Hello,
this is my first topic in Statalist. However, I have been using it as reader throughout the last 1-2 years and it has always helped me alot, so a general thanks to everyone!

Here is my question: Is there a spatial regression model for panel data that works with a binary dependent variable?

I have created an artificial grid net for a specific country. My panel dataset (2004-2019) consists of 4.416 cell years. I am interested in whether changes in population density are related to violent conflict. Since several measures indicate the existence of Spatial Auto Correlation, I want to run spatial regression models rather than not including WxY into the regression. While looking for a model, I was reading the Stata spatial autoregressive models reference manual (https://www.stata.com/manuals/sp.pdf) where it says that "Datasets contain at a minimum a continuous outcome variable [...]" (Manual, 5). I wanted to run two regressions, one with my dummy conflict variable and one with my continous conflict variable. Now, to me it appears that Spatial Panel Regression is mostly for continous variables, is that true?
I have not found much information regarding the selection of spatial models at all.

Dependent variables:
sumconflict (amount of conflicts in a cell per year)
conflict_dummy (0 no conflict 1 at least one conflict)

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input double gid int year byte(sumconflict conflict_dummy) float(ttime_mean popd) byte excluded double _ID
135732 2004  0 0 907.9863 68.387314 1 135732
135732 2005  0 0 907.9863  72.25968 1 135732
135732 2006  0 0 907.9863  73.41225 1 135732
135732 2007  0 0 907.9863  69.58721 1 135732
135732 2008  0 0 907.9863  74.76343 0 135732
135732 2009  0 0 907.9863  79.55742 0 135732
135732 2010  0 0 907.9863   76.8337 0 135732
135732 2011  0 0 907.9863  85.13601 0 135732
135732 2012  0 0 907.9863  87.23365 0 135732
135732 2013  0 0 907.9863  89.18589 0 135732
135732 2014  0 0 907.9863  91.60899 . 135732
135732 2015  0 0 907.9863  106.7828 . 135732
135732 2016  0 0 907.9863 108.58791 . 135732
135732 2017  0 0 907.9863 105.73356 . 135732
135732 2018  0 0 907.9863  109.4948 . 135732
135732 2019  2 1 907.9863 116.57528 . 135732
135733 2004  0 0 923.2635  84.51994 1 135733
135733 2005  1 1 923.2635  86.62513 1 135733
135733 2006  0 0 923.2635  91.15457 1 135733
135733 2007  0 0 923.2635  87.64269 1 135733
135733 2008  0 0 923.2635  91.08348 0 135733
135733 2009  1 1 923.2635  94.86053 0 135733
135733 2010  0 0 923.2635  97.45685 0 135733
135733 2011  0 0 923.2635 101.14142 0 135733
135733 2012  0 0 923.2635  108.7501 0 135733
135733 2013  2 1 923.2635 112.10914 0 135733
135733 2014  0 0 923.2635  119.4397 . 135733
135733 2015  1 1 923.2635 129.12605 . 135733
135733 2016  0 0 923.2635 136.11842 . 135733
135733 2017  0 0 923.2635 139.63719 . 135733
135733 2018  2 1 923.2635 143.26768 . 135733
135733 2019  1 1 923.2635 145.26973 . 135733
135734 2004  1 1 758.0011 173.39325 1 135734
135734 2005  0 0 758.0011  173.6193 1 135734
135734 2006  0 0 758.0011 186.25314 1 135734
135734 2007  0 0 758.0011  191.2999 1 135734
135734 2008  2 1 758.0011  176.4213 0 135734
135734 2009  0 0 758.0011   181.021 0 135734
135734 2010  0 0 758.0011  199.8898 0 135734
135734 2011  0 0 758.0011 209.20265 0 135734
135734 2012  0 0 758.0011 221.16185 0 135734
135734 2013  0 0 758.0011  228.7141 0 135734
135734 2014  0 0 758.0011 237.82196 . 135734
135734 2015  0 0 758.0011 234.76636 . 135734
135734 2016  0 0 758.0011  243.8495 . 135734
135734 2017  0 0 758.0011  255.1242 . 135734
135734 2018  0 0 758.0011  258.0424 . 135734
135734 2019  1 1 758.0011  253.5568 . 135734
136451 2004  0 0 697.6842  150.1506 1 136451
136451 2005  0 0 697.6842 156.79945 1 136451
136451 2006  0 0 697.6842 157.73026 1 136451
136451 2007  0 0 697.6842 171.83656 1 136451
136451 2008  0 0 697.6842 163.15063 0 136451
136451 2009  0 0 697.6842 171.12045 0 136451
136451 2010  0 0 697.6842 177.78214 0 136451
136451 2011  0 0 697.6842  187.9707 0 136451
136451 2012  0 0 697.6842 195.00113 0 136451
136451 2013  0 0 697.6842  208.7737 0 136451
136451 2014  0 0 697.6842  198.0281 . 136451
136451 2015  0 0 697.6842 202.61552 . 136451
136451 2016  0 0 697.6842  211.0389 . 136451
136451 2017  1 1 697.6842  211.1622 . 136451
136451 2018  1 1 697.6842 219.50172 . 136451
136451 2019  0 0 697.6842  215.3898 . 136451
136452 2004  0 0 924.1018  95.67027 1 136452
136452 2005  1 1 924.1018  99.37617 1 136452
136452 2006  1 1 924.1018 100.88332 1 136452
136452 2007  0 0 924.1018 102.85384 1 136452
136452 2008  1 1 924.1018 106.59133 0 136452
136452 2009  0 0 924.1018 112.33856 0 136452
136452 2010  0 0 924.1018 116.47848 0 136452
136452 2011  0 0 924.1018 121.70628 0 136452
136452 2012  0 0 924.1018 122.18845 0 136452
136452 2013  0 0 924.1018 120.75687 0 136452
136452 2014  2 1 924.1018 122.29737 . 136452
136452 2015  1 1 924.1018  133.0313 . 136452
136452 2016  0 0 924.1018 134.71364 . 136452
136452 2017  0 0 924.1018 135.59761 . 136452
136452 2018  0 0 924.1018 139.57538 . 136452
136452 2019  1 1 924.1018 151.63979 . 136452
136453 2004  0 0 607.8061  265.3798 1 136453
136453 2005  2 1 607.8061  271.5488 1 136453
136453 2006  1 1 607.8061 282.21277 1 136453
136453 2007  2 1 607.8061  292.5856 1 136453
136453 2008  3 1 607.8061 304.66647 0 136453
136453 2009  4 1 607.8061   311.215 0 136453
136453 2010  1 1 607.8061 321.79785 0 136453
136453 2011  0 0 607.8061   329.783 0 136453
136453 2012  0 0 607.8061  335.1554 0 136453
136453 2013  5 1 607.8061  350.1456 0 136453
136453 2014  7 1 607.8061   361.531 . 136453
136453 2015  6 1 607.8061  363.4155 . 136453
136453 2016  3 1 607.8061  378.2019 . 136453
136453 2017  6 1 607.8061  395.1161 . 136453
136453 2018  0 0 607.8061  407.6138 . 136453
136453 2019 12 1 607.8061  414.1178 . 136453
137171 2004  0 0 669.3231  109.2089 1 137171
137171 2005  0 0 669.3231 113.38412 1 137171
137171 2006  0 0 669.3231 123.85465 1 137171
137171 2007  0 0 669.3231 131.08997 1 137171
end

I use Stata 15.0.

Greetings Anton von Poblozki