this file has been compiled by Antonio Spilimbergo with the help of Rafael Romeu and Adrian De La Garza. It is based on the Reinhart-Rogoff (2002) June 7 2002 version. A readme.txt file explains the variables
This data set contains the data necessary to replicate Table 1 in James D. Fearon and David D. Laitin, Ethnicity, Insurgency, and Civil War, _American Political Science Review_ 97, 1 (March, 2003):1-17. A few additional variables are included relevant to claims made in the paper. See Fearon and Laitin, , at http://www.stanford.edu/group/ethnic/ for more information on the data contained here.
gdpppp95 data for Bosnia/Herzegovina; Bhutan; Brunei; */
SGCI are Specialized Governmental Credit Institutions
this file contains a subset of the COW Inter-State War Data, 1816-1997 The files were obtained from the site http://cow2.la.psu.edu/cow2dslist.htm organized as a panel
21 Jan 2003 16:30 date of creation
The following variables have been checked in check1.do:
1) rgdpch 2) ifsinf 3) pwtopen 4) wgbdef
Also spot-checking on regime variables
update fhp from website
the availability of some variables, like unemployment, are poor
Vintage: WEOOct2020Pub.
Vintage: WEOOct2014Pub.
Vintage: WEOOct2016Pub.
Vintage: WEOOct2017Pub.
Vintage: WEOOct2018Pub.
Vintage: WEOOct2019Pub.
This dataset is from jaimovich and Panizza (2006) Public Debt Around The World , please quote the source
Vintage: WEOJun2020Pub.
this file was complete as of 30 Sep 1998 17:15 . contact amar for the latest version.
this file was updated 29 Oct 1998 09:21 . contact amar to see if it's the latest version.
Table 2 regressions
Column 1, checks, no gdp
column 2, add GDP per capita
column 3, pr(forb) on rdtv_new
column 4, use trade statistics info variable
LOG FILE FOR RESULTS OF BANK WORKING PAPER
TABLE 1: CHECKS AND FISCAL COST
Column 1
column 2, add GDP/capita
column 3, controlling for terms of trade
TABLE 2, Incomplete info and fiscal costs
Delete Last Regression
Column 2, Table 2, using papr_new
Column 3, terms of trade statistics
Table 3, checks and forbearance
column 1: no control for gdp/cap
column 2, control for gdp/cap
column 3, RDTV_NEW and forbearance
column 4, availability of trade statistics
footnote 33 to Table 3 (effects of elections in competitive systems)
delete above, footnote 33 deleted b/c difference with competitive elections not large
Table 4, forbearance determinants generally and eiecav==7
Column 1: for all countries
column 2, for eiecav==7
Robustness results
First robustness result: including sull_new in Table 1 column 1
ABOVE IS TABLE 1, Col 2.
Check table 1, col 2 adding atl_new
check table 4 results with sull_new and atl_new (four regs).
sull_new and atl_new in table 3, cols 3 and 4
robustness of regressions to private credit and liqu. liabi
Table 1, columns 1 and 2, using liq liabilities and priv.cred
robustness of Table 4 results (w/, w/o eiecav) to liqliab, pri.cre
Table 3 forbearance results (checks first), robustness
robustness to ln(checks)
Table 1, col. 2 (with gdp/cap)
robustness of table 3 results to logcheck
robustness of table 4 results to log check
'TABLE ONE
TABLE 3
TAKE OUT LIEC<5, Reg 1, Table 1
TAKE OUT LIEC<7, Reg 1, Table 1
TAKE OUT LIEC<6, Reg 1, Table 2
TAKE OUT LIEC<7, Reg 1, Table 2
Table 4
PREVIOUS SYSTEM WRONG: included noncompetitive elections
financial liberalization
POLARIZATION
Alternatives to m2/GDP
CLUSTER BY YEAR
For Sachs Warner (1995) SW and WW openness: data from Trade Liberalization and Growth: New Evidence Romain Wacziarg and Karen Horn Welch - December 2003. Period for the liberalization dates begins in 1950 and ends in 2000.
Re WW: The liberalization date is intended to be the date after which all of the SW openness criteria are continuously met... Our choice of liberalization dates was based on annual tariff, nontariff,and black market premium primary data. In addition, a variety of secondary sources were utilized,... In our systematic review of the SW dates since 1990, we came to disagree with SW on the liberalization status or dates in the case of several countries.
