scholarly journals Estimating Ordered Categorical Variables Using Panel Data: A Generalized Ordered Probit Model with an Autofit Procedure

2010 ◽  
Author(s):  
Christian Pfarr ◽  
Andreas Schmid ◽  
Udo Schneider
Keyword(s):  
Panel Data ◽  
Probit Model ◽  
Ordered Probit ◽  
Categorical Variables ◽  
Ordered Probit Model ◽  
Ordered Categorical Variables ◽  
Ordered Categorical ◽  
Generalized Ordered Probit

A generalized ordered Probit model

2019 ◽  
Vol 49 (7) ◽  
pp. 1712-1729 ◽  
Author(s):  
Carla Johnston ◽  
James McDonald ◽  
Kramer Quist
Keyword(s):  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Generalized Ordered Probit

scholarly journals Economic Inequality in Portugal: A Picture in the Beginnings of the 21st Century

2010 ◽  
Author(s):  
Santiago Budria
Keyword(s):  
21St Century ◽  
Employment Status ◽  
Economic Status ◽  
Economic Inequality ◽  
Probit Model ◽  
Ordered Probit ◽  
Economic Mobility ◽  
Ordered Probit Model ◽  
Capital Income ◽  
Generalized Ordered Probit

This article uses data from the 1994-2001 waves of the European Community Household Panel to study economic inequality in Portugal. It reports data on the distributions of income, labour earnings, and capital income, and on related features of inequality, such as age, employment status, educational attainment, marital status, and economic mobility. A Generalized Ordered Probit model is used to investigate how and to what extent the different household characteristics contribute to economic status and economic mobility. The article shows that education is by and large the dimension most closely related to inequality.

Do the heterogeneous determinants of life satisfaction affect differently across borrowers of diverse credit sources? A propensity score approach

2018 ◽  
Vol 45 (8) ◽  
pp. 1142-1158 ◽  
Author(s):  
Tiken Das ◽  
Manesh Choubey
Keyword(s):  
Life Satisfaction ◽  
Propensity Score ◽  
Probit Model ◽  
Ordered Probit ◽  
Primary Data ◽  
Ordered Probit Model ◽  
Future Research ◽  
Content Type ◽  
Credit Access ◽  
Physical Assets

Purpose The purpose of this paper is to evaluate the non-monetary effect of credit access by providing an econometric framework which controls the problem of selection bias. Design/methodology/approach The study is conducted in Assam, India and uses a quasi-experiment design to gather primary data. The ordered probit model is used to evaluate the non-monetary impact of credit access. The paper uses a propensity score approach to check the robustness of the ordered probit model. Findings The study confirms the positive association of credit access to life satisfaction of borrowers. It is found that, in general, rural borrower’s life satisfaction is influenced by the ability and capacity to work, the value of physical assets of the borrowers as well as some other lenders’ and borrowers’ specific factors. But, the direction of causality of the factors influencing borrowers’ life satisfaction is remarkably different across credit sources. Research limitations/implications The study argues to provide productive investment opportunities to semiformal and informal borrowers while improving their life satisfaction score. Although the results are adjusted for selection and survivorship biases, it is impossible with the available data to assess which non-income factors explain the findings, and therefore this limitation is left to future research. Originality/value The study contributes to the literature of rural credit by assessing the probable differences among formal, semiformal and informal credit sources with respect to non-monetary impacts.

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