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Marina Tkalec Institute of Economics, Zagreb PowerPoint Presentation
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Marina Tkalec Institute of Economics, Zagreb

Marina Tkalec Institute of Economics, Zagreb

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Marina Tkalec Institute of Economics, Zagreb

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  1. The determinants of deposit euroization in European post-transition countries: evidence from threshold VAR Marina Tkalec Institute of Economics, Zagreb Marina Tkalec 17th DEC - YES

  2. Content • Financial euroization • Contribution • Data and methodology • Results • Policy recommendations Marina Tkalec 17th DEC - YES

  3. Financial euroization Contribution Data and methodology Results • unofficial euroization is a result of voluntarily using foreign currency for different money functions (Feige and Dean, 2002) • DE is a result of households, government and enterprises saving in foreign currency • CE is a result of banks’ behaviour of granting loans in foreign currency or linked to foreign currency Marina Tkalec 17th DEC - YES

  4. Financial euroization Contribution Data and methodology Results • came with high inflation rates in 1980s’ and persisted with the exchange rate as the nominal anchor (Mishkin, 2000; Frankel, 2010) • exchange rate based monetary regimes continued to persist (currency boards, pegs, fixed, managed or even dirty floating exchange rate regimes) • “fear of floating” (Calvo and Reinhart, 2002) central banks’ reluctance to allow the exchange rate to adjust significantly and rapidly resulting in episodes of central bank interventions aimed at avoiding major devaluation shifts • high levels of FE limit the choices for monetary policy makers  large exchange rate depreciations increase the cost of servicing foreign currency denominated debt (Reinhart, Rogoff and Savastano, 2003) • Chang and Velasco (2002) find that detaining depreciation eventually pushes output down • Cabral (2010) warns of larger employment losses under “fear of floating” • Tsangarides (2010) reports that pegs have been recovering much slower than floaters in the latest 2010-2011 recovery phase • FE is one of the biggest weaknesses in European post-transition economies Marina Tkalec 17th DEC - YES

  5. Financial euroization Contribution Data and methodology Results • Theoretical determinants of FE (Levy-Yeyati, 2003.): T1 portfolio view  FE is an outcome of minimum variance portfolio choices, taking returns on various curencies into consideration T2 market failure view FE is a result of moral hazard induced by aysmmetric information T3institutional viewFE is a consequence of domestic market and legal framework imperfections; weak institutional framework and low level of confidence in economic policy encourage policy makers to build confidence through exchange rate anchoring Marina Tkalec 17th DEC - YES

  6. Financial euroization Contribution Data and methodology Results • Research on FE determinants: PANEL DATA ANALYSIS • DE: real exchange rate (+), exchange rate volatility (-) (Kokeyne, Ley and Veyrune, 2010) • DE: interest rate differential (-), access to foreign funds (-) (Basso, Calvo-Gonzales and Jurgilas, 2011) • DE: interest rate differential (+), exchange rate volatility (-) (Luca and Petrova, 2008) • FE: large depreciations have a negative affect on the pass-through coefficient with the impact being higher the higher the level of euroization(Carranza, Cayo and Galdón-Sanchez, 2003) • FE: increased access to global capital markets (Reinhart, Rogoff and Savastano, 2003), closeness to the European Union (ECB, 2010; Neanidis, 2010), country size (Rosenberg and Tirpák, 2008) TIME SERIES ANALYSIS • FE: role of underdeveloped domestic financial markets(Feige, 2002; Levy Yeyati, 2003) • FE in Croatia: massive arbitrage opportunities Šošić (2007) MICRO DATA ANALYSIS • FE: remittances and income from tourism and underdevelopment of domestic financial markets (Stix, 2010) Marina Tkalec 17th DEC - YES

  7. Financial euroization Contribution Data and methodology Results • FE decreases very slowly in periods of macroeconomic stability but increases swiftly in periods of economic uncertainty • exchange rate depreciations seem to push FE strongly and quickly while the opposite exchange rate changes have a much more moderate impact regime/threshold dynamics  transaction costs NONLINEAR: • DE: positive short-run effects of depreciations decrease with the level of euroization, interest rate differentials (-), they use an index of asymmetry of exchange rate movements (Neanidis and Savva,2009) • FE in Croatia: nominal exchange rate (-),they use threshold cointegration (Ivanov, Tkalec and Vizek, 2011);no possibility of diverse DE responses to exchange rate appreciations/depreciations Marina Tkalec 17th DEC - YES