For SW and WW openness: Those classifed as open at beginning of dataset in 1950 (coded as always open in original): CHE GBR HKG NOR PRT THA USA YEM. These have opendate coded as -9999.
For SW and WW openness indicates: Temporary liberalisations for BOL Bolivia 1956-79; CRI Costa Rica 1952-61; ECU Ecuador 1950-82; GTM Guatemala 1950-61; HND Honduras 1950-61; JAM Jamaica 1962-1973; KEN Kenya 1963-67; LKA Sri Lanka 1950-56, 1977-83; MAR Morocco 1956-64; NIC Nicaragua 1950-60; PER Peru 1948-67; SLV El Salvador 1950-61; SYR Syrian Arab Republic 1950-65; TUR Turkey 1950-53; VEN Venezuela 1950-59, 1989-93.
Source for er_parallel and er_official is Reinhart and Rogoff QJE 2004. Data from http://www.wam.umd.edu/~creinhar/Links.html. er_bmp=100*(er_parallel-er_official)/er_official if er_official~=. & er_parallel~=.
Source for xrat ppp cgdp cc ci cg p pc pg pi openc cgnp csave y rgdpl rgdpch rgdpeqa rgdpwok rgdptt openk kc kg ki grgdpch: Alan Heston, Robert Summers and Bettina Aten, Penn World Table Version 6.2, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, September 2006. http://pwt.econ.upenn.edu/php_site/pwt_index.php. Constant price entries are for 2000: rgdpl rgdpch rgdpeqa rgdpwok rgdptt openk kc kg ki grgdpch
Source for ckon gkon ikon expk impk ccur gcur icur expc impc : Penn World Tables version 6.1. Alan Heston, Robert Summers and Bettina Aten, Penn World Table Version 6.1, Center for International Comparisons at the University of Pennsylvania (CICUP), October 2002. Data from http://pwt.econ.upenn.edu/php_site/pwt_index.php . Constant price entries are for 1996: rgdpl rgdpch rgdpeqa rgdpwok rgdptt openk kc kg ki grgdpch
Source for taxrev pcgdp trd mtrd pop cagdp rgdp rgpdlc gdpdefl tot rir credbgdp credp m2gdp m2gr fdinet gfcf gdplc gdp rgdppcppp taxtrade resimpm gcf ores fuelexp: World Bank World Development Indicators 2006.
Source for er ressdr resexgsdr reerifs caifs cpiinfl cpiind dcred drate money qmoney gdplcifs gdpdeflifs gdpvol USDsdr : IMF International Financial Statistics .
govrevlcifs govexplcifs govexplrifs from line 81 and 82 respectively of IMF IFS. Statistics cover operations of the budgetary central government or of the consolidated central government. Revenue (line 81) comprises all nonrepayable government receipts, whether requited or unrequited, other than grants; revenue is shown net of refunds and other adjustment transactions. Expenditure (line 82) comprises all nonrepayable payments by government, whether requited or unrequited and whether for current or capital purposes. Some countries have data for expenditure and lending minus repayments (line 82Z). Countries ifscode 111,138,682,917,924 only have 82z and not 82. Countries ifscode have >30% annual obs for 82z than 82. govexpAifs is composite measure which uses line 82 (govexplcifs ) for all countries except those listed previously and uses 92Z (govexplrifs ) for those listed.
Source for pea pel fdia fdil da dl fda fdl resmg ta tl nea neo is The External Wealth of Nations Mark II: Revised and Extended Estimates of Foreign Assets and Liabilities, 1970-2004 , by Philip R. Lane and Gian Maria Milesi-Ferretti, IMF Working Paper 06/69. Data available at http://www.imf.org/external/pubs/ft/wp/2006/data/wp0669.zip
Source for fdiafl portafl peafl pdafl othafl rafl fdifl portlfl pelfl pdlfl othlfl: LMF not publicly available.
