Hello,

I am new to statalist but I used the forum previously to find help which I did. However, I came to a point where I am stuck.

For my work, I want to estimate the effect of protected areas (PA) on tourism development (arrivals and overnight stays) in all 116 municipalities of South Tyrol. There are 8 nature parks (PA) which have been established in different years. I use panel data for arrivals and overnight stays in 116 municipalities from 1961 - 2018 (annually):

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input int m_id str26 municipality int year long(arrivals overnights) byte PA float(log_arr arr_base100 log_arrb)
  6 "ABTEI"   1961   7522   71120 0  8.925588       100 4.6051702
  6 "ABTEI"   1962  13237  165871 0  9.490771 175.97713  5.170354
  6 "ABTEI"   1963  15657  191603 0  9.658673 208.14943  5.338256
  6 "ABTEI"   1964  14396  184650 0  9.574706 191.38527  5.254289
  6 "ABTEI"   1965  15928  184252 0  9.675834  211.7522  5.355417
  6 "ABTEI"   1966  19376  216295 0  9.871791 257.59106  5.551373
  6 "ABTEI"   1967  19704  213352 0  9.888577  261.9516   5.56816
  6 "ABTEI"   1968  19857  220955 0  9.896312 263.98566  5.575895
  6 "ABTEI"   1969  23981  251514 0 10.085017  318.8115    5.7646
  6 "ABTEI"   1970  26459  277988 0 10.183352 351.75485  5.862935
  6 "ABTEI"   1971  31739  320192 0   10.3653  421.9489  6.044884
  6 "ABTEI"   1972  39973  427143 0  10.59596  531.4145  6.275542
  6 "ABTEI"   1973  38053  413686 0 10.546735  505.8894  6.226318
  6 "ABTEI"   1974  39263  441310 0 10.578038  521.9755  6.257621
  6 "ABTEI"   1975  41858  449302 0 10.642038 556.47437  6.321621
  6 "ABTEI"   1976  46712  477531 0 10.751757  621.0051  6.431339
  6 "ABTEI"   1977  53115  544028 0 10.880215  706.1287  6.559797
  6 "ABTEI"   1978  54583  556876 1 10.907477  725.6448   6.58706
  6 "ABTEI"   1979  61419  571494 1 11.025475  816.5248  6.705057
  6 "ABTEI"   1980  64724  621425 1 11.077888  860.4626   6.75747
  6 "ABTEI"   1981  61869  602025 1 11.032775  822.5073  6.712358
  6 "ABTEI"   1982  70020  647032 1 11.156536  930.8694  6.836119
  6 "ABTEI"   1983  75717  700907 1 11.234758 1006.6073  6.914341
  6 "ABTEI"   1984  77979  706885 1 11.264194 1036.6791  6.943778
  6 "ABTEI"   1985  82779  773536 1  11.32393  1100.492  7.003512
  6 "ABTEI"   1986  90312  784212 1 11.411026 1200.6382  7.090609
  6 "ABTEI"   1987  93510  763064 1 11.445824 1243.1534  7.125407
  6 "ABTEI"   1988  99995  824433 1 11.512876 1329.3672  7.192458
  6 "ABTEI"   1989  87205  683006 1 11.376017 1159.3326    7.0556
  6 "ABTEI"   1990  92841  709036 1 11.438643 1234.2595  7.118227
  6 "ABTEI"   1991 112045  841027 1 11.626656  1489.564  7.306239
  6 "ABTEI"   1992 112577  828805 1 11.631392 1496.6365  7.310976
  6 "ABTEI"   1993 114378  818302 1 11.647264 1520.5796  7.326847
  6 "ABTEI"   1994 118910  852218 1 11.686122 1580.8296  7.365705
  6 "ABTEI"   1995 121083  857737 1  11.70423  1609.718  7.383814
  6 "ABTEI"   1996 125680  884659 1 11.741494 1670.8323  7.421077
  6 "ABTEI"   1997 122908  834693 1 11.719192 1633.9803  7.398774
  6 "ABTEI"   1998 125639  826321 1 11.741168  1670.287  7.420751
  6 "ABTEI"   1999 118384  784853 1  11.68169 1573.8368  7.361272
  6 "ABTEI"   2000 122733  789364 1 11.717767 1631.6538  7.397349
  6 "ABTEI"   2001 127152  812215 1 11.753139 1690.4015  7.432721
  6 "ABTEI"   2002 128549  822323 1 11.764066 1708.9736  7.443648
  6 "ABTEI"   2003 147372  901245 1 11.900715  1959.213  7.580298
  6 "ABTEI"   2004 148577  913264 1 11.908858 1975.2327  7.588441
  6 "ABTEI"   2005 154307  920089 1   11.9467 2051.4092  7.626282
  6 "ABTEI"   2006 152078  901103 1  11.93215  2021.776  7.611732
  6 "ABTEI"   2007 159660  937788 1 11.980802 2122.5737  7.660385
  6 "ABTEI"   2008 164169  964797 1 12.008652  2182.518  7.688234
  6 "ABTEI"   2009 169124  974105 1 12.038387 2248.3914   7.71797
  6 "ABTEI"   2010 176108 1018866 1 12.078853  2341.239  7.758436
  6 "ABTEI"   2011 176865 1009760 1 12.083142 2351.3027  7.762725
  6 "ABTEI"   2012 185005 1042815 1 12.128139  2459.519  7.807721
  6 "ABTEI"   2013 186238 1037318 1  12.13478  2475.911  7.814363
  6 "ABTEI"   2014 178510  977337 1   12.0924  2373.172  7.771983
  6 "ABTEI"   2015 190071 1012389 1 12.155153  2526.868  7.834736
  6 "ABTEI"   2016 208679 1091140 1 12.248552  2774.249  7.928135
