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This is part of dataset. I want to analyze the impact of the conflict（lconflict_o lconflict_d） between A (origin) and B (destination) on the ltrade between A and countries (destinaton) except B or ltrade between B and countries ( destinaton) except A in stata.In other words,I want to analyze the trade diversion effect of conflict. the model is gravity model. my time period is year 2001~2020. Now I want to analyze trade diversion effect of the conflict between CHINA(CHN) and USA(USA) .Here is my code:
generate conflict_dummy = 0
replace conflict_dummy = 1 if origin == "CHN" & destination == "USA"|origin == "USA" & destination == "CHN"
local allcountries "AFG ALB DZA ASM AND AGO ATG AZE ARG AUS AUT BHS BHR BGD ARM BRB BEL BMU BTN BOL BIH BWA BRA BLZ IOT SLB VGB BRN BGR MMR BDI BLR KHM CMR CAN CPV CYM CAF LKA TCD CHL CHN CXR CCK COL COM MYT COG COD COK CRI HRV CUB CYP CSK CZE BEN DNK DMA DOM ECU SLV GNQ ETH ERI EST FLK FJI FIN FRA PYF ATF DJI GAB GEO GMB PSE DEU DDR DEU GHA GIB KIR GRC GRL GRD GUM GTM GIN GUY HTI HND HKG HUN ISL IDN IRN IRQ IRL ISR ITA CIV JAM JPN KAZ JOR KEN PRK KOR KWT KGZ LAO LBN LSO LVA LBR LBY LTU LUX MAC MDG MWI MYS MDV MLI MLT MRT MUS MEX MNG MDA MNE MSR MAR MOZ OMN NAM NRU NPL NLD ANT CUW ABW SXM BES NCL VUT NZL NIC NER NGA NIU NFK NOR MNP FSM MHL PLW PAK PAN PNG PRY PER PHL PCN POL PRT GNB TLS QAT ROU RUS RWA BLM SHN KNA AIA LCA SPM VCT SMR STP SAU SEN SRB SYC SLE IND SGP SVK VNM SVN SOM ZAF ZAF ZWE ESP SSD SDN SDN SUR SWZ SWE CHE SYR TJK THA TGO TKL TON TTO ARE TUN TUR TKM TCA TUV UGA UKR MKD SUN EGY GBR TZA USA BFA URY UZB VEN WLF WSM YEM SCG ZMB"
foreach country in `allcountries' {
if (origin == "CHN" & destination == `country') | (origin == "USA" & destination == `country') {
reghdfe ltrade i.country##c.conflict_dummy, absorb( origin destination)
predict yhat, fitted
gen diff = ltrade - yhat
summarize diff
}
output using "results_`country'.dta", replace
}
But it turns nothing. So please tell me what's wrong with the above code. Thanks in advance.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input int year str3(origin destination) float(ltrade lconflict_o lconflict_d) 2015 "ABW" "AUS" . 1.3862944 2.3025851 2015 "ABW" "BEL" 4.430174 2.912351 2.3025851 2018 "ABW" "BEL" 3.47035 3.871201 3.2580965 2019 "ABW" "BEL" 5.643151 .6931472 3.178054 2001 "ABW" "BGR" . 3.6888795 2.3025851 2012 "ABW" "BGR" 3.9740584 2.995732 2.995732 2017 "ABW" "BHS" 2.498645 2.3025851 1.609438 2019 "ABW" "BMU" 2.1400661 1.3862944 2.772589 2009 "ABW" "BRA" 12.039488 2.70805 1.609438 2017 "ABW" "CAN" 9.943563 4.0073333 4.787492 2010 "ABW" "CHL" 5.39918 2.944439 2.70805 2014 "ABW" "CHN" 12.01103 1.8718022 1.3862944 2004 "ABW" "COL" 7.490289 2.1747518 2.1972246 2014 "ABW" "COL" 10.532575 4.882802 2.0794415 2020 "ABW" "COL" 9.13134 2.0794415 2.70805 2009 "ABW" "CUB" . 3.555348 3.295837 2011 "ABW" "CUB" . 