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Lecture14 - Lecture 14 Serial Correlation Econ 444 Winter...

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Lecture 14: Serial Correlation Econ 444, Winter 2010 March 3, 2010
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Serial Correlation : Motivation When we have time series data we have information on same variable at different points in time. It is not surprising to find that there is a high degree of correlation between adjacent time observations of the same variable. For example, 1 In stock market, price of IBM stock in Feb 2008 can be correlated with the price in Jan. 2 Output for 2007 in a chemical manufacturing plant will be correlated with output in 2006.
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Nature of Serial Correlation Serial Correlation or equivalently autocorrelation occurs when the error in one observation is correlated with the error in another observation. Classical Assumption IV is violated Serial correlation is a time series problem. If the correlation is with the previous observation error, this is called 1st order serial correlation or first order autocorrelation.
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Statistical Model One of the most commonly used model for serially correlated stochastic error i is AR(1) : i = ρ i - 1 + u i u i : no autocorrelation; regular error term satisfying all classical assumptions.
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