis in this dataset is country-year, with unique observations

identified by Gleditsch-Ward number (gwno) and year. Alternative country

identifiers, i.e. Correlates of War (COW) codes and International Financial Statistics

(IFS) codes are provided for convenience, but the Gleditsch-Ward numbers are the

basis on which component datasets are merged together. Two alternative versions

of the dataset are also produced, one of which treats COW codes as the primary

identifier and one of which limits the length of the panel to the period 1988-2014.

Countries not present in the Gleditsch-Ward system (i.e. those with populations of

less than 250,000) are excluded from this dataset.

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Annual coverage for this dataset begins in 1800, but most component datasets begin

coverage somewhere in the post-WWII period. Version 1.3 contains 73 component

datasets, with bi-annual updates/expansions planned for the foreseeable future.

Version 1.3 exists in three different forms:

1. Full Data by Gleditsch-Ward Number: This is the “primary” version of

the resource.

2. Full Data by COW code: This version has unique observations by COW

code and year.

3. Partial Data by Gleditsch-Ward Number: This version contains only

observations from 1975-present, making for a smaller file.

Variable Naming

This codebook lists the name and description of all variables included in the

resource, organized by component dataset. Each component data source is given a

unique suffix. This facilitates restriction of the dataset to only a few of its component

parts. For example, if one wanted to retain only the Strøm et al. powersharing data

(suffix IDC) and the Credendo Group political risk data from Graham, Johnston, and

Kingsley (suffix ON), the following stata command would suffice:

keep gwno ccode country year *_IDC *_ON

Transparency of the Data Management Process

I have attempted to make every step in the creation of this data resource entirely

transparent. All data management is conducted in Stata 14. We include all of the

following files on dataverse:

1. A raw data file for each component dataset, i.e. the files that we

downloaded from the web or were e-mailed by authors. These files are in

various formats, but primarily .dta .csv .xls and .xlsx

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2. Each of the 73 merge prep .do files that were used to prepare these

component datasets to be merged together. These files append Gleditsch-

Ward Numbers, name and label variables, and engage in data cleaning as

necessary (though we keep this cleaning as minimal as possible). The

most common form of cleaning involves dropping observations that

would result in duplicate observations by Gleditsch-Ward number and

year.

3. Two dependency files titled “Append_ids.do” and “country to gwno

[ongoing].do” The Append_ids file is called by most of the merge prep do

files. It appends the Gleditsch-Ward Numbers, the COW Country Codes,

and the IFS codes for each country by country name. The “country to

gwno [ongoing].do” file only appends the Gleditsch-Ward numbers, and is

used by a small subset of the merge prep do files in place of the

Append_ids file.

4. The master merge .do file that merges these 73 component datasets

together.

5. Three versions of the completed data resource (main version, COW

version, and short-panel version).

The dataverse URL for this study is: https://dataverse.harvard.edu/dataset.xhtml?

persistentId=doi:10.7910/DVN/28003

Request for Comments and Recommendations

This project remains a work in progress. Recommendations, error corrections, and

other comments or questions are welcomed. In particular, I appreciate suggestions

for datasets that should be added to this resource. The author may be contacted at

benjamin.a.graham [at] usc.edu.

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A Note on raw country names and country codes

The primary alteration made to raw datasets is the appending of new country id

numbers. We retain raw country names and (where relevant) raw country ID

numbers in the final dataset to lend additional transparency. The raw country name

variables are given as countryname_raw_[suffix] where [suffix] is the 2-3 letter

suffix associated with the component dataset in question.

A Note Regarding Citation:

Any publications using data drawn from this resource should include citation to the

original source(s) of the data used. Citation information for each component dataset

is included in this codebook. It is important to give direct credit to the scholars and

institutions that created the original data compiled here.

Less importantly, if you use this resource in your work and find that the data

management efforts it represents are valuable to a particular project, the

appropriate citation for the resource itself is:

Graham, Benjamin A.T. 2015. “The International Political Economy Data Resource.”

Available at SSRN: http://ssrn.com/abstract=2534067.

Funding

Primary funding for this project is provided by the Center for International Studies

at the University of Southern California. Additional funding for undergraduate

research assistance is provided by the Dornsife Student Opportunities for Advanced

Research (SOAR); Dornsife Summer Undergraduate Research Fund (SURF); and

Provost’s Undergraduate Research Fund (PURF), all programs of the University of

Southern California.

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Research Assistance

This project would not be possible without the contributions of a large number of

research assistants. Major contributions to this project have been made by the

following individuals: Rod Albuyeh, Joey Huddleston, Jacob Tucker, Gloria Koo,

Katrin Vasku, and Patrick Vossler. Additional contributions have been made by:

Matthew Biggar, India Bulkeley, Matthew Cheung, Katherine Lee, Mariana Rangel-

Padilla and Jocelyn Zhao.

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Table of Contents

Economic Datasets.............................................................................................8Fernandez et al. (Schindler) De Facto Capital Controls [FK]..............................................8Economic Freedom of the World [EF]......................................................................................10Aizenmann, Chin and Ito Open Economy Trilemma [TR]..................................................10COW Materials Capabilities (CINC) [MC].................................................................................11COW Military Expenditures [CX]................................................................................................12SIPRI Military Expenditures [SI]................................................................................................12Nordhaus, Oneal and Russett MID Propensity [MP]............................................................13Claessens and van Horen Bank Ownership [CV]..................................................................13Bodea and Hicks Central Bank Independence Data [BH]..................................................14Fitch Sovereign Risk Ratings [FI]...............................................................................................14S&P Sovereign Risk Ratings [SP]................................................................................................15IMF Contract Intensive Money [CIM]........................................................................................15IMF Agreement Data [BCG].......................................................................................................... 16Financial Development and Structure Dataset [FS]............................................................16IMF International Financial Statistics: Exchange Rates [ER]...........................................17Laeven Valencia Financial Crisis Episodes [LV]....................................................................18Levy-Yeyati and Sturzenegger Exchange Rate Regimes [LY]...........................................18LexisNexis-based Information Measures [LX]......................................................................19Newspaper Circulation Data from the 2010 WDI [WB].....................................................19I/B/E/S Analyst Coverage (Graham, Johnston, and Kingsley) [IB]................................20FDI Data from UNCTAD and the International Trade Centre [UTD]..............................20US Department of Treasury, List of Tax Havens [TH].........................................................21Road Measures from the World Bank [WB]...........................................................................21Emma Ashford Oil Exports Data [AE].......................................................................................22PENN World Tables Exchange Rates [PW]..............................................................................22World Development Indicators from the World Bank [WB]............................................23Augmented Data: GDP, GDPPC, Growth, Population, Labor/Capital Ratio [FULL]....25Long-Term Interest Rates OECD [OECD].................................................................................26ILOSTAT – International Labor Organization [ILO].............................................................26Li Tax Incentives Data [LI]........................................................................................................... 27World Bank Doing Business Indicators [BZ].........................................................................27World Financial Development Indicators, Bank Activity [WFD]....................................29World Bank MFN Tariff Data [MFN]..........................................................................................31

Political Datasets.............................................................................................32Alvarez et al. (ACLP) Regime Type [AC]...................................................................................32Polity IV Democracy [P4]..............................................................................................................32Database of Political Institutions (DPI ) [PI].........................................................................33Geddes, Wright and Frantz Regime Type Data [GE]............................................................37Boix, Miller, and Rosato Democracy Data [BX].....................................................................38System Level Democracy [DE].................................................................................................... 38Henisz Political Constraint Index (Polcon) [PC]...................................................................39Inclusion, Dispersion, and Constraint Data on Powersharing [IDC].............................39World Bank World Governance Indicators (WB_WGI) [WGI]..........................................41State Fragility Index (SFI) [SFI].................................................................................................. 42

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Graham Data on Bureaucratic Risk, Policy Risk, and Political Violence [BE].............43International Country Risk Guide (IRCG) [IC].......................................................................43Political Risk Data from the Credendo Group (Formerly ONDD) [ON].........................44Cingranelli-Richards (CIRI) Human Rights dataset [CR]...................................................44Freedom House: Freedom in the World [FH]........................................................................45Fariss Latent Human Rights Protection [FA].........................................................................46Economic Globalization and Collective Labor Rights Dataset [MU]...............................47Freedom House: Freedom of the Press [FH]..........................................................................48Reporters Without Borders: Freedom of the Press [FP]....................................................48HRV Transparency Data [HR]..................................................................................................... 49Transparency International Corruption Perceptions Index 2012 [TI]........................49Major Episodes of Political Violence (MEPV) [PV]...............................................................50Political Terror Scale [PTS]......................................................................................................... 51UCDP/PRIO Armed Conflict Dataset [PO]...............................................................................51PRIO Battle Deaths Dataset [BD]............................................................................................... 52Onset of Armed Conflict [AO]......................................................................................................53Patent Protection Index (Park 2008) [IP]..............................................................................54Strength of International Property Protection (Zhao 2006) [ZH]..................................54US Global Troop Deployment Data (Heritage Foundation) [GTD].................................55Transparency: WEF Global Competitiveness Dataset [WE]..............................................55Bilateral Investment Treaties (BIT) Count Data [BIT].......................................................56DESTA Cumulative International Trade Agreements [TA]...............................................57Membership in WTO, IMF, EU, NATO, and OECD [EU, IMF, NATO, WTO, OECD].........57

Social and Cultural Datasets........................................................................59Barro-Lee Educational Attainment Data [BL].......................................................................59Ethnic Power Relations Dataset (1946-2005) [EP].............................................................59Official Languages, NationsOnLine [LN]..................................................................................61Six Dimensions of Culture [6D]..................................................................................................63UN Emigrant Stock data [EMS]....................................................................................................64

Geographic Datasets.......................................................................................65Archipelagos Data [AP]................................................................................................................. 65Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) [CE]..........65

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Economic Datasets

Fernandez et al. (Schindler) De Facto Capital Controls [FK]

Suffix: FK

Description: This is a dataset of capital control restrictions on both inflows and outflows of ten categories of assets for 100 countries over the period 1995 to 2013. Building on the data first presented in Martin Schindler (2009), and on the analysis of the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions, this dataset includes additional asset categories, more countries, and a longer time period.

Data: http://www.columbia.edu/~mu2166/fkrsu/fkrsu.xls

Citation: Fernández, Andrés, Michael W. Klein, Alessandro Rebucci, Martin Schindler, and Martín Uribe. 2015. Capital Control Measures: A New Dataset. No. w20970. National Bureau of Economic Research.Paper: http://www.nber.org/papers/w20970

Original Schindler Paper: Schindler, Martin. 2009. "Measuring Financial Integration: A New Data Set." IMF Staff Papers 56: 222-38.

