Recent time series methods are applied to the problem of forecasting New Zealand’s real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz (1978) BIC and the Phillips-Ploberger (1996) PIC criteria. The forecasts generated by the data-deter...

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...

The estimation of remaining useful life (RUL) of a faulty component is at the center of system prognostics and health management. It gives operators a potent tool in decision making by quantifying how much time is left until functionality is lost. RUL prediction needs to contend with multiple sources of errors like modeling inconsistencies, system noise and degraded sensor fidelity, which leads...

This paper quantifies and assesses the impact of an adverse loan supply (LS) shock on Peru's main macroeconomic aggregates using a Bayesian vector autoregressive (BVAR) model in combination with identification scheme sign restrictions. The results indicate that LS shock: (i) reduces credit real GDP growth by 372 75 basis points period, respectively; (ii) explains 11.2% variability average over ...

I propose a Bayesian approach to identify vector autoregressive (VAR) models via proxies in data-rich environment. The setup augments small-scale VAR model with latent factors . It allows trace out the responses of disaggregated series unified while controlling for broad economic conditions posterior sampler accounts estimation uncertainty these as well measurement precision proxy. In first app...

The paper investigates the effects of uncertainty shocks in emerging economies (EMEs). We construct a global indicator as well country measures for fifteen relatively small economies. adopt an instrumental variable approach to identify exogenous EMEs. To deal with data limitations specific countries, we develop new Bayesian algorithm estimate proxy panel structural vector autoregressive (SVAR) ...