The use and impact of business advice by SMEs in Britain: an empirical assessment using logit and ordered logit models

2000 ◽  
Vol 32 (13) ◽  
pp. 1675-1688 ◽  
Author(s):  
P. J. A. Robson ◽  
R. J. Bennett
Keyword(s):  
Logit Models ◽  
Ordered Logit ◽  
Empirical Assessment

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.

The Use and Deployment of Soft Process Technologies within UK Manufacturing SMEs: An Empirical Assessment Using Logit Models

2004 ◽  
Vol 42 (3) ◽  
pp. 303-324 ◽  
Author(s):  
Kevin F. Mole ◽  
Abby Ghobadian ◽  
Nicholas O'Regan ◽  
Jonathan Liu
Keyword(s):  
Logit Models ◽  
Empirical Assessment

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.

Influence of familiarity with traffic regulations on delivery riders’ e-bike crashes and helmet use: Two mediator ordered logit models

2021 ◽  
Vol 159 ◽  
pp. 106277
Author(s):  
Xuesong Wang ◽  
Jiawen Chen ◽  
Mohammed Quddus ◽  
Weixuan Zhou ◽  
Ming Shen
Keyword(s):  
Logit Models ◽  
Ordered Logit ◽  
Helmet Use

Ideology, Vote Choice, and Bureaucracy Across Time: A Longitudinal Test of the Bureau Voting Model in the United States

2015 ◽  
Vol 50 (6) ◽  
pp. 812-834 ◽  
Author(s):  
Michael Bednarczuk
Keyword(s):  
United States ◽  
The United States ◽  
Vote Choice ◽  
Logit Models ◽  
Ordered Logit ◽  
Government Employees ◽  
Generalized Ordered Logit ◽  
Using Data ◽  
Election Studies ◽  
Voting Model

How applicable is the bureau voting model to the United States? Although the literature suggests that government employees are more liberal and vote more Democratic, these findings have recently become inconsistent stateside. In addition, there are strong counterarguments to the premises of the bureau voting model. It is hypothesized that bureaucrats are neither more likely to support Democrats nor more liberal. Using data from the American National Election Studies covering a 30-year period, probit and generalized ordered logit models support these new hypotheses. These results suggest that the bureau voting model may need to be refined for the United States.

Sign in / Sign up

Export Citation Format

Share Document