Arellano, Manuel, and Stephen Bond, 1991, “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” Review of Economic Studies, Vol. 58 (2), pp. 277–97.
Arena, Marcos, Reinhart, Carmen M., and Francisco Vazquez, 2006, “The Lending Channel in Emerging Economies: Are Foreign Banks Different?” NBER Working Paper No. W12340 (Cambridge, Massachusetts: National Bureau of Economic Research).
Baba, Naohiko, and Ilhyuk Shim, 2010, “Policy Responses to Dislocations In the FX Swap Market: The Experience of Korea,” BIS Quarterly Review, pp. 29–39. June.
Baltagi, Badi H., and Young-Jae Chang, 1994, “Incomplete Panels: A Comparative Study of Alternative Estimators for the Unbalanced One-Way Error Component Regression Model,” Journal of Econometrics 62, pp. 67–89.
Bernanke, Ben S., and Alan Blinder, 1988, “Credit, Money and Aggregate Demand,” The American Economic Review, Vol. 78 (2), pp. 435–39.
Bernanke, Ben S., and Mark L. Gertler, 1995, “Inside the Black Box: The Credit Channel of Monetary Policy Transmission,” The Journal of Economic Perspectives, Vol. 9 (4), pp. 27–48.
Cetorelli, Nicola, and Linda S. Goldberg, 2009, “Global Banks and International Shock Transmission: Evidence from The Crisis,” mimeo (available at: http://www.ny.frb.org/research/economists/goldberg/IMF-BOF-PSG_121409all.pdf).
Hernando, Ignacio, and Jorge Martinez Pagés, 2001, “Is There a Bank Lending Channel of Monetary Policy in Spain,” Working Paper 99 (Frankfurt: European Central Bank).
Kashyap, Anil, and Jeremy C. Stein, 1995, “The Impact of Monetary Policy on Bank Balance Sheets,” Carnegie-Rochester Conference Series on Public Policy, 42, pp. 151–95.
Kashyap, Anil, and Jeremy C. Stein, 2000, “What Do a Million Observation on Banks Say About the Transmission of Monetary Policy,” American Economic Review, Vol. 90 (3), pp. 407–28.
McCauley Robert N., and Jenes Zukunft, 2008, “Asian Banks and the International Interbank Market,” BIS Quarterly Review, pp. 67–79, June.
Modigliani, Franco, and Merton Miller, 1958, “The Cost of Capital, Corporation Finance, and the Theory of Investment,” American Economic Review, Vol. 48 (4), pp. 261–97.
Raddatz, Claudio, 2010, “When the Rivers Run Dry: Liquidity and the Use of Wholesale Funds in the Transmission of the U.S. Subprime Crisis,” Policy Research Working Paper Series 5203 (Washington: World Bank).
Ree, J., 2009, Philippines: Selected Issues: “Contagion of the Recent Global Financial Turmoil,” IMF Staff Country Report 09/63, Chapter I, (Washington).
Shin, H.S., “Reflections on Northern Rock: The Bank Run That Heralded the Global Financial Crisis,” Journal of Economic Perspectives, Vol. 23 (1), pp. 101–19.
Yang, Y., and H. Lee, 2008, “An Analysis on Arbitrage Transaction Opportunities and the Investment in the Domestic Bond Market By Foreign Bank Branches And Foreign Investors,” Bank of Korea Monthly Bulletin, pp. 55–89, August.
Yu, Bok-Keun, 2010, “The Global Financial Crisis and the Covered Interest Rate Differential: The Case of Korea,” Kukje Kyungje Yongu, Vol. 16 (3), pp. 77–99.
I would like to thank Jonathan Dunn, Shogo Ishii, Byung Kyoon Jang, Mahmood Pradhan, Masahiko Takeda, Olaf Unteroberdoerster, participants at the IMF’s Asia Pacific Department Seminar, and the Financial Surveillance Group Seminar for helpful comments and suggestions, as well as Masato Miyazaki for his invaluable guidance. All remaining errors are mine.
For the purpose of this paper, MTM gains are defined as a sum of (i) realized gains on securities trading, (ii) changes in fair value of held-for-trading securities, (iii) changes in fair value of derivative position, and (iv) changes in fair value of available-for-sale loans or securities. This definition is an augmented one relative to the formal accounting definition that excludes the first item. The augmentation intends to capture all changes in capitalization resulting from market price changes, and can be especially useful in a market context where insufficient liquidity causes understatement of unrealized gains and losses on fair-valued securities until they are traded off. The first three items affect total equity by changing the current year profit, which is the basis for corporate income tax and also dividend payouts. The fourth item only affects banks’ capitalization level without affecting the current year profit.
