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  • Confusing with the area of DID with multiple time periods

    Hello all,
    I am doing research based on firm-level unbalanced panel data. Here, I am working on the de-reservation policy impact on the performance of the small-scale manufacturing sector.
    The reservation policy is the policy of the Indian government that certain products were exclusively manufactured by small-scale industries from 1967. It was highly criticized by the researchers that it decelerates the overall manufacturing sector growth in India. Finally, the de-reservation of these products started gradually in 1997 and ended in 2015.
    Here I plan to analyze incumbent small firms' performance using unbalanced panel data from 2001 to 2020. Here I plan to use the CSDID command in Stata that determines difference-in difference with multiple time periods.
    My data looks likes this:
    Code:
    * Example generated by -dataex-. For    more info, type    help    dataex
    clear
    input str8 Factory_id int Year float    yearderesfirst
    "0000003F" 2002    0
    "0000006F" 2010    0
    "0000006F" 2017    0
    "0000008B" 2019    0
    "0000008B" 2020    0
    "0000022F" 2017 2007
    "0000023F" 2017    0
    "0000033F" 2005    0
    "0000033F" 2010    0
    "0000033F" 2018    0
    "0000103F" 2003 2005
    "0000103F" 2004 2005
    "0000103F" 2011 2005
    "0000103F" 2018 2005
    "0000106F" 2007 2006
    "0000106F" 2014 2006
    "0000106F" 2015 2006
    "0000108B" 2006    0
    "0000108B" 2013    0
    "0000108B" 2015    0
    "0000108B" 2019    0
    "0000110F" 2013 1997
    "0000129F" 2005 2008
    "0000132F" 2018    0
    "0000132F" 2019    0
    "0000133F" 2003 2007
    "0000133F" 2009 2007
    "0000133F" 2010 2007
    "0000133F" 2015 2007
    "0000206F" 2007    0
    "0000206F" 2008    0
    "0000206F" 2009    0
    "0000206F" 2010    0
    "0000206F" 2011    0
    "0000206F" 2013    0
    "0000206F" 2014    0
    "0000206F" 2015    0
    "0000206F" 2016    0
    "0000206F" 2017    0
    "0000206F" 2018    0
    "0000206F" 2019    0
    "0000206F" 2020    0
    "0000208B" 2006    0
    "0000208B" 2007    0
    "0000208B" 2008    0
    "0000208B" 2009    0
    "0000208B" 2010    0
    "0000208B" 2011    0
    "0000208B" 2012    0
    "0000208B" 2013    0
    "0000209F" 2003 2015
    "0000209F" 2005 2015
    "0000209F" 2013 2015
    "0000209F" 2019 2015
    "0000209F" 2020 2015
    "0000219F" 2004    0
    "0000219F" 2020    0
    "0000220F" 2014    0
    "0000220F" 2015    0
    "0000222F" 2018    0
    "0000233F" 2005    0
    "0000233F" 2009    0
    "0000233F" 2011    0
    "0000306F" 2007    0
    "0000306F" 2008    0
    "0000306F" 2014    0
    "0000306F" 2017    0
    "0000308B" 2007    0
    "0000308B" 2011    0
    "0000308B" 2012    0
    "0000319F" 2004    0
    "0000319F" 2005    0
    "0000322F" 2019    0
    "0000323F" 2020 2008
    "0000333F" 2006 2007
    "0000333F" 2011 2007
    "0000333F" 2013 2007
    "0000333F" 2017 2007
    "0000406F" 2007 2008
    "0000406F" 2008 2008
    "0000406F" 2017 2008
    "0000407F" 2019    0
    "0000407F" 2020    0
    "0000408B" 2006    0
    "0000408B" 2010    0
    "0000408B" 2016    0
    "0000408B" 2017    0
    "0000408B" 2018    0
    "0000408B" 2019    0
    "0000408B" 2020    0
    "0000419F" 2004    0
    "0000419F" 2005    0
    "0000420F" 2011 2007
    "0000420F" 2019 2007
    "0000420F" 2020 2007
    "0000424F" 2001    0
    "0000424F" 2003    0
    "0000424F" 2007    0
    "0000429F" 2001    0
    "0000429F" 2011    0
    end

    Note that here the variable "yearderesfirst" first is not zero for all the years. It varied between 1997 to 2015. I don't have any issue with the CSDID stata commands.

    My doubts are:
    1. Is it possible to include the data after 2015? because the de-reservation ended in 2015.
    2. How can we interpret CSDID results? Are there any reference materials available?
    3. Do we need to use covariates for the CSDID regression? Because I am getting the results without covariates.
    Your valuable help makes lots of difference in my research.
    Thank you
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