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Codebook: Regions, Regional Power, and Status AttributionOctober 2009Table of Contents TOC \o "1-3" \h \z \u Variables: PAGEREF _Toc243835214 \h 2Works Cited: PAGEREF _Toc243835215 \h 6Appendices: Coding Processes PAGEREF _Toc243835216 \h 7Appendix 1: Process by which missing SIPRI data was imputed PAGEREF _Toc243835217 \h 7Appendix 2: Coding the Cultural Indicators PAGEREF _Toc243835218 \h 16Appendix 3: ISO Country Codes PAGEREF _Toc243835219 \h 18Variables: cowabb1: 3 letter country abbreviation, state 1cowabb2: 3 letter country abbreviation, state 2ccode1: COW Country code, state 1ccode2: COW Country code, state 2iso1: ISO 3 letter country code, state1iso2: ISO 3 letter country code, state2year: Year of observationFrom COW’s CINC data: irst: Iron and steel production (thousands of tons)milex: Military Expenditures (thousands of current year US Dollars)milper: Military Personnel (thousands)energy: Energy consumption (thousands of coal-ton equivalents)tpop: Total Population (thousands)upop: Urban population (population living in cities with population greater than 100,000)cinc: Composite Index of National Capability (CINC) scoreFrom the SIPRI data: milexp: Military expenditure (in millions of 2005 USD)missing data was imputed; process is listed in Appendix 1From the WDI: (*need to check these explanations)gdp: GDP (how is this measured?)captl: market capitalization of domestic firmspop: total populationresid: residual of regression population on GDPFrom EUgene: (*need to check these explanations)contig: Direct contig (1=Lnd, 2=1-12 miles watr, 3=13-24, 4=25-150, 5=151-400, 6=?)distance: Distance, from the capitol of country 1 to the capitol of country 2, in milseFrom the IDEA Events Data: statevisits: Number of state visits from state 1 to state 2 per yearcc: sum of the absolute value on the Goldstein scale of events between country 1 and country 2 per yearcc_nosv: Identical to cc, but excludes all state visits from state 1 to state 2cc_count: A count of all events, conflictual, cooperative, and neutral, from state 1 to state 2 per yearcc_countnosv: Identical to cc_count, but excludes all state visits from state 1 to state 2coop: Sum of all cooperative events between state 1 and state 2 per year, using weighted values of events from the Goldstein scalecoop_nosv: Identical to coop, but excludes all state visits from state 1 to state 2conflict: Sum of all conflictual events between state 1 and state 2 per year, using weighted values of events from the Goldstein scalecoop_count: Count of all cooperative events between state 1 and state 2 per yearcoop_countnosv: Identical to coop_count, but excludes all state visits from state 1 to state 2conf_count: Count of all conflictual events between state 1 and state 2 per yearFrom Goertz and Powers (2009):rei: 1 signifies the dyad shares membership to a common REI, 0 not; this data is coded from the list provided by Goertz and Powers (2009)From The Military Balance (MB) (range 2002-2005): milpers: number of active military personnel per country; countries for which ranges are given (e.g., 11-15000) are treated as missing datalowbound: if a range is given for military personnel, the lower bound of the range is listedhighbound: if a range is given for military personnel, the upper bound of the range is listedmilpersavg: lists the number of active military personnel per country, using the average if a range is given milperslow: lists the number of active military personnel per country, using the lower bound if a range is given (a more conservative measure of active personnel)milpershigh: lists the number of active military personnel per country, using the upper bound if a range is given (a more liberal measure of active personnel)milpersavg_th: identical to milpersavg, but divided by 1000 milperslow_th: identical to milperslow, but divided by 1000milpershigh_th: identical to milperhigh, but divided by 1000Military Personnel Variables: milper_avg: combines the CINC milper variable (ranges from 1988-2001) and the MB’s, milpersavg_th variable (ranges from 2002-2005), to obtain a count of military personnel in