Open AccessStructuring State Intervention Policies to Boost Rice Production by Multinomial Logistic and Ordinal Regression Application and Multicollinearity Cautiousness
Author(s) -
Shahin Shadfar,
Iraj Malekmohammadi
Publication year - 2013
Publication title -
journal of agricultural studies
Language(s) - English
Resource type - Journals
ISSN - 2166-0379
DOI - 10.5296/jas.v1i2.3869
Subject(s) - multicollinearity , categorical variable , variance inflation factor , multinomial logistic regression , ordinal regression , econometrics , statistics , logistic regression , psychological intervention , production (economics) , overdispersion , ordered logit , quartile , multinomial distribution , mathematics , regression analysis , psychology , economics , count data , psychiatry , macroeconomics , confidence interval , poisson distribution
To structure state interventions policies to develop production of rice in Iran; developing two indexes to measure level of rice production development in dichotomous and categorical level; ordinal and multinomial logistic regression application are implicated to test the model by predictor variables in proposed policy structure. Taking extra care on Multicollinearity (MC), appropriate treatment by calculating Tolerance and Variance Inflation Factor (VIF) is performed. This is to test the fitness of the model by real data from the field, and to evaluate state intervention policies and plans, given this fact if the model fits at this stage, then it merits for further analysis to light up casual relationships among the effective factors on rice production development in Iran.