A Nonlinear Model to Estimate the Long Term Correlation between Market Capitalization and GDP per capita in Eastern EU Countries
Radu Lupu () and
Adrian Cantemir Calin
Working Papers of Institute for Economic Forecasting from Institute for Economic Forecasting
The connection between the macroeconomic development on one hand and the stock market dynamics on the other hand is the focus of many research initiatives. We are trying to apply the methodology used in the field of macroeconomic convergence to the dynamics of market capitalization for European economies. Under the general standard form of the convergence theory, which states that in the long run, as income per capita increases its corresponding growth rate will decrease, we propose a non-linear model that simulates the convergence based on data for the Central and Eastern European countries pursuing the estimation of a theoretical (hypothetical) optimal trend with respect to certain rational criteria. The model is applied on both macroeconomic variables and the market capitalization and we relate the differences that were found to the increased volatility of the latter set of data.
Keywords: market capitalization; GDP per capita; nonlinear models; eastern EU countries. (search for similar items in EconPapers)
JEL-codes: C51 C53 G17 (search for similar items in EconPapers)
Pages: 19 pages
New Economics Papers: this item is included in nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:rjr:wpiecf:141115
Access Statistics for this paper
More papers in Working Papers of Institute for Economic Forecasting from Institute for Economic Forecasting Contact information at EDIRC.
Bibliographic data for series maintained by Corina Saman ().