thousands from 1988 to 2005milper_h: identical to milper_avg, but uses the upper bound of the MB rangemilper_l: identical to milper_avg, but uses the lower bound of the MB rangeBarbieri Trade Data (Non-directed dyad bilateral trade data)flow1: imports of state 1 from state 2 (rename to imports)flow2: imports of state 2 from state 1 (rename exports) From CIA world fact book? langmaj: 1 if the majority language family of state 1 and state 2 is the same, 0 otherwise langmin: 1 if the minority language family of state 1 and state 2 is the same, 0 otherwiselangminmaj: 1 if the minority language family of state 1 matches the majority language family of state 2, 0 otherwiselangmajmin: 1 if the majority language family of state 1 matches the minority language family of state 2, 0 otherwisescriptmaj: 1 if the majority writing script of state 1 and state 2 is the same, 0 otherwise scriptmin: 1 if the minority writing script of state 1 and state 2 is the same, 0 otherwisescriptminmaj: 1 if the minority writing scrip of state 1 matches the majority script of state 2, 0 otherwisescriptmajmin: 1 if the majority writing scrip of state 1 matches the minority script of state 2, 0 otherwisereligionmaj: 1 if the majority religion of state 1 and state 2 is the same, 0 otherwisereligionmin: 1 if the minority religion of state 1 and state 2 is the same, 0 otherwisereligionmajmin: 1 if the majority religion of state 1 matches the minority religion of state 2, 0 otherwisereligionminmaj: 1 if the majority religion of state 1 matches the minority religion of state 2, 0 otherwiseOur Opportunity and Willingness Measures:milexp_total: sum of all military expenditure in the system per yearmilpers_total: sum of all military personnel in the system per yearmilexp_cinc1: the military expenditure of country 1 (milexp) divided by the sum of all military expenditure in the system that year (milexp_total)milexp_cinc2: the military expenditure of country 2 (milexp) divided by the sum of all military expenditure in the system that year (milexp_total)milper_cinc1: the military personnel of country 1 (milper_avg) divided by the sum of all military expenditure in the system that year (milpers_total)milper_cinc2: the military personnel of country 1 (milper_avg) divided by the sum of all military expenditure in the system that year (milpers_total)military_cinc1: the average value of the military expenditure “cinc” score and the military personnel “cinc” score for country 1military_cinc2: the average value of the military expenditure “cinc” score and the military personnel “cinc” score for country 2captl_total: the total amount of capital in the system per yearcaptl_cinc1: the amount of capital of country 1 (captl1) divided by the total amount of capital in the system captl_cinc2: the amount of capital of country 1 (captl1) divided by the total amount of capital in the systemlofp_military: loss of power gradient for military strength (military_cinc1^log10[(distance/500) + 10 – e ] )lofp_economic: loss of power gradient for military strength (captl_cinc1^log10[(distance/500) + 10 – e ] )milpower_comp: a comparison of country 1’s military power at home versus at country 2’s capital (lofp_military / military_cinc1)econpower_comp: a comparison of country 1’s economic power at home versus at country 2’s capital (lofp_econmic / captl_cinc1)mil_opp: coded 1 if country 1 has at least 50 % of its military power at country 2’s capital as compared to its military power at home (mil_opp = 1 if milpower_comp > .5; 0 if milpower_comp ≤ .5)econ_opp: coded 1 if country 1 has at least 50 % of its economic power at country 2’s capital as compared to its economic power at home (mil_opp = 1 if milpower_comp > .5; 0 if milpower_comp ≤ .5)mill_will: coded 1 if country 1 directs at least 1 event towards country 2econ_will: coded 1 if country 1 and country 2 trade at least 1 USD worthmil_oxw: military opportunity times military willingness; 1 indicates countries are able and willing to interact diplomatically/militarily)econ_oxw: economic opportunity times military willingness; 1 indicates countries are able and willing to interact economically)max_oxw: the maximum value of mil_oxw and econ_oxwWorks Cited:Barbieri, Katherine, Omar Keshk, and Brian Pollins. 