The original data set consists of all the EP elections ever held (64). The old member countries have held 5 elections, Spain and Portugal 4 elections and the three newcomers only 2 elections.In practise this means that the old member countries have 2,5 times more weight in the analysis than the newcomers. Basically, this is ok since we are analysing elections, not countries. However, the difference in weights may have some bearing on the empirical results. The results below show that is not the case. The results are from weighted leasts squares (WLS) analysis, where the weights are such that each country has equal weight in the analysis (1 for the old countries, 1.25 for Spain and Portugal, and 2.5 for three latest members).
Compulsory voting ++++++ Simultanous elections ++++++ Weekend voting ++++++ Country net payer ----- Country net receiver ++ Share of seats ++ Strict party lists - Multiple constituencies ++ New member country ++
--> REGRESS;Lhs=EPELEC;Rhs=ONE, compulso, arrival, concurr, seatshar, restday...
,constitu, netpayer, netrecei
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = EPELEC Mean= 58.70166667 , S.D.= 18.59343724 |
| Model size: Observations = 64, Parameters = 10, Deg.Fr.= 54 |
| Residuals: Sum of squares= 5056.057207 , Std.Dev.= 9.67630 |
| Fit: R-squared= .767859, Adjusted R-squared = .72917 |
| Model test: F[ 9, 54] = 19.85, Prob value = .00000 |
| Diagnostic: Log-L = -232.0687, Restricted(b=0) Log-L = -278.8018 |
| LogAmemiyaPrCrt.= 4.685, Akaike Info. Crt.= 7.565 |
| Autocorrel: Durbin-Watson Statistic = 1.14714, Rho = .42643 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant 40.03455424 3.3275405 12.031 .0000
COMPULSO 28.75725047 3.8572011 7.455 .0000 .24000000
ARRIVAL 4.117893439 4.0533721 1.016 .3142 .14666667
CONCURR 9.772786597 3.2656862 2.993 .0042 .25666667
SEATSHAR 1.111202075 .39714737 2.798 .0071 7.6670991
RESTDAY 8.202811906 3.5979736 2.280 .0266 .73333333
LIST -14.67521185 4.9926436 -2.939 .0048 .40000000
CONSTITU -3.474726518 4.2181767 -.824 .4137 .26666667
NETPAYER -5.438879648 3.3966010 -1.601 .1152 .20000000
NETRECEI 7.509107255 4.3866188 1.712 .0927 .26666667
--> REGRESS;Lhs=EPELEC;Rhs=ONE, compulso, arrival, concurr, seatshar, restday...
,constitu, netpayer, netrecei, y1999, italcomp,uk, finland, sweden, france
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = EPELEC Mean= 58.70166667 , S.D.= 18.59343724 |
| Model size: Observations = 64, Parameters = 16, Deg.Fr.= 48 |
| Residuals: Sum of squares= 1331.270708 , Std.Dev.= 5.26638 |
| Fit: R-squared= .938877, Adjusted R-squared = .91978 |
| Model test: F[ 15, 48] = 49.15, Prob value = .00000 |
| Diagnostic: Log-L = -189.3662, Restricted(b=0) Log-L = -278.8018 |
| LogAmemiyaPrCrt.= 3.546, Akaike Info. Crt.= 6.418 |
| Autocorrel: Durbin-Watson Statistic = 2.05410, Rho = -.02705 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant 46.26026345 2.5400071 18.213 .0000
COMPULSO 23.05822641 2.9689112 7.767 .0000 .24000000
ARRIVAL 4.816880720 2.7359257 1.761 .0847 .14666667
CONCURR 11.52538956 2.0046825 5.749 .0000 .25666667
SEATSHAR .9150792064 .37168490 2.462 .0175 7.6670991
RESTDAY 11.14183131 2.8702801 3.882 .0003 .73333333
LIST -7.649597506 5.7850456 -1.322 .1923 .40000000
CONSTITU 5.299130667 3.4376645 1.541 .1298 .26666667
NETPAYER -8.733692955 2.7544506 -3.171 .0026 .20000000
NETRECEI -5.142435279 4.4026426 -1.168 .2486 .26666667
Y1999 -6.921439310 1.8470970 -3.747 .0005 .26666667
ITALCOMP -22.98998666 5.7790996 -3.978 .0002 .40000000E-01
UK -25.47044219 6.7856977 -3.754 .0005 .66666667E-01
FINLAND -19.40137083 3.3902004 -5.723 .0000 .66666667E-01
SWEDEN -10.88205582 4.3245889 -2.516 .0153 .66666667E-01
FRANCE -10.45314284 3.9353118 -2.656 .0107 .66666667E-01
--> REGRESS;Lhs=differen;Rhs=ONE, compulso, arrival, concurr, seatshar, restd...
