Information about Asia and the Pacific Asia y el Pacífico
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Back Matter

Author(s):
International Monetary Fund. Asia and Pacific Dept
Published Date:
October 2007
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References

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Note: The main authors of this chapter are Paul Gruenwald, Nita Thacker, David Cowen, Ranil Salgado, and Olaf Unteroberdoerster.
1China continues to run a sizable trade deficit, on the order of 8 percent of GDP, with the rest of Asia (excluding Hong Kong SAR).
2On August 17, the U.S. Federal Reserve lowered the discount rate by 50 basis points to 5.75 percent and extended the term of the discount window to 30 days. It also announced that it would accept investment-quality commercial paper as collateral.
3This and other recent developments in the “other investment” category of the balance of payments across a number of Asian economies appear in Box 1.2.
4The net short yen positions of noncommercial traders at the Chicago Mercantile Exchange and Japanese foreign exchange margin traders were substantially reduced, and foreign security purchases by investment trusts and foreign short-term lending by target country banks fell.
5For New Zealand, the total stock of Uridashi bonds maturing in 2007 is equivalent to 11 percent of GDP.
6Banks in Taiwan Province of China and Hong Kong SAR, usually providers of U.S. dollar liquidity, also reportedly became more cautious in their lending, in particular for high-yield names and tenures over one week.
7Under the new policy, proceeds from ECB in excess of $20 million can be used only for foreign currency expenditure. Further, prior approval by the Reserve Bank of India is required even for ECB up to $20 million before these can be used for rupee expenditure.
8See Fitch Ratings (2007). However, the amounts of reported exposure by various institutions continue to be updated, and have generally exceeded initially reported estimates.
9A recent survey by CLSA (CLSA, 2007) found that 10 financial companies in Asia had exposure to CDOs and other ABSs exceeding 5 percent of shareholder funds, eight of which are banks and the remaining two insurance companies. Only two of the banks reported holdings greater than 2 percent of assets and for most of the remainder, exposure was under 1 percent of assets. With regard to the two insurance companies, exposure is again small, ranging from 0.7–2.2 percent of assets.
10In the October 2007World Economic Outlook, growth in the United States is assumed to slow to 1.9 percent this year and next, while euro area growth should decline in 2008 to 2.1 percent from 2.5 percent this year.
11On purchasing power parity basis using 2007 data. Japan and India together account for an additional 40 percent of the region’s GDP.
Note: The main authors of this chapter are Jacques Miniane and Murtaza Syed.
12For relate IMF views on Asia 10 years after the crisis, see de Rato (2007) and Burton (2007a, 2007b).
13There is some evidence that, despite substantial appreciations, real effective exchange rates remain undervalued relative to fundamentals in a few countries.
14See DSG Asia (2007) for a detailed discussion. Note that household debt has increased substantially in Korea and Taiwan Province of China.
15Note that, for India, the national index in IMF (2007a) was constructed as the aggregate of the six main cities, and hence it is very hard to distinguish local from national trends.
Note: The main authors of this chapter are Hali Edison, Roberto Guimarães-Filho, Charles Kramer, and Jacques Miniane.
16Edison (1993) is an early survey of the intervention literature; Sarno and Taylor (2001) provide a more recent survey of theory and empirical evidence. Truman (2004) concludes “Intervention has definite limits as a policy instrument. Its effectiveness is uncertain and imprecise, and therefore it is at best blunt or a blunted instrument.”
17The risk premium is the differential between home and foreign interest rates, adjusted for the expected depreciation of the foreign currency.
18The well-known empirical violations of uncovered interest parity, surveyed in Engel (1996) and, more recently, Chinn (2006), are consistent with the assumptions underpinning the portfolio balance channel.
19Typically, the literature focuses on the effects of intervention on the nominal bilateral exchange rate vis-à-vis the U.S. dollar, since most countries intervene against the dollar.
20Edison (1993) surveys the literature from the 1980s through early 1990s. Dominguez and Frankel (1993) found some evidence in favor of the portfolio and signaling channels while Obstfeld (1990) found that portfolio balance effects are statistically significant but small. For Japan, Ito (2002) found that large and infrequent intervention had quantitatively small but statistically significant effects on the dollar-yen nominal exchange rate.
21Dominguez (2006) and Edison, Cashin, and Liang (2006) have found that intervention increases exchange rate volatility, in contrast with claims by central banks that intervention does not increase (or is not associated with an increase in) volatility (Neely, 2007)
22Guimarães and Karacadag (2004), using daily data for Mexico and Turkey, find that intervention tends to increase exchange rate volatility. Disyatat and Galati (2005) find weak evidence that intervention is effective in the Czech Republic. On India, see Pattanaik and Sahoo (2003).
23See Neely (2007) and Fatum and Hutchinson (2006) for evidence supporting this view.
24Ideally, intervention should also be adjusted for passive intervention, for example, when the monetary authorities accumulate reserves for the purpose of treasury operations and not to affect the exchange rate. However, such adjustments are not possible in our sample given lack of data.