2008. Correlates of War Project Trade Data Set Codebook, Version 2.0. Online: , Gary, and Kathy L. Powers. 2009. “The economic–institutional construction of regions: conceptualization and operationalization.”COWSIPRIMilitary BalanceIDEA Events DataEUgene DataWDI indicators ATOP data? Appendices: Coding Processes Appendix 1: Process by which missing SIPRI data was imputedAdded data is color coded in excel and details for each added entry are listed below by country in the order which they appear in the revised SIPRI dataset.For countries with red numbers, data was calculated for the missing state (state A) using expenditures of the neighboring state with the largest military expenditures (state B) for all years missing in state A. The ratio of State B to State A's military expenditures was calculated using data from the correlates of war. That ratio was then multiplied by the SIPRI data for State B. The resulting figure was entered for the missing value of State A for each year available.For countries with green 0's, COW data was not available for the missing state. These missing points typically correspond with periods of domestic turmoil and conflict, or the missing entry falls after 2001.For countries with blue numbers, data was provided in a previous version of SIPRI, but the most recent version of SIPRI has removed that entry for review. Libya88-92; 94-96 extrapolated from Libya-Algeria COW ratio93 data coded 0, missing in COWAngola88-91; 93-97 extrapolated from Angola-Zambia COW ratio92 data coded 0, missing in COW98 extrapolated from Angola-Namibia COW ratioBenin91-92; 94-98 extrapolated from Benin-Nigeria COW ratio93 data coded 0, missing in COWCape Verde89-90 data coded 0, missing in COW91-92 extrapolated from Cape Verde-Senegal COW ratioCentral African Republic88-90; 97-01 extrapolated from Central African Republic-Cameroon COW ratioChad88-92 extrapolated from Chad-Nigeria COW ratioCongo88-90; 92; 94-00 extrapolated from Congo-Cameroon COW ratio91; 93 coded 0, missing in COWCongo, Dem. Rep.88-92; 93-95; 01 extrapolated from Cong, Dem. Rep.-Sudan COW ratio92; 02 coded 0, missing in COWCote d'Ivoire95 extrapolated from Cote d'Ivoire-Ghana COW ratio98-01 extrapolated from Cote d'Ivoire-Guinea COW ratio02 coded 0, COW ends in 01Equatorial Guinea88-93 coded 0, missing from COW96-01 extrapolated from Equatorial Guinea-Cameroon COW ratio02-05 coded 0, COW ends in 01Eritrea88-92 coded "." Eritrea not a state04-05 coded 0, COW ends in 01Gabon88-90; 94-99 extrapolated from Gabon-Cameroon COW ratio91-93 coded 0, missing in COWGuinea88-90; 95-96 extrapolated from Guinea-Senegal COW ratio05 coded 0, COW ends in 01Guinea-Bissau88; 91-93 coded 0, missing in COW90; 99 extrapolated from Guinea-Bissau-Senegal COW ratio04 coded 0, COW ends in 01Liberia88-91;93-97; 00 extrapolated from Liberia-Sierra Leone COW ratio92 coded 0, missing in COW01-02 coded from 06 SIPRI data03 coded 0, COW ends in 01Mali91-92 extrapolated from Mali-Algeria COW ratioNamibia88-89 coded "." not a state90 coded from 06 SIPRI dataNiger88-93 extrapolated from Niger-Algeria COW ratioSierra Leone98-99 extrapolated from Sierra Leone-Guinnea COW ratioSomalia88-90; 95-01 extrapolated Somalia-Ethiopia COW ratio91-94 coded 0, missing in COW02-05 coded 0, COW ends in 01Sudan89 extrapolated from Sudan-Egypt COW ratioTanzania88 extrapolated from Tanzania-Kenya COW ratioTogo96 coded from 06 SIPRI data97-01 coded from Togo-Ghana COW ratio02 coded 0, COW ends in 01Zambia98; 00 coded from 06 SIPRI data01 extrapolated from Zambia-Angola COW ratio02-03 coded 0, COW ends in 01Cuba88-91;94-01 extrapolated from Cuba-USA COW ratio92-93 coded 0, missing from COW02-05 coded 0, COW ends in 01Haiti88-92; 95-01 extrapolated from Haiti-Dominican Republic Ratio93-94 coded 0, missing from COW02-05 coded 0, COW ends in 01Jamaica88-89 extrapolated from Jamaica-Dominican RepublicTrinidad and Tobago88;90;93 coded 0, mising in COW89 extrapolated from Trinidad and Tobago-Guyana COW ratio91-92; 96-01 extrapolated from Trinidad and Tobago-Venezuala COW ratio94-95 coded from 2006 