2.0794415 2.484907 2015 "ABW" "DEU" . 2.1972246 2.3025851 2020 "ABW" "DOM" 7.695891 1.3862944 .6931472 2004 "ABW" "ESP" 10.512612 1.609438 2.3025851 2009 "ABW" "ESP" 5.138149 2.564949 2.484907 2017 "ABW" "ESP" 3.5122616 2.3025851 2.3025851 2018 "ABW" "ESP" 4.1237903 1.609438 2.3025851 2019 "ABW" "ESP" 3.93306 2.995732 3.3322046 2020 "ABW" "ESP" 4.750897 3.5263605 2.70805 2008 "ABW" "GBR" 12.215594 2.3025851 1.609438 2011 "ABW" "GBR" 8.551253 2.484907 3.317816 2019 "ABW" "GBR" 4.252416 2.3025851 2.3025851 2017 "ABW" "GRC" .6365768 .6931472 5.105946 2007 "ABW" "GRD" 5.356775 2.3025851 2.95491 2017 "ABW" "GUY" 5.281466 2.2512918 2.70805 2019 "ABW" "GUY" 5.984385 2.3025851 2.484907 2018 "ABW" "ISR" . 2.995732 2.484907 2016 "ABW" "ITA" 4.272672 2.3025851 2.3025851 2017 "ABW" "ITA" 2.0761862 2.70805 2.995732 2014 "ABW" "JAM" 3.592231 .6931472 2.890372 2015 "ABW" "JAM" .4317824 .6931472 2.0794415 2019 "ABW" "JAM" 3.932727 1.3862944 2.995732 2009 "ABW" "MEX" 10.566823 1.4816046 1.4816046 2005 "ABW" "NLD" 10.963469 5.231109 4.477337 2006 "ABW" "NLD" 9.385333 4.7518644 4.304065 2007 "ABW" "NLD" 8.363364 5.170484 5.838896 2008 "ABW" "NLD" 9.99617 4.5217886 3.417727 2009 "ABW" "NLD" 10.623775 4.4426513 1.7917595 2010 "ABW" "NLD" 8.642346 5.68358 5.910254 2011 "ABW" "NLD" 9.544036 5.342334 5.755742 2012 "ABW" "NLD" 8.81578 5.17615 4.2541933 2014 "ABW" "NLD" 9.128975 4.882802 4.951593 2015 "ABW" "NLD" 8.990466 4.4485164 5.078294 2016 "ABW" "NLD" 9.701871 4.204693 4.5152454 2017 "ABW" "NLD" 9.18637 4.304065 3.178054 2018 "ABW" "NLD" 11.609614 3.5263605 4.1108737 2019 "ABW" "NLD" 8.551231 4.925803 5.389072 2020 "ABW" "NLD" 8.099095 3.8286414 4.021774 2010 "ABW" "PER" 1.2510473 5.78996 5.290789 2011 "ABW" "PER" 11.173037 4.624973 4.6395717 2012 "ABW" "PER" -.7277386 5.446737 4.060443 2014 "ABW" "PER" .44596705 4.0073333 4.248495 2015 "ABW" "PER" 7.772379 4.919981 4.875197 2016 "ABW" "PER" -1.1809075 3.678829 2.890372 2017 "ABW" "PER" . 3.6888795 3.6888795 2011 "ABW" "RUS" . .6931472 2.2512918 2016 "ABW" "SYR" . 2.995732 2.995732 2015 "ABW" "THA" 4.5891423 2.944439 2.0794415 2016 "ABW" "THA" 1.419971 2.3025851 2.3025851 2004 "ABW" "USA" 14.347646 3.4011974 2.6390574 2005 "ABW" "USA" 14.836447 5.190732 5.322034 2006 "ABW" "USA" 14.793563 4.6151204 4.204693 2007 "ABW" "USA" 14.85459 5.583496 5.288267 2008 "ABW" "USA" 14.918602 1.609438 3.7612 2009 "ABW" "USA" 14.00742 4.0253515 2.3025851 2010 "ABW" "USA" 9.616868 4.836282 5.141664 2011 "ABW" "USA" 14.93233 7.30317 6.650538 2012 "ABW" "USA" 13.543797 6.047372 5.719656 2013 "ABW" "USA" 10.477158 4.804021 3.8286414 2014 "ABW" "USA" 10.09177 5.998937 6.436951 2015 "ABW" "USA" 10.505176 5.609472 5.335131 2016 "ABW" "USA" 8.54795 5.133443 5.129899 2017 "ABW" "USA" 9.117947 5.169916 5.827474 2018 "ABW" "USA" 9.327619 5.583496 5.116796 2019 "ABW" "USA" 9.22293 5.010635 5.098035 2020 "ABW" "USA" 8.744246 4.304065 