Ordered Logit Model

This paper compares the performance of trip generation models. Trip generation estimates the number of trips to and from a traffic analysis zone. This process is the first stage of the conventional four-step travel forecasting framework. Although many approaches have been suggested for this step, regression and category analyses have been widely applied. The two methods have generated an acceptable level of performance from the perspective of transport planning. Critical problems, however, have also been observed. In the regression analysis, trip rates are treated as continuous variables that can be negative, which is obviously unrealistic. Furthermore, the method does not incorporate traveler behavior. For the category analysis, its arbitrary way of choosing independent variables and their strata has drawn critiques. The cell-by-cell calculation in this method also increases the concerns about unreliable estimation of trip rates. Censored regression, count data, and discrete choice models have been visited for the alternative of regression approach while the multiple classification method has been conceived for the substitute of the category analysis. A systematic examination of the performance among the models has not been discussed sufficiently yet, which is the motive of this paper. Six representative models – regression, tobit, Poisson, ordered logit, category, and multiple classification analyses – were applied to the home-based work trips in the Seoul metropolitan area. Cross-validation and back-casting were the key for checking the performance among the models. In this process, the measures of correlation, variance, and coincidence were compared. The category-type model was superior in overall performance."

En el presente trabajo se analizan los factores que influyen de manera positiva y negativa el riesgo relativo para las mujeres de 14 a 29 años en México de tener un embarazo no deseado con información obtenida de la Encuesta Nacional de Juventud 2010. Los datos extraídos de dicha fuente fueron utilizados para modelar las variables que, de manera teórica, se encuentran asociadas al embarazo no deseado en nuestro país. Los resultados sugieren que las mujeres del área urbana con mayor número de hijos que viven en una situación de violencia con la pareja tienen un riesgo relativo mayor de tener un embarazo no deseado al controlar por el resto de las variables . Al concluir este breve documento se puede constatar que dentro los retos de salud reproductiva en México, el embarazo no deseado continúa siendo un factor importante en materia de políticas públicas y es prioridad  disminuir su incidencia.

Determining independent variable relative importance is a highly useful practice in organizational science. Whereas techniques to determine independent variable importance are available for normally distributed and binary dependent variable models, such techniques have not been extended to multicategory dependent variables (MCDVs). The current work extends previous research on binary dependent variable relative importance analysis to provide a methodology for conducting relative importance analysis on MCDV models from a dominance analysis (DA) perspective. Moreover, the current work provides a set of comprehensive data analytic examples that demonstrate how and when to use MCDV models in a DA and the advantages general DA statistics offer in interpreting MCDV model results. Moreover, the current work outlines best practices for determining independent variable relative importance for MCDVs using replicable examples on data from the publicly available General Social Survey. The present work then contributes to the literature by using in-depth data analytic examples to outline best practices in conducting relative importance analysis for MCDV models and by highlighting unique information DA results provide about MCDV models.

Adoption of improved food crop technologies is known to be the prerequisite for productivity improvement. However, due to different
socioeconomic, demographic and institutional factors the level of food crop technology adoption and utilization is not optimal. A meta-analysis is
performed to review empirical estimates of Adoption factors of improved food crop technologies in Ethiopia. The result indicated the adoption of the
technology defined by sample size, technology type, study period. The analysis result also confirmed that the mean size effect of food crop technology
adoption estimate is function of training, irrigation, extension service and credit access, oxen holding, cooperative membership, TLU, labor force
and income. This implied that through awareness creation, improving farmer to farmer and farmer to extension and research linkage, improving
credit access, infrastructural development, livestock ownership and income earning opportunity, it is possible to accelerate the speed of food crop
technologies. The study results also justified that food crop technologies only focused on the specific technology type and quantity, not on how the
technology implemented by farmers, these assumed to be probable reason for low adoption of improved practices that resulted in low agricultural production and productivity the sector

Improving road safety through proper pavement maintenance is one of the goals of pavement management. Many studies have found that pavement conditions significantly influence traffic safety. Although several studies have explored the relationship between pavement conditions and crash occurrence, the effect of poor pavement conditions on crash severity levels has not been investigated, especially by using a discrete model that can handle ordered data. This paper focuses on the development of the relationship between poor pavement conditions and crash severity levels using a series of Bayesian ordered logistic models for low/medium/high speed roads and single/multiple collision cases. The Bayesian ordered logistic regression models indicated that the poor pavement condition decreases the severity of singlevehicle collisions on low-speed roads whereas it increases their severity on high-speed roads. On the other hand, the poor pavement condition increases the severity of multiple-vehic...

In this paper, we present an ordered logit model. The choice variable (dependent variable) is the number of trips done by an individual in a day. We estimate the model using the data of the Swiss national travel survey, the Mobility and Transport Microcensus, collected in 2015. We internally validate the model. We also externally validate the model using a synthetic population of the Swiss resident population of 2017. Finally, we apply the model to a synthetic population for 2030, forecasting the number of trips that will be done in the future. This is a work in progress, describing an approach and not final results. In particular, no calibration of the cuts of the ordered logit model was done.