  8. DE in European post-transition Marina Tkalec 17th DEC - YES

  9. DE in European post-transition Marina Tkalec 17th DEC - YES

  10. DE in European post-transition Marina Tkalec 17th DEC - YES

  11. Financial euroization Contribution Data and methodology Results • we investigate monetary determinants of deposit euroization in European post-transition economies • DE determinants: exchange rates and differences between domestic and euro interest rates • linear (cointegration) and threshold (TVAR) models(Koop, Pesaran and Potter, 1996; Balke, 2000) • we test for the presence of threshold effects with respect to the level of DE Q1 What kind of threshold effects characterize an economy with a high level of DE? Q2And if existing, how do these nonlinearities differ with respect to the prevailing exchange rate regime and/or the DE level? Marina Tkalec 17th DEC - YES

  12. Financial euroization Contribution Data and methodology Results C1New insights into the origins, characteristics and consequences of DE in European post-transition economies since we model monetary determinants of DE C2Scarce existing research on FE that tests for nonlinear or threshold effects C3We test whether the determinants of DE behave in a nonlinear fashion Marina Tkalec 17th DEC - YES

  13. Financial euroization Contribution Data and methodology Results DATA: • deposit euroization (DE), nominal exchange rate (NER)/real exchange rate (RER) and interest rate differential (IRD) • monthly observations, seasonally adjusted (X12ARIMA), DE and NER/REER in logarithms • stationary in first differences (ADF) LINEAR METHOD: • Johansen cointegration NONLINEAR METHOD: • Threshold Vector Autoregression (TVAR) • Generalized impulse response functions Marina Tkalec 17th DEC - YES

  14. Financial euroization Contribution Data and methodology Results • transition variable separates the baseline VAR into different regimes (Hansen 1996, 1997; Tsay 1998) • VAR model adjusted for the threshold specification: • gamma - coefficient matrices • - error matrix • - threshold variable with d being a possible time lag Marina Tkalec 17th DEC - YES

  15. Financial euroization Contribution Data and methodology Results • Hansen linearity test (Hansen, 1996, 1997) • Least Squares (LS) estimation: • since the threshold value is not identified under the null of linearity, distribution is not standard (Hansen, 1996) approximation of the asymptotic distribution using a bootstrap procedure Marina Tkalec 17th DEC - YES

  16. Financial euroization Contribution Data and methodology Results • the nonlinear model requires impulse response functions that account for nonlinearity of the system: 1. history dependent (Gallant, Rossi and Tauchen, 1993; Koop 1996; Koop, Pesaran and Potter, 1996) 2. asymmetric (i.e. negative shocks are not exactly the opposite of positive shocks) 3. shocks not proportional to their size • GIRF is the difference between two conditional expectations with a single exogenous shock: • m - forecasting horizon • - history at time t-1 Marina Tkalec 17th DEC - YES

  17. Financial euroization Contribution Data and methodology Results Johansen cointegration Marina Tkalec 17th DEC - YES

  18. Financial euroization Contribution Data and methodology Results Estimation of TVAR and test of nonlinearity Note: *** null hypothesis about linearity rejected on 1 percent level of significance; ** hypothesis about linearity rejected on 5 percent level of significance. Marina Tkalec 17th DEC - YES

  19. Financial euroization Contribution Data and methodology Results Note: circles denote nonlinear behaviour Marina Tkalec 17th DEC - YES

  20. Financial euroization Contribution Data and methodology Results • nonlinear behaviour  depreciations have a stronger effect on DE and on IRD than appreciations • rise in domestic interest rates relative to euro ones increases DE levels • Czech Republic and Poland  flexible ER regimes  lowest FE levels • Latvia, Lithuania and Bulgaria convergence  official euroization • Croatia, Hungary, Romania, Serbia and Turkey  reform of macroeconomic regimes and institutions  increase macroeconomic and institutional credibility Marina Tkalec 17th DEC - YES

  21. Thank you for your attention! mtkalec@eizg.hr Marina Tkalec 17th DEC - YES