Analysis of the Export Activity of Hungarian FinTech Companies

Péter Fáykiss () and Lívia Ónozó ()
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Péter Fáykiss: Magyar Nemzeti Bank
Lívia Ónozó: Magyar Nemzeti Bank

Financial and Economic Review, 2020, vol. 19, issue 4, 60-82

Abstract: In our analysis, we examine domestic FinTech SMEs by using micro-data, focusing on the export activity of companies in the Hungarian FinTech sector. Our study offers new content not only because of the range of examined enterprises, but also due to the uniqueness of the database used, as we have endeavoured to provide a deeper picture of domestic FinTech companies with the help of company data rarely used thus far. The purpose of our examination is twofold: first, based on the company characteristics that can be extracted from the annual accounts of the companies concerned, we organise the Hungarian FinTech companies into distinct groups by cluster analysis. Second, using logistic regression estimation on the crosssectional data, we identify the most important factors affecting the export activity of domestic FinTech companies. Our results have shown that FinTech companies active in Hungary can be divided into three distinct clusters based on the company characteristics involved: export share, headcount and various financial indicators. Regarding the three clusters, medium-sized companies make up half of the cluster in the group of FinTech companies with the highest export share, and the group is characterised by high value added relative to balance sheet totals. Based on our logistic regression estimation, among the FinTech companies we examined, a significantly positive effect on the probability of exporting can be identified in the case of value added, headcount and foreign ownership.

Keywords: FinTech; export; cluster analysis (search for similar items in EconPapers)
JEL-codes: G23 G3 L26 O33 (search for similar items in EconPapers)
Date: 2020
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