Employee turnover is one of the challenging issues in many organizations, including in the banking industry. Most employers are not aware of why employees choose to leave and what drives their job satisfaction. Due to the distributed questionnaire, employee turnover measurement will be accomplished by the derivation of PQ (probability of quit). The author estimates PQ with logistic technique, using collected responses from 140 RA banking sector employees (or ex-employees). Job satisfaction was measured using ordered logit & probit models. Preliminary results show significant association with 6 factors, which drives employee turnover and several consequences impacting on job satisfaction. For further, the study can be extended using data science tools with large sample size or for the concrete bank to better understand employee’s behavior and predict their turnover & job satisfaction.

Improving road safety through proper pavement maintenance is one of the goals of pavement management. Many studies have found that pavement conditions significantly influence traffic safety. Although several studies have explored the relationship between pavement conditions and crash occurrence, the effect of poor pavement conditions on crash severity levels has not been investigated, especially by using a discrete model that can handle ordered data. This paper focuses on the development of the relationship between poor pavement conditions and crash severity levels using a series of Bayesian ordered logistic models for low/medium/high speed roads and single/multiple collision cases. The Bayesian ordered logistic regression models indicated that the poor pavement condition decreases the severity of singlevehicle collisions on low-speed roads whereas it increases their severity on high-speed roads. On the other hand, the poor pavement condition increases the severity of multiple-vehic...

In this paper a method is proposed to assess the safety and security perceived by travelers in the railway stations and an application to the case study of the (medium size) station of Frosinone, Italy, is presented. The methodology is based on Probit and Logit ordered choice models, estimated using data collected through a RP/SP survey. Main findings confirm that security issues are perceived as more threatening than safety ones. Models estimates show that thefts, harassments, aggressions are the most relevant variable affecting the perception of safety and security in the station. Railways underpasses to reach platforms and the presence of commercial activities resulted to be significant factors as well. Moreover, the levels of perception vary also with the socio-economic characteristics and the personal attitudes, meaning that not all the measures for effective safety and security are equally perceived.

Resumen: Este trabajo examina los determinantes de la duración del primer desempleo de una cohorte de jóvenes graduados: los que obtuvieron su titulación en el curso 2001/2002 en las carreras del área económica de la Universidad de Sevilla. Tras estimar un logit ...

The research aims to examine the vulnerability and resilience of road transport enterprises in Poland to a crisis caused by the COVID-19 pandemic. In theory, we refer to the Schumpeterian perspective of creative destruction. In the empirical analysis, survey data on 500 transport companies randomly selected from the database were used. We estimated partial proportional odds models to show the factors responsible for the enterprises' vulnerability and resilience to unforeseen shock. The perspective refers to the total sample size and the division into two subgroups: micro and small and medium enterprises. To justify the results, we calculated a set of statistical indicators and tests. These models enable separating enterprises according to the vulnerability level. Transport enterprises occurred significantly vulnerable to the COVID-19 crisis, particularly the demand shock. The only factor that influenced resilience was the decrease in fuel prices, which allowed a cost reduction. The crisis showed that government aid was helpful in the short run, particularly for micro and small enterprises. The medium-sized enterprises were more resilient than micro and small ones. We formulated several recommendations to help transport enterprises to adjust in the medium term.

Public health initiatives are the result of strategies developed to address current health issues facing a population that are posing a significant concern to the public. This concern is primarily driven by the economics of health care. The objective of this study is to provide a contemporary analysis of how socio-economic and behavioral factors influence subjective health status. By understanding how these factors influence perceived health status, we can develop successful policies and strategies to target those groups who have a gap between their perceived and real health status and significantly lower health care costs. This analysis makes use of the socio-economic and behavioral data from the 2005-2006 NHANES and an extension of the traditional economic model for ordered data. Results indicate that higher education and an individual's perceived diet quality have a significant effect on influencing an individual's health perception. Strategies to improve health status ma...

The aim of this study is to put forward income differences for Turkey according to the ordered logit and human capital models. For this reason, data of the Budget Survey between 2002 and 2006 by TurkStat were used. The dependent variable was the annual yearly disposable income from the main job acquired by an individual, who brought income to the household from his main job. Interpolation was used in categorizing income, a continuous variable, and curve fitting was performed with the least squares approach. In the study, the probabilities in income groups and the changes in probabilities were calculated by the ordered logit model. Later on, it was aimed to put forward the factors that determine income differences for Turkey by using the information on education, age, occupation and marital status of individuals and the social and economic information for a household through the Mincer type of human capital model.
Keywords: Income difference, Continuous variable, Curve fitting, Discrete variable, Ordered Logit, Selectivity bias, Least squares method.

The household income distribution is an important explanatory variable of the residential
electricity consumption. This paper specifies a proportional odds model and a proportional
hazard model to forecast the household share in each income class. The models are applied on an
average income scenario and the projections for household income distribution are evaluated by
income inequality indices.

