Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a...

In this paper, the determinants of the portfolio based capital flows are examined for the Turkish economy. Following the structural vector autoregression methodology, the estimation results reveal that the ‘push’ factors based on the external developments for the Turkish economy have a...

This paper aims at determining the relationship between economic growth and energy consumption in Jordan within the neo-classical productivity theory framework where capital, labour and energy are treated as separate production factors. It constructs an econometric model using annual time series...

Seeking for the existence of bull and bear regimes in the Indian stock market, a two state Markov switching autoregressive model (MS (2)-AR (2)) is used to identify bull and bear market regimes. The model predicts that Indian stock market will remain under bull regime with very high probability...

Kehoe2006 advocates that in evaluating an economic model, the Sims-Cogley-Nason (SCN) approach should be adopted in which empirical impulse responses are compared to those obtained from the identical structural VAR run on model generated data of the same length as actual observations. This paper...

This paper studies regime dependence in the effects of monetary policy shocks for the U.S. using a threshold vector autoregressive model. In a high inflation regime the standard results from the literature obtain. In a low inflation regime output shows no significant response to monetary policy...

DSGE models are currently estimated with a two step approach: data is first filtered and then DSGE structural parameters are estimated. Two step procedures have problems, ranging from trend misspecification to wrong assumption about the correlation between trend and cycles. In this paper, I...

In this study, we investigate forecasting performance of various univariate and multivariate models in predicting inflation for different horizons. We design our forecast experiment for the post-oil boom years of 2010-2014 and compare forecasting ability of the different models with that of...

We propose the unified approach to construct the non–informative prior for time–series econometric models that are invariant under some group of transformations. We show that this invariance property characterizes some of the most popular models hence the applicability of the proposed...

Dramatic changes in macroeconomic time series volatility pose a challenge to contemporary vector autoregressive (VAR) forecasting models. Traditionally, the conditional volatility of such models had been assumed constant over time or allowed for breaks across long time periods. More recent work,...