Years: Number of Countries:1995-2013 100

Variables:

ka_FKOverall restrictions index (all asset categories, bo only 1997 onwards) [FK]

kai_FKOverall inflow restrictions index (all asset categories, bo only 1997 onwards) [FK]

kao_FKOverall outflow restrictions index (all asset categories, bo only 1997 onwards) [FK]

eq_FK Average equity restrictions [FK]eqi_FK Equity inflow restrictions [FK]eqo_FK Equity outflow restrictions [FK]eq_plbn_FK Purchase locally by nonresidents (equity) [FK]eq_siln_FK Sale or issue locally by nonresidents (equity) [FK]eq_pabr_FK Purchase abroad by residents (equity) [FK]eq_siar_FK Sale or issue abroad by residents (equity) [FK]

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bo_FK Average bond restrictions [FK]boi_FK Bond inflow restrictions [FK]boo_FK Bond outflow restrictions [FK]bo_plbn_FK Purchase locally by nonresidents (bonds) [FK]bo_siln_FK Sale or issue locally by nonresidents (bonds) [FK]bo_pabr_FK Purchase abroad by residents (bonds) [FK]bo_siar_FK Sale or issue abroad by residents (bonds) [FK]mm_FK Average money market restrictions [FK]mmi_FK Money market inflow restrictions [FK]mmo_FK Money market outflow restrictions [FK]mm_plbn_FK Purchase locally by nonresidents (money market instruments) [FK]mm_siln_FK Sale or issue locally by nonresidents (money market instruments) [FK]mm_pabr_FK Purchase abroad by residents (money market instruments) [FK]mm_siar_FK Sale or issue abroad by residents (money market instruments) [FK]ci_FK Average collective investments restrictions [FK]cii_FK Collective investments inflow restrictions [FK]cio_FK Collective investments outflow restrictions [FK]ci_plbn_FK Purchase locally by nonresidents (collective investments) [FK]ci_siln_FK Sale or issue locally by nonresidents (collective investments) [FK]ci_pabr_FK Purchase abroad by residents (collective investments) [FK]ci_siar_FK Sale or issue abroad by residents (collective investments) [FK]de_FK Average derivatives restrictions [FK]dei_FK Derivatives inflow restrictions [FK]deo_FK Derivatives outflow restrictions [FK]de_plbn_FK Purchase locally by nonresidents (derivatives) [FK]de_siln_FK Sale or issue locally by nonresidents (derivatives) [FK]de_pabr_FK Purchase abroad by residents (derivatives) [FK]de_siar_FK Sale or issue abroad by residents (derivatives) [FK]cc_FK Average commercial credits restrictions [FK]cci_FK Commercial credits inflow restrictions [FK]cco_FK Commercial credits outflow restrictions [FK]fc_FK Average financial credits restrictions [FK]fci_FK Financial credits inflow restrictions [FK]fco_FK Financial credits outflow restrictions [FK]

gs_FKAverage guarantees, sureties and financial backup facilities restrictions [FK]

gsi_FKGuarantees, sureties and financial backup facilities inflow restrictions [FK]

gso_FKGuarantees, sureties and financial backup facilities outflow restrictions [FK]

di_FK Average direct investment restrictions [FK]dii_FK Direct investment inflow restrictions [FK]

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dio_FK Direct investment outflow restrictions [FK]ldi_FK Direct investment liquidation restrictions [FK]re_FK Average real estate restrictions [FK]rei_FK Real estate inflow restrictions [FK]reo_FK Real estate outflow restrictions [FK]re_pabr_FK Purchase abroad by residents (real estate) [FK]re_plbn_FK Purchase locally by nonresidents (real estate) [FK]re_slbn_FK Sale locally by nonresidents (real estate) [FK]

Economic Freedom of the World [EF]

Suffix: EF

Description: This dataset contains indicators of economic freedom for 153 countries. Only the top marginal income tax rate is kept.

Data: http://www.freetheworld.com/datasets_efw.html

Citation: Gwartney, James, Robert Lawson, Joshua Hall, James Gwartney, Robert Lawson, and Joshua Hall. "2014 Economic Freedom Dataset, published in Economic Freedom of the World: 2014 Annual Report." (2014).

Years: Number of Countries:1970-2012 153

Variables:top_margintax_EF

Top marginal income tax rate [EF]

propright_EF Protection of property rights [EF]

Aizenmann, Chin and Ito Open Economy Trilemma [TR]

Suffix: TR

Description: This dataset measures the degree of achievement along the three dimensions of the “trilemma” hypothesis: monetary independence, exchange rate stability, and financial openness.

Data: http://web.pdx.edu/~ito/trilemma_indexes.htm

Citation:

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Aizenman, Joshua, Menzie D. Chinn, and Hiro Ito. 2008. “Assessing the emerging global financial architecture: Measuring the trilemma's configurations over time.” National Bureau of Economic Research, No. w14533.

Codebook: http://web.pdx.edu/~ito/ReadMe_trilemma_indexes.pdf

Years: Number of Countries:1960-2010 187

Variables:ers_TR Exchange Rate Stability Index [Tril]mi_TR Monetary Independenc Index [Tril]ka_open_TR Financial Openness Index [Tril]

COW Materials Capabilities (CINC) [MC]

Suffix: MC

Description: This dataset contains information on military, population, energy and production data nad the CINC index.

Citations:Singer, J. David, Stuart Bremer, and John Stuckey. (1972). "Capability Distribution, Uncertainty, and Major Power War, 1820-1965." in Bruce Russett (ed) Peace, War, and Numbers, Beverly Hills: Sage, 19-48.

Singer, J. David. (1987). "Reconstructing the Correlates of War Dataset on Material Capabilities of States, 1816-1985" International Interactions, 14: 115-32.

Codebook: http://www.correlatesofwar.org/COW2%20Data/Capabilities/NMC_Documentation.pdf

Version: 3.02

Years: Number of Countries:1816-2001 212

Variables:cinc_MC CINC score [COW]irst_MC Iron and Steel Production [COW]

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milex_MC Military Expenditures [COW]milper_MC Military Personnel [COW]energy_MC Energy Consumption [COW]tpop_MC Total Population [COW]upop_MC Urban Population [COW]

COW Military Expenditures [CX]

Suffix: CX

Description: The National Material Capabilities data set contains annual values for total population, urban population, iron and steel production, energy consumption, military personnel, and military expenditure of all state members, currently from 1816-2007. The widely used Composite Index of National Capability (CINC) index is based on these six variables and included in the data set.

Data: http://www.correlatesofwar.org/COW2%20Data/Capabilities/nmc4.htm

Citation:Singer, J. David, Stuart Bremer, and John Stuckey. (1972). "Capability Distribution, Uncertainty, and Major Power War, 1820-1965." in Bruce Russett (ed) Peace, War, and Numbers, Beverly Hills: Sage, 19-48.

Singer, J. David. (1987). "Reconstructing the Correlates of War Dataset on Material Capabilities of States, 1816-1985" International Interactions, 14: 115-32.

Years: Number of Countries:1820-2007 199

Variables:milex_COW_CX Military Expenditures in millions (2011 USD) [COW]

SIPRI Military Expenditures [SI]

Suffix: SI

Description: This dataset contains data on the military expenditures of 171 countries over 25 years.

Data: http://www.sipri.org/research/armaments/milex/milex_database

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Citation:SIPRI Military Expenditure Database 2012, http://milexdata.sipri.org

Years: Number of Countries:1988-2013 171

Variables:milex_SIPRI Military Expenditures in millions (2011 USD) [SIPRI]

Nordhaus, Oneal and Russett MID Propensity [MP]

Suffix: MP

Description: This dataset contains information on the level of military spending in each country and its effect on democracy in that country and its relations with other countries.

Data: www.journals.cambridge.org/ino2012008

Citation:Nordhaus, William, John R. Oneal, and Bruce Russett. "The effects of the international security environment on national military expenditures: A multicountry study." International Organization 66.03 (2012): 491-513.

Years: Number of Countries:1951-2001 165

Variables:MID_phat_MP Preferred estimate of predicted probability by state and year

[MP]

Claessens and van Horen Bank Ownership [CV]

Suffix: CV

Description: This dataset contains information on the number of foreign banks in each country in a given year.

Data: http://www.dnb.nl/en/binaries/CvH%20Bank%20Ownership%20Database_def_tcm47-287454.xlsx

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Citation:Claessens, Stijn and Neeltje van Horen, 2013, "Foreign banks: Trends and impact", Journal of Money, Credit and Banking (forthcoming).

Years: Number of Countries: 1995-2009 137

Variable:foreignbkct_CV Count of foreign banks open in a given country in a given year

[CV]

Bodea and Hicks Central Bank Independence Data [BH]

Suffix: BH

Description: This dataset contains data on central bank independence. The data is an updated version of the Cukierman, Webb and Neyapti index by Bodea and Hicks.

Data: http://www.princeton.edu/~rhicks/data/cb_rh_data.zip

Citation:Bodea, Cristina, and Raymond Hicks. 2015. "Price Stability and Central Bank Independence: Discipline, Credibility, and Democratic Institutions." International Organization 69: 35-61.

Years: Number of Countries: 1972-2010 82

Variable:cbi_BH Central Bank Independence score [BH]cbiw_BH Weighted Central Bank Independence score [BH]reform_BH Reform year (yes/no) [BH]

Fitch Sovereign Risk Ratings [FI]

Suffix: FI

Description: This dataset contains information on short-term and long-term credit risk for foreign currency and long-term risk for local currency in each country.

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Data: https://www.fitchratings.com/gws/en/sector/overview/sovereigns

Historical data courtesy of Allison F. Kingsley, University of Vermont.

Year: Number of Countries:1994-2012 108

Variables:fitch_foreign_lt_raw_FI Foreign Currency Sovereign Risk, Long Term [Fitch] (raw)fitch_foreign_st_FI Foreign Currency Sovereign Risk, Short Term [Fitch] (raw)fitch_local_lt_raw_FI Local Currency Sovereign Risk, Long Term [Fitch] (raw)fitch_local_lt_FI Local Currency Sovereign Risk, Long Term [Fitch]fitch_foreign_lt_FI Foreign Currency Sovereign Risk, Long Term [Fitch]

S&P Sovereign Risk Ratings [SP]

Suffix: SP

Description: This dataset contains information on short-term and long-term credit risk for both local and foreign currency.

Data: http://www.standardandpoors.com/ratings/sovresearch/en/us

Historical data courtesy of Allison F. Kingsley, University of Vermont.

Years: Number of Countries:1975-2013 122

Variables:local_lt_SP Local Currency Sovereign Risk, Long Term [S&P]foreign_lt_SP Foreign Currency Sovereign Risk, Long Term [S&P]tc_SP Transfer and Convertability Risk [S&P]tc_raw_SP Transfer and Convertability Risk [S&P] (raw)local_lt_raw_SP Local Currency Sovereign Risk, Long Term [S&P] (raw)foreign_lt_raw_SP Foreign Currency Sovereign Risk, Long Term [S&P] (raw)

IMF Contract Intensive Money [CIM]

Suffix: CIM

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Description: This dataset contains information about the amount of contract intensive money in each country.

Citation: IMF, International Financial Statistics, Contract Intensive Money

Codebook: http://www.imf.org/external/pubs/ft/mfs/manual/index.htm

Years: Number of Countries:1948-2012 184

Variables:cim_CIM Contract intensive money [IMF_IFS]cim_adj_CIM Contract intensive money adjusted [IMF_IFS]

IMF Agreement Data [BCG]

Suffix: BCG

Description: This dataset contains data about whether countries are under an IMF agreement in a given country year.

Citation: Bauer, Molly, Cesi Cruz, and Benjamin Graham. 2012. "Democracies Only: When Do Imf Agreements Serve as a Seal of Approval?". The Review of International Organizations 7: 33-58.

Codebook:

Years: Number of Countries:1960-2008 188

Variables:under_BCG Whether a country was under an agreement in the year

(1) or not (0) [BCG]undertype_BCG Type of agreement [BCG]

Financial Development and Structure Dataset [FS]

Suffix: FS

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Description: This dataset contains information about the size, activity, and efficiency of financial intermediaries and markets.

Citation: Thorsten Beck, Aslı Demirgüç-Kunt and Ross Levine, (2000), "A New Database on Financial Development and Structure," World Bank Economic Review 14, 597-605. (An earlier version was issued as World Bank Policy Research Working Paper 2146.)

Codebook: http://www1.worldbank.org/finance/assets/images/Fs02_web.pdf

Years: Number of Countries:1960-2011 175

Variables:pcred_depbank_gdp_FS Private credit by deposit money banks to GDP (%)

[FS]pcred_depbank_other_gdp_FS

Private credit by money banks and other financial institutions to GDP (%) [FS]

IMF International Financial Statistics: Exchange Rates [ER]

Suffix: ER

Description: This dataset contains the exchange rate arrangement reported to the IMF by each participating country.

Citation: IMF, International Financial Statistics. "Country Tables, Exchange Rates, Official Rates, June, 2013." International Financial Statistics. International Monetary Fund. July, 2013.

Codebook: https://www.imf.org/external/np/mfd/er/2004/eng/0604.htm

Years: Number of Countries:1970-2010 196

Variables:ER_ER Exchange rate arrangement [IMF]

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Laeven Valencia Financial Crisis Episodes [LV]

Suffix: LV

Description: This dataset contains data on finanical crisis containment and resolution policies for 42 crisis episodes, and also includes data on the timing of currency crises and sovereign debt crises.

Data: http://www.economicsofcrisis.com/databases.html

Citation: Laeven, Luc, and Fabián Valencia, 2008, “Systemic Banking Crises: A New Database,” IMF Working Paper 08/224, (Washington: International Monetary Fund).

Years: Number of Countries:1971-2008 57

Variables:debt_crisis_LV Debt crisis [LV]currency_crisis_LV Currency crisis [LV]sysbank_crisis_LV Systemic banking crisis [LV]

Levy-Yeyati and Sturzenegger Exchange Rate Regimes [LY]

Suffix: LY

Description: This dataset contains a de facto classification 17 of exchange rate regimes that reflects actual rather than announced policies.

