O comportamento dos deputados federais quando a agenda legislativa interessa aos servidores públicos federais do executivo - Vitor Cândido Leles de Paulo (2020)
The objective of this dissertation is to analyze the agenda and behavior of federal deputies in the propositions related to federal civil servants working for the Executive Branch. The period studied runs from 1995 to 2018, which corresponds to six legislatures (50th, 51st, 52nd, 53rd, 54th and 55th) and seven presidential governments (FHC I, FHC II, Lula I, Lula II, Dilma I, Dilma II and Temer). The object belongs to the field of legislative studies, where the relations that the Legislative Branch establishes with the Executive and parliamentary behavior are highlighted, including for the Brazilian case. In this work, I test the following hypotheses: 1) deputies who are former unionists or former public servants vote more favorably on propositions of interest to public servants; 2) legislators affiliated to left-wing parties in the ideological spectrum vote more favorably on propositions of interest to public servants; and 3) deputies who support the government vote less favorably on propositions of interest to federal public servants. To test the hypotheses, descriptive analysis and logistic regression models are employed in different samples, in which the degrees of disagreement in voting vary: in a sample, the cut is at least 10% disagreement; in the other, the dissent is at least 25%. The results of all the samples show that being former unionist or former public employee increases the chances of voting for the interests of the federal civil servants. The logistic regression also reinforces that being affiliated to left-wing parties increases the chances of voting in favor of federal civil servants. The findings also reinforce the third hypothesis by showing that government officials are less likely to vote in favor of the interests of federal servants. The control variables (percentage of disagreement, type of quorum and term of office) also showed statistical significance and played an explanatory role in the models.