scholarly journals Modèle de régression avec variables d’écart

2009 ◽  
Vol 50 (2) ◽  
pp. 177-190 ◽  
Author(s):  
Jean-Guy Loranger
Keyword(s):  
Regression Models ◽  
Likelihood Function ◽  
Threshold Model ◽  
Probability Model ◽  
Switching Regression ◽  
Linear Probability Model ◽  
New Approach ◽  
Slack Variables ◽  
Linear Probability ◽  
Switching Regression Models

Abstract A look at M. G. Dagenais' contributions (1969, 1973) on threshold regression models and at chapter 9 of S.M. Goldfeld and R.E. Quandt's book (1972) concerning switching regression models suggested to me that a new approach to estimating the threshold model by introducing slack variables might be possible. One of the main advantages of this new method is to simplify to a great extent the estimation of the likelihood function which is reduced partly to the problem of estimating a limited number of simple integrals for each iteration in the process of optimization. In order to facilitate a better understanding of our approach, two main models will be reviewed in the next section: the twin linear probability model (which can be estimated either by OLS, by a combination of probit and OLS, or by the tobit approach) and the threshold model. A critical look at the empirical results obtained by Dagenais (1973) will also be made before closing this section. Our new threshold model with slack variables is presented in section 3 and the main features of our new approach are summarized in the last section of this paper.

scholarly journals Pengaruh Faktor Sosial Ekonomi terhadap Perkawinan Muslim di Indonesia

2020 ◽  
Vol 6 (8) ◽  
pp. 1674
Author(s):  
Fauzia Aqilla Fadhil ◽  
Ilmiawan Auwalin
Keyword(s):  
Family Life ◽  
Regression Models ◽  
Probability Model ◽  
Muslim Women ◽  
Sample Population ◽  
Probit Regression ◽  
Linear Probability Model ◽  
Logit Regression ◽  
Indonesian Family Life Survey ◽  
Linear Probability

This study aims to find out what factors that affect a Muslim's decision to get married. This study uses the data from the Indonesian Family Life Survey (IFLS) with a quantitative approach using 83% of the sample population in Indonesia covering approximately 30,000 people taken in 13 of the 27 provinces in Indonesia. This study was analyzed using Linear Probability Model (LPM) regression, Logit regression and Probit regression. The data in this study were processed using STATA MP software. According to the results of data using three regression models, the factors that affect the decision of each individual in Indonesia in general to marry are gender, religion, age, education and occupation. The factors that affect each individual Muslim in Indonesia to make a decision to marry are gender, age, education and occupation. Then, for women in Indonesia in general, the factors that affect the decision to get married are religion, age, and occupation. Last but not least, for Muslim women, the factors that affect the decision to marry is age and occupation.Keywords: Socio-Economy, Muslim Marriage, Marital Decision

Sibling Models, Categorical Outcomes, and the Intra-Class Correlation

2021 ◽  
Author(s):  
Richard Breen ◽  
John Ermisch
Keyword(s):  
Random Effects ◽  
Probability Model ◽  
Intraclass Correlation ◽  
Linear Probability Model ◽  
Intra Class Correlation ◽  
Sibling Differences ◽  
Sibling Models ◽  
Alternative Measures ◽  
Linear Probability ◽  
Parametric Estimate

Abstract In sibling models with categorical outcomes the question arises of how best to calculate the intraclass correlation, ICC. We show that, for this purpose, the random effects linear probability model is preferable to a random effects non-linear probability model, such as a logit or probit. This is because, for a binary outcome, the ICC derived from a random effects linear probability model is a non-parametric estimate of the ICC, equivalent to a statistic called Cohen’s κ. Furthermore, because κ can be calculated when the outcome has more than two categories, we can use the random effects linear probability model to compute a single ICC in cases with more than two outcome categories. Lastly, ICCs are often compared between groups to show the degree to which sibling differences vary between groups: we show that when the outcome is categorical these comparisons are invalid. We suggest alternative measures for this purpose.

The same deep water as you? The impact of alternative governance arrangements of water service delivery on efficiency

2017 ◽  
Vol 3 (2) ◽  
pp. 78-101 ◽  
Author(s):  
Miguel Rodrigues ◽  
António F Tavares
Keyword(s):  
Regulatory Authority ◽  
Regression Models ◽  
Water Governance ◽  
Water Utilities ◽  
Switching Regression ◽  
Water Utility ◽  
Utility Systems ◽  
The Impact ◽  
Switching Regression Models ◽  
Governance Arrangements

This work contributes to the literature on water governance by attempting to provide an answer to the question of what are the differences in efficiency of alternative governance arrangements of water utilities. We test hypotheses derived from property rights, principal–agent, and transaction costs theories using a comprehensive database of 260 water utility systems provided by the Portuguese Regulatory Authority of Water and Waste Services. Using endogenous switching regression models estimated through maximum likelihood, the study is designed in two steps. First, we investigate differences in efficiency between in-house options and externalization and find that in-house solutions as a set (direct provision and municipal companies) are more efficient than externalization options (mixed companies and concessions). Second, we test differences in efficiency within both in-house and externalization solutions, and fail to find statistically significant differences in efficiency between in-house bureaucracies and municipal companies and between mixed companies and concessions.

Charged with Instability: Are Paternal Arrests and Criminal Charges Enough to Shake the Marital Stability of American Couples?

2020 ◽  
Vol 41 (12) ◽  
pp. 2423-2447
Author(s):  
Antonius D. Skipper ◽  
Douglas S. Bates ◽  
Zachary D. Blizard ◽  
Richard G. Moye
Keyword(s):  
Justice System ◽  
Probability Model ◽  
Well Being ◽  
Marital Stability ◽  
Fragile Families ◽  
Linear Probability Model ◽  
Paternal Incarceration ◽  
Criminal Charges ◽  
Linear Probability ◽  
The Relationship

With the growing rate of divorce, increasing efforts are being made to identify the factors that contribute to relationship dissolution for many American couples. One commonly noted, and particularly concerning, factor toward relationship instability is the incarceration of husbands and fathers. Although paternal incarceration and familial stability have been studied, little is known about the relationship between criminal charges and divorce. The current study utilized data from the Fragile Families and Child Wellbeing Study to understand the effect of paternal criminal charges on divorce for 725 families. Utilizing a logistic regression and two-stage least squares linear probability model, results show that, even without incarceration, being charged with a crime as a husband significantly increases the likelihood that a couple will get divorced. These findings have significant implications for understanding how encounters with the criminal justice system affect familial well-being and stability.

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