Citation: Levy-Yeyati, Eduardo, and Federico Sturzenegger. "Classifying exchange rate regimes: Deeds vs. words." European Economic Review 49, no. 6 (2005): 1603-1635.

Codebook: http://www.utdt.edu/Upload/_126797338585330000.pdf

Years: Number of Countries:1974-2004 183

Variables:class_5way_LY 5-way classification [LY&S]class_3way_LY 3-way classification [LY&S]

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LexisNexis-based Information Measures [LX]

Suffix: LX

Description: This dataset contains information on the number of English-language business and investment related articles published in a country in a given year.

Citation:Graham, Benjamin A.T., Noel Johnston, and Allison Kingsley. 2015. “The Capital Effects of Information Voids in Emerging Markets.” Working Paper.

Years: Number of Countries:1992-2012 171

Variables:

baselinemwp_LX Total Articles in LexisNexis [GKJ]investmentmwp_LX Investment Articles in LexisNexis (keyword) [GKJ]subjectmwp_LX Potentially Business Relevant Articles in LexisNexis

(subjects) [GKJ]ln_baselinemwp_LX Total Articles in LexisNexis (logged) [GKJ]ln_investmentmwp_LX

Investment Articles in LexisNexis (keyword) (logged) [GKJ]

ln_subjectmwp_LX Potentially Business Relevant Articles in LexisNexis (subjects) (logged) [GKJ]

Newspaper Circulation Data from the 2010 WDI [WB]

Suffix: WB

Description: This is the newspaper circulation data from the World Bank’s World Development Indicators. 2010 is the last version of the WDI in which the newspaper data was published.

Data: http://databank.worldbank.org/data/download/archive/WDIandGDF_excel_2010_12.zip

Citation: World Development Indicators, The World Bank (2010).

Years: Number of Countries:

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1961-2010 192

news_WB Daily newspapers (per 1,000 people) [WB]

I/B/E/S Analyst Coverage (Graham, Johnston, and Kingsley) [IB]

Suffix: IB

Description: This dataset contains information on the number of unique I/B/E/S analysts covering firms based in a country in a given year.

Citation: Graham, Benjamin A.T., Noel P. Johnston, and Allison Kingsley. 2015. “The Capital Effects of Information Voids in Emerging Markets.” Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2533651

Years: Number of Countries:1993-2015 94

Variables:

reportcount_IB Number of Unique I/B/E/S Analyst Reports [GJK]firmcount_IB Number of Unique Firms Covered in I/B/E/S Analyst Reports

[GJK]analystcount_IB Number of Unique I/B/E/S Analysts [GJK]lnfirmcount_IB Number of Unique Firms Covered in I/B/E/S Analyst Reports

(logged) [GJK]lnreportcount_IB Number of Unique I/B/E/S Analyst Reports (logged) [GJK]lnanalystcount_IB Number of Unique I/B/E/S Analysts (logged) [GJK]

FDI Data from UNCTAD and the International Trade Centre [UTD]

Suffixes: UTD

Description: This dataset contains information on inward FDI flows and stocks as reported to the UNCTAD. Values are in US$ millions.

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Codebook: http://www.investmentmap.org/docs/invmap-userguide-en.pdf

Years: Number of Countries:2002-2011 191

Variables:fdi_flows_UTD FDI inflows US [UNCTAD]fdi_stocks_UTD FDI instocks US [UNCTAD]

US Department of Treasury, List of Tax Havens [TH]

Suffix: TH

Description: This dataset contains a list of known tax havens.

Citation: Gravelle, Jane G. 2009. "Tax Havens: International tax avoidance and evasion." Congressional Research Service, Library of Congress. http://www.fas.org/sgp/crs/misc/R40623.pdf

Years: Number of Countries:1800- 2013 211

Variables:taxhav_TH Tax Havens [DOT]

Road Measures from the World Bank [WB]

Suffix: WB

Description: This contains the measures of countries’ road networks and road density. They are pulled from the 2014 version of the WDI as that is the last version of the dataset in which they were reported.

Data: http://databank.worldbank.org/data/download/archive/WDI_excel_2014_04.zip

Citation: World Development Indicators, The World Bank (2014).

Years: Number of Countries:

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1961-2014 192

roads_WB Roads, total network (km) [WB]roaddensity_WB Road density (km of road per 100 sq. km of land area) [WB]

Emma Ashford Oil Exports Data [AE]

Suffix: AE

Description: This dataset contains data on oil revenues generated from supplementing the WDI data with data from the BP Statistical Index and the Energy Information Administration.

Citation: Emma Ashford, “Crude Power: The Foreign Policy of Oil-Exporting States” (diss., University of Virginia, 2013).

Years: Number of Countries:1960-2001 188

Variables:combinedoil_AE Oil Exports as a Share of GDP [AE]

PENN World Tables Exchange Rates [PW]

Suffix: PW

Description: This dataset contains the nominal exchange rates reported in the Penn World Tables.

Ciation:Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" forthcoming American Economic Review, available for download at www.ggdc.net/pwt

Codebook: http://www.rug.nl/research/ggdc/data/pwt/v80/exchange_rates_in_pwt80.pdf

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Years: Number of Countries:1950-2011 166

Variables:currency_unit_PW Currency Unit [Penn]xr_PW Exchange rate, national currency/USD (market+estimated)

[Penn]

World Development Indicators from the World Bank [WB]

Suffix: WB

Description: These data are initially reported by host governments, then cleaned and collated by the World Bank. The variables in this dataset are only a subset of the total variables available from WDI and include those deemed most likely to be of used to international relations scholars.

Data: http://data.worldbank.org/products/wdi

Citation: World Development Indicators, The World Bank (2015).

Years: Number of Countries:1961-2013 192

area_WB Surface area (sq. km) [WDI]area_land_WB Land area (sq. km)armed_WB Armed forces personnel, total [WDI]deaths_bt_WB Battle-related deaths (number of people) [WDI]debt_cgov_WB Central government debt, total (% of GDP) [WDI]

ex_agri_WB Agricultural raw materials exports (% of merchandise exports) [WDI]

ex_food_WB Food exports (% of merchandise exports) [WDI]ex_fuel_WB Fuel exports (% of merchandise exports) [WDI]ex_mfg_WB Manufactures exports (% of merchandise exports) [WDI]ex_oresmet_WB Ores and metal exports (% of merchandise exports) [WDI]exp_WB Exports of goods and services (% of GDP) [WDI]extdebt_WB External debt stocks (% of GNI) [WDI]

extdebt_avgint_WB Average interest on new external debt commitments (%) [WDI]

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extdebt_avgintoff_WB Average interest on new external debt commitments, official (%) [WDI]

extdebt_avgintpriv_WB Average interest on new external debt commitments, private (%) [WDI]

extdebt_intpaygni_WB Interest payments on external debt (% of GNI) [WDI]

extdebt_intpayperex_WB Interest payments on external debt (% of exp of g,s & primary

extdebt_pv_WB Present value of external debt (current US$) [WDI]extdebt_tot_WB External debt stocks, total (DOD, current US$) [WDI]

fdidollars_WB Foreign direct investment, net inflows (BoP, current US$) [WDI]

fdi_inper_WB Foreign direct investment, net inflows (% of GDP) [WDI]fdi_outper_WB Foreign direct investment, net outflows (% of GDP) [WDI]gdp_WB GDP (constant 2005 US$) [WDI]growth_WB GDP growth (annual %) [WDI]gdppc_WB GDP per capita (constant 2005 US$) [WDI]gini_WB GINI index [WDI]gni_WB GNI (constant 2005 US$) [WDI]gnipc_WB GNI per capita (constant 2005 US$) [WDI]inf_mort_WB Mortality rate, infant (per 1000 live births) [WDI]inflation_WB Inflation, consumer prices (annual%) [WDI]

insfin_svc_WB Insurance and financial services (% of commercial service exports) [WDI]

internet_WB Internet users (per 100 people) [WDI]

internet_br_WB Fixed broadband Internet subscribers (per 100 people) [WDI]

journal_WB Scientific and technical journal articles [WDI]legal_rt_WB Strength of legal rights index (0=weak to 12=strong) [WDI]lending_intrate_WB Lending interest rate (%) [WDI]life_exp_WB Life expectancy at birth, total (years) [WDI]

lit_WB Literacy rate, adult total (% of people ages 15 and above) [WDI]

migrant_per_WB International migrant stock (% of population) [WDI]migrant_tot_WB International migrant stock, total [WDI]mobile_WB Mobile cellular subscriptions (per 100 people) [WDI]patapps_WB Patent applications, residents [WDI]pop_WB Population, total [WDI]pop_den_WB Population density (ppl per sq km of land area) [WDI]pop_urb_WB Urban population (% of total) [WDI]workingpop_WB Population ages 15-64 (% of total)power_out_WB Power outages in firms in a typical month (number) [WDI]portfolio_WB Portfolio equity, net inflows (BoP, current US$) [WDI]

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reer_WB Real effective exchange rate index (2010 = 100) [WDI]remittances_WB Personal remittances, received (% of GDP)reserves_im_WB Total reserves in months of imports [WDI]reserves_tot_WB Total reserves (includes gold, current US$) [WDI]rir_WB Real interest rate (%) [WDI]

risk_prem_WB Risk premium on lending (lending rate minus treasury bill rate, %) [WDI]

surdef_WB Cash surplus/deficit (% of GDP)tax_rev_WB Tax revenue (% of GDP) [WDI]tech_rnd_WB Technicians in R&D (per million people) [WDI]tele_WB Telephone lines (per 100 people) [WDI]trade_WB Trade (% of GDP) [WDI]trade_services_WB Trade in services (% of GDP)trdmk_apps_WB Trademark applications, total [WDI]natresource_rents_WB Total natural resources rents (% of GDP)

govt_consump_WB General government final consumption expenditure (% of GDP)

GNI_growth_WB GNI per capita growth (annual %)capform_WB Gross fixed capital formation (% of GDP)capformraw_WB Gross capital formation (constant 2005 US$)elec_consump_WB Electric power consumption (kWh per capita)

Augmented Data: GDP, GDPPC, Growth, Population, Labor/Capital Ratio [FULL]

Suffix: full, IPE

Description: I use the GDP and population data from the Penn World Tables to supplement missing values in the WDI data to create “full” variabels for population, gdp, gdp per capita, and growth. I also create a labor to capital formation variable using the WDI data from the World Bank.

Ciation:Graham, Benjamin A. T., The International Political Economy Data Resource (January 26, 2015). Available at SSRN: http://ssrn.com/abstract=2534067 or http://dx.doi.org/10.2139/ssrn.2534067

Years: Number of Countries:1950-2011 161

gdp_full GDP (constant 2005 US$) [FULL]

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gdppc_full Gross Domestic Product Per Capita [FULL]growth_full GDP growth (annual %) [FULL]pop_full Population, total [FULL]lngdp_full GDP (constant 2005 US$) [FULL] loggedlngdppc_full Gross Domestic Product Per Capita [FULL] loggedlngrowth_full GDP growth (annual %) [FULL] loggedlnpop_full Population, total [FULL] logged

lcratio Ratio of working population to gross capital formation (2005 US $)

lnlcratio Ratio of working population to gross capital formation (2005 US $, logged)

Long-Term Interest Rates OECD [OECD]

Suffix: OECD

Descripion: This dataset includes a broad range of indicators for OECD countries. Here, we draw only long-term interest rates.

Data: http://stats.oecd.org/

Citation:OECD (2015), OECD Stat, (database), http://stats.oecd.org/.

Years: Number of Countries:2010-2014 34

ltinterest_OECD Long-term interest rates [OECD]

ILOSTAT – International Labor Organization [ILO]

Suffix: ILO

Description: This dataset contains labor statistics from the international labor organization for various countries.

URL: http://www.ilo.org/ilostat/faces/oracle/webcenter/portalapp/pagehierarchy/

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Page131.jspx?_afrLoop=530031617961158&clean=true#%40%3F_afrLoop%3D530031617961158%26clean%3Dtrue%26_adf.ctrl-state%3Dxrbhfkbv0_9

Years: Number of Countries:2000-2013 201

unitlaborcost_ILO Mean nominal hourly labour cost per employee (Local Currency) [ILO]

Li Tax Incentives Data [LI]

Suffix: LI

Description: This dataset contains a measure of the presence of different types of tax incentives including value added tax, corporate income tax, property tax, licensing fees, import dutiesand sales taxes.

