Chapter5 UNDERSTANDING LINEAR DEPENDENCE: A LINK TO ECONOMIC MODELS_solutions University of Alabama EC 410
1 view 0 purchase
Course
EC 410
Institution
EC 410
CHAPTER 5.
UNDERSTANDING LINEAR DEPENDENCE:
A LINK TO ECONOMIC MODELS
SOLUTIONS
by
Wei Lin and Yingying Sun
(University of California, Riverside)
Exercise 1
We simulate 1000 observations of the process pt = 6.43 + 0.55pt−1 + εt and plot 100 observations.
Compare Figures 1, 2, and 3 with...
chapter 5 understanding linear dependence a link to economic models solutions by wei lin and yingying sun university of california
riverside exerci
Written for
EC 410
All documents for this subject (12)
Seller
Follow
ExamsConnoisseur
Reviews received
Content preview
Gloria González-Rivera Forecasting For Economics and Business 2013
CHAPTER 5.
UNDERSTANDING LINEAR DEPENDENCE:
A LINK TO ECONOMIC MODELS
SOLUTIONS
by
Wei Lin and Yingying Sun
(University of California, Riverside)
Exercise 1
We simulate 1000 observations of the process pt = 6.43 + 0.55pt−1 + εt and plot 100 observations.
Compare Figures 1, 2, and 3 with Figures 5.2 and 5.3 in the textbook. The price oscillates around
an average price of $14.3 in all these graphs. The time series of the simulated prices in Figures 1, 2
and 3 exhibit smooth dynamics similar to those of the time series in Figure 5.3, in contrast to the
zig-zag behavior of the simulated price in Figure 5.2. This is due to the sign of the autoregressive
parameter, which is positive, i.e. φ = 0.55. When the variance of the error term εt increases,
the time series become noisier and more volatile, so that it tends to ‘hide’ the time dependence.
However, the autocorrelation functions in the three Figures 4, 5 and 6 deliver the same message.
The profile of the three ACF and PACFs is the same: a smooth decay of the autocorrelations
towards zero in the ACFs, and only a significant spike, partial autocorrelation of order one, in the
PACFs. Different variances in the error term do not affect the autocorrelation functions because
the effect of the error variance in the numerator and denominator of the autocorrelation coefficients
cancel each other out. Observe that these autocorrelation functions are similar to that in Figure
5.3 of the textbook. The main difference with the time series and the ACF and PCF in Figure
5.2 of the textbook is the sign of the autoregressive parameter. In Figure 5.2, the sign is negative
(φ = −0.6), which produces the ziz-zag behavior of the time series and the alternating signs of the
autocorrelation coefficients.
1
, Gloria González-Rivera Forecasting For Economics and Business 2013
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller ExamsConnoisseur. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $11.49. You're not tied to anything after your purchase.
