I am trying to examine the impact of export participation of the firm on firm productivity. To this end, I want to examine how the productivity of the firm changes one year from its participation in export market, two years after participation and so on. To understand if the effect of participating in the export market on its productivity dissipate or accelerate over time. I have an unbalanced panel for the period 2001-2013. TFP is my dependent variable and export status (t1) is my independent variable which is a dummy. I think I need to proceed with a psm-did but I am not able to understand its operation for my dataset.
If I could get some inputs on how to achieve this in stata would be much appreciated
A small sample of my data
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double id float(year t1 ltfp) 365 2001 0 .39686665 365 2002 1 .3967393 365 2003 1 .6374343 365 2004 0 .6560543 365 2005 1 .6640503 365 2006 1 .7698439 365 2007 0 .8161478 365 2008 0 .87566 365 2009 0 1.1369226 365 2010 0 1.2058983 365 2011 0 1.0512627 365 2012 0 1.0222095 365 2013 0 .9116122 381 2001 1 .28473413 381 2002 1 .2790297 381 2003 1 .4228754 381 2004 1 .4589705 381 2005 1 .443521 381 2006 1 .6932002 381 2007 1 .51895165 381 2008 1 .4412919 381 2009 1 .4278684 381 2010 1 .4917918 569 2001 0 .4084495 569 2002 0 .32361555 569 2003 0 .312629 569 2004 0 .3549544 569 2005 0 .4214703 569 2006 0 .5034326 569 2007 0 .52623117 569 2008 0 .58975697 569 2009 0 .55094194 569 2010 0 .3773664 595 2006 0 .2977381 595 2007 0 .3644855 595 2008 0 .3293638 595 2009 0 .3146657 595 2010 0 .3185207 595 2011 0 .4280073 595 2012 0 .5122329 595 2013 0 .4275252 600 2009 0 .7721639 600 2010 0 .787946 600 2011 0 .6881346 600 2012 0 .6645668 783 2001 0 .729115 783 2002 0 .7449946 783 2003 0 .7614059 783 2004 0 .870962 783 2005 0 .8693857 783 2006 0 .8836148 783 2007 0 1.0283844 783 2008 0 1.0673563 783 2009 0 1.2047342 783 2010 0 1.2074325 783 2011 0 1.2030094 783 2012 0 1.209522 783 2013 0 1.193356 870 2010 0 .4383901 934 2004 0 .6618422 934 2005 0 .677335 934 2006 0 .698532 934 2007 0 .6574489 934 2008 0 .602454 934 2009 0 .9306454 1120 2001 1 1.0948371 1120 2002 1 1.1048775 1120 2003 1 1.2104284 1120 2004 1 1.1987357 1120 2005 1 1.3653517 1120 2006 1 1.479699 1120 2007 1 1.614259 1120 2008 1 1.8814026 1120 2009 1 2.1619618 1120 2010 1 1.977049 1120 2011 1 2.043859 1120 2012 1 2.134581 1120 2013 1 2.2729049 1621 2007 0 .3721843 1621 2008 0 .4280191 1621 2009 0 .435424 1621 2010 0 .4076315 1621 2011 0 .3898215 1621 2012 0 .4241333 1954 2009 0 .4050439 1954 2010 0 .41772455 2015 2004 0 .17348923 2015 2005 0 .25310284 2015 2006 0 .3803225 2015 2007 0 .4936106 2015 2008 0 .5817891 2015 2009 0 .4436422 2015 2010 0 .42046455 2015 2011 0 .51623964 2015 2012 0 .5415064 2015 2013 0 .4652313 2216 2001 1 .3285122 2216 2002 0 .3717326 2216 2003 0 .40993 2216 2004 0 .3402351 end
0 Response to Productivity effects
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