,constitu, netpayer, netrecei
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = DIFFEREN Mean= -20.99073333 , S.D.= 15.37090991 |
| Model size: Observations = 64, Parameters = 10, Deg.Fr.= 54 |
| Residuals: Sum of squares= 3139.816796 , Std.Dev.= 7.62527 |
| Fit: R-squared= .789057, Adjusted R-squared = .75390 |
| Model test: F[ 9, 54] = 22.44, Prob value = .00000 |
| Diagnostic: Log-L = -216.8232, Restricted(b=0) Log-L = -266.6205 |
| LogAmemiyaPrCrt.= 4.208, Akaike Info. Crt.= 7.088 |
| Autocorrel: Durbin-Watson Statistic = 1.41877, Rho = .29061 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant -38.50327652 2.6222223 -14.683 .0000
COMPULSO 14.99815535 3.0396141 4.934 .0000 .24000000
ARRIVAL 1.646990326 3.1942039 .516 .6082 .14666667
CONCURR 13.76536362 2.5734789 5.349 .0000 .25666667
SEATSHAR .6067475030 .31296650 1.939 .0578 7.6670991
RESTDAY 10.83976892 2.8353334 3.823 .0003 .73333333
LIST -6.993120484 3.9343838 -1.777 .0811 .40000000
CONSTITU -.3561474328 3.3240759 -.107 .9151 .26666667
NETPAYER -9.648479284 2.6766445 -3.605 .0007 .20000000
NETRECEI 8.846538391 3.4568144 2.559 .0133 .26666667
--> REGRESS;Lhs=differen;Rhs=ONE, compulso, arrival, concurr, seatshar, restd...
,constitu, netpayer, netrecei, y1999,uk, luxembou, italcomp, sweden
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = DIFFEREN Mean= -20.99073333 , S.D.= 15.37090991 |
| Model size: Observations = 64, Parameters = 15, Deg.Fr.= 49 |
| Residuals: Sum of squares= 1167.807475 , Std.Dev.= 4.88189 |
| Fit: R-squared= .921543, Adjusted R-squared = .89913 |
| Model test: F[ 14, 49] = 41.11, Prob value = .00000 |
| Diagnostic: Log-L = -185.1740, Restricted(b=0) Log-L = -266.6205 |
| LogAmemiyaPrCrt.= 3.382, Akaike Info. Crt.= 6.255 |
| Autocorrel: Durbin-Watson Statistic = 2.10252, Rho = -.05126 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant -36.30189097 2.2512930 -16.125 .0000
COMPULSO 11.64069963 2.7340010 4.258 .0001 .24000000
ARRIVAL 7.416148732 2.7890859 2.659 .0106 .14666667
CONCURR 9.108110211 2.0333295 4.479 .0000 .25666667
SEATSHAR .4335544342 .34142395 1.270 .2101 7.6670991
RESTDAY 7.612218153 2.6166946 2.909 .0054 .73333333
LIST 2.432630093 5.3821971 .452 .6533 .40000000
CONSTITU 11.86198643 3.5493892 3.342 .0016 .26666667
NETPAYER -7.515052045 2.2978571 -3.270 .0020 .20000000
NETRECEI 2.582692085 3.6801433 .702 .4861 .26666667
Y1999 -3.375698605 1.7615951 -1.916 .0612 .26666667
UK -26.86046714 6.2952054 -4.267 .0001 .66666667E-01
LUXEMBOU 12.46295880 4.4524774 2.799 .0073 .66666667E-01
ITALCOMP -12.76123230 5.4135253 -2.357 .0224 .40000000E-01
SWEDEN -11.48917393 3.7471953 -3.066 .0035 .66666667E-01
--> REGRESS;Lhs=EPELEC;Rhs=ONE, compulso, arrival, concurr, seatshar, restday...
,constitu, netpayer, netrecei, npelec
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = EPELEC Mean= 58.70166667 , S.D.= 18.59343724 |
| Model size: Observations = 64, Parameters = 11, Deg.Fr.= 53 |
| Residuals: Sum of squares= 3138.785917 , Std.Dev.= 7.69561 |
| Fit: R-squared= .855887, Adjusted R-squared = .82870 |
| Model test: F[ 10, 53] = 31.48, Prob value = .00000 |
| Diagnostic: Log-L = -216.8126, Restricted(b=0) Log-L = -278.8018 |
| LogAmemiyaPrCrt.= 4.240, Akaike Info. Crt.= 7.119 |
| Autocorrel: Durbin-Watson Statistic = 1.42464, Rho = .28768 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant -40.36763694 14.376546 -2.808 .0070
COMPULSO 14.67153680 3.9419627 3.722 .0005 .24000000
ARRIVAL 1.588335103 3.2541791 .488 .6275 .14666667
CONCURR 13.86014091 2.6947320 5.143 .0000 .25666667
SEATSHAR .5947725717 .32863565 1.810 .0760 7.6670991
RESTDAY 10.90236600 2.9005540 3.759 .0004 .73333333
LIST -6.810760124 4.2043700 -1.620 .1112 .40000000
CONSTITU -.2821174356 3.4013392 -.083 .9342 .26666667
NETPAYER -9.748408335 2.8055083 -3.475 .0010 .20000000
NETRECEI 8.878286831 3.4969898 2.539 .0141 .26666667
NPELEC 1.023738374 .17992442 5.690 .0000 79.692400
--> REGRESS;Lhs=EPELEC;Rhs=ONE, compulso, arrival, concurr, seatshar, restday...
,constitu, netpayer, netrecei, npelec, y1999,uk, italcomp, luxembou, sweden
;wts=weight$
+-----------------------------------------------------------------------+
| Ordinary least squares regression Weighting variable = WEIGHT |
| Dep. var. = EPELEC Mean= 58.70166667 , S.D.= 18.59343724 |
| Model size: Observations = 64, Parameters = 16, Deg.Fr.= 48 |
| Residuals: Sum of squares= 1135.852558 , Std.Dev.= 4.86452 |
| Fit: R-squared= .947849, Adjusted R-squared = .93155 |
| Model test: F[ 15, 48] = 58.16, Prob value = .00000 |
| Diagnostic: Log-L = -184.2862, Restricted(b=0) Log-L = -278.8018 |
| LogAmemiyaPrCrt.= 3.387, Akaike Info. Crt.= 6.259 |
| Autocorrel: Durbin-Watson Statistic = 2.08448, Rho = -.04224 |
+-----------------------------------------------------------------------+
+---------+--------------+----------------+--------+---------+----------+
|Variable | Coefficient | Standard Error |t-ratio |P[|T|>t] | Mean of X|
+---------+--------------+----------------+--------+---------+----------+
Constant -25.21363888 9.8020449 -2.572 .0133
COMPULSO 13.90122309 3.3475033 4.153 .0001 .24000000
ARRIVAL 7.496478219 2.7800267 2.697 .0096 .14666667
CONCURR 8.760967485 2.0480026 4.278 .0001 .25666667
SEATSHAR .5404496973 .35242648 1.534 .1317 7.6670991
RESTDAY 7.196146579 2.6318576 2.734 .0087 .73333333
LIST 1.076440399 5.4885696 .196 .8453 .40000000
CONSTITU 11.33981511 3.5651975 3.181 .0026 .26666667
NETPAYER -7.172482290 2.3085846 -3.107 .0032 .20000000
NETRECEI 2.364444853 3.6718620 .644 .5227 .26666667
NPELEC .8591545719 .12120325 7.089 .0000 79.692400
Y1999 -3.707214370 1.7783619 -2.085 .0424 .26666667
UK -27.27501088 6.2829533 -4.341 .0001 .66666667E-01
ITALCOMP -14.27793022 5.5499262 -2.573 .0132 .40000000E-01
LUXEMBOU 11.95031472 4.4585218 2.680 .0100 .66666667E-01
SWEDEN -10.90890081 3.7671114 -2.896 .0057 .66666667E-01