Transcription of Chapter 9 Autocorrelation - IIT Kanpur
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Econometrics | Chapter 9 | Autocorrelation | Shalabh, IIT Kanpur 11 Chapter 9 Autocorrelation One of the basic assumptions in the linear regression model is that the random error components or disturbances are identically and independently distributed. So in the model ,yXu it is assumed that 2if 0(, )0 if 0uttssEu us , the correlation between the successive disturbances is zero. In this assumption, when 2(, ) , 0ttsuEu us is violated, , the variance of disturbance term does not remain constant, then the problem of heteroskedasticity arises.
The autocorrelation function begins at some point determined by both the AR and MA components but thereafter, declines geometrically at a rate determined by the AR component. In general, the autocorrelation function - is nonzero but is geometrically damped for AR process.
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