A structural vector autoregression model for the study of the Japanese GDP and of the Japanese inflation

Rosa Ferrentino and Luca Vota

Advances in Management and Applied Economics, 2019, vol. 9, issue 2, 6

Abstract: In this paper is presented an historical decomposition of the Japanese GDP and inflation, make, on quarterly data included between the first quarter of 2000 and the fourth quarter of 2016, through a structural VAR of order 1, with the aim of understanding the contribution of the monetary and fiscal policy to the development of these two variables. In the paper is also studied a dynamic forecast of the growth rate of the Japanese real GDP with an ARIMA model, a model belonging to the family of stochastic processes. The results obtained are in line with the forecasts of the economic theory and do not reveal substantial differences compared to those present in the literature. The authors pause also to discuss some limits related to the techniques used in these analyzes and hope that the paper is a very useful for stimulating research and for bridging economics and mathematics. JEL classification numbers: C32, E17, E61, E63Keywords : Structural vector autoregression model, autoregressive integrated moving average, historical decomposition, Cholesky model, Sims models.

Date: 2019
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