Dear Stata users,
I am investigating the impact of regulations on financial stability by using xtabond2. The data is unbalanced panel of 10 countries with more than 200 banks. Following is the code:
xtabond2 Z l.Z llerner_bar lhhi_bar own1 own2 operation size L.linflation L.lgrowth L.loverallfreedomscore L.capreq L.restrict L.supervisor L.marketdisc L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012, gmmstyle(L.Z, lag (1 1) collapse) gmmstyle(L.capreq L.restrict L.supervisor L.marketdisc, lag(2 2) collapse) ivstyle(llerner_bar lhhi_bar size own1 own2 operation L.linflation L.lgrowth L.loverallfreedomscore L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012) twostep robust orthogonal
The mean of some variables were subtracted to minimise the correlation among variables (with _bar). However, the reviewer wants to conduct a robustness check by using an alternative estimator. Since I have endogenous variables (i.e. L.capreq L.restrict L.supervisor L.marketdisc) I have been using ivreg2 with the following code:
ivreg2 Z L.Z llerner_bar lhhi_bar own1 own2 operation size L.linflation L.lgrowth L.loverallfreedomscore L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012 (L.capreq L.restrict L.supervisor L.marketdisc = L2.capreq L2.restrict L2.supervisor L2.marketdisc), gmm cluster(id)
However, ivreg2 has provided different results. I have tried various scenarios, but all produced different results. I have been searching, but failed to find any information that would help me identify what I did wrong with ivreg2. Thank you for your help.
Regards,
Ruslan
I am investigating the impact of regulations on financial stability by using xtabond2. The data is unbalanced panel of 10 countries with more than 200 banks. Following is the code:
xtabond2 Z l.Z llerner_bar lhhi_bar own1 own2 operation size L.linflation L.lgrowth L.loverallfreedomscore L.capreq L.restrict L.supervisor L.marketdisc L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012, gmmstyle(L.Z, lag (1 1) collapse) gmmstyle(L.capreq L.restrict L.supervisor L.marketdisc, lag(2 2) collapse) ivstyle(llerner_bar lhhi_bar size own1 own2 operation L.linflation L.lgrowth L.loverallfreedomscore L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012) twostep robust orthogonal
The mean of some variables were subtracted to minimise the correlation among variables (with _bar). However, the reviewer wants to conduct a robustness check by using an alternative estimator. Since I have endogenous variables (i.e. L.capreq L.restrict L.supervisor L.marketdisc) I have been using ivreg2 with the following code:
ivreg2 Z L.Z llerner_bar lhhi_bar own1 own2 operation size L.linflation L.lgrowth L.loverallfreedomscore L.llerner_capreq_bar L.llerner_restrict_bar L.llerner_supervisor_bar L.llerner_marketdisc_bar yr2001 yr2002 yr2003 yr2004 yr2005 yr2006 yr2007 yr2008 yr2009 yr2010 yr2011 yr2012 (L.capreq L.restrict L.supervisor L.marketdisc = L2.capreq L2.restrict L2.supervisor L2.marketdisc), gmm cluster(id)
However, ivreg2 has provided different results. I have tried various scenarios, but all produced different results. I have been searching, but failed to find any information that would help me identify what I did wrong with ivreg2. Thank you for your help.
Regards,
Ruslan