Transcription of Chapter 9 Autocorrelation - IIT Kanpur
{{id}} {{{paragraph}}}
Example: marketing
Chapter 9 Autocorrelation - IIT Kanpur
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. When (, )0, 0ttsEu us is violated, , the variance of disturbance term remains constant though the successive disturbance terms are correlated, then such problem is termed as the problem of Autocorrelation .
Estimation under the first order autoregressive process: Consider a simple linear regression model yXut nttt 01 ,1,2,...,. Assume usi ' follow a first-order autoregressive scheme defined as uutt t 1 where 1, ( ) 0,E t 2 if 0 (, ) tts0if 0 s E s
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: