Resultados para la banda de 60 GHz

After having defined loyalty and rebelliousness of each MEP in each vote, the dependent variable is created: a dummy variable called

“nationality prevails”. This corresponds to case b2 (as defined in paragraph 5.3), namely those cases when there is a clear contrast between the political group line and the national delegation line and the MEP decides to follow their countrymen, even if this means neglecting the European group line.

The independent variables are created on the basis of the information provided by Hix et al.’s dataset. EPGs are included as a sort of control variables, since it is already well known which groups are cohesive and which are not. The non-attached members are excluded from the regression, following the indication of Kreppel (2013). Nationality is expected to give original results, since except for the generic AI scores that can be calculated via the online platform www.votewatch.eu and

presented in various works (Hix et al. 2007 for the first 5 European legislatures; Hix 2009 for the 6^th EP; Votewatch 2013 report for some crucial votes cast in the current, 7^th EP) no study has actually analysed with more refined statistical tools which countries are more or less cohesive in terms of nationality prevailing over European party membership. On the other hand, the goal is to assess if also some specific characteristics of the MEP (size of country delegation to the EP, origin from EU15 or the recently eastern-enlarged countries) and of the vote (legislative vote, budget vote, result of the vote, margin, vote in the most important committees) have significant influence.

The expectations about the main independent variables (nationality, EPG membership) have already been discussed. As far as the other dummy variables coded 1 if the vote is relative to one of the five most important committees pinpointed by MEPs’ assistant in the July 2012 survey: ECON, ITRE, ENVI, IMCO, AGRI. My expectation is that this variable is not only statistically significant, but it also has a substantial effect on the dependent variable⁵³. This would represent also a confirmation that the information provided by MEPs’ assistants is reliable. Result (0 = rejected, 1 = approved) is included simply as a control variable. “Margin” is expected to have a negative effect on nationality prevails: the rationale is that the smaller the margin between “Yes” and “No” in a certain vote, the more contested the vote is, and I expect national alignments to be more likely to emerge when

53 Actually, the committees in the 6th and 7th European Parliament were not exactly the same: two temporary committees (SURE and CRIS) were dismantled at the beginning of the current legislature, as noted before, and a new committee (CRIM) was established in 2012. But none of these committees was mentioned by MEPs’ assistants as the most important ones, which constitutes the rationale of the variable. Thus, it is not problematic to “retroactively” extend some information drawn from the 7th EP to a statistical analysis performed on RCVs cast in the previous European legislature.

votes are controversial. “Size” is included to control for the fact that bigger member states may be more likely to show a statistical influence on the dependent variable simply because they elect more MEPs.

Finally, a variable called “enlargement” (dummy: 0 = EU15, 1 = eastern countries + Malta, Cyprus) is included to see if the 12 countries that recently joined the EU show different parliamentary behaviour in respect to the EU15 countries. The literature on voting behaviour before and after the eastern enlargement argues, in short, either that these new member states are not yet completely “socialized” to the dynamics of the EP, thus their MEPs are slightly less prone to follow the EPG but this variance is practically negligible (Hix and Noury 2009) or that the enlargement had no effect at all in terms of legislators’ policy preferences and their revealed behaviour (Bressanelli 2012; Costello et al. 2012; McElroy and Benoit 2012). In light of this, I expect this variable to have a consistent effect to these assumptions: either being non significant, or having a slight positive effect.

Two variables are categorical (Euro country, euro group), so they are transformed into dummies with the appropriate STATA command;

two are continuous (margin, size); all others are dummy variables. The basic statistics of these variables are presented in the appendix in table a5. Since the dependent variable is a dummy variable, a logistic regression is run. Three different models are tested separately; after running the regression, the margins are further elaborated to have substantially comparable coefficients⁵⁴. Results of the logistic regression are shown in table 14.

54 The STATA command used is the following: margins, dyd(*)

Table 13. When nationality prevails, 2004-2009: logistic regression.

(0.0411) (0.0409) (0.0180) (0.0179) (0.0179)

Belgium -0.101*** -0.239*** Legislative 0.236*** 0.236*** 0.238***

(0.0220) (0.0218) (0.00647) (0.00644) (0.00643)

Cyprus -0.236*** -0.307*** Rule 0.0700*** 0.0715*** 0.0741***

(0.0413) (0.0411) (0.0104) (0.0104) (0.0104)

Latvia 0.109*** 0.274*** Top 5 comm.0.0146** 0.0139** 0.0128**

(0.0259) (0.0255) (0.00645) (0.00642) (0.00641)

Lithuania -0.286*** -0.289*** Result 0.00961 0.00754 0.00890

(0.0280) (0.0277) (0.00601) (0.00598) (0.00597)

Malta 0.203*** 0.146*** Margin -0.00290*** -0.00287*** -0.00288***

(0.0356) (0.0354) (0.0000160) (0.0000159) (0.0000159)

Denmark 0.643*** 0.616*** Size -0.00304***

(0.0192) (0.0188) (0.000101)

Ireland 0.392*** 0.659*** Enlargment -0.352***

(0.0196) (0.0194) (0.00748)

Bulgaria -1.242*** -1.311*** _cons -2.328*** -2.499*** -2.067***

(0.0481) (0.0479) (0.0125) (0.0116) (0.00949)

Netherlands0.246*** 0.215***

(0.0173) (0.0169) r2

Poland -0.0345** 0.223*** chi2 96177.7 79868.2 64980.6

(0.0144) (0.0140) F

Czech Rep. 0.739*** 0.795*** N 3207960 3207960 3206924

(0.0160) (0.0154)

Austria -0.123*** -0.250*** Standard errors in parentheses (0.0239) (0.0236) * p<0.1, ** p<0.05, *** p<0.01

Model 1 is the complete regression with all the independent variables, excluding “Size” and “Enlargement” that showed collinearity problems with the country dummies. Model 2 excludes the EPG dummies, while model 3 excludes the country dummies and includes the aforementioned two country-related variables. The three models show little difference both in terms of substantial effect of coefficients and of statistical significance. Pseudo-R2 of model 1 is, as expected, the highest of the three models.