Consider the time series data for the real consumptian of hausehalds and government from year 1950 to year 2019, Five autoregressive models, AR(1) to AR(5), are estimated as follows, where the t statistics for the corresponding estimated coefficients are in the parentheses, and the size of the samples, n, used for each estimation is also shown in the table. Accarding to the significant lag approach, which model is the optimal under the 5% significance level? AR(1) 5854.66 AR(2) 5041.07 (2.05) 0.92 AR(3) AR(4) 5689.50 AR(5) 7681.51 5365.55 intercept t stat (2.44) (2.13) 0.92 (2.13) (2.82) rcont-1 0.82 0.92 0.92 t stat (315.53) (9.49) (9.41) (9.33) (9.57)

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 5E
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Consider the time series data for the real consumption of households and government from year 1950 to year 2019. Five autoregressive models, AR(1) to AR(5), are estimated as follows,
where the t statistics for the corresponding estimated coefficients are in the parentheses, and the size of the samples, n, used for each estimation is also shown in the table.
According to the significant lag approach, which model is the optimal under the 5% significance level?
AR(1)
AR(2)
AR(3)
AR(4)
AR(5)
5365.55
7681.51
intercept
t stat
5854.66
5041.07
5689.50
(2.44)
(2.05)
(2.13)
0.92
(2.13)
(2.82)
rcont-1
0.82
0.92
0.92
0.92
t stat
(315.53)
(9.49)
(9.41)
(9.33)
(9.57)
-0.26
rcont-2
-0.18
-0.28
-0.27
t stat
(-1.38)
(-1.38)
(-1.31)
(-1.32)
rcon-s
0.08
0.02
0.07
t stat
(0.64)
(0.09)
(0.32)
rcont-4
0.06
-0.32
t stat
(0.38)
(-1.47)
rcont-s
0.34
t stat
(2.32)
65
65
65
65
65
AIC
18.30
18.30
18.33
18.36
18.29
BIC
18.37
18.40
18.46
18.52
18.50
O A. AR(2).
O B. AR(1).
O C. none.
D. AR(5).
Transcribed Image Text:Consider the time series data for the real consumption of households and government from year 1950 to year 2019. Five autoregressive models, AR(1) to AR(5), are estimated as follows, where the t statistics for the corresponding estimated coefficients are in the parentheses, and the size of the samples, n, used for each estimation is also shown in the table. According to the significant lag approach, which model is the optimal under the 5% significance level? AR(1) AR(2) AR(3) AR(4) AR(5) 5365.55 7681.51 intercept t stat 5854.66 5041.07 5689.50 (2.44) (2.05) (2.13) 0.92 (2.13) (2.82) rcont-1 0.82 0.92 0.92 0.92 t stat (315.53) (9.49) (9.41) (9.33) (9.57) -0.26 rcont-2 -0.18 -0.28 -0.27 t stat (-1.38) (-1.38) (-1.31) (-1.32) rcon-s 0.08 0.02 0.07 t stat (0.64) (0.09) (0.32) rcont-4 0.06 -0.32 t stat (0.38) (-1.47) rcont-s 0.34 t stat (2.32) 65 65 65 65 65 AIC 18.30 18.30 18.33 18.36 18.29 BIC 18.37 18.40 18.46 18.52 18.50 O A. AR(2). O B. AR(1). O C. none. D. AR(5).
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