25Daily turnover data are for 2007, kindly provided by the BIS. Note that it is common in the literature to measure monthly intervention relative to daily turnover.
26Note that June 2007 marks the end of our sample period, not necessarily the end of these “leaning against the wind” episodes.
27Data for Korea start in January 2005; most of its activity in forwards and swaps since then has reflected a slow unwinding of a long forward position, which was mostly built over 2003 and 2004.
28This is an imperfect estimate of sterilization, since reserve money may be changing owing to (for example) shifts in money demand. Also, open market operations of domestic assets are not the only way to sterilize intervention; for example, swaps can be used as well. Further, note that net domestic assets are defined here as reserve money minus net foreign assets, which includes the central bank’s net worth.
29If (narrow) money demand is constant or stable in the very short term, the regressions correctly test for sterilization even for countries that target a short-term interest rate.
30For Korea, calculations were recomputed using the bilateral rate against the yen, but the results were very similar to those using the U.S. dollar. Further work could investigate whether intervention in the region has affected the level or volatility of the real exchange rate.
31Note that “leaning against the wind” policies may generate negative correlations.
32Using the expanded measure of intervention (including the change in the net forward position) for Korea and the Philippines does not qualitatively affect the results.
33Volatility was estimated with daily exchange rate data and then aggregated at the monthly frequency, based on two measures: a fitted GARCH (1,1) process on the daily log difference of the exchange rate, and realized volatility based on the rolling 20-day moving average of the square of the log difference of the exchange rate.
34When controlling for the endogeneity of intervention using two-stage least squares, only in the Philippines was intervention associated with lower volatility in a statistically significant way.
Note: The main author of this chapter is Masahiro Hori.
35See IMF (2002, 2005) and ADB (2007), for example.
36This chapter focuses only on trade in goods. We leave the service trade issue for future research.
37Of note, the data analyzed in this chapter are on residency basis and do not address the issue of the nationality of firm ownership. Thus, for example, exports from Japanese-owned firms producing in China would appear in the data set as Chinese exports.
38An economy engages in intra-industry trade if it exports and imports commodities that are in the same commodity categories. As a measure of the degree of intra-industry trade, the Grubel and Lloyd index defined as GLI(j,t)=Σi(X(i,j,t)+M(i,j,t))-|X(i,j,t)-M(i,j,t)|Σi(X(i,j,t)+M(i,j,t)) is the value of commodity i exports by country j in year t, and M(i,j,t) is that of imports. Here, we calculated the index using the SITC 2-digit classification for i. Although this index has a tendency to get smaller when measured with more detailed data, the 2-digit index is appropriate to identify the processing intra-industry trade (between parts and final goods in the same industries) in Asia.
39The present analysis does not preclude a rise in the domestic value-added content of China’s exports. Indeed, some papers argue that China’s role as the regional assembly line has started to decline, as rising domestic production capacity and strong domestic demand in China have made it a fast-expanding market (see Cui and Syed, 2007).
40Manufactured exports in this chapter are defined to include commodities classified in categories 5, 6 (except 68), 7, and 8 in the SITC (revision 3) classification of trade.
41The seven countries are selected using the rank in the IMD World Competitiveness Yearbook, and include Denmark, Finland, Germany, Japan, Sweden, Switzerland, and the United States.
42Here, we implicitly assume China is the last “goose.”
43The export similarity index between economy j1 and economy j2 (for year t) is defined as IES(j1,j2,t)=100×Σis(i,j1,t)s(i,j2,t)/(Σis(i,j1,t)2Σis(i,j2,t)2) is the share of commodity i exports in economy j’s total exports in year t. The reported indices are calculated using SITC (revision3) 5-digit data for more than 3,000 commodities.
44From economy j1’s viewpoint, the export overlap index between economy j1 and economy j2 (for year t) is defined as IEO(j1;j1,j2,t)=100×Σimin(X(i,j1,t),X(i,j2,t))/ΣiX(i,j1,t) where X(i,j,t) is the value of commodity i exports by economy j in year t.
45While the IES captures the similarity of the comparative advantage structures of two economies, it totally omits their size effects, which sometimes matter in competition and are captured by the IEO.
46The unit price of commodity i exports by country j in year t(P(i,j,t)) is derived as the value of country j exports of commodity i divided by its volume. We calculated the unit price relative to the ASEAN-5 price as RP (i, j, t) = P(i,j,t) / P(i, ASEAN 5, t) for all SITC 5-digit commodities, and took the median as a representative measure.
47This effect depends on Asian cross rates, and is strongest when only the renminbi appreciates among currencies in the supply chain countries. In that case, the prices of Chinese (intermediate good) imports will decline, implying a smaller rise in Chinese export prices in U.S. dollar terms needed to maintain profit levels. On the other hand, if all supply chain country currencies appreciate equally against the U.S. dollar, Chinese export prices will need to rise one-for-one with the dollar depreciation to maintain profit levels, with a correspondingly larger decline in exports.

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