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The author would like to thank Bas Bakker, Lone Christiansen, Jeffrey Franks, Anne-Marie Gulde, James John, Daehaeng Kim, Zuzana Murgasova, Catriona Purfield, Robert Tchaidze, Delia Velculescu, and participants of the IMF European Department brown bag seminar for their comments.
For the purposes of this paper European Union NMS comprise Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and the Slovak Republic. Slovenia is excluded since it became a Eurozone member in the midst of the boom years (2007). The Baltics comprise Estonia, Latvia, and Lithuania.
Hungary was an exception, where GDP growth slowed drastically near the end of the boom years, largely reflecting the impact of fiscal consolidation on domestic demand. IMF 2008 provides details.
The sectors into which capital flows also determine the economic agent who bears the ultimate investment risk.
The Czech Republic is now classified as an advanced country by the IMF, although early in the period under study it was an emerging market.
Between 2004-08, the National Bank of Romania took measures to limit mortgage debt of households (IMF, 2009a).
Source: Authorities. The boom period is defined as 2003Q1-2007Q4 for Latvia.
Housing prices, through their wealth effect, have been shown to have a significant impact on consumption. See Campbell and Cocco (2005) and Benito and Mumtaz (2006). In the Baltics and Romania two common channels were people who fully owned their homes (i.e. had no mortgage) could sell them at high prices or take mortgages out on them.
During 2005-06, the Bulgarian National Bank imposed limits on credit expansion. However, domestic bank borrowing was replaced by domestic non-bank and foreign borrowing. See Vandenbussche (2010).
In countries with low pre-boom per capita GDP (Bulgaria, Latvia, Lithuania, and Romania), EU accession and income convergence may have both contributed to the consumption- investment boom and to increased capital inflows.
Estonia, Hungary, Latvia, Lithuania, Poland, and the Czech and Slovak Republics joined the European Union in 2004, followed by Bulgaria and Romania in 2007.
Dullien (2010), Hais, Mahlberg, and Molling (2009) provide details on the integrated nature of production of these NMS with the Euro Area, particularly Germany. Ariel, Kurz, and Tesar (2008) assess the alignment of production integration with the business cycles of a country’s largest production and trade partners.
Downturn change in net capital flows compares net capital flows during the downturn with that of the four quarters preceding the downturn (in percent of GDP during the four quarters preceding the downturn).
Latvia not only had a reduction in inflows from parent banks but also outflows through the withdrawal of non-resident (non-parent bank) deposits which triggered a bank run in one of the largest domestic banks (IMF 2009b provides details).
Since the fall of 2008, the decline in investment was similar across the Baltics, Bulgaria, and Romania. As the downturn has lasted longer in the Baltics, the total decline in investment has been more.
All reductions of capital inflows and credit during the downturn are calculated in comparison with the year preceding the downturn. Consequently, although FDI for example remained positive during every quarter of the downturn in Bulgaria and Romania, the change in FDI is negative since the level of FDI during the downturn was lower relative to the previous year.
Having started the downturn later than the Baltics, the contraction in consumption has continued throughout 2010. Nonetheless, the decline in consumption in Bulgaria has still been much smaller than that in the Baltics.
The extent to which factors such as wages, employment, and various fiscal measures impacted consumption in these NMS is an interesting area for future research.
In particular, reductions in PIT and disability contribution rates played an important role in maintaining robust consumption.
Sancak et al. (2010) elaborates on the impact of consumption and compliance declines on tax revenues in the Baltics.
Hungary, Poland and the Slovak Republic had the lowest declines in revenue growth amongst NMS. With high debt to GDP ratios, Hungary contracted public expenditures and improved the deficit in order to maintain investor confidence. Poland and the Slovak Republic allowed real expenditures to grow during the crisis, worsening their fiscal balances.
This section intends to portray a qualitative story. As such, exact numerical comparisons across fiscal balances should not be made using this data as the fiscal balance is reported as a cash balance for Bulgaria and Latvia and an accrual balance for the others.
Risk premiums, measured as CDS spreads are typically an additive factor for the parent banks’ setting of interest rates charged to their foreign subsidiaries in NMS.
During the boom, sizeable fiscal reserves were accumulated as a result of fiscal surpluses.
A flexible exchange rate provides a natural buffer against surges in global liquidity by making it more expensive for foreign investors to purchase assets and, as a result, reducing valuation pressures on domestic assets.
High public debt (65 percent of GDP in 2009) compounded market fears in Hungary.
Capital inflows to banks may be in the form of FDI, loans or deposits by foreigners (often parent banks) to domestic banks.
Each of the nine NMS then has three observation sets (pre-boom, boom, and crisis), for a total of 27 observations in the regression. Crisis is defined as 2008Q1-2010Q1for Estonia, 2008Q1-2010Q2 for Latvia, 2008Q2-2009Q4 for Hungary, 2008Q2-2010Q2 for Lithuania and Romania, 2008Q4-2010Q1 for Bulgaria, 2008Q4-2009Q4 for the Czech and Slovak Republics, and 2008Q4-2009Q1 for Poland (the only new member state that did not suffer from recession). There may be a bias in the crisis period since the recession is still running its course in some NMS.
Granger causality tests found some causality of GDP on credit but none for FDI. The implied endogeneity is addressed with instrumental variables. The coefficients from estimates of regressions of GDP growth on the lagged RHS variables were not significant and thus they were deemed appropriate as instruments.
Although bank credit was largely funded by capital inflows in most NMS, a portion of credit was also funded from domestic deposits and interbank markets. As this may be creating a bias in the results, a robustness check applying the predicted values of credit variables regressed on bank flows as a proxy for the actual credit variables themselves supported the results above (see Appendix 2). However, the broader set of results reported in Table 2 and Appendix 1 capture also the important indirect effects of large capital inflows influencing incomes and thus deposits, which in turn supported further loan growth.
Regressions of consumption growth on the RHS variables described above (see Appendix 3) find that consumption growth is strongly correlated to growth in mortgage flows (a 10 pps increase yields 0.71-0.96 pps rise in consumption growth), and to a lesser extent consumer credit flows (less than half the impact of mortgage flows).
Investment growth, more generally, appears to be most highly correlated with growth in both real estate and non-real estate FDI flows (a 10 pps increase of each corresponds to about a 1 ppt rise in investment growth), followed by growth in corporate real estate credit flows (having about a quarter to half as much impact as FDI flows), and growth in mortgage flows (about one tenth the impact of FDI). Appendix 3 provides details.
This result for NMS is in line with the broader finding that the exchange rate regime in emerging market countries is uncorrelated with output fluctuations during crisis (IMF World Economic Outlook, April 2010).