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Use all the data in PHILLIPS to answer this question. You should now use 56 years of data.(i) $\quad$ Reestimate equation $(11.19)$ and report the results in the usual form. Do the intercept and slope estimates change notably when you add the recent years of data? (ii) Obtain a new estimate of the natural rate of unemployment. Compare this new estimate with that reported in Example $11.5 .$(iii) Compute the first order autocorrelation for unem. In your opinion, is the root close to one?(iv) Use cunem as the explanatory variable instead of unem. Which explanatory variable gives a higher $R$ -squared?

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(i) See video. Similar (ii) Slightly smaller than 11.15 (iii) .75, not close to one (iv) cunem somewhat better

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Chapter 11

Further Issues in Using OLS with Time Series Data

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Use the data in PHILLIPS f…

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Use the data in TRAFFIC2 f…

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(i) Estimate equation $(10…

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Use the data in EZANDERS f…

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Use the data in PHILLIPS t…

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For the following exercise…

part one. This is the regression result using the data through 2000 and three. Compared to equation 11.19, these estimates are similar. Both the intercept and slope have a little smaller magnitude. Yeah, mark you. The new estimate of the natural rate is 2.83 divided by 0.518 and you can get 5.46 which is slightly smaller. Then the 5.58 obtain using Onley the data through 1996 for three. The first order auto correlation of unemployment is about 0.75 This correlation between unemployment and its first leg is large, but it is not especially close to one. In Part four, we will use the change in unemployment as the main explanatory variable. This variable fits somewhat better. This model is somewhat better. We have a slightly higher Oscar, and the coefficient of unemployment is somehow larger, which implies a more pronounced trade off between inflation and unemployment.

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