Table 4
Granger causality test results for industrial property
Δ tbi |
Δ reit |
Explanatory variable |
ΔD |
Adj. RP2P | ||
ΔIRN |
Δ S |
Δ SE | ||||
Pairwise model | ||||||
■g ω Δ ind_tbi .52 |
.00 |
.54 | ||||
■8 5 Δ ind reit .07 eg — о Й |
.45 |
.56 | ||||
Multiple variable model | ||||||
Δ indtbi .20 |
.00 |
.26 |
.99 |
.97 |
.91 |
.54 |
Δ ind reit .19 |
.34 |
.80 |
.53 |
.07 |
.11 |
.61 |
The table shows the p-values in the tests. The null hypothesis is that of no Granger causality between the
variables. The models include one lag and two dummy variables that take the value one in a single period
(1995Q2, 2008Q4) and are zero otherwise.
Table 5 Granger causality test results for offices
Δ tbi |
Δ reit |
Explanatory variable |
ΔD |
Adj. RP2P | |||
ΔIRN |
Δ S |
Δ SE | |||||
Pairwise model | |||||||
й O <υ əa й S |
Δ of_tbi .00 |
.03 |
.22 | ||||
Δ ofreit .92 |
.00 |
.32 | |||||
Multiple variable model Δ of_tbi .14 |
.00 |
.02 |
.22 |
.58 |
.03 |
.28 | |
Δ ofreit .70 |
.40 |
.70 |
.50 |
.07 |
.12 |
36 |
The table shows the p-values in the tests. The null hypothesis is that of no Granger causality between the
variables. The models include one lag and one dummy variable that takes the value one in a single period
(2008Q4) and is zero otherwise.
Table 6 Granger causality test results for retail property
Explanatory variable |
Adj RP2P | |||||||||
Δ tbi |
Δ reit |
INF |
ΔIR |
Δ S |
Δ SE |
ΔD |
Δ GDP | |||
O ð S Q |
Pairwise model | |||||||||
Δ retbi Δ re reit |
.15 .96 |
.07 .00 |
.41 .34 | |||||||
Multiple variable model | ||||||||||
Δ retbi |
.28 |
.04 |
.08 |
.64 |
.21 |
.04 |
.31 |
.01 |
.47 | |
Δ re reit |
.39 |
.50 |
.14 |
.58 |
.19 |
.51 |
.01 |
.09 |
.46 |
The table shows the p-values in the tests. The null hypothesis is that of no Granger causality between the
variables. The models include one lag and two dummy variables that take the value one in a single period
(1995Q2, 2008Q4) and are zero otherwise. Due to heteroscedasticity of the residuals in the model for Δrereit,
the p-values for Δ rereit in the multiple variable model are based on a covariance matrix that is computed
allowing for heteroscedasticity as in White (1980).
28
More intriguing information
1. The name is absent2. Learning and Endogenous Business Cycles in a Standard Growth Model
3. Synthesis and biological activity of α-galactosyl ceramide KRN7000 and galactosyl (α1→2) galactosyl ceramide
4. Outsourcing, Complementary Innovations and Growth
5. Models of Cognition: Neurological possibility does not indicate neurological plausibility.
6. Tastes, castes, and culture: The influence of society on preferences
7. PROJECTED COSTS FOR SELECTED LOUISIANA VEGETABLE CROPS - 1997 SEASON
8. THE WELFARE EFFECTS OF CONSUMING A CANCER PREVENTION DIET
9. Corporate Taxation and Multinational Activity
10. Antidote Stocking at Hospitals in North Palestine