3.295837 2010 "ABW" "VEN" 9.854884 4.317488 3.465736 2012 "ABW" "VEN" 10.26128 2.0794415 1.609438 2013 "ABW" "VEN" 10.031178 2.3025851 1.94591 2014 "ABW" "VEN" 9.571469 7.520072 5.210578 2015 "ABW" "VEN" 8.486908 5.398163 5.347107 2016 "ABW" "VEN" 9.173629 3.7281 1.3862944 2018 "ABW" "VEN" 7.929356 4.7458014 4.204693 2019 "ABW" "VEN" 8.284257 2.995732 4.5196123 2020 "ABW" "VEN" 8.859817 4.836282 3.9512436 2009 "ARE" "ARG" 7.90403 2.0794415 2.0794415 2010 "ARE" "ARG" 9.501249 4.85203 3.367296 2011 "ARE" "ARG" 10.690032 3.583519 3.2386785 2012 "ARE" "ARG" 10.830348 2.3025851 2.3025851 2013 "ARE" "ARG" 10.835363 2.3025851 3.8286414 2015 "ARE" "ARG" 10.688694 2.9704144 2.70805 2016 "ARE" "ARG" 11.169586 1.3862944 3.713572 2017 "ARE" "ARG" 11.187625 3.218876 1.7917595 2018 "ARE" "ARG" 12.02374 3.919991 .6931472 end format %ty year
This is part of dataset. I want to analyze the impact of the conflict（lconflict_o lconflict_d） between A (origin) and B (destination) on the ltrade between A and countries (destinaton) except B or ltrade between B and countries ( destinaton) except A in stata.In other words,I want to analyze the trade diversion effect of conflict. the model is gravity model. my time period is year 2001~2020. Now I want to analyze trade diversion effect of the conflict between CHINA(CHN) and USA(USA) .Here is my code:
generate conflict_dummy = 0
replace conflict_dummy = 1 if origin == "CHN" & destination == "USA"|origin == "USA" & destination == "CHN"
local allcountries "AFG ALB DZA ASM AND AGO ATG AZE ARG AUS AUT BHS BHR BGD ARM BRB BEL BMU BTN BOL BIH BWA BRA BLZ IOT SLB VGB BRN BGR MMR BDI BLR KHM CMR CAN CPV CYM CAF LKA TCD CHL CHN CXR CCK COL COM MYT COG COD COK CRI HRV CUB CYP CSK CZE BEN DNK DMA DOM ECU SLV GNQ ETH ERI EST FLK FJI FIN FRA PYF ATF DJI GAB GEO GMB PSE DEU DDR DEU GHA GIB KIR GRC GRL GRD GUM GTM GIN GUY HTI HND HKG HUN ISL IDN IRN IRQ IRL ISR ITA CIV JAM JPN KAZ JOR KEN PRK KOR KWT KGZ LAO LBN LSO LVA LBR LBY LTU LUX MAC MDG MWI MYS MDV MLI MLT MRT MUS MEX MNG MDA MNE MSR MAR MOZ OMN NAM NRU NPL NLD ANT CUW ABW SXM BES NCL VUT NZL NIC NER NGA NIU NFK NOR MNP FSM MHL PLW PAK PAN PNG PRY PER PHL PCN POL PRT GNB TLS QAT ROU RUS RWA BLM SHN KNA AIA LCA SPM VCT SMR STP SAU SEN SRB SYC SLE IND SGP SVK VNM SVN SOM ZAF ZAF ZWE ESP SSD SDN SDN SUR SWZ SWE CHE SYR TJK THA TGO TKL TON TTO ARE TUN TUR TKM TCA TUV UGA UKR MKD SUN EGY GBR TZA USA BFA URY UZB VEN WLF WSM YEM SCG ZMB"
foreach country in `allcountries' {
if (origin == "CHN" & destination == `country') | (origin == "USA" & destination == `country') {
reghdfe ltrade i.country##c.conflict_dummy, absorb( origin destination)
predict yhat, fitted
gen diff = ltrade - yhat
summarize diff
}
output using "results_`country'.dta", replace
}
But it turns nothing. So please tell me what's wrong with the above code. Thanks in advance.
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