1. Explain the difference between time series data and cross-sectio...

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1. Explain the difference between time series data and cross-sectional data.
2. Why do we detrend time series data?
3. Define serial correlation and give an example of a time series model that could have serial correlation.
4. What is the difference between consistent and unbiased β?
5. What is the difference between a static and dynamic model? Give an example of each.
6. Complete the remaining tasks with the phillips.dta data on carmen.
(a) Estimate unemployment as a function of inflation in a static model. Write out your estimated equation (numbers) and interpret the result.
(b) Estimate the expectations augmented phillips curve.1 (unemploymentt =α+β1∆inft+et) Write out your estimated equation (numbers) and interpret the result.
(c) Make a time series plot of the residuals from regression (b). (See directions at end)
(d) Do the errors appear to exhibit serial correlation. (Hint: after the regression you can type ”estat bgod” and stata will test for serial correlation with a H0: no serial correlation.)

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1. Explain the difference between time series data and cross-sectional data.
Answer: Cross-Section Data: Different units, workers, consumers, companies, government departments and others are given a single time period. Time Series: Collected data for a single unit (person, company, country) in multiple time periods.

2. Why do we detrend time series data?
Answer: In time series analysis, long-term trends should be removed in order to show short-term changes. To do this, we manipulate data. In other words, we detrend time series data in order to remove the general tendency of a set of data as related to time....

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