Applying Principal Component Analysis in order to Assess Potential Gross Domestic Product in Central and Eastern Europe Region

Abstract

The potential gross domestic product (GDP), together with the difference between real GDP and its potential amount, are commonly used nowadays for macroeconomic modeling, policy assessment, fiscal sustainability evaluation and measuring the structural budget balance. The European Commission, OECD nations and central banks pay attention to identify potential output and GDP gap due to their great significance. The paper provides estimation of potential GDP and GDP gap for the Central and Eastern European region. The strategy is to combine the Cobb-Douglas structural method with other statistical methods of de-trending, in order to determine an aggregation measure for potential GDP, based on a weighting scheme determined with principal component analysis (PCA). Since a regional evaluation of potential economic growth is helpful for drawing well-structured economic policies, the assessment is based on 2000 – 2017 Eurostat aggregated data for all Central and Eastern European countries, except Albania. Using an aggregation method can help assessing economic growth trend in Central and Eastern Europe (CEE) economies, while capturing the useful information provided by different methods.

Keywords

• potential gdp
• gdp gap
• cobb-douglas function
• univariate filters
• pca.