Title:      The Trouble with Tobit:  A District-Level Sample
Selection Model of Voting for Extreme Right Parties in Europe,
1980-2004

Authors:    Benjamin Bowyer

Entrydate:  2008-07-07 08:37:54

Keywords:   Tobit, Heckman sample selection, censored data,
aggregate data, extreme right parties

Abstract:   The growing electoral success of extreme right
parties (ERPs) in many European countries has sparked academic
interest in explaining variation in extreme right success. 
However, much of the extant research on the electoral success of
extreme right parties suffers from at least two types of
selection bias.  The first involves the selection of cases and
occurs when only those national elections that were contested by
extreme right parties are included in the cross-national
analysis.  To address this problem, a growing number of scholars
of ERP electoral support employ Tobit models to analyze
national-level election results pooled across countries and
election years.  However, this approach conceals a second source
of selection bias:  ERPs are extremely selective about which
election districts within a country they choose to contest.  The
correct specification of this process of self-selection requires
the recognition of two fundamental points.  First, the causal
factors that determine whether an extreme right party contests
an election are not identical to those that influence its share
of the vote if it does appear on the ballot.  Second, this
decision about when and where to field candidates is one that is
observable at the level of the election district.  This paper
argues that the appropriate way to model is as a Heckman sample
selection model estimated at the level of electoral district.  I
present a preliminary analysis of a dataset that pools
district-level election results for eighteen European countries
from 1980-2004 (N=12,050), the results of which demonstrate the
value of this approach.   

http://polmeth.wustl.edu/retrieve.php?id=791

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