Introduction The oft-coined Time-Series and Cross-Sectional (TSCS) analyses have become a widely used method in cross-national research in recent years. The latest decade has witnessed growing methodological interest and sophistication in the TSCS technique (Beck and Katz, 1995; Kittel, 1999; Wooldridge, 2002; Greene, 2003a; Plümper et al., 2005). Their application runs the gamut from the government spending (Garrett and Mitchell, 2001), bargaining system and economic performance (Traxler and Kittel, 2000), and to macroeconomic policies in developed democra- cies (Franzese, 2002). Furthermore, the advance of the technique goes beyond the linear regres- sion models, and limited dependent variables, no- tably the binary choice variables, have been rigorously applied to the TSCS data analysis (Katz, 2001; Coupé, 2005). Yet, there has been only a limited discussion of analysing censored dependent variables in the TSCS design where dependent variables are trun- cated at a particular value. In light of growing number of application of Tobit models for analys- ing censored dependent variables (e.g. Jackman and Volpert, 1996; Golder, 2003a; 2003b), such a discussion seems much needed (1) . First, I review the application of Tobit models made in the TSCS contexts and identify that their estimations are of- ten biased due to the ‘incidental parameter problem’. Next, the article overviews possible remedies for the incidental parameter problem and gives practical suggestions to cope with the problem in applied research. The article further applies the decomposed Tobit model (i.e. Cragg’s model) to censored dependent variables and dis- cusses the methodological problems that arise 88 abstract: The article examines why extreme right parties are successful in some elections while not in others by analyzing the elections held in 19 West European democracies from 1970 to 2000. To that end, the article discusses the methodological limitations that arise from applying the Tobit and the decomposed Tobit model (Cragg’s model) to the Time-Series and Cross-Sectional (TSCS) data. The Tobit model in the presence of fixed effects is known to be biased and inconsistent due to the so-called ‘incidental parameter problem’. The article first reviews the possible remedies for the incidental parameter problem, including the conditional frequentist, semi-parametric, and Bayesian approaches, proposed in the econometric literature. While discussing the alternative approaches to cope with the incidental parameter problem, the article pursues an approach to decompose the Tobit model and overviews the Cragg’s model and its application to the TSCS data. To demonstrate the Tobit and Cragg’s model in the TSCS analyses, the analysis of the vote share of extreme right parties in the extant literature is replicated. The re-analysis of the vote share suggests that the Cragg’s model can further improve the Tobit model usually applied in the literature.                                                         〈特集２　ヨーロッパの選挙〉 Censored and Hurdle Regression Models in TSCS Data: Electoral Support for Extreme Right Parties in 19 West European Democracies Airo Hino 選挙研究　２６巻１号　２０１０年