After been using the advices here for several years without being a member, it is now time for my first question regarding help. Hopefully I make my self clear and follow the faq.
I am trying to create "sub periods" from my data set. My data is between 1980-2014 on countries, years, elections etc. Every country has elections differently and thus for elections my voting data is constant for 3-5 years while all other data is still changing which becomes a problem when doing regressions.
I want to be able to do something like "If election take average of <varlist> to next election.". I need to have averages of all variables (per variable) in my data set corresponding to the amount of years between two elections in one country.
I am looking forward to answers and to clarify if its needed.
Thank you!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input long Country int(Year Elections) double(ip tradeopen popvote) 1 1980 . .2192838302 66.82500604862834 0 1 1981 . .2166291172 68.396550301208 0 1 1982 . .2090544166 64.11711392349588 0 1 1983 8514 .2126598031 62.47218498724764 0 1 1984 . .2223274877 66.5750060351522 0 1 1985 . .2248569158 70.08316147624951 0 1 1986 9823 .216564363 64.01459721216203 9.7 1 1987 . .2194225564 62.85372272692686 9.7 1 1988 . .2283248892 66.562550344062 9.7 1 1989 . .2380358262 70.53835879455089 9.7 1 1990 11237 .2440088484 71.48836948192262 16.6 1 1991 . .2482316847 70.04840589285222 16.6 1 1992 . .2485028767 67.63016746537562 16.6 1 1993 . .2361753364 63.26505049155278 16.6 1 1994 12700 .2510384177 65.98709333788209 22.5 1 1995 13134 .2562872031 68.25660110272 21.9 1 1996 . .2599885442 70.08367112068267 21.9 1 1997 . .2687096818 74.86769021558281 21.9 1 1998 . .2727328475 76.9271493915785 21.9 1 1999 14520 .2738576729 78.26014034397156 26.9 1 2000 . .2851453874 85.3604956179232 26.9 1 2001 . .2941603639 87.53666476393525 26.9 1 2002 15668 .2921390095 86.94816799966057 10 1 2003 . .2963529696 86.38738241628248 10 1 2004 . .3081622988 90.79234569292967 10 1 2005 . .3137299618 94.03380568330545 10 1 2006 17075 .3188569952 98.08831120534364 17.9 1 2007 . .322258439 100.733254061926 17.9 1 2008 17803 .3211315156 102.0736827317061 28.2 1 2009 . .301992492 87.06223097427956 28.2 1 2010 . .3230191689 99.01979623695625 28.2 1 2011 . .3292108445 105.1027886297255 28.2 1 2012 . .3303752091 105.1521774278381 28.2 1 2013 19630 .332350068 104.0664140863733 24.1 1 2014 . .3372894244 103.5035352510687 24.1 1 2015 . .3422488354 102.4300546702535 24.1 1 2016 . .3450714632 101.0020250810702 24.1 2 1980 . .2816145769 102.306683920574 0 2 1981 7982 .2809780569 109.4176861613412 2.7 2 1982 . .283057865 117.0639042762904 2.7 2 1983 . .2800385733 119.5094603178238 2.7 2 1984 . .2843406502 127.2864360507372 2.7 2 1985 9417 .2828523194 122.9633391064458 0 2 1986 . .2875734248 111.4945548135144 0 2 1987 10208 .2955695668 109.105628431747 0 2 1988 . .302948319 115.5598990323904 0 2 1989 . .3134892514 124.0119131587489 0 2 1990 . .3155399501 120.5696727146501 0 2 1991 11650 .3183815591 117.7127732340387 9.8 2 1992 . .3236491167 114.2157113395169 9.8 2 1993 . .3249747551 108.201663534969 9.8 2 1994 . .331990655 112.3889369502991 9.8 2 1995 12924 .3359774354 115.511365408443 10.1 2 1996 . .3436807272 118.0600938027919 10.1 2 1997 . .3531981125 124.3666932632705 10.1 2 1998 . .3596413258 123.4844956876552 10.1 2 1999 14408 .3590086961 123.9972402610697 9.9 2 2000 . .3795161999 141.0790714966192 9.9 2 2001 . .375420947 138.694465221206 9.9 2 2002 . .3735640572 135.1248849817734 9.9 2 2003 15843 .3751812716 131.9903126453944 13.7 2 2004 . .3807863321 136.0378332487476 13.7 2 2005 . .3903834839 143.3762209420292 13.7 2 2006 . .3950167822 147.6939014351527 13.7 2 2007 17327 .4000258135 151.1636218587954 14 2 2008 . .4062239782 158.9080450842626 14 2 2009 . .3900065166 136.3567578633131 14 2 2010 18426 .4051918683 151.1001765267372 7.8 2 2011 . .417446467 162.7536656605285 7.8 2 2012 . .4171383949 163.9949770335543 7.8 2 2013 . .4174767817 162.2186431251685 7.8 2 2014 19868 .4286128623 164.6983927979592 3.7 2 2015 . .4324144044 160.1720103296707 3.7 2 2016 . .4487138877 164.1156472597038 3.7 6 1980 . . . . 6 1981 . . . . 6 1982 . . . . 6 1983 . . . . 6 1984 . . . . 6 1985 . . . . 6 1986 . . . . 6 1987 . . . . 6 1988 . . . . 6 1989 . . . . 6 1990 11117 . 63.80639159580962 0 6 1991 . . 71.61825999276348 0 6 1992 11845 . 78.89511604541855 6 6 1993 . .1907769366 79.13457296431604 6 6 1994 . .1987149572 75.69958560215952 6 6 1995 . .2173680212 83.89495520493278 6 6 1996 13301 .2273601739 81.49325044463582 8 6 1997 . .237533033 85.07416814509439 8 6 1998 14050 .2469036941 84.68860956704492 3.9 6 1999 . .2525193269 86.26125292485742 3.9 6 2000 . .2696520409 98.23312080013685 3.9 6 2001 . .2837223159 99.30997399456218 3.9 6 2002 15506 .2894371739 91.5259818230906 0 6 2003 . .2986614059 95.01519722229932 0 6 2004 . .3366525698 113.8683352250686 0 6 2005 . .3494116662 122.0152585154173 0 end format %tdnn/dd/CCYY Elections label values Country nyCountry label def nyCountry 1 "Austria", modify label def nyCountry 2 "Belgium", modify label def nyCountry 6 "Czech Republic", modify
0 Response to Transform data set to sub-periods with corresponding averages of all other variables
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