Citation: Li, Quan. "Democracy, Autocracy, and Tax Incentives to Foreign Direct Investors: A Cross-National Analysis." Journal of Politics 68, no. 1 (2006): 62-74.

Number of Countries:202

Variables:taxincentsum_LI

Sum of six incentives, two all kinds [LI]

World Bank Doing Business Indicators [BZ]

Suffix: BZ

Description: This dataset contains variables that measure barriers to starting a business within each country including the number of days to get permits, costs of starting a business, etc.

Citation: World Bank. Doing Business 2013. Published 2012. www.doingbusiness.org

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Codebook: http://www.doingbusiness.org/methodology/methodology-note

Years: Number of Countries:2004-2013 181

Variables:rank_BZ Ease of Doing Business Rank [WB_Biz]rank_sb_BZ Starting a Business Rank [WB_Biz]sb_proc_BZ Starting a business, procedures (number) [WB_Biz]sb_time_BZ Starting a business, time (days) [WB_Biz]sb_cost_BZ Starting a business, cost (% of income percapita) [WB_Biz]sb_paid_BZ Starting a business, paid in min. cap (% of income per capita)

[WB_Biz]rank_cp_BZ Dealing with Construction Permits Rank [WB_Biz]cp_proc_BZ Dealing with Construction Permits, procedures (number) [WB_Biz]cp_time_BZ Dealing with Construction Permits, time (days) [WB_Biz]cp_cost_BZ Dealing with Construction Permits, cost (% of income per capita)

[WB_Biz]rank_ge_BZ Getting Electricity Rank [WB_Biz]ge_proc_BZ Getting Electricity, procedures (number) [WB_Biz]ge_time_BZ Getting Electricity, time (days) [WB_Biz]ge_cost_BZ Getting Electricity, cost (% of income per capita) [WB_Biz]rank_rp_BZ Registering Property Rank [WB_Biz]rp_proc_BZ Registering Property, procedures (number) [WB_Biz]rp_time_BZ Registering Property, time (days) [WB_Biz]rp_cost_BZ Registering Property, cost (% of income per capita) [WB_Biz]rank_gc_BZ Getting Credit Rank [WB_Biz]gc_legal_BZ Getting Credit, stregth of legal rights index (0-10) [WB_Biz]gc_info_BZ Getting Credit, depth of credit information index (0-6) [WB_Biz]gc_pub_BZ Getting Credit, public registry coverage (% of adults) [WB_Biz]gc_priv_BZ Getting Credit, private bureau coverage (% of adults) [WB_Biz]rank_pi_BZ Protecting Investors Rank [WB_Biz]pi_disc_BZ Protecting Investors, extent of disclosure index (0-6) [WB_Biz]pi_dl_BZ Protecting Investors, extent of director liability index (0-10)

[WB_Biz]pi_shsu_BZ Protecting Investors, ease of shareholder suits index (0-10)

[WB_Biz]pi_ip_BZ Protecting Investors, strength of investor protection index (0-10)

[WB_Biz]rank_pt_BZ Paying Taxes Rank [WB_Biz]pt_pay_BZ Paying Taxes, payments (number per year) [WB_Biz]pt_time_BZ Paying Taxes, time (hours per year) [WB_Biz]pt_prof_BZ Paying Taxes, profit tax (%) [WB_Biz]

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pt_lab_BZ Paying Taxes, labor tax and contributions (%) [WB_Biz]pt_other_BZ Paying Taxes, other taxes (%) [WB_Biz]pt_tot_BZ Paying Taxes, total tax rate (% profit) [WB_Biz]rank_tr_BZ Trading Across Borders Rank [WB_Biz]tr_exdo_BZ Trading Across Borders, documents to export (number) [WB_Biz]tr_exti_BZ Trading Across Borders, time to export (days) [WB_Biz]tr_exco_BZ Trading Across Borders, cost to export (US$ per container)

[WB_Biz]tr_imdo_BZ Trading Across Borders, documents to import (number) [WB_Biz]tr_imti_BZ Trading Across Borders, time to import (days) [WB_Biz]tr_imco_BZ Trading Across Borders, cost to import (US$ per container)

[WB_Biz]rank_ec_BZ Enforcing Contracts Rank [WB_Biz]ec_time_BZ Enforcing Contracts, time (days) [WB_Biz]ec_cost_BZ Enforcing Contracts, cost (% of claim) [WB_Biz]ec_proc_BZ Enforcing Contracts, procedures (number) [WB_Biz]rank_ri_BZ Resolving Insolvency Rank [WB_Biz]ri_time_BZ Resolving Insolvency, time (years) [WB_Biz]ri_cost_BZ Resolving Insolvency, cost (% of estate) [WB_Biz]ri_out_BZ Resolving Insolvency, outcome (0 as piecemeal sale and 1 as going

concern) [WB_Biz]ri_reco_BZ Resolving Insolvency, recovery rate (cents on the dollar) [WB_Biz]

World Financial Development Indicators, Bank Activity [WFD]

Suffix: WFD

Description: This dataset contains information on the characteristics of the banking sector within each country.

Data: http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=global-financial-development#

Citation: World Bank. World Financial Development Indicators, Bank Activity Indicators Global Financial Development Database (GFDD), Bank Activity Indicators, The World Bank.

Martin Cihák, Asli Demirgüç-Kunt, Erik Feyen and Ross Levine, 2012. "Benchmarking Financial Systems Around the World." World Bank Policy Research Working Paper 6175, World Bank, Washington, D.C.

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Codebook:http://databank.worldbank.org/data/views/variableselection/selectvariables.aspx?source=global-financial-development#

Years: Number of Countries:1960-2011 198

Variables:frmlacct_WFD Account at a formal financial institution (% age 15+) (WB_wfd)bk_acct_WFD Bank accounts per 1,000 adults (WB_wfd)bk_branch_WFD Bank branches per 100,000 adults (WB_wfd)finconst_WFD Firms identifying access to finance as a major constraint (%)

(WB_wfd)firms_bf_WFD Firms using banks to finance investments (%) (WB_wfd)firms_bw_WFD Firms using banks to finance working capital (%) (WB_wfd)firms_loc_WFD Firms with a bank loan or line of credit (%) (WB_wfd)firms_chksv_WFD Firms with a checking or savings account (%) (WB_wfd)loancollat_WFD Value of collateral needed for a loan (% of the loan amount)

(WB_wfd)wc_bfin_WFD Working capital financed by banks (%) (WB_wfd)fd_gdp_WFD Financial system deposits to GDP (%) (WB_wfd)dc_priv_WFD Domestic credit to private sector (% of GDP) (WB_wfd)bkconc_WFD Bank concentration (%) (WB_wfd)bkcrisis_WFD Banking crisis dummy (1=banking crisis, 0=none) (WB_wfd)depos_gdp_WFD Bank deposits to GDP (%) (WB_wfd)forbnkast_WFD Foreign bank assets among total bank assets (%) (WB_wfd)forbnk_WFD Foreign banks among total banks (%) (WB_wfd)h_stat_WFD H-statistic (WB_wfd)nr_loan_WFD Loans from nonresident banks (amounts outstanding) to GDP

(%) (WB_wfd)fb_cons_WFD Consolidated foreign claims of BIS reporting banks to GDP (%)

(WB_wfd)gpd_liab_WFD Gross portfolio debt liabilities to GDP (%) (WB_wfd)gpe_liab_WFD Gross portfolio equity liabilities to GDP (%) (WB_wfd)marketcap_WFD Stock market capitalization to GDP (%) (WB_wfd)compratio_WFD Number of listed companies per 1,000,000 people (WB_wfd)stockvol_WFD Stock price volatility (WB_wfd)

World Bank MFN Tariff Data [MFN]

Suffix: MFN

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Description: This is data that member governments supply annually on the tariffs they apply normally under the non-discrimination principle of most-favoured nation (MFN). Data on lower preferential duties under free trade agreements or preferential schemes for developing countries are available for some members.

Citation:World Bank. (2014).Most-Favored Nation Tariff Data. Data retrieved April 2014, from World Trade Organization: Tariff Analysis Online.

Year: Number of Countries:1981-2010 167

Variables:MFNtariff_MFN MFN Applied Tariff Rate (unweighted %)

[MFN]

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Political Datasets

Alvarez et al. (ACLP) Regime Type [AC]

Suffix: AC

Descripion: This dataset contains regime variables that classify countries from dictatorships to democracies.

Citation:Alvarez, Mike, JoséAntonio Cheibub, Fernando Limongi, and Adam Przeworski. 1996. "Classifying Political Regimes." Studies In Comparative International Development 31: 3-36.

Codebook: http://www.u.arizona.edu/~mishler/PrzeworskiCodebook.PDF

Years: Number of Countries:1950-1990 135

Variables:AUT_AC Same as LAWS, adjusted for transition cases, legislature, 0 if

dem, 1 if bureau [ACLP]DIVIDED_AC Same as LAWS, adjusted for transition cases, legislature, 0 if

dem, 1 if bureaucracy, 2 if autocracy [ACLP]INST_AC Political regimes, 0 if dictatorship, 1 if parliamentary

democracy, 2 if mixed democracy 3 if presidential democracies [ACLP]

INST2_AC Same as INST except for cases in a transition from above [ACLP]

LAWS_AC Legislature, 0 if dem, 1 if bureaucracy, 2 if autocracy [ACLP]MOBILIZE_AC Political parties, 0 if democracy, 1 if dictatorship with parties, 2

if dictatorship without parties [ACLP]REG_AC Dummy 1 for dictatorships, 0 for democracies [ACLP]

Polity IV Democracy [P4]

Suffix: P4

Description: This dataset contains information about political regimes, including each country’s polity score, state collapse, and political violence

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Citation: Marshall, Monty G., Ted Robert Gurr. 2012. "Polity IV Project: Political Regime Characteristics and Transitions, 1800-2012.” http://www.systemicpeace.org/polity/polity4.htm

Codebook: http://www.systemicpeace.org/inscr/p4manualv2012.pdf

Years: Number of Countries:1800-2014 184

Variables:fragment_P4 Polity fragmentation [Polity IV]democ_P4 Institutionalized democracy [Polity IV]autoc_P4 Institutionalized autocracy [Polity IV]polity_P4 Combined polity score [Polity IV]polity2_P4 Revised combined polity score [Polity IV]durable_P4 Regime durability [Polity IV]xconst_P4 Executive constraints [Polity IV]parreg_P4 Regulation of participation [Polity IV]parcomp_P4 Competitiveness of participation [Polity IV]polcomp_P4 Political competition [Polity IV]change_P4 Total change in polity value [Polity IV]sf_P4 State failure [Polity IV]regtrans_P4 Regime transition [Polity IV]

Database of Political Institutions (DPI ) [PI]

Suffix: PI

Description: This dataset contains information about the party system, political parties, and political orientations within each country.

Citation: Keefer, Philip. 2010. DPI 2010: Database of Political Institutions: Changes and Variable Definitions. Development Research Group, World Bank.

Thorsten Beck, George Clarke, Alberto Groff, Philip Keefer, and Patrick Walsh. "New tools in comparative political economy: The Database of Political Institutions." 15:1, 165-176 (September), World Bank Economic Review. 2001.

