The Canadian lumber industry and the macroeconomy: a vector autoregression analysis

1991 ◽  
Vol 21 (3) ◽  
pp. 288-299 ◽  
Author(s):  
Sarah Jennings ◽  
Wiktor Adamowicz ◽  
Luis Constantino
Keyword(s):  
Model Specification ◽  
Forest Sector ◽  
Vector Autoregressive Model ◽  
Lumber Industry ◽  
Vector Autoregressive ◽  
Rate Effects ◽  
Alternate Model ◽  
Strong Exchange ◽  
Housing Start ◽  
Forest Sector Modeling

The nature of the relationships between the Canadian lumber industry and the macroeconomy are investigated by estimating a 10-variable, three-lag vector autoregressive model for the period 1968 to 1987. We find that housing-start activity in North America has a prolonged and significant effect on the level of Canadian lumber production, exports, and prices. However, our results do not support the existence of strong exchange and interest-rate effects in the lumber sector. The use of general equilibrium specifications in forest sector modeling is suggested by the analysis. We explore the robustness of our results to alternate model specification and estimation procedures and identify problems that merit further investigation.

scholarly journals A Spatial Panel Structural Vector Autoregressive Model with Interactive Effects and Its Simulation

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 883
Author(s):  
Yaqing Liu ◽  
Hongbing Ouyang ◽  
Xiaolu Wei
Keyword(s):  
Autoregressive Model ◽  
Common Factors ◽  
Interactive Effects ◽  
Vector Autoregressive Model ◽  
Finite Sample ◽  
Vector Autoregressive ◽  
Spatial Panel ◽  
The Common ◽  
Structural Vector Autoregressive Model ◽  
Structural Vector

The existing spatial panel structural vector auto-regressive model can effectively capture the time and spatial dynamic dependence of endogenous variables. However, the hypothesis that the common factors have the same effect for all spatial units is unreasonable. Therefore, incorporating time effects, spatial effects, and time-individual effects, this paper develops a more general spatial panel structural vector autoregressive model with interactive effects (ISpSVAR) that can reflect the different effects of common factors on different spatial units. Additionally, based on whether or not the common factors can be observed, this paper proposes procedures to estimate ISpSVAR separately and studies the finite sample properties of estimators by Monte Carlo simulation. The simulation results show the effectiveness of the proposed ISpSVAR model and its estimation procedures.

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