321_09_slides14

321_09_slides14 - Introduction to Time Series Chapters 10 +...

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Introduction to Time Series 1 Chapters 10 + 11 + 12 Part I
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Outline Definitions and Examples Properties of OLS estimators Trends and seasonality Dependence series Weakly Dependent Time Series Highly persistent Time Series Autocorrelated/Serially correlated errors Testing and correcting Heteroscedasticity and serial correlation 2 Chap . 10 Chap. 11 Chap. 12
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Time Series Data Y -> sample (Y 1 , … Y n ) -> Statistics to estimate either the mean unconditional or the conditional mean E(Y i |X i ) = α 0 + α 1 X i where (X 1 , … X n ) Where observations are unique to individuals, firms, cities, … at a given point in time. Y-> sample (Y 1 , … Y T ) -> Statistics to estimate either the mean unconditional or the conditional mean E(Y t |X) = α 0 + α 1 X t where (X 1 , … X T ) Where observations are unique to one specific period of time (year, quarter, month, day, hour,…) 3
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Example of Time Series 4
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Example of Time Series 5
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6 Population Regression for relationship between with Time Series Data y t = 0 + 1 x t1 + . . .+ k x tk + u t
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Time Series vs. Cross Sectional Time series data has a temporal ordering, unlike cross-section data no longer have a random sample of individuals Will need to alter some of our assumptions Instead, we have one realization of a stochastic (i.e. random) process for each variable 7
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Not like Al Gore! You Tube
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This note was uploaded on 07/11/2011 for the course ECON 321 taught by Professor Louis during the Fall '09 term at Waterloo.

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321_09_slides14 - Introduction to Time Series Chapters 10 +...

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