While completely insignificant one year before the occurrence of the crisis, lagging the variable by two-year periods turns the current account balance into the second-best performing indicator, once controlling for the presence of multicollinearity
. A strong performance is also evident for three-year lags.
An issue with applications of stochastic frontier analysis emerges when inputs are highly correlated, from which the multicollinearity
problem arises, leading to precision loss in estimates.
It has been observed that the problem of autocorrelation and multicollinearity
arise simultaneously in several cases.
[34, 35] proposed a new multivariate statistical analysis method to overcome multicollinearity
, namely, partial least squares regression (PLS).
among variables was observed, so these variables were offered to the multivariate logistic regression model process.
In general, the width of a confidence interval of an estimated regression coefficient increases when multicollinearity
On the other hand, our proposed method reduces the possible multicollinearity
Some methods of variable selection, in addition to the effects on the dependent variable is not significant variables can also be removed from the variable group collinear relations in the screening effects on the dependent variable of a few variables significantly, so as to overcome the multicollinearity
. However, for some practical problems, even if the independent variables have a co linear problem, we still want to establish the regression formula of the dependent variable Y and the given independent variables, such as the problem of economic analysis.
The sample and variables were described, and the results of the tests for assumptions and multicollinearity
However, in situations such as faced in the Western case, where the high degree of competition causes significant multicollinearity
among both purchase and sale prices, substantial statistical difficulties impede precise estimations.
These results indicate that the degree of multicollinearity
among the four predictors could be negligible.
Several categories were integrated to avoid multicollinearity
and to achieve unbiased outcome.