The paper analyses the impact of different types of capital flows to Croatia on the kuna exchange rate. SVAR models based on Cholesky decomposition with block exogeneity restrictions are estimated using different types of capital flows and the key finding is that the structure of capital flows matters for their impact on the exchange rate. On the one hand, debt capital inflows lead to kuna appreciation, irrespective of their maturity, while in terms of sectoral structure this is mostly due to corporate and government borrowing. On the other hand, equity capital flows seem to affect it in the opposite direction, which is in line with results from other empirical research. The opposite effects of debt and equity flows could stem from the differences in their relative orientations towards the tradable versus the non-tradable sector, with the latter being more prominent in debt flows. The paper also confirms that capital flows to the banking sector have no effect on the exchange rate, providing support to the intensive use of countercyclical macroprudential measures by the central bank. These findings are relevant for the design of monetary policy, especially in countries like Croatia where central bank uses the exchange rate of the kuna against the euro as the main tool for achieving its primary objective of price stability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.