scholarly journals Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco Use

2012 ◽  
Vol 2012 ◽  
pp. 1-26 ◽  
Author(s):  
Shiferaw Gurmu ◽  
Getachew A. Dagne
Keyword(s):  
Regression Model ◽  
Probit Model ◽  
Joint Modeling ◽  
Ordered Probit ◽  
Probit Regression ◽  
Chewing Tobacco ◽  
Excess Zeros ◽  
Monte Carlo Techniques ◽  
Excess Of Zeros ◽  
Bivariate Ordered Probit

This paper presents a Bayesian analysis of bivariate ordered probit regression model with excess of zeros. Specifically, in the context of joint modeling of two ordered outcomes, we develop zero-inflated bivariate ordered probit model and carry out estimation using Markov Chain Monte Carlo techniques. Using household tobacco survey data with substantial proportion of zeros, we analyze the socioeconomic determinants of individual problem of smoking and chewing tobacco. In our illustration, we find strong evidence that accounting for excess zeros provides good fit to the data. The example shows that the use of a model that ignores zero-inflation masks differential effects of covariates on nonusers and users.

scholarly journals Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

2019 ◽  
Vol 16 (14) ◽  
pp. 2632 ◽  
Author(s):  
Chen ◽  
Song ◽  
Ma
Keyword(s):  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Seat Belt ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Random Parameters ◽  
Factors Affecting ◽  
Bivariate Ordered Probit ◽  
Bivariate Ordered Probit Model

The existing studies on drivers’ injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers’ injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

scholarly journals Analysis of Factors Influencing Household Preference Level for Seafood in Southwest Nigeria

2021 ◽  
pp. 1-10
Author(s):  
Olaniran Anthony Thompson
Keyword(s):  
Logistic Model ◽  
Nutritive Value ◽  
Sampling Technique ◽  
Probit Model ◽  
Ordered Probit ◽  
Probit Regression ◽  
Multinomial Logistic Model ◽  
Factors Influencing ◽  
Southwest Nigeria ◽  
Household Preference

Seafood is known worldwide as a very important component of human diet because of its high nutritive value and significance in improving human health. The study examines the factors influencing households’ preference level for seafood and determines the factors inducing the choice of seafood consumption by households in Southwest Nigeria. Multi-stage sampling technique was used to select 300 households in Oyo and Lagos States, Southwest Nigeria. Ordered probit regression model was used to examine the factors influencing household preference level for seafood and multinomial logistic model was used to determine the factors inducing the choice of seafood consumed by the households in the study area. The ordered probit model estimation results revealed that access to seafood within 1km – 4km was significant at 5% and positively relates to household preference for seafood. Increase in income of the household will increase the likelihood of having high preference for seafood (14.39%) by the respondents in the study area. Multinomial logistic model results revealed that the education level of the respondents influenced the choice of croaker fish by 12.01% relative to shrimp in the study area. Therefore, the study recommends that seafood marketers should ensure a good distribution network that will enhance its accessibility within one and four kilometers in the study area.

scholarly journals Macroeconomic imbalance procedure (MIP) scoreboard indicators and their predictive strength of “multidimensional crises”

Equilibrium ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 11-28
Author(s):  
Krzysztof Biegun ◽  
Jacek Karwowski
Keyword(s):  
Value Added ◽  
Probit Model ◽  
International Investment ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Probit Regression ◽  
Cost Index ◽  
Eu Countries ◽  
Predictive Strength ◽  
The Eu

Research background: The evaluation of the predictive strength of MIP indicators in relation to crises is extremely important for the process of coordinating the economic policies of the EU countries. MIP is one of the pillars of the economic crisis prevention procedure. Predictive power of individual indicators has not been tested before their introduction. Purpose of the article: Evaluation of the predictive strength of fourteen MIP indicators in relation to multidimensional crises in the EU countries. Methods: We used ordered probit model to test the ability of MIP indicators to correctly predict episodes of “multidimensional crises” (as defined by the authors) in the period between 2008 and 2017 in all EU Member States. Findings & Value added: We defined “multidimensional crises”, combining several negative phenomena into one limited dependent variable. This work is also novel in its application of probit regression to test the predictive strength of MIP indicators with an ordered probit model. We identified five MIP variables which were statistically significant in predicting “multidimensional crises” for all EU countries: net international investment position, nominal unit labour cost index, house price index, private sector credit flow and general government gross debt. Other variables turned out to be less important or not effective in crises prediction.

Migration and Subjective Poverty in sending countries: An analysis of the Egyptian case

2014 ◽  
Vol 11 (3) ◽  
pp. 353-367 ◽  
Author(s):  
Yehudith Kahn ◽  
Audrey Dumas ◽  
Yovav Eshet ◽  
Nir Billfeld
Keyword(s):  
Probit Model ◽  
Ordered Probit ◽  
Survival Strategy ◽  
Significant Determinant ◽  
Individual Level ◽  
Subjective Poverty ◽  
Bivariate Ordered Probit ◽  
The Individual ◽  
The Impact ◽  
Bivariate Ordered Probit Model

Migration has traditionally been used as a survival strategy in times of financial crisis; however, a debate exists as to whether migration influences poverty on the individual level. The current study analyses the influence of past subjective poverty on migration choice and to determine the impact of migration on current subjective poverty perception. Using a simultaneous bivariate ordered probit model, we found that poorer individuals in Egypt tend to migrate more than others. Migration was found to be a significant determinant of current poverty in Egypt. Finally, migration improved migrant’s financial situation. 

Conflict determinants in Africa

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
J. Paul Dunne ◽  
Nan Tian
Keyword(s):  
Political Science ◽  
Statistical Significance ◽  
Probit Model ◽  
Ordered Probit ◽  
Regional Context ◽  
Excess Zeros ◽  
Recent Developments ◽  
Definition Of ◽  
Conflict In Africa ◽  
Model Approach

This article considers the determinants of conflict in Africa. It revisits the greed versus grievance debate to consider the specific regional context and changing nature of conflict in Africa. This is a literature that has grown rapidly in economics and political science, but some recent developments in modeling and conceptualization are providing important new contributions. The article uses the zero-inflated ordered probit technique that deals with the problem of excess zeros in datasets, revisits the definition of conflict, and improves upon some proxy measures. It also considers the substantive as well as statistical significance of the variables. Changes in the technique used provide more support for the influence of grievance terms than given credit for with the usual probit model approach. Both greed and grievance determine conflict in Africa.

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