I am looking to find the relationship between house price shocks on divorce rates. I have annual data for 8 time periods. I have time and county fixed effects so I am using the reghdfe command with absorb, from the scc install library.
My main regression looks like such:
Code:
reghdfe divorce_rate HPSHOCK femalelf_num unemployment_rate_num degree_num GCSE_num a_level_num noGCSE_num under10_num i10to34hours_num i35to44hours_num over45hours_num white_num weekly_pay_num, absorb(countynum d) vce(cluster countynum)
I have a subset of my dataset below to illustrate.
Thanks,
Jamie
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str9 mnemonic str46 county float(degree_num under10_num i10to34hours_num i35to44hours_num over45hours_num unemployment_rate_num white_num femalelf_num weekly_pay_num d) int year float(divorce_rate HPSHOCK countynum ln_divorce_rate) "" "Bath and North East Somerset UA" 29.4 4 30 41.7 24.2 5.7 90.4 71.7 500.1 1 2011 1.1543634 -.04652044 1 .14354903 "" "Bath and North East Somerset UA" 33.3 5.6 28.3 44 22.1 4.7 90.1 70.4 481.1 2 2012 1.1265371 -.015247965 1 .1191484 "" "Bath and North East Somerset UA" 35.4 3.5 29.4 43 24.1 6.1 88.4 76.6 509.2 3 2013 .9782556 .037154894 1 -.021984324 "" "Bath and North East Somerset UA" 34.8 5.7 26.9 39.2 28.2 4.3 90.2 70.7 542.5 4 2014 1.1008123 .07657316 1 .09604838 "" "Bath and North East Somerset UA" 35.1 6.3 28.9 39.1 25.7 5.6 89.7 73.6 514.7 5 2015 1.0057058 -.1214285 1 .005689617 "" "Bath and North East Somerset UA" 40.7 3.7 32.9 39.9 23.5 4.2 88.1 76.8 522.3 6 2016 1.1473192 -.2731231 1 .13742809 "" "Bath and North East Somerset UA" 40 5.9 31.5 41.4 21.1 3.8 86.4 74.7 564.1 7 2017 .9564212 .13611344 1 -.04455688 "" "Bath and North East Somerset UA" 40.2 4.6 31.7 41.9 21.8 2.2 88.1 73.6 544.2 8 2018 1.0258412 .2302647 1 .025512993 "" "Bedford UA" 25 4.2 29.3 42.7 23.8 6.1 76 73.7 494.7 1 2011 2.184815 -.3184305 2 .7815311 "" "Bedford UA" 24.8 6.5 24.4 43.7 25.4 7 72.3 73.4 499.6 2 2012 2.3504815 -.50932974 2 .8546202 "" "Bedford UA" 33.4 2.2 28.1 41.4 28.4 6.4 76.1 82.3 517.5 3 2013 2.1145895 -.44200635 2 .7488607 "" "Bedford UA" 32.9 2.5 27.1 37.9 32.6 8.8 73.6 81.1 555.7 4 2014 2.1417122 -.3783329 2 .7616056 "" "Bedford UA" 30.8 2.9 26.3 40.9 29.9 4.1 73.4 76.3 530.9 5 2015 2.1768427 -.28063366 2 .7778755 "" "Bedford UA" 30.6 4.6 20.5 47.7 27.2 5.7 72.2 74.5 556.5 6 2016 2.1397316 .13171378 2 .7606804 "" "Bedford UA" 35.5 5.3 24.2 40.8 29.7 3.8 76 73.4 584 7 2017 1.9548142 .787049 2 .6702951 "" "Bedford UA" 32.1 4.2 24.3 44.6 26.9 2.6 66.3 82.1 565.7 8 2018 2.048119 .8929451 2 .7169219 "" "Blackburn with Darwen UA" 18.445915 2.5 28.38741 50.77852 18.3037 8.956295 75.005165 64.02518 432.8548 1 2011 .224107 .1946874 3 -1.4956317 "" "Blackburn with Darwen UA" 17.114372 2.652533 28.99493 50.20765 18.079626 8.99576 75.97445 64.377045 427.8786 2 2012 .2287373 .4383854 3 -1.4751812 "" "Blackburn with Darwen UA" 16.584013 3.080531 29.31168 48.76189 18.811268 9.111681 75.94077 64.06885 426.417 3 2013 .1985797 .3540271 3 -1.6165646 "" "Blackburn with Darwen UA" 17.216702 3.248777 28.34053 49.57016 18.775053 9.80601 74.055 65.21558 460.467 4 2014 .18671684 .064940214 3 -1.678162 "" "Blackburn with Darwen UA" 17.618029 2.654105 29.636055 47.70984 20 6.754105 74.137665 64.84753 448.56235 5 2015 .1806629 -.29422763 3 -1.7111225 "" "Blackburn with Darwen UA" 20.826815 2.537642 29.17738 47.6538 20.63118 7.206462 75.09224 67.34717 449.4172 6 2016 .2001491 -.4519042 3 -1.6086926 "" "Blackburn with Darwen UA" 23.01605 3.696901 29.456335 44.34311 22.50365 5.828168 73.17913 67.30703 458.5236 7 2017 .198256 -.3384984 3 -1.618196 "" "Blackburn with Darwen UA" 24.12458 3.065688 29.70092 46.90881 20.258894 5.740184 71.50806 66.80696 466.9022 8 2018 .17811483 -.1549169 3 -1.7253268 end
0 Response to Multi fixed effects time series - bootstrapping standard errors.
Post a Comment