************************************************************************************************** *** This do file creates the replication results for *** The “Peer-Effect” in Counterterrorist Policies */ *** Eric Neumayer (LSE), Thomas Pluemper (U of Essex) and Mariaelisa Epifanio (U of Warwick) */ *** */ *** Published in: International Organization, 68 (1), 2014, pp. 209-232 */ ************************************************************************************************** ************************************************************************************************** /* Note: You have to change "local DIR" to the directory you copy the original stata files contained */ /* in the zip file and then run the do file. /* You must have Stata version 12 or higher installed */ ************************************************************************************************** */ version 11 drop _all clear matrix clear mata *********************************************************************************** local DIR = "C:\Research\Conflict\ITERATE\Data from Mariaelisa\" /*change relative path to the directory where the files are located */ cd "`DIR'" *********************************************************************************** use "Article for IO (counter-terrorism)", clear * figure 1 capture drop SL_peers_exp gen SL_peers_exp=exp(sl_pi_lnsumtot_wpeers_tots)-1 label var SL_peers_exp "SL (peers)" capture drop SL_nonpeers_exp gen SL_nonpeers_exp=exp(sl_pi_lnsumtot_wnonpeers_tots)-1 label var SL_nonpeers_exp "SL (non-peers)" label var sumtot "Regulations" twoway line sumtot SL_peers_exp SL_nonpeers_exp year if year>=2000 & year<=2008, by(threat_level country, note("") caption("") b1title("")) xlabel(2000 2002 2004 2006 2008) lstyle(solid solid solid) lpattern(solid dash dot) lcolor(black) *** Main estimations, table 2 * model 1 xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots year if year>2000, cluster(country) margins, at((mean) _all (p25) sl_pi_lnsumtot_wpeers_tots ) margins, at((mean) _all (p75) sl_pi_lnsumtot_wpeers_tots ) margins, at((mean) _all (p25) predinc_total ) margins, at((mean) _all (p75) predinc_total ) margins, at((mean) _all (p95) predinc_total ) * model 2 capture drop sumtotasobservedann_3grps egen sumtotasobservedann_3grps=mean(sumtot), by(i_pi_totsum_rank_3grps year) capture drop belowasobservedann_3grps gen belowasobservedann_3grps=0 replace belowasobservedann_3grps=. if sumtot==. replace belowasobservedann_3grps=1 if sumtot2000, cluster(country) margins, at((mean) _all (p25) sl_pi_lnsumtot_wpeers_tots) over(belowasobservedann_3grps) margins, at((mean) _all (p75) sl_pi_lnsumtot_wpeers_tots) over(belowasobservedann_3grps) *** Robustness tests, table 3 * model 3: clustering on peer group level xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots year if year>2000, cluster(threat_level) * model 4: LDV and country fixed effects tsset capture drop lsumtot gen lsumtot=l.sumtot xi: xtpoisson sumtot lsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots year if year>2000, fe * model 5: Include "cultural peer"-link variables xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots sl_lnsumtot_w_cult_grp2_peers sl_lnsumtot_w_cult_grp2_nonpeers year if year>2000, cluster(country) * model 6: Year fixed effects xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots i.year if year>2000, cluster(country) * model 7: Include SL with unitary and CINC weights xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wpeers_tots sl_pi_lnsumtot_wnonpeers_tots sl_lnsumtot_unitary_tots sl_lnsumtot_cinc_tots year if year>2000, cluster(country) * model 8: Separate spatial lags for the groups replace sl_pi_lnsumtot_wi_k_low_tots=0 if sl_pi_lnsumtot_wi_k_low_tots==. replace sl_pi_lnsumtot_wi_k_mid_tots=0 if sl_pi_lnsumtot_wi_k_mid_tots==. replace sl_pi_lnsumtot_wi_k_high_tots=0 if sl_pi_lnsumtot_wi_k_high_tots==. xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predinc_total sl_pi_lnsumtot_wi_k_low_tots sl_pi_lnsumtot_wi_k_mid_tots sl_pi_lnsumtot_wi_k_high_tots sl_pi_lnsumtot_wnonpeers_tots year if year>2000, cluster(country) test sl_pi_lnsumtot_wi_k_low_tots= sl_pi_lnsumtot_wi_k_mid_tots= sl_pi_lnsumtot_wi_k_high_tots , mtest * model 9: Groupings based on actual incidents xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 actualincidents_total sl_ai_lnsumtot_wpeers_tots sl_ai_lnsumtot_wnonpeers_tots year if year>2000, cluster(country) * model 10: Groupings based on predicted killings xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 predkill_total sl_pk_lnsumtot_wpeers_tots sl_pk_lnsumtot_wnonpeers_tots year if year>2000, cluster(country) * model 11: Groupings based on actual killings xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 actualkillings_total sl_ak_lnsumtot_wpeers_tots sl_ak_lnsumtot_wnonpeers_tots year if year>2000, cluster(country) * model 12: Groupings based on actual incidents (1996 to 2000) xi: poisson sumtot icsumtot gdppcconst gov_left1 gov_right1 actualincidents_total sl_ai_lnsumtot_wpeers_pre911 sl_ai_lnsumtot_wnonpeers_pre911 year if year>2000, cluster(country)