Codebook: http://siteresources.worldbank.org/INTRES/Resources/469232-1107449512766/DPI2012_Codebook2.pdf

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Years: Number of Countries:1975-2010 178

Variables:system_PI Political System [DPI]yrsoffc_PI Chief Executive Years in Office [DPI]finittrm_PI Finite Term in Office [DPI]yrcurnt_PI Years Left in Current Term [DPI]multpl_PI Can Chief Executive Serve Multiple Terms [DPI]military_PI Is Chief Executive a Military Officer? [DPI]defmin_PI Is Defense Minister a Military Officer? [DPI]percent1_PI President Percentage of Votes, first round [DPI]percentl_PI President Percentage of Votes, last round [DPI]prtyin_PI Party of Chief Executive Length of Time in Office [DPI]execme_PI Name of Executive Party [DPI]execrlc_PI Chief Executive Party Orientation [DPI]execnat_PI Chief Executive Party: Nationalist [DPI]execrurl_PI Chief Executive Party: Rural [DPI]execreg_PI Chief Executive Party: Regional [DPI]execrel_PI Chief Executive Party: Religious [DPI]execage_PI Age of Chief Executive Party [DPI]allhouse_PI Does Party of Executive Control All Houses? [DPI]

nonchief_PIParty affiliation of Non-Chief Executive in Systems with bothPresident and PM [DPI]

totalseats_PI Total Seats in Legislature [DPI]gov1me_PI Name of Largest Government Party [DPI]gov1seat_PI Number of Seats of Largest Government Party [DPI]gov1vote_PI Vote Share of Largest Government Party [DPI]gov1rlc_PI Largest Government Party Orientation [DPI]gov1nat_PI Largest Government Party: Nationalist [DPI]gov1rurl_PI Largest Government Party: Rural [DPI]gov1reg_PI Largest Government Party: Regional [DPI]gov1rel_PI Largest Government Party: Religious [DPI]gov1age_PI Age of Largest Government Party [DPI]gov2me_PI Name of 2nd Largest Government Party [DPI]gov2seat_PI Number of Seats of 2nd Largest Government Party [DPI]gov2vote_PI Vote Share of 2nd Largest Government Party [DPI]gov2rlc_PI 2nd Largest Government Party Orientation [DPI]gov2nat_PI 2nd Largest Government Party: Nationalist [DPI]gov2rurl_PI 2nd Largest Government Party: Rural [DPI]gov2reg_PI 2nd Largest Government Party: Regional [DPI]

34

gov2rel_PI 2nd Largest Government Party: Religious [DPI]gov2age_PI Age of 2nd Largest Government Party [DPI]gov3me_PI Name of 3rd Largest Government Party [DPI]gov3seat_PI Number of Seats of 3rd Largest Government Party [DPI]gov3vote_PI Vote Share of 3rd Largest Government Party [DPI]gov3rlc_PI 3rd Largest Government Party Orientation [DPI]gov3nat_PI 3rd Largest Government Party: Nationalist [DPI]gov3rurl_PI 3rd Largest Government Party: Rural [DPI]gov3reg_PI 3rd Largest Government Party: Regional [DPI]gov3rel_PI 3rd Largest Government Party: Religious [DPI]gov3age_PI Age of 3rd Largest Government Party [DPI]govoth_PI Number of Other Government Parties [DPI]govothst_PI Number of Seats of Other Government Parties [DPI]govothvt_PI Vote Share of Other Government Parties [DPI]opp1me_PI Name of Largest Opposition Party [DPI]opp1seat_PI Number of Seats of Largest Opposition Party [DPI]opp1vote_PI Vote Share of Largest Opposition Party [DPI]opp1rlc_PI Largest Opposition Party Orientation [DPI]opp1nat_PI Largest Opposition Party: Nationalist [DPI]opp1rurl_PI Largest Opposition Party: Rural [DPI]opp1reg_PI Largest Opposition Party: Regional [DPI]opp1rel_PI Largest Opposition Party: Religious [DPI]opp1age_PI Age of Largest Opposition Party [DPI]opp2me_PI Name of 2nd Largest Opposition Party [DPI]opp2seat_PI Number of Seats of 2nd Largest Opposition Party [DPI]opp2vote_PI Vote Share of 2nd Largest Opposition Party [DPI]opp3me_PI Name of 3rd Largest Opposition Party [DPI]opp3seat_PI Number of Seats of 3rd Largest Opposition Party [DPI]opp3vote_PI Vote Share of 3rd Largest Opposition Party [DPI]oppoth_PI Number of Other Opposition Parties [DPI]oppothst_PI Number of Seats of Other Opposition Parties [DPI]oppothvt_PI Number of Votes of Other Opposition Parties [DPI]ulprty_PI Number of Non-Aligned Parties [DPI]numul_PI Number of Seats of Non-Aligned Parties [DPI]ulvote_PI Vote Share of Non-Aligned Parties [DPI]oppmajh_PI Does One Opposition Party have a Majority in the House? [DPI]oppmajs_PI Does One Opposition Party have a Majority in the Senate? [DPI]dateleg_PI Month Legislative Elections Held [DPI]dateexec_PI Month Presidential Elections Held [DPI]legelec_PI Legislative Election Held [DPI]exelec_PI Presidential Election Held [DPI]liec_PI Legislative Electoral Competitiveness [DPI]

35

eiec_PI Executive Electoral Competitiveness [DPI]mdmh_PI Mean District Magnitude House [DPI]mdms_PI Mean District Magnitude Senate [DPI]ssh_PI Number of Seats in Senate/Total Seats in Both Houses [DPI]plurality_PI Plurality [DPI]pr_PI Proportional Representation [DPI]housesys_PI Electoral Rule House [DPI]sensys_PI Electoral Rule Senate [DPI]thresh_PI Vote Threshold [DPI]dhondt_PI D'Hondt System [DPI]cl_PI Closed List [DPI]select_PI Candidate Selection [DPI]fraud_PI Vote Fraud [DPI]auton_PI Autonomous Regions [DPI]muni_PI Municipal Government [DPI]state_PI State Government [DPI]

author_PIState Government Authority over Taxing, Spending, or Legislating [DPI]

stconst_PI Are the Constituencies of the Senators the States/Provinces? [DPI]numgov_PI Number of Government Seats [DPI]numvote_PI Vote Share of Government Parties [DPI]numopp_PI Number of Opposition Seats [DPI]oppvote_PI Vote Share of Opposition Parties [DPI]maj_PI Margin of Majority [DPI]partyage_PI Average Age of Parties [DPI]herfgov_PI Herfindahl Index of Government Parties [DPI]herfopp_PI Herfindahl Index of Opposition Parties [DPI]herftot_PI Herfindahl Index Total [DPI]frac_PI Fractionalization Index [DPI]oppfrac_PI Opposition Fractionalization Index [DPI]govfrac_PI Government Fractionalization Index [DPI]tensys_strict_PI tensys_strict [DPI]tensys_PI System Tenure [DPI]checks_lax_PI checks_lax [DPI]checks_PI Checks and Balances [DPI]stabs_strict_PI Stability (Threshold: LIEC = 6) [DPI]stabs_PI Stability [DPI]stabns_strict_PI Stability, single chamber (Threshold: LIEC = 6) [DPI]stabns_PI Stability, single chamber [DPI]tenlong_strict_PI Longest Tenure of a Veto Player (Threshold: LIEC = 6) [DPI]tenlong_PI Longest Tenure of a Veto Player [DPI]tenshort_strict_PI Shortest Tenure of a Veto Player (Threshold: LIEC = 6) [DPI]

36

tenshort_PI Shortest Tenure of a Veto Player [DPI]polariz_PI Polarization [DPI]

Geddes, Wright and Frantz Regime Type Data [GE]

Suffix: GE

This dataset includes information about different types of political regimes, violence during regime failure events, different categories of regime failure events, etc.

Citation: Geddes, Barbara, Joseph Wright, and Erica Frantz. "Autocratic breakdown and regime transitions: A new data set." Perspectives on Politics 12.02 (2014): 313-331.

Codebook: http://sites.psu.edu/dictators/wp-content/uploads/sites/12570/2014/06/GWF-Codebook.pdf

Years: Number of Countries:1946-2010 120

Variables:spell_GE Time invariant count of number of years in power [Geddes]

duration_GE Time at risk of failure at time t [Geddes]

fail_GE Binary variable indicating regime failure (fail==1) [Geddes]fail_subsregime_GE Regime failure, transition to 1=democracy; 2=dictatorship;

3=failed state/does not existfail_type_GE Regime failure, type (howend) [Geddes]fail_violent_GE Regime failure, violence [Geddes]

regimetype_GE Regime type, including hybrids (10) [Geddes]

party_GE Party regime (including hybrids, oligarchy, and Iran) [Geddes]

personal_GE Personalist regime [Geddes]

military_GE Military regime (including military personel and indirect military) [Geddes]

monarch_GE Monarchy [Geddes]

Boix, Miller, and Rosato Democracy Data [BX]

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Suffix: BX

Description: This dataset gives a comprehensive, dichotomous measure of democracy where democratic country is one that satisfies conditions for both contestation and participation.

Citation:Boix, Carles, Michael K. Miller, and Sebastian Rosato. "A Complete Dataset of Political Regimes, 1800-2007." Comparative Political Studies (2013). Web. <https://www.princeton.edu/~cboix/Boix_Miller_Rosato%20--%20Final_CPS.pdf>.

Years:1800-2010

Variables:democracy_BX Democracy [Boix]sovereign_BX Sovereign Dummy [Boix]democracy_trans_BX Democratic Transition [Boix]democracy_breakdowns_BX Democratic Breakdown [Boix]democracy_duration_BX Democratic Duration [Boix]democracy_omitteddata_BX Democracy Omitted Data [Boix]

System Level Democracy [DE]

Suffix: DE

Description: These system-level democracy measures are built from the Boix et al. data above. This data was created by Fariss, Graham and Gartzke.

Citation:Boix, Carles, Michael K. Miller, and Sebastian Rosato. "A Complete Dataset of Political Regimes, 1800-2007." Comparative Political Studies (2013). Web. <https://www.princeton.edu/~cboix/Boix_Miller_Rosato%20--%20Final_CPS.pdf>.

Graham, Benjamin A. T. and Gartzke, Erik and Fariss, Christopher J., “Regime Type, Coalition Size, and Victory.” Forthcoming. Political Science Research and Methods. Available at SSRN: http://ssrn.com/abstract=1915353

Years: Number of Countries:1800-2010 194

Variables:democracy_share_DE System Level Democratic Share [Boix]

38

democracy_count_DE Count of Democracies in the System [Boix]lndemsys_DE Count of Democracies in the System (logged) [Boix]

Henisz Political Constraint Index (Polcon) [PC]

Suffix: PC

Description: This dataset measures underlying political structures and their ability to support credible policy commitments.

Citation: Henisz, Witold J. "Political Constraint Index." (2010).

Henisz, Witold J. 2000. “The Institutional Environment for Economic Growth.” Economics and Politics 12 (1): 1-31.

Henisz, Witold J. 2002. “The Institutional Evironment for Infrastructure Investment.” Industrial and Corporate Change 11 (2): 355-389.

Codebook: Henisz, Witold J. "POLCON 2005 codebook." Manuscript, University of Pennsylvania (2005). http://www-management.wharton.upenn.edu/henisz/

Years: Number of Countries:1800-2012 206

Variables:polconiii_PC Polcon III [Polcon]polconv_PC Polcon V [Polcon]polconvj_PC Polcon VJ [Polcon]l1_PC Effective legislative chambers [Polcon]l2_PC Effective second legislative chambers [Polcon]j_PC Independent judiciary [Polcon]f_PC Independent sub-federal entities [Polcon]

Inclusion, Dispersion, and Constraint Data on Powersharing [IDC]

Suffix: IDC

39

Description: The Inclusion, Dispersion, and Constraints dataset measures underlying political structures and their ability to support credible policy commitments.

Citation:Strøm, Kaare, Scott Gates, Benjamin A.T. Graham and Håvard Strand. Forthcoming.Inclusion, Dispersion, and Constraint: Powersharing in the World’s States, 1975-2010. British Journal of Political Science.

