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Methods to Remove Autocorrelation - Econometric Modeling - Lecture Notes

Lecture Notes, Econometrics

Post: October 22th, 2012
Description
Econometric models are statistical models used in econometric. This modelling tool help economist develop future economy plan for the company. This lecture note discuss important points for understanding Econometric modelling, it includes Methods, Remove, Autocorrelation, Difference, Iterative, Regression, Sensex
Econometric models are statistical models used in econometric. This modelling tool help economist develop future economy plan for the company. This lecture note discuss important points for understanding Econometric modelling, it includes Methods, Remove, Autocorrelation, Difference, Iterative, Regression, Sensex
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2 | P a g e       ui = ρ ui‐1 + εt  For the runs test, in Column VI of the above table, the total number of positive values (N1), and the total  number of negative values (N2) are counted. We also count that R=80 times ui changed signs from  positive to negative and then from negative to positive.   So, for the Runs test, we have N1 = 677, N2 = 720, N=N1+N2 = 1397, and R = 80.  So, E(R) =   + 1 =   + 1 = 698.84  Var(R) =   =   = 348.34  Then, for 95% confidence level (or equivalently, 5% significance level), if observed R falls between  E(R)±1.96σR, then there is no autocorrelation, but if it falls outside, it can be said that autocorrelation  exists.   Now, E(R) + 1.96σR= 698.84 + 1.96 * √348.34 = 735.42  and    E(R) - 1.96σR= 698.84 ‐ 1.96 * √348.34 = 662.26  But observed R is 80, and it lies outside the ..

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