Source Workbook and Sheet: List1.xls workbook List 1 sheet
Source File URL: www.census.gov/population/metro/files/lists/2013/List1.xls
Source Page: http://www.census.gov/population/metro/data/def.html
cbsa2fipsxw2013 set up by Jean Roth , jroth@nber.org , 15 Mar 2016
which is dated March 24, 2015
Created from Reuven's mergedDOTv9_rtasV5bl.dta
"We need to remember what's important in life. Friends, waffles, and work. Or waffles, friends, work. It doesn't matter. But work comes third."
December 2009
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
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
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
TINTHOM includes attempted and commited homicides
the index takes the value 1 if the number of procedures is highest
already an index, goes from 0 to 1
Data from FRED, downloaded on May 31 2011, saved at c:/papers/sterilization/excel
c:\papers\nfa\stata\\dta\/gsdCrisis.dta created by 5_gsdCrisisDefinition.do
c:\papers\nfa\stata\\dta\/currencyCrisisNov2010 prepared by 4_currencyCrisisDefinition_v1.do (on c:/papers/nfa/stata/do)
q:\doc\oe\cger\docs\nfa\stata\data\VEE_data_Aug2010.dta is based on data provided by Marcos Chamon on Aug 27 2010
q:\doc\oe\cger\docs\nfa\stata\data\VEA_data_Aug2010.dta is based on data provided by Chris Crowe on Aug 27 2010
ERALIC DATASET LAST UPDATE OCTOBER 2009
3 Less indebted
2 Moderately indebted
1 Severely indebted
. Debt not classified
Debtor Groupings
5 Low income
4 Lower middle income
3 Upper middle income
2 High income: nonOECD
1 High income: OECD
Income Groupings
A Sub-Saharan Africa
S South Asia
M Middle East & North Africa
L Latin America & Caribbean
E Europe & Central Asia
P East Asia & Pacific
Regional Groupings
Source: WEO, October 2013 (Published). WEO Data from P:\WRK\CHT\Databases\WEO
Data as of Dec. 2012. Converted into Stata by Angela Espiritu (mespiritu@imf.org).
Long and short run Project Macroeconomic Studies Division.
Source http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/papersum.html
"p_" prefi  stands for production; "s_" prefi  stands for stock; "c_" prefi  stands for consumption
zinc=zinc;  alum=aluminium; cadm=cadmium; copp=copper; gold=gold;  lead=lead; moly=molybdenum; nick=nickel; silv=silver; tin=tin
"p_" prefix stands for production; "s_" prefix stands for stock; "c_" prefix stands for consumption
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.
Trade weights were calculated by Andy Salazar (asalazar2@imf.org). Imports+exports from/to country divided by imports and exports from/to world.
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).
all stock variables from "External Wealth of Nations" (by Gian-Maria) database are in millions of US dollars. Downloaded by John Bluedorn, on 20101201
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
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.
Australia needs 2009 IIP data from the Australian Bureau of Statistics.
The raw data is from the U.N. comtrade database at http://comtrade.un.org/db/default.aspx
Data processed and prepared by Andrew McCallum <econandy@umich.edu> on Jan. 26, 2010.
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)
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]
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)
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.
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.
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.
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.
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 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.
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_
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.*/
sample is that used in Kose et al Financial globalization a reappraisal.
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
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).
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- A 0 indicates the lack of a control/requirement, and a 1 represents the presence thereof.
AREAER dummies- Sourced from summary tables in IMF Annual Report on Exchange Arrangements and Exchange Restrictions AREAER (sourcefile Indices - 1966 Methodology.xls).
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
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.
source for m2weo cengovweo erweo gengovweo gdpdeflweo gdplcweo gdpweo ppperweo ppppcweo pubconweo: IMF WEO database April 2006.
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
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.
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 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 fdiafl portafl peafl pdafl othafl rafl fdifl portlfl pelfl pdlfl othlfl: LMF not publicly available.
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
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 er ressdr resexgsdr reerifs caifs cpiinfl cpiind dcred drate money qmoney gdplcifs gdpdeflifs gdpvol USDsdr : IMF International Financial Statistics .