For voice polinstab goveff rule concorrup regqual: Estimate of aggregate governance based on various sources. Source - World Bank Aggregate Governance Indicators 1996-2004. See Governance Matters IV: Governance Indicators for 1996-2004 by D. Kaufmann A. Kraay, and M. Mastruzzi (2005), Draft, May 9, 2005. Data available at http://www.worldbank.org/wbi/governance/pubs/govmatters4.html
Source for repud exprop: IRIS-3 File of International Country Risk Guide (ICRG) Data. Constructed by Stephen Knack and the IRIS Center, University of Maryland. Dataset available at http://www.countrydata.com/datasets/. Value is annual average of monthly observations. Note that Germany takes on West Germany pre-reunification and Yemen takes on Yemen, Arab Rep.
For corrup, ethn, irisk, lo, bur : Data at end Dec of each year. Source - International Country Risk Guide, The PRS Group, http://www.countrydata.com/. Germany value pre-1990 is that of West Germany.
bl_ variables from updated Barro-Lee dataset (Barro, Robert J. and Jong-Wha Lee, International Data on Educational Attainment: Updates and Implications, CID Working Paper, April 2000.) Data available at http://www.cid.harvard.edu/ciddata/ciddata.html
source for m2weo cengovweo erweo gengovweo gdpdeflweo gdplcweo gdpweo ppperweo ppppcweo pubconweo: IMF WEO database April 2006.
Source for sab_ lic_ emp_ regist_ getcred_ invprot_ taxpay_ trad_ contenf_ closing_ informal: World Bank/International Finance Corporation Doing Business Database http://www.doingbusiness.org/. See website for full definitions.
Regional values have been deleted from dataset.eg by ifscode 1 World ;10 All Countries ; 200 Developing Countries; 201 Non-Oil Develop.Ctys; 505 Asia; 110 Industrial Countries; 170 Europe ;999 Oil Exporting Ctys ; 205 Western Hemisphere; 405 Middle East; 163 Euro Area; 605 Africa; 759 WAEMU; 58 CEMAC; 309 ECCU
AREAER dummies- Sourced from summary tables in IMF Annual Report on Exchange Arrangements and Exchange Restrictions AREAER (sourcefile Indices - 1966 Methodology.xls).
AREAER dummies- A 0 indicates the lack of a control/requirement, and a 1 represents the presence thereof.
AREAER dummies- Blanks indicate either country not IMF member or authorities did not respond. If authorities indicated that the information was not available then this is coded as 99999.
AREAER dummies- Data are as a calendar year-end, and reflect the data in the volume of the following year (e.g., 1998 data are taken from the 1999 volume).
IMF WEO Sep 2006 groupings : adv_weo euroarea_weo majadv_weo eu_weo niasia_weo othadv_weo emdev_weo africa_weo ssafrica_weo cee_weo cismon_weo devasia_weo asean_weo me_weo wh_weo
sample is that used in Kose et al Financial globalization a reappraisal.
Check ...JUL06\DATABASE\AUXILIAR FILES\External indicator.xls for details.
re BOP flows data. Normalized by US from WDI. fdioutflow: FDI outflow BoP, US$ IFS bop78BDD. portoutflow: portfolio investment outflow BoP, US$ IFS bop78BHD. porteqoutflow: portfolio equity inv, outflow BoP, US$ bop78BKD. portdeoutflow : portfolio debt outflow BoP, US$ bop78BLD. othoutflow: other investment outflow BoP, US$ IFS bop78BHD. othbankoutflow : other bank investment outflow BoP, US$ IFS bop78BQD. totoutfl=Total financial account outflows US$, totoutfl=othoutflow+portoutflow+fdioutflow fdiinflow: FDI inflow BoP, US$ IFS bop78BED.*/
Variables are means over period from 1975 to 2004 unless indicated by suffix init which is initial value. Time varying variables required to have at least 50% of observations present over period. Intitutional variables with limited time period coverage are just simple averages where available - this applies to iqindex voice polinstab goveff regqual rule concorrup and variables with prefix emp_ sab_ lic_ invprot_ getcred_ taxpay_ trad_ contenf_ closing_
aus_* BoP Series are just for Australia, National sources. USD, millions. Downloaded from Australian Bureau of Statistics on 11/23/2010 (see table 25 at www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/5302.0Jun%202010?OpenDocument). Data are at the quarterly frequency. No splicing has been performed. Contact person regarding this variable (data compiler at IMF) is Andy Salazar, asalazar2@imf.org.
