Results 101 to 110 of about 132,600 (302)
Outliers in Cross-Sectional Regression [PDF]
The robustness of the results coming from an econometric application depends to a great extent on the quality of the sampling information. This statement is a general rule that becomes especially relevant in a spatial context where data usually have lots
Jørgen Lauridsen, Jesus Mur
core
Partial ridge regression under multicollinearity
, 2016 In multiple linear regression analysis, linear dependencies in the regressor variables lead to ill-conditioning known as multicollinearity. Multicollinearity inflates variance of the estimates as well as causes changes in direction of signs of the ...
BAGYALAKSHMI H +3 more
core +1 more source
Agribusiness, EarlyView.ABSTRACT This study investigates the financial literacy (FL) of Swedish farmers, its linkages to farmer characteristics, management accounting practices and farm outcomes by surveying Swedish Farm Accountancy Data Network farmers. Using item response theory, we expand the existing FL measurement specifically to the farming context, assess measurement ...
Uliana Gottlieb, Helena Hansson
wiley +1 more source
Agribusiness, EarlyView.ABSTRACT Smallholder farmers are reverting to traditional production methods due to the high opportunity costs and unintended consequences of new technologies. This study focuses on row planting technology, which is labor‐intensive and slow without mechanized operations.
Emmanuel Tetteh Jumpah +4 more
wiley +1 more source
Repercussions of Multicollinearity in Binary Logistic Regression
, 2022 The type I error rates for the binary logistic regression model were examined across varying levels of multicollinearity. Population data sets were created using the statistical software package R and then used to create data suitable for binary logistic
Ghaner, Aaron Wayne
core
How Competitive Is Myanmar's Rice Sector? A Comparison of Production Costs and Efficiency
Agribusiness, EarlyView.ABSTRACT This paper analyzes the cost competitiveness of rice production in Myanmar by examining production costs, cost efficiency, and the potential effect of improving cost efficiency on the country's global competitiveness. To achieve this, we conduct a comparative analysis of production costs among major rice‐producing countries and estimate the ...
Nandar Aye Chan +3 more
wiley +1 more source
A MODEL TO MINIMIZE MULTICOLLINEARITY EFFECTS [PDF]
, 2013 Multicollinearity implies near-linear dependence among regressors and is one of the diagnostics that harms enough the quality and the estimation of the regression models.
Parpucea Ilie, Baciu Olivia
core
Multicollinearity evaluation results (VIF: Variance inflation factor).
, 2020 Multicollinearity evaluation results (VIF: Variance inflation factor).
Yongsheng Wu (756180) +6 more
core +1 more source
StatsMulticollinearity in logistic regression models can result in inflated variances and yield unreliable estimates of parameters. Ridge regression, a regularized estimation technique, is frequently employed to address this issue.
H. M. Nayem +2 more
doaj +1 more source
Agribusiness, EarlyView.ABSTRACT Farmers markets provide a direct‐to‐consumer marketing path for farmers and small businesses, facilitating customer discovery and product refinement. This paper explores farmers markets as a business incubator, with a focus on beginning vendors and resilience to a shock, namely, COVID‐19 market restrictions.
Mallory L. Rahe +2 more
wiley +1 more source