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 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 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 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~=.
the availability of some variables, like unemployment, are poor
update fhp from website
Also spot-checking on regime variables
1) rgdpch 2) ifsinf 3) pwtopen 4) wgbdef
The following variables have been checked in check1.do:
21 Jan 2003 16:30 date of creation
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
Check ...JUL06\DATABASE\AUXILIAR FILES\External indicator.xls for details.
This dataset is from jaimovich and Panizza (2006) Public Debt Around The World , please quote the source
SGCI are Specialized Governmental Credit Institutions
China BoP data can be found in the directory P:\WRK\CHT\s2012weo\Ch2\AE\CapFlows_Downloads\BOP_others\China_wBoP.
Hmm, when running the update, variable co4623 wasn't found? I couldn't find it in the March update DTA files either?? -andy salazar
Excel files and dta files for BOP data on the following ifscoded countries (576 946 288 548 534 566 196 916 248 964 233 238 298 684 686 912 936 944) can be found in P:\WRK\CHT\w2011weo\Ch4\data\Quarterly\Raw\BoP_others\raw_files. Contact party - Jessie Yang (yyang2@imf.org) and Andy Salazar, asalazar2@imf.org.
Hungarian BOP data was downloaded from the national source at http://english.mnb.hu/Kiadvanyok/mnben_statisztikai_kiadvanyok?action=Search&text=fmuq #42.
Haver BOP data is USD, millions, NSA. Downloaded by Andy Salazar, asalazar2@imf.org. 12/7/2010. Excel file and other related files can be found at: P:\WRK\CHT\w2011weo\Ch4\data\Quarterly\Raw\BoP_others\raw_files\Haver
Taiwan BoP data source data for Taiwan is CEIC and the files can be found in P:\WRK\CHT\s2012weo\Ch2\AE\CapFlows_Downloads\BOP_others\Taiwan_BoP
for the BOP series, Australia has been updated with the sum of the quarterly data during 2009, source: Australian Bureau of Statistics.
Australia BoP data came from the national source (53020 table 25), files found in P:\WRK\CHT\s2012weo\Ch2\AE\CapFlows_Downloads\BOP_others\Australia_wBoP
WEO Data from P:\WRK\CHT\Databases\WEO. Data as of April 24, 2012.
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.
Data from 2012 vintage of IMF FAD's debt database
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
summer 2011; WEO, Chapter4; database; all source files/work are  saved in  P:\WRK\CHT\s2011weo\Ch4\data\Sources
Downloaded on: 20140507.
Source: WEO, April 2014 (Published) WEO Data from P:\WRK\CHT\Databases\WEO
http://www.freedomhouse.org/template.cfm?page=16
Please cite Chiozza, Giacomo and Hein Goemans and Kristian Skrede Gleditsh (2009), Introducing Archigos: A Data Set of Political Leaders. Journal of Peace Research, 46(2): 269-283.
See http://mail.rochester.edu/~hgoemans/data for documentation and current data.
Authors : Hein Goemans, Kristian Skrede Gleditsch and Giacomo Chiozza
Alastair directed downloaded these dates from the WTO website on 11/8/2012 because of inconsoistencies-- mainly in B&R originl data
This dataset accompanies Marc L. Busch and Eric Reinhardt, Developing Countries and GATT/WTO Dispute Settlement, Journal of World Trade 37(4): 719-735, 2003.
use wb_classif and code5dig for classifications
assign min weight because of the size of these countries
sergdp and servei are not always consistent; in the future, check two series for consistency
primary source for gdp90loc gdp90usd gdpcurusd - UNCD; IMF WEO 2006 for Taiwan; for gdpcap_ppp - IMF WEO 2006 supplemented by WDI
primary source - UNCD; IMF WEO for Taiwan
6 categories, 1 for a tradition of depending on physical force or illegal means to setting claims, 6 for strong law and order tradition
7 categories, 1 for executive authrity, 7 for executive parity or subordination
legislative fractionalization is the probability that two random draws from the lower (upper) legislative chamber will be from the same party.