Years: Number of Countries:1975-2010 175

Variables:inclusive_IDC Inclusive powersharing [IDC]dispersive_IDC Dispersive Powersharing [IDC]constraining_IDC Constraining Powersharing [IDC]constsusp_IDC Constitution Suspended [IDC]treaty_IDC Treaty serving in lieu of a constitution [IDC]martiallaw_binary_IDC Martial Law [IDC]gcman_IDC Grand Coalition (mandated) [IDC]gcimp_IDC Grand Coalition (implemented) [IDC]unity_IDC National Unity Government [IDC]

gcseats1_IDCGrand Coalition by Seats (Two largest parties in government) [IDC]

gcseats2_IDCGrand Coalition by Seats (Excess Party in Coalition) [IDC]

gcseats3_IDCGrand Coalition by Seats (Either gscseats1 or gcseats2 = 1) [IDC]

gcnew_IDC gcman or unity = 1 [IDC]partynoethnic_IDC Ethnic Party Ban [IDC]mveto_IDC Mutual Veto [IDC]resman_IDC Reserved Executive Positions (Mandated) [IDC]resimp_IDC Reserved Executive Positions (Implemented) [IDC]resseats_IDC Reserved Seats (Mandated) [IDC]resseats2_IDC Reserved Seats Binary (Mandated) [IDC]resseatsimp_IDC Reserved Seats (Implemented) [IDC]relestablish_IDC State Establishment of Religion [IDC]relestablish_binary_IDC State Establisment of Religion [IDC]relrestrict_IDC State Restriction of (minority) religions [IDC]relconstp_IDC Religion Protected (Practice) [IDC]relconstd_IDC Religion Protected (Discrimination) [IDC]stconst_IDC Regional Constituencies in the Upper House [IDC]state_IDC State/Provincial Governments Locally Elected [IDC]state_dummy1_IDC state_dummy1_IDC [IDC]state_dummy2_IDC state_dummy2_IDC [IDC]

40

muni_IDC Municipal Governments Locally Elected [IDC]muni_dummy1_IDC muni_dummy1_IDC [IDC]muni_dummy2_IDC muni_dummy2_IDC [IDC]subtax_IDC Sub-National Tax Authority [IDC]subed_IDC Subnational Education Authority [IDC]subpolice_IDC Subnational Police Authority [IDC]fedunits_IDC Fedunits [IDC]auton_IDC Asymmetric Federalism [IDC]milleg_IDC Military Legislator Ban [IDC]miman_IDC Inclusive Military [IDC]mfound_IDC Foundational Military [IDC]milvote_IDC Constitutional Provision Against Military Voting [IDC]

milparty_IDCConstitutional Provision Against Military Party Membership [IDC]

milparty2_IDC Mandatory Party Membership for Military [IDC]jtenure_IDC Judicial Tenure [IDC]jtenure_dummy1_IDC jtenure_dummy1_IDC [IDC]jtenure_dummy2_IDC jtenure_dummy2_IDC [IDC]jcause_IDC Judges can be removed without cause [IDC]japptbr_IDC Judicial Appointment Authority Divided [IDC]japptbr_binary_IDC japptbr_binary_IDC [IDC]jconst_IDC Judicial Constitution [IDC]jrevman_IDC Judicial Review [IDC]violation_IDC Violation of Mandated Powersharing [IDC]pr_IDC Proportional Representation [IDC]

World Bank World Governance Indicators (WB_WGI) [WGI]

Suffix: WGI

Description: This dataset contains measures of political stability, government accountability, and rule of law within a country.

Citation: Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi. 2009. "Governance Matters VIII: Aggregate and Individual Governance Indicators, 1996-2008." World Bank Policy Research Working Paper 4978.

Codebook: http://info.worldbank.org/governance/wgi/resources.htm

Years: Number of Countries:1996-2011 195

41

Variables:VA_EST_WGI Voice and accountability, estimate [WB WGI]VA_PRANK_WGI Voice and accountability, % rank [WB WGI]PV_EST_WGI Political stability absence of violence, estimate [WB WGI]PV_PRANK_WGI Political stability absence of violence, % rank [WB WGI]GE_EST_WGI Government effectiveness, estimate [WB WGI]GE_PRANK_WGI Government effectiveness, % rank [WB WGI]RQ_EST_WGI Regulatory quality, estimate [WB WGI]RQ_PRANK_WGI Regulatory quality, % rank [WB WGI]RL_EST_WGI Rule of law, estimate [WB WGI]RL_PRANK_WGI Rule of law, % rank [WB WGI]CC_EST_WGI Control of corruption, estimate [WB WGI]CC_PRANK_WGI Control of corruption, % rank [WB WGI]

State Fragility Index (SFI) [SFI]

Suffix: SFI

Description: This dataset rates each country’s stability based upon political, social, and economic factors

Citation: Marshall, Monty G., and Benjamin R. Cole. "State Fragility Index and Matrix 2009." Center for Systemic Peace (2010). http://www.systemicpeace.org/inscr/inscr.htm

Codebook: http://www.systemicpeace.org/GlobalReport2011.pdf

Years: Number of Countries:1995-2011 166

Variables:sfi_SFI State fragility index [SFI]effect_SFI Effectiveness score [SFI]legit_SFI Legitimacy score [SFI]seceff_SFI Security effectiveness score [SFI]secleg_SFI Security legitimacy score [SFI]poleff_SFI Political effectiveness score [SFI]polleg_SFI Political legitimacy score [SFI]ecoeff_SFI Economic effectiveness score [SFI]ecoleg_SFI Economic legitimacy score [SFI]soceff_SFI Social effectiveness score [SFI]socleg_SFI Social legitimacy score [SFI]

42

Graham Data on Bureaucratic Risk, Policy Risk, and Political Violence [BE]

Suffix: BE

Description: Data on bureaucratic risk, policy risk and war risk.

Citation:Graham, Benjamin A.T. 2014. "Political Risk and New Firm Entry." Available on SSRN at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2166139

Years:1988-2013

Variables:Fbureau_BE Bureaucratic Risk [Graham]Fbureau_long_BE Bureaucratic Risk (extended) [Graham]Fpolicy_BE Policy Risk [Graham]Fviolence_BE Risk of Political Violence [Graham]

International Country Risk Guide (IRCG) [IC]

Suffix: IC

Description: This dataset uses a variety of metrics to assess the level of political risk within each country.

Citation: Political Risk Services Group. 2011. “International Country Risk Guide.”

Codebook: http://www.prsgroup.com/ICRG_Methodology.aspx

Years: Number of Countries:1984-2011 145

Variables:sociocon_IC Socioeconomic Conditions [ICRG]investprofile_IC Investment Profile [ICRG]govstab_IC Government Stability [ICRG]burqual_IC Bureaucratic Quality [ICRG]relpol_IC Religion in Politics [ICRG]

43

corruption_icrg_IC Corruption [ICRG]demacct_IC Democratic Accountability [ICRG]External_Conflict_IC External Conflict [ICRG]ethnictension_IC Ethnic Tension [ICRG]Internal_Conflict_IC Internal Conflict [ICRG]milpol_IC Politicization of the Military [ICRG]laworder_IC Law and Order [ICRG]icrg_index_IC Index of IRCG scores [ICRG]

Political Risk Data from the Credendo Group (Formerly ONDD) [ON]

Suffix: ON

Description: This dataset contains expert assessments of expropriation risk (government risk), transfer risk, and war risk. These ratings inform the premiums charged for political risk insurance. Credendo is the price leader in the industry.

Citation: Graham, Benjamin A.T., Allison F. Kingsley, and Noel P. Johnston. 2014. "Even Constrained Governments Steal: The Domestic Politics of Transfer and Expropriation Risks." http://ssrn.com/abstract=2106621

Codebook: http://www.delcredereducroire.be/en/country-risks/?OpenDocument

Years: Number of Countries:1992-2012 196

Variables:wargovrisk_ON

War and Government action risk (higher value = riskier) [ONDD]

warrisk_ON Risk of War (higher value = riskier) [ONDD]transrisk_ON Transfer risk (higher value = riskier) [ONDD]govrisk_ON Risk from expropriation and government action (higher value =

riskier) [ONDD]

Cingranelli-Richards (CIRI) Human Rights Dataset [CR]

Suffix: CR

44

Description: This dataset contains information on government adherence to 13 internationally recognized human rights in different countries throughout the world.

Citation: Cingranelli, David L. and David L. Richards. 2008. The Cingranelli-Richards Human Rights Dataset Version 2008.03.12.

Codebook:"Cingranelli, David L., and David L. Richards. 2008. The Cingranelli-Richards (CIRI) Human Rights Data Project Coding Manual Version 2008.3.13." (http://www.humanrightsdata.org/documentation/ciri_coding_guide.pdf)

Years: Number of Countries:1981-2007 200

Variables:physint_CR Physical integrity rights index [CIRI]disap_CR Disappearnace [CIRI]kill_CR Extrajudicial killing [CIRI]polpris_CR Political imprisonment [CIRI]tort_CR Torture [CIRI]assn_CR Freedom of assembly and association [CIRI]formov_CR Freedom of foreign movement [CIRI]dommov_CR Freedom of domestic movement [CIRI]old_move_CR Freedom of movement before 2007 [CIRI]speech_CR Freedom of speech [CIRI]elecsd_CR Electoral self-determination [CIRI]old_relfre_CR Freedom of religion before 2007 [CIRI]new_relfre_CR Freedom of religion from 2007 [CIRI]worker_CR Worker's rights [CIRI]wecon_CR Women's economic rights [CIRI]wopol_CR Women's political rights [CIRI]wosoc_CR Women's social rights [CIRI]injud_CR Independence of the judiciary [CIRI]

Freedom House: Freedom in the World [FH]

Suffix: FH

Description: This dataset includes measures of political and civil liberties.

45

Data: https://freedomhouse.org/report-types/freedom-world#.VbAczPlViko

Citation: Freedom House. 2015. Freedom in the World. https://freedomhouse.org/report-types/freedom-world#.VZV8p_lVikp

Years: Number of Countries:1972-2014 195

Variables:pl_FH Gastil index of political liberties [FH]cl_FH Gastil index of civil liberties [FH]

Fariss Latent Human Rights Protection [FA]

Suffix: FA

Description: This dataset includes several different measures of human rights protection.

Codebook: http://thedata.harvard.edu/dvn/dv/CJFariss/faces/study/StudyPage.xhtml;jsessionid=e7af33cc17dea625f160fbbfe463?globalId=doi:10.7910/DVN/24872&studyListingIndex=0_e7af33cc17dea625f160fbbfe463Citation: Fariss, Christopher, 2014, "Latent Human Rights Protection Scores Version 2", http://dx.doi.org/10.7910/DVN/24872 UNF:5:uYLNJHm5G1rDApL7kQzk0g== Human Rights Scores [Distributor] V4 [Version]

Years: Number of Countries:1949-2013 180

Variables:disap_FA 3 category ordered variable for disappearances from the

CIRI dataset [Fariss]kill_FA 3 category ordered variable from extra-judical killing the

CIRI dataset [Fariss]polpris_FA 3 category ordered variable for political imprisonment

from the CIRI dataset [Fariss]tort_FA 3 category ordered variable for torture from the CIRI

46

dataset [Fariss]amnesty_FA 5 category [Fariss]state_FA 5 category [Fariss]hathaway_FA 5 category ordered variable for torture from the

Hathaway (2002) article. [Fariss]itt_FA 6 category ordered variable for torture from the ITT

dataset [Fariss]genocide_FA a binary variable for genocide from Harff's 2003 APSR

article [Fariss]rummel_FA a binary variable for politicide/genocide based on data

from Rummel [Fariss]massive_repression_FA

a binary variable for massive repressive events taken from Harff and Gurr's 1988 ISQ article [Fariss]

executions_FA a binary variable taken from the World Handbook of political indicators [Fariss]

killing_FA binary version based on the UCDP one sided violence count data [Fariss]

additive_FA the CIRI Physint scale [Fariss]latentmean_FA the posterior mean of the latent variable (i.e. human

rights protection) [Fariss]latentsd_FA the standard deviation of the posterior estimates for

human rights protection [Fariss]

Economic Globalization and Collective Labor Rights Dataset [MU]

Suffix: MU

Description: This dataset includes indicators of labor rights for developing nations.

Citation: Layna Mosley and Saika Uno, 2007. Collective Labor Rights Dataset, University of North Carolina and University of Notre Dame.

Codebook: http://www.unc.edu/~lmosley/CPSDataAppendixJuly2007.pdf

Years: Number of Countries:1985-2002 90

Variables:laborrights_MU Weighted measure of the number of labor rights violations [MU]

47

Freedom House: Freedom of the Press [FH]

Suffix: FH

Description: Freedom House data on freedom of the press in countries.

Codebook: http://www.freedomhouse.org/sites/default/files/Methodology_0.pdf

Citation: Freedom House. Freedom of the Press Indicators. "Freedom in the World 2013."

Years: Number of Countries:1993-2012 198

Variables:sr_FH Numerical Score [FH]

ss_FH Free status [FH]

p_FH Printing press freedom [FH]b_FH Broadcast press freedom [FH]

Reporters Without Borders: Freedom of the Press [FP]

Suffix: FP

Description: An alternate freedom of the press measure from Reporters Without Borders.

Citation: Reporters Without Borders. "World Press Freedom Index". 2014. Web. 24 April 2015.

