Recently, a significant share of the empirical analysis on the impact of public capital on regional growth has used multivariate time-series frameworks based on vector auto regressive (VAR) models. Nevertheless, not as much attention has been dedicated to the analysis of the long-run determinants of regional growth processes using multi-region panel data and applying panel integration and co-in...

t he objective of this study is using the markov switching vector autoregressive method and regime dependent impulse response functions to measure the pass-through of world food prices to consumer price index in iran from 1990 to 2013. with respect to information criteria and the log-likelihood ratio statistic, msia(2)-var(1) model has a better fit to data than other models. the magnitude of th...

The classical theory of rank-based inference is essentially limited to univariate linear models with independent observations. The objective of this paper is to illustrate some recent extensions of this theory to time-series problems (serially dependent observations) in a multivariate setting (multivariate observations) under very mild distributional assumptions (mainly, elliptical symmetry; fo...

Renewable energy forecasting is a key for efficient resource use in terms of power generation and safe grid control. In this study, we investigated short-term statistical model with 1 to 3 h horizons using photovoltaic operation data from 215 plants throughout South Korea. A vector autoregression (VAR) model-based regional system proposed seven clusters This method showed better predictability ...

Abstract This article mainly analyzes how to use the vector autoregressive VAR model study development of Shanghai port logistics. First, co-integration test analyze long-term relationship between logistics and regional economy; Then, by constructing a cargo throughput Shanghai’s GDP, construct an impulse response function dynamic mechanism two; Then contribution rate two through variance decom...

This paper analyzes whether a wealth of information contained in 126 monthly series used by large-scale Bayesian Vector Autoregressive (LBVAR) models, as well as Factor Augmented Vector Autoregressive (FAVAR) models, either Bayesian or classical, can prove to be more useful in forecasting real house price growth rate of the nine census divisions of the US, compared to the small-scale VAR models...

The purpose of this paper is to investigate the relationship between Foreign Direct Investment (FDI) and Economic growth as measured by Gross Domestic Product (GDP) over Uganda, from 1980-2018. Vector Autoregressive Model (VAR) Granger Causality test were used. results show thatlag 1 optimal lag hence bivariate VAR (1) model was GDP FDI exhibits long-term equilibrium since two-time series are c...