See Ree (2009) for a detailed discussion. The CLNs offered to the Philippine banks typically used highly rated U.S. or Euro private debt as base securities, which were bundled up with CDS contracts on the Philippines’ external sovereign bonds (ROP), with buyers of the base securities providing default protection in the CDS. The notional amount of the CDS contract could deviate from that of the base security allowing for synthetic leverages.
Sri Lanka is an outlier among the Asian LICs both in terms of little reliance on ODA and sustained access to international markets for bond financing. Vietnam resumed its first significant sovereign bond issuance since the onset of the crisis in January 2010.
Vietnam Asian Commercial Joint-Stock Bank (ACB) and Á Châu-Asia Commercial Joint-Stock Bank increased their assets by double to triple in 2007. As expansion of the loans slightly lagged behind, both banks expanded their trading and available-for-sale securities holding by 3 to 25 times to fill the slack.
Wholesale funding (end of year stock) is defined as total funding minus customer deposit for the purpose of the paper, as is common in other studies.
The top 20 banks were selected based on the size of total assets at end-2007.
These banks had their wholesale funding growing at 19 percent (y/y) and gross lending at 31 percent (y/y) in 2007.
The decline in loan-to-deposit ratio of the large EME banks can be attributed to two key factors. First, there was a visible shift by the EME domestic corporate borrowers to capital market financing, which created a slack that could not be quickly filled by banks’ increased emphasis on retail lending. Second, a rapid development of securitization led to massive off-loading of loans from banks’ balance sheets, with the resulting cash flows not immediately deployed to lending activities. In a related development, large increase in off-balance sheet activities, for example, through residential mortgage-backed securities conduits, augmented the demand for prudent liquidity buffer.
Cross-country difference in economic stimulus packages, in particular measures to support bank lending, must also have affected variation at the county level in resilience of lending growth. Among the EME sample countries, Malaysia and Thailand introduced some version of credit guarantee schemes, easing credit constraint faced by SMEs. However, government measures like these neither explain the relatively stronger resilience by the larger banks in lending growth, nor undermine observed association at an individual bank level between initial liquidity and the level of its deployment during the crisis. Monetary stimulus measures such as policy rate reduction and reserve requirement does not have explanatory power on relative resilience of loans over deposits.
The actual observation included 19 banks because of a missing value.
The actual observation included 16 banks because of missing values.
If deposits and wholesale funding are perfect substitutes to each other, as in Modigliani and Miller (1958), a shock in crossborder funding will affect lending entirely through changes in interest rates. In the presence of an informational asymmetry, however, banks will not be able to seamlessly substitute one source of capital to another. Hence, a shock on crossborder funding will propagate through the same transmission mechanism as studied by the literature on bank lending channels.
Monte Carlo studies have revealed a positive relation between imbalances of panel data and the mean squared error of the coefficients estimated on them. Despite the caveat, the paper uses an unbalanced panel data for three reasons, all based on Baltagi and Chang (1994): (i) carving out a balanced subset from an unbalanced panel data is known to worsen the estimation performance; (ii) the imbalances of the data studied here is relatively moderate; and (iii) the size of the cross section is significantly larger than the spectrum of hypothetical dataset in Baltagi and Chang (1994), making large sample asymptotic properties work better.
This occurs because the within transformation of the disturbance (while purging off μi) brings νi,t−1 (buried in the within average νi,.) in the equation, which is correlated with yi,t−1. See Baltagi (2008), p. 147.
For large EME banks, the paper uses a relatively lower percentile as a cut-off in a bid to level this with a cutoff that was applied to the LIC banks. However, the estimation results are robust to substantial changes in cutoffs.
Its inclusion in equation 2 will lead to singularity (as the vector is identical with growthi,t) and in equation 3 the same problem (as the variable becomes a vector of all zeros).
The result should be interpreted with caution given that the time domain of the regression is rather short.
The exact condition to assure a positive relationship between the liquid asset growth and interbank capital flows for the large EME banks is liquidityi,t-1 > -0.5752 (=-(-4.034+8.673)/8.065). About three-quarters of all the EME large bank observations meeting the filtering rules satisfy this threshold condition.
Residual effects like these can potentially be related to unquantifiable supply side factors, examples of which include lending standards and loan officer sentiments.
It would be easier to hoard dollars in an economy where firms and households have easy access to foreign currency deposits, and economic transactions are commonly settled in foreign currencies.
The intersection between the regression line and the 45 degrees line renders a threshold initial NPL ratio, which in this case is 2.5 percent. The thresholds in all the panels appear severely distorted by outliers, and thus ignored.
The flipping of the effect of other macroeconomic factors between 2008 and 2009 mainly reflected receding of inflation in 2009 that passed through an estimated positive link between NPLs and the inflation. Average real interest rates fell in 2008 and rose in 2009, partially offsetting the impacts of the inflation in both years.
Examples can be global factors directly affecting asset quality, correlated changes in loan policy, or rigor of banking supervision.