Codebook: http://rsf.org/index2014/en-index2014.php

Years: Number of Countries:2012-2014 177

Variables:ranking_FP Reporters without Borders Press Freedom Annual Ranking [FP]score_FP Reporters with Borders Press Freedom Score [FP]

48

HRV Transparency Data [HR]

Suffix: HR

Description: This dataset contains the HRV index value for each country, which measures transparency for a given country in a given year.

Data: http://0001c70.wcomhost.com/wp2/download-data/

Citation:Hollyer, James R., B. Peter Rosendorff, and James Raymond Vreeland. 2011. "Democracy and Transparency." The Journal of Politics 73: 1191-205.

Hollyer, James R., B. Peter Rosendorff, and James Raymond Vreeland. 2014. "Measuring Transparency." Political Analysis.

Years: Number of Countries:1980-2010 125

Variables:transparencyindex_HR The point estimate of the HRV index for each country

and year. [HR]transparencyindexub_HR

The estimated upper bound of the HRV index for each country and year. [HR]

transparencyindexlb_HR The estimated lower bound of HRV index for each country and year. [HR]

transparencyindexsd_HR The standard deviation of “HRV index” for each country and year. [HR]

transdiff_HR The estimated one-year change in HRV index for each country and year. [HR]

transdiffub_HR The estimated upper bound of a one year change in the HRV index for each country and year. [HR]

transdifflb_HR The estimated lower bound of a one year change in the HRV index for each country and year. [HR]

Transparency International Corruption Perceptions Index 2012 [TI]

Suffix: TI

49

Description: This dataset contains the Transparency International corruption index score for each country. Scores range 0-100, with zero meaning 0 highly corrupt and 100 meaning very transparent.

Data: http://cpi.transparency.org/cpi2012/

Citation: Transparency International. 2012. "Corruption Perceptions Index 2012." http://www.transparency.org/policy research/surveys indices/cpi

Codebook: http://cpi.transparency.org/cpi2012/in_detail/#myAnchor4

Years: Number of Countries:1946-2012 216

Variables:ti_cpi_TI Corruption perceptions index [TI]

Major Episodes of Political Violence (MEPV) [PV]

Suffix: PV

Description: This dataset contains information on major wars and other episodes of political violence that have occurred in a country.

Citation:Monty G. Marshall. 1999. Third World War. Lanham, MD: Rowman & Littlefield.

Marshall, Monty G. 2012. Center for Systemic Peace (CSP) Major Episodes of Political Violence, 1946-2012, URL: www.systemicpeace.org/warlist.htm.

Codebook: http://www.systemicpeace.org/inscr/MEPVcodebook2012.pdf

Year: Number of Countries:1946-2010 176

Variables:intind_PV War of Independence, Magnitude [MEPV]intviol_PV International Violence, Magnitude [MEPV]intwar_PV International Warfare, Magnitude [MEPV]civviol_PV Civil Violence, Magnitude [MEPV]civwar_PV Civil War, Magnitude [MEPV]ethviol_PV Ethnic violence, Magnitude [MEPV]

50

ethwar_PV Ethnic War, Magnitude [MEPV]inttot_PV Total interstate MEPVS, Magnitude [MEPV]civtot_PV Total civil and ethnic MEPVS, Magnitude [MEPV]actotal_PV Total MEPVS, Magnitude [MEPV]nborder_PV Number of states sharing a border [MEPV]totint_PV Sum of interstate MEPV magnitude scores for neighboring states

[MEPV]totciv_PV Sum of civil and ethnic MEPVs in neighboring states [MEPV]totalac_PV Sum of all MEPVs in neighboring states [MEPV]nint_PV Number of bodering states with international MEPVs [MEPV]nciv_PV Number of bodering states with civil or ethnic MEPVs [MEPV]nac_PV Number of bodering states with any MEPVs [MEPV]region_PV Region [MEPV]nregion_PV Number of states in region [MEPV]regint_PV Sum of interstate MEPV magnitude scores in region [MEPV]regciv_PV Sum of civil and ethnic MEPVs in region [MEPV]regac_PV Sum of all MEPVs in region [MEPV]nrint_PV Number of states in region with international MEPVs [MEPV]nrciv_PV Number of states in region with civil or ethnic MEPVs [MEPV]nrac_PV Number of states in region with any MEPVs [MEPV]

Political Terror Scale [PTS]

Suffix: PTS

Description: This dataset contains measures of political violence and terror coded from three different sources.

Citation:Gibney, Mark, Linda Cornett, Reed Wood, Peter Haschke, and Daniel Arnon. 2015. The Political Terror Scale 1976-2015. 20 June 2015, from the Political Terror Scale website: http://www.politicalterrorscale.org.

Codebook: http://www.politicalterrorscale.org/about/

Year: Number of Countries:1976-2014 192

Variables:politterr_a_PTS Political Terror Scale based on Amnesty International [PTS]politterr_s_PTS Political Terror Scale based on the US State Department [PTS]politterr_HRW_PTS Political Terror Scale based on HRW [PTS]

51

UCDP/PRIO Armed Conflict Dataset [PO]

Suffix: PO

Description: This dataset contains measures of conflict intensity and involvement

Citation:Gleditsch, Nils Petter, Peter Wallensteen, Mikael Eriksson, Margareta Sollenberg, and Håvard Strand. "Armed conflict 1946-2001: A new dataset." Journal of peace research 39, no. 5 (2002): 615-637.

Codebook: https://www.prio.org/Global/upload/CSCW/Data/UCDP/2009/Codebook_UCDP_PRIO%20Armed%20Conflict%20Dataset%20v4_2009.pdf

Year: Number of Countries:1946-2008 188

Variables:id_PO Conflict identifier [PRIO]sidea_PO Identifies the country of SideA. Always the government side in an

internal conflict. [PRIO]sidea2nd_PO Name of state(s) supporting side A with troops [PRIO]incomp_PO Dyad incompatibility [PRIO]terr_PO Name of territory [PRIO]intensity_PO Intensity level (minor armed conflicts and wars) [PRIO]cumintensity_PO Cumulative intensity [PRIO]type_PO Conflict type [PRIO]region_PO Region of location [PRIO]

PRIO Battle Deaths Dataset [BD]

Suffix: BD

Description: This dataset builds on the UCDP/PRIO Armed Conflict Dataset to provide data on annual battle deaths.

Citation:Lacina, Bethany, and Nils Petter Gleditsch. "Monitoring trends in global combat: A new dataset of battle deaths." European Journal of Population/Revue européenne de Démographie 21, no. 2-3 (2005): 145-166.

52

Codebook: https://www.prio.org/Global/upload/CSCW/Data/PRIObd3.0_codebook.pdf

Year: Number of Countries:1946-2008 188

Variables:id_BD The unique conflict identifier. This corresponds to the conflict

IDs in the UCDP/PRIO Armed Conflict Dataset. [PRIO]bdeadlow_BD Low estimate of annual battle fatalities [PRIO]bdeadhigh_BD High estimate of annual battle fatalities [PRIO]bdeadbest_BD Best estimate of annual battle fatalities [PRIO]annualdata_BD Describes how specific the battle-deaths data is to a given year

[PRIO]source_BD Describes whether a source other than the UCDP/PRIO coding

rules is available [PRIO]

Onset of Armed Conflict [AO]

Suffix: AO

Description: This dataset gives a list of armed conflict onsets.

Citation:Strand, Havard. "Onset of armed conflict: A new list for the period 1946–2004, with applications." (2006).

Codebook: https://www.prio.org/Global/upload/CSCW/Data/README.txt

Year: Number of Countries:1946-2010 176

Variables:onset2_AO 2 years between onset variables coded [Strand]onset3_AO 3 years between onset variables coded [Strand]onset4_AO 4 years between onset variables coded [Strand]onset5_AO 5 years between onset variables coded [Strand]onset6_AO 6 years between onset variables coded [Strand]onset7_AO 7 years between onset variables coded [Strand]onset8_AO 8 years between onset variables coded [Strand]onset9_AO 9 years between onset variables coded [Strand]

53

Patent Protection Index (Park 2008) [IP]

Suffix: IP

Description: This dataset contains an index score based on the strength of patient protection laws and patient rights in each country. Note: the index score for 1990 is the average of 1960-1990

Citation: Park, Walter G. "International patent protection: 1960-2005." Research policy 37, no. 4 (2008): 761-766.

Codebook: http://147.9.1.186/cas/faculty/wgpark/upload/IPP-Research-Policy-May-2008-3.pdf

Years: Number of Countries:1990, 1995, 2000, 2005 122

Variables:ipp_index_IP International patent protection index [Park]

Strength of International Property Protection (Zhao 2006) [ZH]

Suffix: ZH

Description: This dataset contains measures of the strength in property protection rights in each country.Note: Zhao asserts that these measures are relatively stable, and assigns these values cross-sectionally in a study that uses data from 1993-2001. Therefore, we assume these values to be valid for those years and missing in all other years.

Citation: Zhao, Minyuan. "Conducting R&D in countries with weak intellectual property rights protection." Management Science 52, no. 8 (2006): 1185-1199.

Codebook: http://carlsonschool.umn.edu/Assets/45555.pdf

Years: Number of Countries:N/A 47

54

Variables:ippstrength_ZH Strength of international property protection, 1 for weak, 2 for

strong [Zhao]

US Global Troop Deployment Data (Heritage Foundation) [GTD]

Suffix: GTD

Description: Data regarding the number of U.S. troops deployed in foreign countries. Note: The Troop Deployment Dataset was merged with the more recent data provided by the Defense Manpower Data Center.

Data: www.heritage.org/Research/NationalSecurity/troopsdb.cfm www.dmdc.osd.mil/appj/dwp/reports.do?category=reports&subCat=milActDutReg

Citation:Tim Kane, Ph.D., Troop Deployment Dataset, 1950-2003, The Heritage Foundation, Center for Data Analysis, October 2004, www.heritage.org/Research/NationalSecurity/troopsdb.cfm.

“Total Military Personnel and Dependent End Strength By Service, Regional Area, and Country". Defense Manpower Data Center. July 31, 2014www.dmdc.osd.mil/appj/dwp/reports.do?category=reports&subCat=milActDutReg

Years: Number of Countries:1950-2014 176

Variables:troops_deployed_GTD Number of troops deployed in a foreign country [GTD]

Transparency: WEF Global Competitiveness Dataset [WE]

Suffix: WE

Description: From this dataset, we extract only the variable on transparency of government policy making.

Citation:

55

Schwab, Klaus. "The Global Competitiveness Report 2012-2013." Geneva, Switzerland (2010).

Codebook: http://www3.weforum.org/docs/CSI/2012-13/GCR_Chapter1.1_2012-13.pdf

Years: Number of Countries:2004-2010 39

Variables:tgpm_WE Transparency in government policy making [WEF]

Bilateral Investment Treaties (BIT) Count Data [BIT]

Suffix: BIT

Description: This dataset contains information on the number of bilateral investment treaties signed by each country.

Citations: Graham, Benjamin A.T., Noel P. Johnston and Allison Kingsley. 2015. "Even Constrained Governments Steal: The Domestic Politics of Transfer and Expropriation Risks." Working Paper. http://ssrn.com/abstract=2106621

Hicks, Raymond and Kristina Johnson. 2011. "The Politics of Globalizing Production: Why we See Investment Chapters in Preferential Trade Agreements." Paper presented at the conference on The Politics of Foreign Direct Investment, Princeton University, September 23.

Allee, Todd, and Clint Peinhardt. "Delegating differences: Bilateral investment treaties and bargaining over dispute resolution provisions." International Studies Quarterly 54, no. 1 (2010): 1-26.

An original dataset from Allee and Peinhardt was first supplemented by Johnston and Hicks and then by Graham, Johnston, and Kingsley, all drawing on the UNCTAD lists of agreements.

Codebook: http://dingo.sbs.arizona.edu/~ggoertz/pol595ist/allee_peinhardt2010.pdf

Years: Number of Countries:1959-2008 190

56

Variables:bitstodate_BIT BITs signed to date [BIT]lnbitstodate_BIT BITs signed to date [BIT] (logged)

DESTA Cumulative International Trade Agreements [TA]

Suffix: TA

Description: This dataset contains the cumulative number of PTAs signed by included countries.

Citations: Dür, Andreas, Leonardo Baccini, Manfred Elsig and Karolina Milewicz (2012) 'The Design of International Trade Agreements: Introducing a New Database', unpublished paper.

