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book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

Edition 3ISBN: 978-9352863501
book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

Edition 3ISBN: 978-9352863501
Exercise 12
Suppose that Y t is the monthly value of the number of new home construction projects started in the United States. Because of the weather, Y t has a pronounced seasonal pattern; for example, housing starts are low in January and high in June. Let
Suppose that Y t is the monthly value of the number of new home construction projects started in the United States. Because of the weather, Y t has a pronounced seasonal pattern; for example, housing starts are low in January and high in June. Let     , denote the average value of housing starts in January and denote the average values in the other months. Show that the values of can be estimated from the OLS regression     where Feb t is a binary variable equal to 1 if t is February, Mar t is a binary variable equal to 1 if t is March, and so forth. Show that ß 0 + ß 2 =     and so forth. , denote the average value of housing starts in January and denote the average values in the other months. Show that the values of can be estimated from the OLS regression
Suppose that Y t is the monthly value of the number of new home construction projects started in the United States. Because of the weather, Y t has a pronounced seasonal pattern; for example, housing starts are low in January and high in June. Let     , denote the average value of housing starts in January and denote the average values in the other months. Show that the values of can be estimated from the OLS regression     where Feb t is a binary variable equal to 1 if t is February, Mar t is a binary variable equal to 1 if t is March, and so forth. Show that ß 0 + ß 2 =     and so forth. where Feb t is a binary variable equal to 1 if t is February, Mar t is a binary variable
equal to 1 if t is March, and so forth. Show that ß 0 + ß 2 =
Suppose that Y t is the monthly value of the number of new home construction projects started in the United States. Because of the weather, Y t has a pronounced seasonal pattern; for example, housing starts are low in January and high in June. Let     , denote the average value of housing starts in January and denote the average values in the other months. Show that the values of can be estimated from the OLS regression     where Feb t is a binary variable equal to 1 if t is February, Mar t is a binary variable equal to 1 if t is March, and so forth. Show that ß 0 + ß 2 =     and so forth. and so forth.
Explanation
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The given regression model is
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Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
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