The Interaction Between Time Nonseparable Preferences And Time Aggregation
The Interaction Between Time Nonseparable Preferences And Time Aggregation
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In our eReader you can find the full English version of the book. Read The Interaction Between Time Nonseparable Preferences And Time Aggregation Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book The Interaction Between Time Nonseparable Preferences And Time Aggregation
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17 quarters using adjusted data. Estimation of a model with just seasonal habit persistence (5--00) results in a log-likelihood value of 140. 61. Testing this restriction against the model with S unrestricted, results in a P-value of 0. 0002 for the likelihood ratio test. Hence there is evidence of an important role for durability in the unadjusted data even at quarterly frequencies that does not exist in seasonally adjusted data.
In sum, the seasonally unadjusted data at quarterly frequencies ...indicates that durability in the goods is important and there is evidence 32 for seasonal habit persistence The model with time-separable preferences does a very poor job in fitting this Quarterly data set. In Section 2, the evidence against the time-additive model came in the form of negative first-order autocorrelation in monthly data. Unfortunately, the Department of Commerce does not publish monthly, seasonally-unadjusted data, which 48 makes the corresponding exercise difficult to perform here.
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To quickly assess the difficulty of the text, read a short excerpt:
17 quarters using adjusted data. Estimation of a model with just seasonal habit persistence (5--00) results in a log-likelihood value of 140. 61. Testing this restriction against the model with S unrestricted, results in a P-value of 0. 0002 for the likelihood ratio test. Hence there is evidence of an important role for durability in the unadjusted data even at quarterly frequencies that does not exist in seasonally adjusted data.
In sum, the seasonally unadjusted data at quarterly frequencies ...indicates that durability in the goods is important and there is evidence 32 for seasonal habit persistence The model with time-separable preferences does a very poor job in fitting this Quarterly data set. In Section 2, the evidence against the time-additive model came in the form of negative first-order autocorrelation in monthly data. Unfortunately, the Department of Commerce does not publish monthly, seasonally-unadjusted data, which 48 makes the corresponding exercise difficult to perform here.
What to read after The Interaction Between Time Nonseparable Preferences And Time Aggregation?
You can find similar books in the "Read Also" column, or choose other free books by John Eaton to read onlineMoreLess
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