**** Wired Voters: The Effects of Internet Use on VotersŐ Electoral Uncertainty ### DATASET FOR REPLICATION ### * Note: At this point of time (October, 2013) the INES 2011 has not been officially released yet * here we provide a reduced dataset that allows for replication of the tables in the article and in the appendix. ****** Labels ****** *label variable switching "Potential for vote switching" *label variable open "Openness" *label variable exposure_def "Boradband coverage" *label variable offline "Offline discussion of politics" *label variable morefrag "Reading multiple newspapers" *label variable party_id "Party identifier" *label variable gender "Gender" *label variable class "Social class" *label variable education "Education" *label variable tv1 "TV binary" *label variable radio1 "Radio binary" *label variable newspaper1 "Newspaper binary" *label variable agei "Age" *label variable pol_inte "Interest in politics" *label variable cand_v "Visited by candidates during the campaign" *label variable vote_m "Vote matters" *label variable duty_ch "Vote is duty/choice" *label variable prev_ff "Voted Fianna Fail in 2007" *label variable distance_city "Distance from closest city" *label variable dist_m "Minimum distanc from closest unit in the other group" *label variable self1 "Placement on L/R center" *label variable self2 "Placement on L/R extremes" *label variable online1 "Online newsgathering binary" *label variable online "Online newsgathering ordinal" *label variable twitter1 "Twitter binary" * Table 2. Browsing political news and broadband coverage. tab online exposure_def *Table 3. Instrumental variables (IVREG2) models of electoral uncertainty, Internet instrumented using Broadband Coverage*. *Models 1-6 ivreg2 switching gender educa agei class (online1=exposure_def), r first ivreg2 switching gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off (online1=exposure_def), r first ivreg2 switching gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def), r first ivreg2 open gender educa agei class (online1=exposure_def), r first ivreg2 open gender educa agei class newspaper1 morefrag tv1 radio1 party_id pol_inte cand_v off (online1=exposure_def), r first ivreg2 open gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def), r first *Table 4. Instrumental variables (IVREG2) models of electoral uncertainty, Twitter instrumented using Broadband Coverage*. *MODELS 7-12 ivreg2 switching gender educa agei class (twitter1=exposure_def), r first ivreg2 switching gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off (twitter1=exposure_def), r first ivreg2 switching gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (twitter1=exposure_def), r first ivreg2 open gender educa class (twitter1=exposure_def), r first ivreg2 open gender educa agei class newspaper1 morefrag tv1 radio1 party_id pol_inte cand_v off (twitter1=exposure_def), r first ivreg2 open gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (twitter1=exposure_def), r first *Table 5. Instrumental variables (IVREG2) With robustness checks for across group imbalances: Distance from closest unit in the other group smaller than 13 Km (13 and 14), and matching (15 and 16). Internet instrumented using Broadband Coverage*. * MODELS 13-14 ivreg2 switching gender educa agei class tv1 morefrag newspaper1 radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def) if dist_m<15,r first ivreg2 open gender educa agei class tv1 morefrag newspaper1 radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def) if dist_m<15,r first ********************************************************************************** imb newspaper1 duty_ self1 self2 party_i educ vote_m distance_city, treatment(exposure_def) cem newspaper1 duty_ self1 self2 party_i educ(3) vote_m(2) distance_city(15), treatment(exposure_def) ********************************************************************************** * MODELS 15-16 ivreg2 switching gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def) if cem_mat==1,r first ivreg2 open gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def) if cem_mat==1 , r first ############################ ######## APPENDIX ######## ############################ * Table A1 - Univariate Statistics and Distribution of Control Variables. sum gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city *Table A2 Significance tests of difference between dichotomous control variables in areas with and without broadband. ****** * PRTEST ***** prtest newspaper1 , by(exposure_d) prtest duty_, by(exposure_d) prtest self1, by(exposure_d) prtest self2, by(exposure_d) prtest party_i, by(exposure_d) ******************************* prtest radio1 , by(exposure_d) prtest offline , by(exposure_d) prtest tv1 , by(exposure_d) prtest morefrag, by(exposure_d) prtest cand_v, by(exposure_d) *Table A-3. Robustness checks: Log of of Potential for vote switching; Openness without outliers. Robust C.I. in parentheses. ** p<0.01, * p<0.05. * MODELS A1-A2 gen abssw = abs(switching) gen lnsw= ln(abs+1) ivreg2 lns gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def), r first ** MAKE A NOTE ON WHY IS NEGATIVE SIGN sum open , d ivreg2 open gender educa agei class tv1 newspaper1 morefrag radio1 party_id pol_inte cand_v off vote_m self1 self2 duty_choi prev_ff distance_city (online1=exposure_def) if open>.58, r first