align_l1_l2=1 when the same party or coalition of parties controls a majority in both legislative chambers.
align_e_l2=1 when the party controlling the executive branch is either the largest party in the upper legislative chamber or is a member of a ruling coalition in that chamber.
align_e_l1=1 when the party controlling the executive branch is either the largest party in the lower legislative chamber or is a member of a ruling coalition in that chamber.
pc_injudic=1 if pc_xconst>2 (POLITY score on executive constraints)& pc_lorder>=4 (ICRG score on Law & Order)
pc_legchm2=1 if pc_legchm1=1&records on the composition of such a legislative chamber exist and where that legislative chamber is elected under a distinct electoral system and has a substantive (not merely delaying) role in the implementation of fiscal policy
drop negative values for Germany
when GDP or earnings used, check countries that have negative T for >50
keeping gdp_usd constant at 2000 figure
units for govexp and fixcap are consistent with GDP units
"I am 100% sure that we're not completely sure."
Contains UNPS 2010\11 HH Questionnaire Section 17 data stemming from question 10. The file is at the household-month-level.
Contains UNPS 2010\11 HH Questionnaire Section 18 data stemming from questions 7 & 8. The file is at the household-level.
Contains UNPS 2010\11 HH Questionnaire Section 18 data stemming from questions 9-11. The file is at the household-activity-level.
Contains UNPS 2010\11 HH Questionnaire Section 18 data stemming from all questions, with the exception of 7-11, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 17 data stemming from question 11. The file is at the household-food shortage reason-level.
Contains UNPS 2010\11 HH Questionnaire Section 13 data stemming from questions 1-3 & 5-12 that were also asked in UNPS 2009\10. The file is at the household-financial act-level.
Contains UNPS 2010\11 HH Questionnaire Section 13 data stemming from all questions, with the exception of 1-3 & 5-12, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 10 data stemming from question 8 that was also asked in UNPS 2009\10. The file is at the household-stove type-level.
Contains UNPS 2010\11 HH Questionnaire Section 10 data stemming from all questions, with the exception of 8, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 9 data stemming from question 15 that was also asked in UNPS 2009\10. The file is at household-water collector-level.
Contains UNPS 2010\11 HH Questionnaire Section 7 Question 9. In UNPS 2009\2010, Question 9 aimed to capture the "main" measure that was taken to improve  [NAME]'s performance of activities in the last 12 months. In UNPS 2010\11, Question 9 is now asked at the individual-rehabilitation measure-level, meaning for each possible rehabilitation measure, individual is probed for whether it was undertaken or not.
Contains UNPS 2010\11 HH Questionnaire Section 7 data stemming from all questions, with the exception of 9, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 6 data stemming from question 23 that was also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 6 data stemming from question 18 that was also asked in UNPS 2009\10. The item is at the individual-treatment-level.
Contains UNPS 2010\11 HH Questionnaire Section 6 data stemming from all questions, with the exception of 18 & 23, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 17 data stemming from all questions, with the exception of 10 & 11, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 9 data stemming from all questions, with the exception of 15, that were also asked in UNPS 2009\10.
Contains UNPS 2010\11 HH Questionnaire Section 8 data stemming from all questions, with the exception of 67, that were also asked in UNPS 2009\10 The changes in the content and order of questions were accommodated by adding an appropriate suffix to the end of variable name in order to yield  a datastructure that was comparable to the 2009\10 counterpart.