SIPRI data02-05 coded 0, COW ends in 01Belize88; 98-99 extrapolated from Belize-Mexico COW ratioCosta Rica88-99 extrapolated from Costa Rica-Panama COW ratio00-01 extrapolated from Costa Rica-Nicaragua COW ratio02-05 coded 0, COW ends in 01Honduras88-99 extrapolated from Honduras-Guatemala COW ratioNicaragua88;90 extrapolated from Nicaragua-Guatemala COW ratio89 coded 0, missing in COWPanama00-01 extrapolated from Panama-Colombia COW ratio02-05 coded 0, COW ends in 01Bolivia88 extrapolated from Bolivia-Chile COW ratioGuyana97-01 extrapolated from Guyana-Brazil COW ratio02-05 coded 0, COW ends in 01Paraguay88 coded from the 06 SIPRI dataPeru88 extrapolated from Peru-Chile COW ratioVenezuala88-90 extrapolated from Venezuala-Brazil COW ratioKazakhstan88-90 coded "." state does not exist91 coded 0, missing in COW data92 extrapolated from Kazakhstan-Russia COW ratioKyrgyzstan88-90 coded "." state does not exist91 coded 0, missing in COW dataTajikistan88-90 coded "." state does not exist91 coded 0, missing in COW data05 coded 0, COW ends in 01Turkmenistan88-90 coded "." state does not exist91 coded 0, missing in COW data92-93; 00-01 extrapolated from Turkmenistan-Iran COW ratio02-05 coded 0, COW ends in 01Uzbekistan88-90 coded "." state does not exist91-93 coded 0, missing in COW data98l 00 extrapolated from Uzbekistan-Kazakhstan COW ratio02; 04-05 coded 0, COW ends in 01North Korea88-94; 98-04 coded from the 06 SIPRI data95-97 coded "0" COW ratio unreliable relative to SIPRI dataLaos88;90-91 coded 0, missing in COW data89 extrapolated froms Laos-China COW ratioMongolia88-89 extrapolated from Mongolia-Russia COW ratioMyanmar88-01 extrapolated from Myanmar-China COW ratio02-05 coded 0, COW ends in 01Vietnam88-94 coded from 06 SIPRI data95-01 extrapolated from Vietnam-China COW ratio02 coded 0, COW ends in 01Afghanistan88-89; 91-94 coded 0, missing in COW90; 95-01 extrapolated from Afghanistan-China COW ratio02 coded 0, COW ends in 01Tongo88 coded "." state does not existAlbania88-89; 91 extrapolated from Albania-Greece COW ratioArmenia88-90 coded "." state does not exist91 extrapolated from Armenia-Turkey COW ratio94 coded 0, missing in COWAzerbaijan88-90 coded "." state does not exist91 extrapolated from Azerbaijan-Iran COW ratioBelarus88-90 coded "." state does not exist91 coded 0, missing in COWBosnia-Herzegovina88-91 coded "." state does not exist92-01 extrapolated from Bosnia-Herzegovina-Croatia RatioCroatia88-91 coded "." state does not existCzech Republic88-92 coded "." state does not existCzechoslovakia88-92 extrapolated from Czechoslovakia-Germany93-05 coded "." state does not existEStonia88-90 coded "." state does not exist91 coded 0, missing in COWGeorgia88-90 coded "." state does not exist91-95 coded 0, COW data unreliableGermany, DR88-89 extrapolated from Germany, DR-Germany FR COW ratio90 coded 0, COW data missingLatvia88-90 coded "." state does not exist91 coded 0, COW data missing92 extrapolated from Latvia-Russia COW ratioLithuania88-90 coded "." state does not exist91 coded 0, COW data missing92 extrapolated from Lithuania-Russia COW ratioMacedonia88-92 coded "." state does not exist93-95 coded from 06 SIPRI dataMoldova88-90 coded "."91-92 coded 0, COW data unreliableMontenegro88-05 coded "." state does not existRussia91 coded from 06 SIPRI dataSerbia/Yugoslavia88-91 coded as 0, COW data unreliable92-95 coded using 06 sIPRI dataSlovak Republic88-92 coded "." state does not existSlovenia88-81 coded "." state does not existUkraine88-90 coded "." state does not exist91-92 coded 0, COW data unreliableIran88 coded from 06 SIPRI dataIraq88-01 extrapolated from Iran-Iraq COW ratio02-04 coded 0, COW data missingLebanon89 extrapolated from Lebanon-Israel COW ratioQatar88; 91; 93-01 extrapolated from Qatar-Saudi Arabia COW ratio89-00; 92 coded 0, COW data missing02-05 coded 0, COW data ends in 01Yemen88-89 coded "." state does not existYemen, Arab Rep88-90 extrapolated from Yemen, Arab Rep-Saudi Arabia COW ratio91-05 coded "." state does not texistYemen, PR88-89 extrapolated from Yemen, PR-Saudi Arabia COW ratio90-05 coded "," state does not existYugoslavia (former) entry merged with Serbia