In this paper, we estimate trend inflation in Sweden using an unobserved components stochastic volatility model. Using data from 1995Q4 to 2021Q4 and Bayesian estimation methods, we find that trend inflation has been well-anchored during the period - although in general at a level below the...

This paper uses Bayesian techniques and Maltese data over the period 2001-2019 to estimate the parameters of MEDSEA-FIN, one of the Central Bank of Malta's DSGE models. The model captures linkages between the housing sector, banks and the rest of the economy via a borrowing collateral...

This paper presents a credit gap for Malta derived from a semi-structural multivariate filter. This modelling approach has several advantages over univariate approaches typically used, for example to construct the Basel gap. The multivariate filtering of observed data into trends and cycles is...

Fluctuations in commodity prices are an important driver of business cycles in small emerging market economies (EMEs). This paper documents how these fluctuations correlate strongly with the business cycle in EMEs. A commodity sector is then embedded into a multi-country EMEs business cycle...

We investigate the financial interactions between countries in the Pacific Basin region (Korea, Singapore, Malaysia, Hong Kong and Taiwan), Japan and US. The originality of the paper is the use of STAR-GARCH models, instead of standard correlation-cointegration techniques. For each country in...

This paper examines the evolution of the cyclicality of real wages and employment in four Latin American economies (Brazil, Chile, Colombia and Mexico) during the period 1980-2010. Wages are highly pro-cyclical during the 1980s and early 1990s, a period characterized by high inflation. As...

This paper describes the theoretical structure and estimation results for a DSGE model for the Macedonian economy. Having as benchmark the model of Copaciu et al. (2015), modified to allow for a fixed exchange rate, we are able to match relatively well the volatility observed in the data. Given...

Aggregate demand forecasting, also known as nowcasting when it applies to current quarter assessment, is of notable interest to policy makers. This paper concentrates on the empirical methods dealing with mixed-frequency data. In particular, it focuses on the MIDAS approach and its later...