This study assesses the agricultural commercialization levels, determinants, and challenges confronting smallholder cassava farmers in Oyo State, Nigeria. This study was conducted in Oyo State, Nigeria using cross-sectional data from 211 smallholder cassava farmers and employing multi-stage sampling procedures. Descriptive statistics, Crop Commercialization Index (CCI), and Ordered Logit Model (OLM) were used to analyze the data collected. The results revealed that 83.9% of the cassava farmers participated in the commercialization of their cassava roots while the remaining farmers were non-participants. The greatest challenge faced by the cassava farmers in the study area was the incessant attacks by the Fulani herdsmen (destroying growing cassava on the farm) while other challenges included cassava cyclical gluts and poor access road. Moreover, OLM revealed that age, farm size, cassava marketing experience and distance to market had significant influence on commercialization levels...

Bu calismada Rize ili merkezindeki ozel ya da devlet okullarinda ilkogretim okumakta olan 288 ogrencinin ailelerine anket uygulanmis ve elde edilen veriler dogrultusunda ailelerin devlet ya da ozel okul tercihlerini etkileyen faktorler Logit ve Probit modeli kapsaminda belirlenmeye calisilmistir Bircok aciklayici degisken arasindan; ailenin aylik toplam geliri toplam gelirin okulda okuyan cocuga ayrilan kismi babanin yasi babanin meslegi annenin meslegi ve annenin maasi on plana cikan degiskenler olarak saptanmistir Anahtar Kelimeler: Egitim Okul Tercihi Logit Modeli Probit Modeli FACTORS INFLUENCING PARENTS’ PRIVATE OR PUBLIC SCHOOL CHOICES THE CASE OF RIZE

Work-related stress is increasing in prevalence, with important consequences for employees, employers, the economy, and wider society. While previous research has identified a link between work-related stress and bullying, gaps remain in our understanding of the nature of the relationship. This article uses ordered logistic regression and nationally representative data on 5110 employees from Ireland to empirically analyse the distribution of subjective work-related stress and its relationship with bullying (self-reported). We also consider the role and importance of gender and the presence of a formal policy on respect and dignity at work, as well as the degree to which relationships between management and staff and between staff themselves are related to work-related stress. Amongst the main findings are that employees who reported that they were bullied were considerably more likely to report that they were often or always stressed, while bad and very bad relationships between management and staff were also significantly associated with greater stress, particularly for female employees. Overall, our findings have a range of implications for employees, employers, and policymakers.

Streszczenie: Celem pracy była wielowymiarowa analiza zróżnicowania poziomu życia mieszkańców Polski według powiatów. Zaproponowano dwuetapowe podejście – w pierw-szym etapie dokonano oceny poziomu życia z wykorzystaniem metody TOPSIS w ujęciu pozycyjnym z zastosowaniem przestrzennej mediany Webera. Biorąc za podstawę wyniki etapu 1, czyli klasy powiatów według poziomu życia, zastosowano wielomianowy model logitowy kategorii uporządkowanych. Zbudowany model pozwolił określić istotność (siłę i kierunek) wybranych czynników zrównoważonego rozwoju (takich jak zdrowie, warunki życia gospodarstw domowych, dostęp do rynku pracy, warunki mieszkaniowe i bioróżno-rodność) na poziom życia mieszkańców. Podstawę empiryczną badań stanowiły dane staty-styczne z Banku Danych Lokalnych GUS dla 2014 roku. Badania potwierdziły, że stymulu-jący wpływ na podniesienie poziomu życia miały: poprawa bazy leczniczej i zabiegowej, rozbudowa terenów zieleni, a także poprawa warunków mieszkaniowych ludności. Słowa kluczowe: metody taksonomiczne, metoda TOPSIS, uporządkowany model logitowy.
Summary: The goal of the paper was a multi-dimensional analysis of the differences in the living standard of the population in districts in Poland. A two-staged approach was proposed. In the first stage the standard of living assessment was performed using the TOPSIS method in the positional aspect and applying the spatial Weber median. Basing on the results of stage 1, the logit ordered model was created. The model allowed specifying the importance (magnitude and direction) of some selected sustainable development factors (such as: health, housing conditions, advancement level of households, access to the job market, biodiversity) and their influence on the standard of living. The statistical data from the Central Statistical Office of Poland for 2014 were the empirical research basis. The studies confirmed the stimulating influence of the improvement in medical care, housing conditions and the extension of town parks on the increase in the standard of living.
Keywords: taxonomic methods, TOPSIS method, ordered logit model.

This paper basically examined the relationship between the country debt ratings based onseveral basic factors like GDP per capita ,GDP growth, Inflation rate, external balance etc. which may affect the country’s ratings. I have used three company’s debt
ratings (Fitch ratings,Standard and Poor, Moody’s ratings) as my dependent variable and tried to see which companygives the closest results towards the actual ratings. I have used the Ordered Logit /Probit model to estimate the parameters .For the regression I have taken the 79 country’s data including Developed, Developing and Under Developing countries. I have used cross-sectional data for the year 2011 to find the results. We will also see how any country’s ratings can be improved in future.