chn_* BoP series are just for China, National sources. USD, millions. Data came from Gian Maria and are from SAFE. Quarterly BOP Table from 1998. Contact person regarding this variable is Andy Salazar, asalazar2@imf.org.
all data is in millions of USD dollars. handlers are Murad Omoev (momoev@imf.org, cell 646-546-3912) and Andy Salazar(asalazar2@imf.org, cell 202-527-4722)
all bi_* variables are total Liabilities/Assets to Foreigners by Type and Country,  Millions of US dollars, [Position at end of period in millions of dollars. Source: Treasury International Capital Reporting System]
for the BOP series, Australia has been updated with the sum of the quarterly data during 2009, source: Australian Bureau of Statistics.
Australia needs 2009 IIP data from the Australian Bureau of Statistics.
IIP data was downloaded on 11/30/2010 via EDSS. Annual Frequency. No splicing performed. Contact party regarding these series are Murad Omoev and Andy Salazar, momoev@imf.org and asalazar2@imf.org. Raw data files can be found at P:\WRK\CHT\w2011weo\Ch4\data\Annual\Raw\IIP.
Series from Beck, Demirguc-kunt, and Levine can be downloaded from http://siteresources.worldbank.org/INTRES/Resources/FinStructure_2008_v4.xls;  Original paper- http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:20696167~pagePK:64214825~piPK:64214943~theSitePK:469382,00.html
all stock variables from "External Wealth of Nations" (by Gian-Maria) database are in millions of US dollars. Downloaded by John Bluedorn, on 20101201
all data is in million of USD dollars. handlers are Murad Omoev (momoev@imf.org, cell 646-546-3912) and Andy Salazar(asalazar@imf.org, cell 202-527-4722)
Data processed and prepared by Andrew McCallum <econandy@umich.edu> on Jan. 26, 2010.
The raw data is from the U.N. comtrade database at http://comtrade.un.org/db/default.aspx
Original source of data are from DOTS. Data were taken from S2010WEO Ch4 data file P:\WRK\CHT\s2010weo\Ch4\datasources\DOTS\new2\bilateral_final_a.dta compiled by Gavin Asdorian (gasdorian@imf.org).
Trade weights were calculated by Andy Salazar (asalazar2@imf.org). Imports+exports from/to country divided by imports and exports from/to world.
Directory for intermediate dta files and the do file can be found in P:\WRK\CHT\w2011weo\Ch4\data\Annual\Raw\trade_weights as well as an excel file used to check STATA data.
The fine classification codes are: 1-No separate legal tender; 2-Pre announced peg or currency board arrangement; 3-Pre announced horizontal band that is narrower than or equal to +/-2%; 4-De facto peg; 5-Pre announced crawling peg; 6-Pre announced crawling band that is narrower than or equal to +/-2%; 7-De factor crawling peg; 8-De facto crawling band that is narrower than or equal to +/-2%; 9-Pre announced crawling band that is wider than or equal to +/-2%; 10-De facto crawling band that is narrower than or equal to +/-5%; 11-Moving band that is narrower than or equal to +/-2% (i.e., allows for both appreciation and depreciation over time); 12-Managed floating; 13-Freely floating; 14-Freely falling; 15-Dual market in which parallel market data is missing
The course classification codes are (gcode): 1-No separate legal tender; 1-Pre announced peg or currency board arrangement; 1-Pre announced horizontal band that is narrower than or equal to +/-2%; 1-De facto peg; 2-Pre announced crawling peg; 2-Pre announced crawling band that is narrower than or equal to +/-2%; 2-De factor crawling peg; 2-De facto crawling band that is narrower than or equal to +/-2%; 3-Pre announced crawling band that is wider than or equal to +/-2%; 3-De facto crawling band that is narrower than or equal to +/-5%; 3-Moving band that is narrower than or equal to +/-2% (i.e., allows for both appreciation and depreciation over time); 3-Managed floating; 4-Freely floating; 5-Freely falling; 6-Dual market in which parallel market data is missing
dataset from SOURCE http://personal.lse.ac.uk/ilzetzki/research/IRRBack.htm, coded for stata as in Catini, Panizza and Saade. Macro Data 4 Stata
December 2009
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subjected to a carryforward operation