Weather forecasting is crucial to both the demand and supply sides of electricity markets. Temperature has a great effect on energy demand. Moreover, solar and wind are very promising renewable energy sources. In this paper, a large vector autoregression (VAR) model is built to forecast three important weather variables for 61 cities around the United States. We estimate the VAR model with 16 y...

Macroeconomists using large datasets often face the choice of working with either a vector autoregression (VAR) or factor model. In this paper, we develop conjugate Bayesian VAR subspace shrinkage prior that combines two. This shrinks towards which is defined by Our approach allows for estimating strength and number factors. After establishing theoretical properties our prior, show it successfu...

This study aims to analyze the analysis of factors that influence amount money in circulation from 1990 2019. The data used this is secondary for period - research model uses Vector Autoregression (VAR) model. unit root test was carried out with Augmented Dickey Fuller (ADF) where all stationary variables were second different. results are based on VAR analysis. Foreign debt affects supply Indo...

This paper examines the power of business and consumer survey indicators in predicting retail activity in Croatia. A brief overview of business and consumer surveys is presented, followed by the conceptual logic behind their use in predicting related macroeconomic variables. Detailed elaboration of methodology used is presented next. The main model used for the analysis is a bivariate vector au...

This paper examines time series evidence to establish a link between trade, economic growth and income inequality in Bangladesh. The empirical results from a Vector Autoregression (VAR) model suggest that there is some evidence of trade liberalization accelerating growth in Bangladesh. Trade openness promotes investment. We find little evidence of trade affecting income distribution or of incom...

This paper offers new insights into the processes of firm growth by applying a reduced-form vector autoregression (VAR) model to longitudinal panel data on French manufacturing firms. We observe the co-evolution of key variables such as growth of employment, sales, and gross operating surplus, as well as growth of multifactor productivity. It seems that employment growth is negatively associate...

Using model selection techniques based on out-of-sample predictive ability criterion in a Vector Autoregression (VAR) framework, this paper empirically examines the causal relations among growth, trade, and wage inequality in Bangladesh between 1971 and 2000. There is some evidence of bi-directional causality between growth and inequality and between trade and growth. That growth causes trade a...

This article derives generalized impulse responses from the estimation of a vector autoregression (VAR) model using monthly data between 1995 and 2005 for Mexico, to examine the inflation–relative price variability (RPV) relationship, and to investigate if remittances could account for the observed relationship. While the positive relationship between inflation and RPV is a robust result, remit...

The vector autoregressive (VAR) model is a powerful tool in learning complex time series and has been exploited in many fields. The VAR model poses some unique challenges to researchers: On one hand, the dimensionality, introduced by incorporating multiple numbers of time series and adding the order of the vector autoregression, is usually much higher than the time series length; On the other h...

This study investigates the potential impacts of food safety outbreaks on domestic shipments, imports, and prices of the produce industry. Three case studies were analyzed to assess these potential impacts: the cantaloupe outbreak of March–April 2008, the spinach outbreak of September 2006, and the tomato outbreak of June–July 2008. Data-determined historical decompositions were conducted to pr...