Mental disorders are common non-communicable diseases whose occurrence rises at epidemic rates globally. The determination of the severity of a mental illness has important clinical implications and it serves as a prognostic factor for effective intervention planning and management. This paper...

In this paper, an improved ridge type estimator is introduced to overcome the effect of multi-collinearity in logistic regression. The proposed estimator is called a modified almost unbiased ridge logistic estimator. It is obtained by combining the ridge estimator and the almost unbiased ridge...

Two-predictor suppression situations continue to produce uninterpretable conditions in linear regression. In an attempt to address the theoretical complexities related to suppression situations, the current study introduces two different versions of a software called suppression simulator...

The age-period-cohort problem has been studied for decades but without resolution. There have been many suggested solutions to make the three effects estimable, but these solutions mostly exploit non-linear specifications. Yet, these approaches may suffer from misspecification or omitted...

Mental disorders are common non-communicable diseases whose occurrence rises at epidemic rates globally. The determination of the severity of a mental illness has important clinical implications and it serves as a prognostic factor for effective intervention planning and management. This paper...

In this paper, an improved ridge type estimator is introduced to overcome the effect of multi-collinearity in logistic regression. The proposed estimator is called a modified almost unbiased ridge logistic estimator. It is obtained by combining the ridge estimator and the almost unbiased ridge...

Two-predictor suppression situations continue to produce uninterpretable conditions in linear regression. In an attempt to address the theoretical complexities related to suppression situations, the current study introduces two different versions of a software called suppression simulator...

In this paper, we suggest improved estimation strategies based on preliminarily test and shrinkage principles in a seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the vector regression coefficient of each equation into two...

In this paper, we suggest improved estimation strategies based on preliminarily test and shrinkage principles in a seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the vector regression coefficient of each equation into two...

Multicollinearity, especially in combination with errors-in-variables, can increase the likelihood of a Type-I error by inflating the value of the estimated coefficients by more than it magnifies their standard errors, thereby increasing the likelihood of obtaining statistically significant...

Multicollinearity, especially in combination with errors-in-variables, can increase the likelihood of a Type-I error by inflating the value of the estimated coefficients by more than it magnifies their standard errors, thereby increasing the likelihood of obtaining statistically significant...

Abstract Multivariate regression models and ANOVA are probably the most frequently applied methods of all statistical analyses. We study the case where the predictors are qualitative variables and the response variable is quantitative. In this case, we propose an alternative to the classic...

It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained by using the Ordinary Least Squares (OLS) method are unstable. As a solution to this situation, in this paper we present the raised method, the ridge method and the orthogonal...

There is a widespread belief among economists that adding additional variables to a regression model causes higher standard errors. This note shows that, in general, this belief is unfounded and that the impact of adding variables on coefficients' standard errors is unclear. The concept of...

In empirischen Analysen werden Testergebnisse häufig tabellarisch als statistisch signifikante oder insignifikante Resultate ausgewiesen. Der vorliegende Beitrag beschäftigt sich mit der sachgerechten Interpretation der insignifikanten Resultate und der Analyse möglicher Ursachen. Als...

There is a widespread belief among economists that adding additional variables to a regression model causes higher standard errors. This note shows that, in general, this belief is unfounded and that the impact of adding variables on coefficients’ standard errors is unclear. The concept of...

It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained by using the Ordinary Least Squares (OLS) method are unstable. As a solution to this situation, in this paper we present the raised method, the ridge method and the orthogonal...

This paper investigates the nature of the IV method for tackling endogeneity. By tracing the rise and fall of the method in macroeconometrics and its subsequent revival in microeconometrics, it pins the method down to an implicit model respecification device-breaking the circular causality of...

Based on Chinese city-level data from 1999 to 2012 and controlling for geological, environmental, and social diversity, this study suggests that credit plays a significant role in driving up house prices after the Great Recession, whereas property prices only influence bank lending before 2008....

Fixed effects (FE) in panel data models overlap each other and prohibit the identification of the impact of ''constant'' regressors. Think of regressors that are constant across countries in a country-time panel with time FE. The traditional approach is to drop some FE and constant regressors by...

Using Chinese city-level data from 1999 to 2012 and considering geological, environmental, and social diversity, this study suggests that credit plays a significant role in driving up house prices after the Great Recession, whereas property prices only influence bank lending before 2008....

Based on Chinese city-level data from 1999 to 2012 and controlling for geological, environmental, and social diversity, this study suggests that credit plays a significant role in driving up house prices after the Great Recession, whereas property prices only influence bank lending before 2008....

Fixed effects (FE) in panel data models overlap each other and prohibit the identification of the impact of ''constant'' regressors. Think of regressors that are constant across countries in a country-time panel with time FE. The traditional approach is to drop some FE and constant regressors by...

This paper investigates the nature of the IV method for tackling endogeneity. By tracing the rise and fall of the method in macroeconometrics and its subsequent revival in microeconometrics, it pins the method down to an implicit model respecification device - breaking the circular causality of...

This paper examines how ëconfluenceí and ëautonomyí, two key concepts introduced by Frisch around 1930, have disappeared in econometrics textbooks and why only some fragments of the two have survived mainstream econometrics. It relates the disappearance to the defect in the textbook position...

This paper investigates the nature of the IV method for tackling endogeneity. By tracing the rise and fall of the method in macroeconometrics and its subsequent revival in microeconometrics, it pins the method down to an implicit model respecification device - breaking the circular causality of...

This paper investigates the nature of the IV method for tackling endogeneity. By tracing the rise and fall of the method in macroeconometrics and its subsequent revival in microeconometrics, it pins the method down to an implicit model respecification device - breaking the circular causality of...