EU accession of Macedonia (FYROM): A DSGE model

Tuesday, 14 October 2014: 4:50 PM
Thierry Warin, Ph.D , International Business, HEC Montreal, Montreal, QC, Canada
Aleksandar Stojkov, Ph.D. , Saints Cyril and Methodius University, Skopje, Former Yugoslav Republic of Mace
Dynamic stochastic general equilibrium (DSGE) models have become one of the most prominent research avenues of the so called new macroeconometrics. Yet their application on data for the European transitional economies has been rather limited. Based on a New Keynesian setting, we estimate a small open economy model characterizing the dynamic behavior of three key macroeconomic variables: output, inflation, and the nominal interest rate. The analytical framework is amended in order to capture some transition-economy specifics.

The objective of this paper is twofold. First, it measures the contributions made by various shocks in driving aggregate fluctuations in the model’s observable and unobservable variables. Second, it contributes to the understanding of the trade and financial linkages between the small open transition economy of Macedonia and the large euro area economy. The main contribution of this paper consists in narrowing a considerable gap in the empirical macroeconomics literature for the transition economies, particularly from South Eastern Europe.

To formalize these ideas, we examine the relevance of four types of shocks to the Macedonian economy: shocks to households’ preferences (associated with the shrinking middle class); technology shocks (due to the substantially increased foreign direct investment inflows); cost-push shocks (or shocks to firms’ desired markups); and disturbances to the short-term nominal interest rate (associated with the pegged exchange-rate mechanism with the euro). The econometric analysis uses quarterly data running from 1997:1 through 2013:4. The impulse response functions allow us to explore the variations of the endogenous variables to the different shocks.

An important avenue for future research is to complement the analysis with a richer model, potentially yielding analytical results of conditions under which policy responses might be strengthened or weakened.