Rank-ordered logit models: An empirical analysis of Ontario voter preferences

1994 ◽  
Vol 9 (4) ◽  
pp. 369-388 ◽  
Author(s):  
G. Koop ◽  
D. J. Poirier
Keyword(s):  
Empirical Analysis ◽  
Logit Models ◽  
Ordered Logit ◽  
Voter Preferences

I Don't Care to Belong to Any Club That Will Have Me as a Member: Empirical Analysis of Municipal Mergers

2013 ◽  
Vol 2 (1) ◽  
pp. 97-117 ◽  
Author(s):  
Tuukka Saarimaa ◽  
Janne Tukiainen
Keyword(s):  
Population Size ◽  
Empirical Analysis ◽  
Economies Of Scale ◽  
Empirical Work ◽  
Local Public Goods ◽  
Local Democracy ◽  
Public Goods Provision ◽  
Trade Off ◽  
Voter Preferences ◽  
Fiscal Pressure

The efficiencyof local public goods provision and the functioning of local democracy crucially depend on the size and number of local jurisdictions. This article empirically analyzes voluntary municipal mergers in Finland. Our main focus is on aspects that have been somewhat neglected in prior empirical work: whether local democracy considerations, representation and voter preferences are involved in shaping the resulting municipal structure. The main results imply that some municipalities are forced to merge due to fiscal pressure and have to trade off political power to be accepted by their partners. The study also finds that the median voter's distance from services matters, while population size does not. The latter, somewhat surprising, observation is possibly explained by existing municipal co-operation, which already exhausts potential economies of scale.

scholarly journals Intention to move and residential satisfaction: evidence from Poland

Equilibrium ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 341-360
Author(s):  
Piotr Maleszyk ◽  
Arleta Kędra
Keyword(s):  
International Migration ◽  
Life Stage ◽  
Value Added ◽  
Residential Satisfaction ◽  
Policy Implications ◽  
Urban Migration ◽  
Logit Models ◽  
Ordered Logit ◽  
Financial Situation ◽  
Intention To Move

Research background: Residential mobility affects the spatial structure of cities and urban development. Longer-distance migration has many additional implications: it affects the demographic situation of a sending area as well as its growth prospects. The literature on interregional and especially international migration regards residential satisfaction as being of at least secondary importance. More attention to this concept is given in research on intra-urban migration and suburbanisation. In a seminal paper of Speare (1974), residential satisfaction was found to be the best predictor of the willingness to move. However, determinants of mobility are country-specific. Purpose of the article: Answering the following research questions: 1) What is the scale and selectivity of the intention to move among city residents? 2) Does residential satisfaction explain variation in migration intentions? Methods: The data are derived from the PAPI survey on life quality in Lublin, Poland (sample: 1101 residents). We build ordered logit models explaining residents’ declarations regarding different types of migration (intra-urban migration, suburbanisation, interregional and international migration) with various proxies of residential satisfaction, as well as financial situation and demographic attributes. Findings & Value added: The propensity to migrate was declared by approx. 15–30% of respondents, depending on the type of migration, which indicates relatively low mobility as against EU countries. We confirm that the intention to move is highly selective. The estimated ordered logit models explaining the intention to move prove that satisfaction with housing and neighbourhood characteristics along with life-stage characteristics are relevant predictors of intention to move both within and outside the region. We disregard the opinion that unemployment and adverse financial situation are key drivers of mobility in contemporary Poland. In a more international context, we provide evidence on how long- and short-distance migration are different in nature and discuss some policy implications regarding countering depopulation in peripheral areas.

Political, Social, and Cultural Capital in the Chilean Political Elite, 1990–2010

2020 ◽  
Vol 62 (1) ◽  
pp. 121-141 ◽  
Author(s):  
Luis Garrido-Vergara
Keyword(s):  
Cultural Capital ◽  
Empirical Evidence ◽  
Empirical Analysis ◽  
Political Elite ◽  
The Political ◽  
Sociological Research ◽  
Logit Models ◽  
Political Field ◽  
Social And Cultural Capital ◽  
The Empirical Analysis

ABSTRACTAlthough sociological research has examined the reproduction of Chile’s elites, there is little empirical evidence of how different forms of capital operate among them. Using datasets for members of the Chilean political elite from 1990 to 2010, this country note examines and measures the effect of political, social, and cultural capital on the access of certain individuals to strategic positions in the political field, comparing the legislative and executive branches as represented by deputies and ministers. The empirical analysis includes logit models.

scholarly journals Firm Size, Competition, Financing and Innovation

2014 ◽  
Vol 44 (1) ◽  
pp. 51-73 ◽  
Author(s):  
Zeina Alsharkas
Keyword(s):  
Empirical Analysis ◽  
Firm Size ◽  
Significant Relationship ◽  
Positive Relationship ◽  
Relevant Literature ◽  
Business Environment ◽  
Enterprise Performance ◽  
Logit Models ◽  
Access To Finance ◽  
The Empirical Analysis

Abstract This paper investigates the effects of firm size, competition and access to finance on the innovation performance of that firm. After a review of the relevant literature, three logit models are proposed and tested. The empirical analysis is based on the business environment and enterprise performance survey (BEEPS) for 1053 enterprises from twenty-six countries in years 2002 and 2005. Our results suggest a positive and statistically significant relationship between firm size and innovation. We also find a positive relationship between both competition and access to finance with innovation.

