How Effective is Macroeconomic Imbalance Procedure (MIP) in Predicting Negative Macroeconomic Phenomena?

Abstract

Purpose: The evaluation of the predictive power of Macroeconomic Imbalance Procedure (MIP) indicators is crucial for coordinating the economic policies of the EU countries. MIP is one of the pillars of the economic prevention procedure. Design/Methodology/Approach: Using the Bayesian model averaging (BMA) framework, we compare different models where lagged MIP indicators try to explain several macroeconomic variables associated with crises. Findings: The results show that the importance of MIP indicators between 2001 and 2017 was diversified. In the case of annual real GDP growth, including a 1-year lagged house price index, nominal unit labor cost, real effective exchange rate (1-year change), and export market share in the model improves the model's explanatory power most. For explaining inflation rate, export market share (again), and house price index is valid. Practical Implications: The construction of the MIP procedure should be simplified, as not all indicators have a fundamental capability of predicting excessive imbalances which result in events. Indicators are relevant to the current economic priorities of the EU, which do not have a significant capacity to anticipate phenomena should be excluded from the Alert Mechanism. Originality/Value: We use the Bayesian model averaging (BMA) framework BMA that directly deals with heterogeneity by finding a combination of regressors that account for it to the greatest extent within a conditioning set of information. Consequently, BMA appears to be ideally suited for finding robust determinants of crisis variables.