for consistency with COW country codesAppendix 2: Coding the Cultural IndicatorsMajority language family: Refers to single biggest language in the country – not the language family. For example, the population of the Cote d’Ivorie speak Niger-Congo languages. However, there are more than 250 different languages in the CDI, spoken by a varying number of people. Instead, French is the language spoken by the most Ivorians, and the CDI is coded as a “Majority Romance” country.Once the majority language has been identified, it is assigned to one of a number of broad categories. If it does not fit into any of them, it is called an “Isolate”. The most prominent isolates are Celtic and Hebrew.A country can only have one majority language. If it has several official languages, the most widespread one is coded as the majority language; the others become minority languages.Minority language families: Includes any language beyond the majority language spoken by at least 10% of the population.These are coded in the same way the majority languages. If there are no languages beyond the official one spoken by at least 10% of the population, this category is coded “0”.A country can have any number of minority languages.Majority script:Refers to the alphabet used to write the majority language.Once the majority script has been identified, it is assigned to one of a number of broad categories. If it does not fit into any of them, it is called an “Isolate”. The most prominent isolates are Greek and Hebrew.A country can only have one majority script. If several alphabets are used, the most widely used is coded as the majority script.Generally, all African and Latin American native languages were converted to Latin characters under colonial administration. Thus, though pre-colonial alphabets exist for many of these languages, they currently use Latin characters and are coded as “Latin script”. Minority scripts: Includes any alphabet(s) beyond the one used by the majority language.These are coded in the same way the minority languages. A minimum of 10% of the population must use the script, otherwise it is coded as “0”A country can have any number of minority scripts.Majority religion:This category refers to the country’s religion with the most followers.Once the majority religion has been identified, it is assigned to one of a number of broad categories. If it does not fit into any of them, it is called an “Isolate/Local/Tribal”. The most prominent isolates are voodoo in the Caribbean and animism and ancestor worship in Africa and SE Asia.A country can only have one majority religion. If a country has several official religions, the largest of these is coded as the “Majority religion”. If a country has an official religion, but this religion is smaller than another religion, the largest religion is still coded as the “Majority religion”.Minority religions:Includes any religion beyond the majority religion practiced by at least 10% of the population.These are coded in the same way the majority religion. If there are no religions beyond the official one practiced by at least 10% of the population, this category is coded “0”.A country can have any number of minority religions.Special:All categories are binary. States are or are not members of each category – this is represented, respectively, with a “1” or a “0”. Countries are not coded as both “Majority” and “Minority” if their languages belong to the same broad language families. The same applies to scripts.The one exception to this rule is Eritrea. Most Eritreans speak Tigrinya written in the Ge’ez alphabet, while a minority speak and write Arabic. Both languages belong to the Afro-Asiatic category, but the languages and the alphabets are mutually unintelligible. Eritrea is thus coded as both majority and minority Afro-Asiatic, with a majority Ge’ez and a minority Perso-Arabic scripts.Appendix 3: ISO Country CodesCountries without ISO codes—pre-2008East GermanyWest GermanyCzechoslovakia South Yemen (Democratic Republic of Yemen) North Yemen (Yemen Arab Republic)Yugoslavia/Serbia and Montenegro/Serbia ................
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