The index of industrial production (IP) is a monthly time series that measures the quantity of industrial commodities produced in a given month. This problem uses data on this index for the United States. All regressions are estimated over the sample period 1986:M1 to 2017:M12 (that is, January 1986 through December 2017). Let Ye=1200 x In(IP/IP-1). Suppose that a forecaster estimates the following AR(4) model for Ye Ŷ=0.749 +0.071Y1 + 0.170Y 2 + 0.216Y 3 + 0.167Y(-4 (0.488) (0.088) (0.053) (0.078) (0.064) The forecaster wants to use this AR(4) to forecast the value of Ye in January 2018, using the following values of IP for July 2017 through December 2017: Date IP 2017:M7 2017:M8 2017:M9 2017:M10 2017:M11 2017:M12 105.01 104.56 104.82 106.58 106.86 107.30 The forecast value is a. The forecast value can not be computed with the given values. O b. 4.104 6.485 Od. 0.787
The index of industrial production (IP) is a monthly time series that measures the quantity of industrial commodities produced in a given month. This problem uses data on this index for the United States. All regressions are estimated over the sample period 1986:M1 to 2017:M12 (that is, January 1986 through December 2017). Let Ye=1200 x In(IP/IP-1). Suppose that a forecaster estimates the following AR(4) model for Ye Ŷ=0.749 +0.071Y1 + 0.170Y 2 + 0.216Y 3 + 0.167Y(-4 (0.488) (0.088) (0.053) (0.078) (0.064) The forecaster wants to use this AR(4) to forecast the value of Ye in January 2018, using the following values of IP for July 2017 through December 2017: Date IP 2017:M7 2017:M8 2017:M9 2017:M10 2017:M11 2017:M12 105.01 104.56 104.82 106.58 106.86 107.30 The forecast value is a. The forecast value can not be computed with the given values. O b. 4.104 6.485 Od. 0.787
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Transcribed Image Text:The index of industrial production (IP) is a monthly time series that measures the quantity of industrial commodities
produced in a given month. This problem uses data on this index for the United States. All regressions are estimated over
the sample period 1986:M1 to 2017:M12 (that is, January 1986 through December 2017). Let Ye=1200 x In(IP/IP-1).
Suppose that a forecaster estimates the following AR(4) model for Ye
Ŷ=0.749 +0.071Y1 + 0.170Y 2 + 0.216Y 3 + 0.167Y(-4
(0.488) (0.088)
(0.053)
(0.078)
(0.064)
The forecaster wants to use this AR(4) to forecast the value of Ye in January 2018, using the following values of IP for
July 2017 through December 2017:
Date
IP
2017:M7 2017:M8 2017:M9 2017:M10 2017:M11 2017:M12
105.01 104.56 104.82 106.58 106.86
107.30
The forecast value is
a.
The forecast value can not be computed with the given values.
O b.
4.104
6.485
Od.
0.787
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