The author sets up a simplistic agent-based model where agents learn with reinforcement observing an incomplete set of variables. The model is employed to generate an artificial dataset that is used to estimate standard macro econometric models. The author shows that the results are...

We conduct a Monte Carlo experiment using an ad-hoc New Keynesian model and a tractable agent-based model to generate artificial credit cycle episodes. We show that fluctuations in the implicit measures of the natural rate of interest obtained using a conventional trivariate Kalman filter on...

The author set up a simplistic agent-based model where agents learn with reinforcement observing an incomplete set of variables. The model is employed to generate an artificial dataset that is used to estimate standard macro econometric models. The author shows that the results are qualitatively...

We examine wealth effects for Russian money demand in a cointegrated vector autoregressive framework. We find that an aggregate wealth variable, as well as the components housing and equity prices included separately, significantly enter the long-run money demand relationship. There are feedback...

We review some aspects of financial dollarization in Russia, applying the main relevant theories to analyze the dynamics of several dollarization indicators. An econometric model of the short run dynamics of deposit and loan dollarization is estimated for the last decade. We find that ruble...

We apply recently developed early warning indicators systems to a cross-section of emerging markets. We find that, with little or no modification, models designed to predict asset price booms/busts in advanced countries may be useful for emerging markets. The concept of monitoring a set of asset...

We estimate money demand models for certain monetary aggregates across different institutional sectors (a novelty for the Russian case). Our results comprise a collection of money demand equations that include different combinations of explanatory variables. Comparing the validity of these...

In the spirit of Borio et al. (2014) we present a model that incorporates information contained in diverse variables when estimating sustainable output growth. For this purpose, we specify a state-space model representing a multivariate HP-filter that links cyclical fluctuation of GDP with...

We apply an econometric approach developed specifically to address the 'curse of dimensionality' in Russian data and estimate a Bayesian vector autoregression model comprising 14 major domestic real, price and monetary macroeconomic indicators as well as external sector variables. We conduct...

​This article presents three alternative models for decomposing loan developments into components associated with changes in loan demand and supply fundamentals. Two models are based on macro data (error correction model and structural vector autoregression with sign restrictions) and one is...