This paper examines the nexus between economic growth and energy consumption shock, over period 1990-2020, in Iran. We employ a Bayesian vector autoregressive (BVAR) with new prior functions, which will give results more acceptable consequences than classical methods to study these relationships. estimates relationship shocks within multivariate BVAR framework by including gross capital formati...

Bayesian models often involve a small set of hyperparameters determined by maximizing the marginal likelihood. optimization is an iterative method where Gaussian process posterior underlying function sequentially updated new evaluations. We propose novel framework for situations user controls computational effort and therefore precision This common in econometrics likelihood computed Markov cha...

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore’s (1981) work at the national level. The performance of the DuaMiller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Index...

Vector autoregression (VAR) models are widely used for multivariate time series analysis in macroeconomics, finance, and related fields. Bayesian methods often employed to deal with their dense parameterization, imposing structure on model coefficients via prior information. The optimal choice of the degree informativeness implied by these priors is subject much debate can be approached hierarc...

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes Factor, which is obtained without any additional computational effort, can be used to assess the plausibility of the restrictions imposed on the VAR parameter vector by competing DSGE models. In other words, it is possible to rank the amount of abstraction implied by each DSGE mode...