Codebook: https://www.wto.org/english/res_e/reser_e/ersd201110_e.pdf

Years: Number of Countries:1948-2009 201

Variables:cumpta_TA The cumulative number of PTAs signed [DESTA]

Membership in WTO, IMF, EU, NATO, and OECD [EU, IMF, NATO, WTO, OECD]

Suffixes: EU, IMF, NATO, WTO, OECD

Description: This dataset contains dummy variables specifying which international organization each country belongs to. These were created by Benjamin Graham.

Data:WTO: http://www.wto.org/english/thewto_e/whatis_e/tif_e/org6_e.htm IMF: http://www.imf.org/external/np/sec/memdir/memdate.htm NATO: http://www.nato.int/cps/en/natolive/topics_52044.htm EU: http://europa.eu/about-eu/countries/

Variables:WTOwhen_WTO year of accession [WTO]WTOmem_WTO binary, 1 if member, 0 if not [WTO]

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IMFwhen_IMF year of accession [IMF]IMFmem_IMF binary, 1 if member, 0 if not [IMF]NATOwhen_NATO year of accession [NATO]NATOmem_NATO binary, 1 if member, 0 if not [NATO]euwhen_EU year of accession [EU]eumem_EU binary, 1 if member, 0 if not [EU]oecd_joinyear_OE year of accession [OECD]oecd_OE binary, 1 if member, 0 if not [OECD]

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Social and Cultural Datasets

Barro-Lee Educational Attainment Data [BL]

Suffix: BL

Description: This dataset contains information about the years of schooling, primary, secondary, tertiary for population aged 25 and over in each country.

Data: http://www.barrolee.com/data/dataexp.htm

Citation:Barro, Robert J., and Jong-Wha Lee. 2012. "A new data set of educational attainment in the world, 1950-2010." Journal of Development Economics.

Years: Number of Countries:1950-2010 146

Variables:lu_BL % of no schooling attained [Barro-Lee]lp_BL % of primary schooling attained [Barro-Lee]lpc_BL % of complete primary schooling attained [Barro-Lee]ls_BL % of secondary schooling attained [Barro-Lee]lsc_BL % of complete secondary schooling attained [Barro-Lee]lh_BL % of tertiary schooling attained [Barro-Lee]lhc_BL % of complete tertiary schooling attained [Barro-Lee]yr_sch_BL Average years of schooling attained [Barro-Lee]yr_sch_pri_BL Average years of primary schooling attained [Barro-Lee]yr_sch_sec_BL Average years of secondary schooling attained [Barro-Lee]yr_sch_ter_BL Average years of tertiary schooling attained [Barro-Lee]

Ethnic Power Relations Dataset (1946-2005) [EP]

Suffix: EP

Description: This data contains information on ethnic conflict over 155 countries.

Citation:

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Wimmer, Andreas, Lars-Erik Cederman, and Brian Min. "Ethnic politics and armed conflict: a configurational analysis of a new global data set." American Sociological Review 74.2 (2009): 316-337.

Codebook:http://www.epr.ucla.edu/AppendixEthnicPolitics.pdf http://www.epr.ucla.edu/CodingMarkers.pdf

Years: Number of Countries:1946-2005 155

Variables:ethrelevant_EP Is ethnicity relevant (1=No, 2=Yes) [Wimmer]groups_EP Number of ethnopolitically relevant groups [Wimmer]egipgrps_EP Number of included groups [Wimmer]exclgrps_EP Number of excluded groups [Wimmer]exclpop_EP Size of excluded population [Wimmer]egippop_EP Size of Included population [Wimmer]ttlpop_EP Total ethnopolitically relevant population (in %) [Wimmer]discpop_EP Discriminated population (in %) [Wimmer]pwrlpop_EP Powerless population (in %) [Wimmer]olppop_EP Only Local Power population (in %) [Wimmer]olpspop_EP Only Local Power Separatist population (in %) [Wimmer]jppop_EP Junior Partner population (in %) [Wimmer]sppop_EP Senior Partner population (in %) [Wimmer]dompop_EP Dominant population (in %) [Wimmer]monpop_EP Monopoly population (in %) [Wimmer]maxexclpop_EP Size of largest excluded group (in %) [Wimmer]maxegippop_EP Size of largest Included group (in %) [Wimmer]maxpop_EP Size of largest group (in %) [Wimmer]minsnrptr_EP Size of smallest senior partner (in %) [Wimmer]elf_EP Ethnic fractionalization index based on ESEG data (i.e. only

ethnopolitically relevant groups) [Wimmer]pelf_EP Fractionalization of excluded groups [Wimmer]celf_EP Fractionalization of included groups [Wimmer]pcelf_EP Fractionalization of included groups (not taking excluded

groups into account) [Wimmer]polrqnew_EP Polarization (all groups calculated in relation to total

population) [Wimmer]poltrqnew_EP Polarization (all groups calculated in relation to total

population) [Wimmer]egiptpolrqnew_EP Polarization (Included groups calculated in relation to total

population) [Wimmer]egippolrqnew_EP Polarization (Included groups calculated in relation to

ethnopolitically relevant) [Wimmer]

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fegip_EP Formerly Included [Wimmer]fexcl_EP Formerly Excluded [Wimmer]dwegip_EP Downgrade within Included Groups [Wimmer]fmds_EP Formerly Monopoly, Dominant, Senior Partner, currently

Junior Partner [Wimmer]fmdcs_EP Formerly Monopoly, Dominant, currently Senior Partner

[Wimmer]fscj_EP Formerly Senior Partner, currently Junior Partner [Wimmer]fmdcj_EP Formerly Monopoly, Dominant, currently Junior Partner

[Wimmer]downgraded_EP Downgraded [Wimmer]dominant_EP Dominant dummy [Wimmer]monop_EP Monopoly dummy [Wimmer]snrptr_EP Senior Partner dummy [Wimmer]jnrptr_EP Junior Partner dummy [Wimmer]powerless_EP Powerless dummy [Wimmer]discrim_EP Discriminated dummy [Wimmer]olp_EP Only Local Power dummy [Wimmer]olps_EP Only Local Power Separatist dummy [Wimmer]pwrshare_EP Powersharing (0=No, 1=Yes) [Wimmer]nonpreg_EP Size of ethnoethnopolitically irrelevant population [Wimmer]rexclpop_EP Share of the excluded population relative to the

ethnopolitically relevant population [Wimmer]lnexclpop_EP ln (exclpop) [Wimmer]rexclpop2_EP Share of excluded population relative to ethnopolitically

relevant population (quadratic term) [Wimmer]rexclpop3_EP Share of excluded population relative to ethnopolitically

relevant population (cubic term) [Wimmer]lrexclpop_EP ln (share of excluded population relative to ethnopolitically

relevant population) [Wimmer]legippolrqnew_EP ln (polarization among included groups) [Wimmer]

Official Languages, NationsOnLine [LN]

Suffix: LN

Description: This dataset contains the first two official languages of each country

Citation: NationsOnline

Codebook: http://www.nationsonline.org/oneworld/index.html

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Years: Number of Countries:1800-2013 250Variables:lang1_LN Official language 1 [LANG]lang2_LN Official language 2 [LANG]

Religious Characteristics of States Dataset [RCS]

Suffix: RCS

Description: This dataset reports estimates of religious demographics for countries.

Data: http://www.thearda.com/Archive/Files/Downloads/BROWN_DL2.asp

Citation:Davis Brown and Patrick James. 2015. Religious Characteristics of State Dataset, Phase 1: Demographics. http://www.thearda.com/Archive/Files/Descriptions/BROWN.asp. An article of record is in progress.

Years: Number of Countries:1815-2010 198

Variables:indep_RCS State is independent on Dec. 31 of observed year [RCS]relmajid_RCS ID code of religion of majority of population (50 percent rounded

up to the next number) [RCS]chrpop_RCS Population of Christians [RCS]chrpct_RCS Percentage of Christians [RCS]jewpop_RCS Population of Jews [RCS]jewpct_RCS Percentage of Jews [RCS]muspop_RCS Population of Muslims (all branches and sects combined, including

Liminal but not Syncretic) [RCS]muspct_RCS Percentage of Muslims [RCS]hinpop_RCS Population of Hindus (Insufficient data or numbers to subdivide)

[RCS]hinpct_RCS Percentage of Hindus [RCS]budpop_RCS Population of Buddhists (all branches and schools of Buddhism

combined) [RCS]budpct_RCS Percentage of Buddhists [RCS]eacomppp_RCS Population of East Asian Religious Complex (combined Shintoist,

Confucianist, Taoist, Chinese Folk) [RCS]

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eacomppt_RCS Percentage of East Asian Religious Complex [RCS]shipop_RCS Population of Shintoists (insufficient data or numbers to

subdivided) [RCS]shipct_RCS Percentage of Shintoists [RCS]cnfpop_RCS Population of Confucianists insufficient data or numbers to

subdivide) [RCS]cnfpct_RCS Percentage of Confucianists [RCS]taopop_RCS Population of Taoists (insufficient data or numbers to subdivide)

[RCS]taopct_RCS Percentage of Taoists [RCS]indpop_RCS Population of Indigenous Religionists (combined animists,

shamanist, pagans, and other ethno-religiions not categorized elsewhere; includes Candomble, Quimbanda (but not Umbanda), Kumina, Palo (but not Palo Cristiano)) [RCS]

notrelpp_RCS Population of Not Religious (all identities of irreligion; including Atheist, Agnostic, None, No Religion, Non-Religious, Not Religious) [RCS]

notrelpt_RCS Percentage of Not Religious [RCS]unkpop_RCS Population of Unknown (all persons of religious – or irreligious –

status unknown) [RCS]unkpct_RCS Percentage of Unknown [RCS]

Six Dimensions of Culture [6D]

Suffix: 6D

Description: This data contains cultural indicators for 80 countries.

Data: http://www.geerthofstede.eu/dimension-data-matrix

Citation:Hofstede, Geert, Gert Jan Hofstede, and Michael Minkov. 1991. Cultures and Organisations-Software of the Mind: Intercultural Cooperation and Its Importance for Survival. McGraw-Hill: New York, NY.

Years: Number of Countries:1800-2014 80

Variables:pdi_6D Power Distance Index [6D]idv_6D Individualism versus Collectivism [6D]mas_6D Masculinity versus Femininity [6D]uai_6D Uncertainty Avoidance [6D]

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ltowvs_6D Long Term Orientation versus Short Term Orientation [6D]ivr_6D Indulgence versus Restraint [6D]

UN Emigrant Stock data [EMS]

Suffix: EMS

Description: Data on the global stock of emigrants from each country from the United Nations Population Division.

Data Source: http://www.un.org/en/development/desa/population/migration/data/estimates2/estimatesorigin.shtml

Citation:United Nations, Department of Economic and Social Affairs, Population Division (2013). Trends in International Migrant Stock: The 2013 Revision - Migrants by Destination and Origin. (United Nations database, POP/DB/MIG/Stock/Rev.2013/Origin)

Years: Number of Countries:1990, 2000, 2010, 2013 188

Variables:EmigrantStock_EMS Total migrant stock [UN]

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Geographic Datasets

Archipelagos Data [AP]

Suffix: AP

Description: This dataset contains information on the number of archipelagos in each country.

Citation: Graham, Benjamin A.T. and Kaare Strøm. 2015. “Variations in Federalism: Explaining Subnational Policy Authority.” Working Paper.

Years: Number of Countries:N/A 58

Variables:numislands_AP Number of Islands where the population is > 100000 [AP]archipelago_AP At least two islands [AP]

Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) [CE]

Suffix: CE

Description: This dataset contains variables relating each country in the world to the United States. Only the data for US-dyads (i.e. distance to the US, contiguity with the US, etc.) were kept for this dataset.

Data: http://www.cepii.fr/cepii/en/bdd_modele/presentation.asp?id=6http://www.cepii.fr/cepii/en/bdd_modele/presentation.asp?id=19

Citation: Mayer, T. & Zignago, S. (2011) Notes on CEPII's distances measures:the GeoDist Database CEPII Working Paper 2011-25 http://www.cepii.fr/anglaisgraph/workpap/pdf/2011/wp2011-25.pdf

Years: Number of Countries:

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1800-2013 222

Variables:english_off_CE

Official Language of the Country is English [CEPPI]

dist_US_CE Distance from US (km between most populous cities) [CEPPI]

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