Bayesian Approaches to Assessing the Parallel Lines Assumption in Cumulative Ordered Logit Models

2019 ◽  
pp. 004912411988246
Author(s):  
Jun Xu ◽  
Shawn G. Bauldry ◽  
Andrew S. Fullerton
Keyword(s):  
Health Research ◽  
Logit Model ◽  
Logit Models ◽  
Ordered Logit ◽  
Bayesian Approaches ◽  
Parallel Lines ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Modeling Techniques ◽  
Null Values

We first review existing literature on cumulative logit models along with various ways to test the parallel lines assumption. Building on the traditional frequentist framework, we introduce a method of Bayesian assessment of null values to provide an alternative way to examine the parallel lines assumption using highest density intervals and regions of practical equivalence. Second, we propose a new hyperparameter cumulative logit model that can improve upon existing ones in addressing several challenges where traditional modeling techniques fail. We use two empirical examples from health research to showcase the Bayesian approaches.

scholarly journals feologit: A new command for fitting fixed-effects ordered logit models

2020 ◽  
Vol 20 (2) ◽  
pp. 253-275 ◽  
Author(s):  
Gregori Baetschmann ◽  
Alexander Ballantyne ◽  
Kevin E. Staub ◽  
Rainer Winkelmann
Keyword(s):  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Logit Models ◽  
Ordered Logit ◽  
The Social ◽  
The Standard Model ◽  
Dependent Variables ◽  
Using Data ◽  
New Community ◽  
Time Invariant

In this article, we describe how to fit panel-data ordered logit models with fixed effects using the new community-contributed command feologit. Fixed-effects models are increasingly popular for estimating causal effects in the social sciences because they flexibly control for unobserved time-invariant heterogeneity. The ordered logit model is the standard model for ordered dependent variables, and this command is the first in Stata specifically for this model with fixed effects. The command includes a choice between two estimators, the blowup and cluster (BUC) estimator introduced in Baetschmann, Staub, and Winkelmann (2015, Journal of the Royal Statistical Society, Series A 178: 685–703) and the BUC- τ estimator in Baetschmann (2012, Economics Letters 115: 416–418). Baetschmann, Staub, and Winkelmann (2015) showed that the BUC estimator has good properties and is almost as efficient as more complex estimators such as generalized method-of-moments and empirical likelihood estimators. The command and model interpretations are illustrated with an analysis of the effect of parenthood on life satisfaction using data from the German Socio-Economic Panel.

scholarly journals A warning on separation in multinomial logistic models

2018 ◽  
Vol 5 (2) ◽  
pp. 205316801876951 ◽  
Author(s):  
Scott J. Cook ◽  
John Niehaus ◽  
Samantha Zuhlke
Keyword(s):  
Political Science ◽  
Empirical Analysis ◽  
Penalized Likelihood ◽  
Logistic Models ◽  
Multinomial Logit ◽  
Logit Models ◽  
Red Flags ◽  
Binary Outcome ◽  
Likelihood Estimator ◽  
Multinomial Logit Models

Oppenheim et al. (2015) provides the first empirical analysis of insurgent defection during armed rebellion, estimating a series of multinomial logit models of continued rebel participation using a survey of ex-combatants in Colombia. Unfortunately, many of the main results from this analysis are an artifact of separation in these data – that is, one or more of the covariates perfectly predicts the outcome. We demonstrate that this can be identified using simple cross tabulations. Furthermore, we show that Oppenheim et al.’s (2015) results are not supported when separation is explicitly accounted for. Using a generalization of Firth’s (1993) penalized-likelihood estimator – a well-known solution for separation – we are unable to reproduce any of their conditional results. While our (re-)analysis focuses on Oppenheim et al. (2015), this problem appears in other research using multinomial logit models as well. We believe that this is both because the discussion on separation in political science has primarily focused on binary-outcome models, and because software (Stata and R) does not warn researchers about seperation in multinomial logit models. Therefore, we encourage researchers using multinomial logit models to be especially vigilant about separation, and discuss simple red flags to consider.

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