17 December 2019
UNU-WIDER
OHS98 Statistics South Africa: Stata translation Matthew Welch Saldru UCT
Sata Translation Matthew Welch SALDRU UCT
Data Signature is 30279:65(51363):1242730938:3282288310
Data Signature is 103922:85(54349):395941958:2876084284
Data Signature is 132469:45(80786):1188475893:597597056
Data Signature is 1445457:10(68176):3534093:1575979286
Data Signature is 46632:5(23328):3404423613:2601586572
Data Signature is 84978:32(62107):2088444856:3622008092
OHS/LFS data version 6, created by Andrew Kerr, August 2019
by Jean Roth, jroth@nber.org Tue Aug 19 14:46:51 EDT 2014
by Jean Roth, jroth@nber.org Wed Nov  4 16:31:16 EST 2009
by Jean Roth, jroth@nber.org Tue Nov 30 10:52:35 EST 2010
by Jean Roth, jroth@nber.org Tue Mar  3 17:12:28 EST 2009
by Jean Roth, jroth@nber.org Fri Jan 20 14:04:36 EST 2012
by Jean Roth, jroth@nber.org Tue May 28 14:32:52 EDT 2013
by Jean Roth, jroth@nber.org Mon Nov 26 15:57:02 EST 2012
by Jean Roth, jroth@nber.org Tue Sep 18 18:26:33 EDT 2012
by Jean Roth, jroth@nber.org Fri Sep 18 17:10:34 EDT 2015
by Jean Roth, jroth@nber.org Wed Sep 30 17:36:30 EDT 2015
by Jean Roth, jroth@nber.org Mon Sep 19 15:32:17 EDT 2016
by Jean Roth, jroth@nber.org Thu Oct 12 15:43:03 EDT 2017
by Jean Roth, jroth@nber.org Wed Oct  9 12:34:40 EDT 2013
Il n'est pas possible de creer une variable diplome pour ce pays
Expenditures are computed in 2011 USD PPP.
It has information on households characteristics and expenditures in Cote d'Ivoire in 1985 1986 1987 1988 1993 1998 2002 2008 and 2015.
25 Oct 2017 17:56 : The dataset is produced by the dofile 010_panelcons.do.
CLUSTER BY YEAR
Alternatives to m2/GDP
POLARIZATION
financial liberalization
PREVIOUS SYSTEM WRONG: included noncompetitive elections
Table 4
TAKE OUT LIEC<7, Reg 1, Table 2
TAKE OUT LIEC<6, Reg 1, Table 2
TAKE OUT LIEC<7, Reg 1, Table 1
TAKE OUT LIEC<5, Reg 1, Table 1
TABLE 3
'TABLE ONE
robustness of table 4 results to log check
robustness of table 3 results to logcheck
Table 1, col. 2 (with gdp/cap)
robustness to ln(checks)
Table 3 forbearance results (checks first), robustness
robustness of Table 4 results (w/, w/o eiecav) to liqliab, pri.cre
Table 1, columns 1 and 2, using liq liabilities and priv.cred
robustness of regressions to private credit and liqu. liabi
sull_new and atl_new in table 3, cols 3 and 4
check table 4 results with sull_new and atl_new (four regs).
Check table 1, col 2 adding atl_new
ABOVE IS TABLE 1, Col 2.
First robustness result: including sull_new in Table 1 column 1
Robustness results
column 2, for eiecav==7
Column 1: for all countries
Table 4, forbearance determinants generally and eiecav==7
delete above, footnote 33 deleted b/c difference with competitive elections not large
footnote 33 to Table 3 (effects of elections in competitive systems)
column 4, availability of trade statistics
column 3, RDTV_NEW and forbearance
column 2, control for gdp/cap
column 1: no control for gdp/cap
Table 3, checks and forbearance
Column 3, terms of trade statistics
Column 2, Table 2, using papr_new
Delete Last Regression
TABLE 2, Incomplete info and fiscal costs
column 3, controlling for terms of trade
column 2, add GDP/capita
Column 1
TABLE 1: CHECKS AND FISCAL COST
LOG FILE FOR RESULTS OF BANK WORKING PAPER
column 4, use trade statistics info variable
column 3, pr(forb) on rdtv_new
column 2, add GDP per capita
Column 1, checks, no gdp
Table 2 regressions
gdpppp95 data for Bosnia/Herzegovina; Bhutan; Brunei; */
this file was updated 29 Oct 1998 09:21 . contact amar to see if it's the latest version.
this file was complete as of 30 Sep 1998 17:15 . contact amar for the latest version.