  6 "ABTEI"   2017 213764 1097517 1 12.272628 2841.8506  7.952211
  6 "ABTEI"   2018 231154 1174720 1  12.35084  3073.039  8.030422
106 "AHRNTAL" 1961   1450   19199 0  7.279319       100 4.6051702
106 "AHRNTAL" 1962   1634   22648 0  7.398786 112.68965 4.7246375
106 "AHRNTAL" 1963   2752   36431 0  7.920083  189.7931  5.245934
106 "AHRNTAL" 1964   5282   52196 0   8.57206 364.27585  5.897912
106 "AHRNTAL" 1965   6313   73572 0  8.750366  435.3793  6.076218
106 "AHRNTAL" 1966   5443   60594 0  8.602086  375.3793  5.927937
106 "AHRNTAL" 1967   5364   65807 0  8.587465   369.931  5.913317
106 "AHRNTAL" 1968   6162   91599 0  8.726156  424.9655  6.052008
106 "AHRNTAL" 1969   7754  111594 0  8.955964  534.7586  6.281816
106 "AHRNTAL" 1970   9796  139704 0   9.18973  675.5862  6.515581
106 "AHRNTAL" 1971  10325  128624 0  9.242324   712.069  6.568175
106 "AHRNTAL" 1972  15321  189095 0   9.63698 1056.6207  6.962831
106 "AHRNTAL" 1973  20621  233070 0  9.934065  1422.138  7.259917
106 "AHRNTAL" 1974  25634  265451 0 10.151675  1767.862  7.477526
106 "AHRNTAL" 1975  29417  316031 0 10.289328 2028.7587   7.61518
106 "AHRNTAL" 1976  30294  312285 0 10.318705 2089.2415  7.644557
106 "AHRNTAL" 1977  34326  332213 0  10.44366 2367.3103   7.76951
106 "AHRNTAL" 1978  42504  397605 0 10.657353   2931.31  7.983205
106 "AHRNTAL" 1979  51702  475314 0 10.853251  3565.655  8.179103
106 "AHRNTAL" 1980  58479  517524 0 10.976423 4033.0344  8.302275
106 "AHRNTAL" 1981  60352  515650 0  11.00795  4162.207    8.3338
106 "AHRNTAL" 1982  57786  511556 0   10.9645 3985.2415  8.290353
106 "AHRNTAL" 1983  57291  464915 0   10.9559 3951.1035   8.28175
106 "AHRNTAL" 1984  60481  484940 0 11.010084 4171.1035  8.335936
106 "AHRNTAL" 1985  62218  490578 0   11.0384 4290.8965  8.364251
106 "AHRNTAL" 1986  68791  544121 0 11.138828  4744.207   8.46468
106 "AHRNTAL" 1987  69395  549393 0  11.14757 4785.8623  8.473421
106 "AHRNTAL" 1988  72740  570428 1 11.194647  5016.552  8.520498
106 "AHRNTAL" 1989  75714  587214 1 11.234718  5221.655   8.56057
106 "AHRNTAL" 1990  77451  577036 1   11.2574  5341.448  8.583252
106 "AHRNTAL" 1991  86199  620580 1 11.364414  5944.759  8.690266
106 "AHRNTAL" 1992  81578  595178 1 11.309315  5626.069  8.635166
106 "AHRNTAL" 1993  83797  599009 1 11.336152  5779.104 8.6620035
106 "AHRNTAL" 1994  83926  600698 1  11.33769      5788  8.663542
106 "AHRNTAL" 1995  86989  630703 1 11.373537  5999.241 8.6993885
106 "AHRNTAL" 1996  88198  635526 1  11.38734  6082.621  8.713191
106 "AHRNTAL" 1997  82290  571886 1 11.318005  5675.172  8.643856
106 "AHRNTAL" 1998  78051  545615 1 11.265118  5382.828  8.590969
106 "AHRNTAL" 1999  83301  585461 1 11.330215  5744.896  8.656067
106 "AHRNTAL" 2000  89884  601053 1 11.406275  6198.896  8.732126
106 "AHRNTAL" 2001  99748  647582 1 11.510403  6879.172  8.836253
106 "AHRNTAL" 2002 102753  673877 1 11.540083  7086.414  8.865934
end
label values PA label_PA
label def label_PA 0 "pre", modify
label def label_PA 1 "post", modify


Because the treatment starts at different points in time, I want to estimate a generalized DD model with the following form:

Yit = ai + bt + Delta * PAit + eit

The interaction term 'PA' = 1 if a municipality is treated AND observed after the respective park establishment. So 'PA' is indicating if treatment is on(POST) or off (PRE) in a respective observation.
(In the dataex example, AHRNTAL became adjacent to a nature park in 1988 whereas ABTEI became adjacent in 1978). a and b stand for municipality and time fixed effects.

My first question:
1) Which command best fits this model? (I will only show for arrivals to shorten things here) So far, I used the following but I am not entirely sure with interpretation:

xtreg arrivals i.year i.PA#i.year, fe r --> coefficient for each year gives me the additional change in arrivals for treatment in each year?

xtreg arrivals c.year i.PA#c.year, fe r --> coefficient over all years gives me the average additional increase in arrivals for the treatment?


If this is right, then my second concern matters and I'll post about that but otherwise I'll have to do the estimation with another command again.

I use Stata 13 and I hope I have been as precise as possible.

Thank you very much and kind regards,

Luis Meier