Wharton-SMU Research Center
Bank Lending and Real Estate in Asia: Market Optimism and Asset Bubbles
Winston T.H. Koh, Roberto S. Mariano, Andrey Pavlov, Sock Yong Phang, Augustine H.H. Tan, Susan M.
Wachter
This project is funded by the Wharton-SMU Research Center of Singapore Management University
Bank Lending and Real Estate in Asia: Market
Optimism and Asset Bubbles*
Winston T.H. Koha +, Roberto S. Marianoa, Andrey Pavlovb, Sock Yong Phanga,
Augustine H. H. Tana , Susan M. Wachterc
10 January 2004
Abstract
This paper investigates the Asian real estate price run-up and collapse in the 1990s.
We identify two sets of potential causes for the observed price behavior:
fundamental shifts in demand and underpricing of the put option imbedded in non-
recourse mortgage loans. This underpricing is due to behavioral causes (herding
or disaster myopia) and/or rational response of lenders to market incentives
(agency conflicts, deposit insurance, or limited liability of bank shareholders).
The empirical evidence strongly suggests that underpricing was widespread in
Thailand, Malaysia, and Indonesia. Consequently, these countries experienced a
far more severe market crash then Hong Kong and Singapore, where underpricing
was kept under control by strong government intervention and/or more appropriate
incentive mechanisms.
Keywords: real estate bubble, lender optimism, disaster myopia, Asian financial crisis
* Research support from the Wharton-SMU Research Centre, Singapore Management University, is gratefully acknowledged. Alvin Ang, James Chow, Vincent Goh, Riki Hidajat and Dion Tan provided excellent research assistance. + Corresponding author. a School of Economics and Social Sciences, Singapore Management University, 469 Bukit Timah Road, Singapore 256976. Contact details: +65 68220853, [email protected] (Winston TH Koh); +65 68220888, [email protected] (Roberto S Mariano); +65 68220368, [email protected] (SY Phang); +65 68220379, [email protected] (Augustine HH Tan). b Faculty of Business Administration, Simon Fraser University, 8888 University Dr., Burnaby, BC V5A 1S6, Canada. Tel: 604 291 5835; E-mail: [email protected] c Department of Finance, The Wharton School, University of Pennsylvania, 2300 Steinberg-Dietrich Hall, Philadelphia, PA 19104, USA. Tel: +215 8986355; Email: [email protected]
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1. Introduction
Real markets are vulnerable to waves of optimism and herd behavior that result in
bubbles. A recent case in point is the real estate property markets in Asia in the run-up to the
Asian financial crisis. Speculation in the real-estate markets was rampant in many Southeast
Asian economies in the 1990s. In Thailand, for instance, short-term capital inflows, mostly
through the offshore Bangkok International Financial Centre, found its way into Thailand’s
real estate market, as banks jostled to make long-term loans to developers, based on little
more than the promise of strong economic growth and continued foreign capital inflows. In
hindsight, this lending wave was based on overly-optimistic market expectations. Similarly,
Hong Kong, Singapore, Malaysia, the Philippines, as well as South Korea, also experienced a
surge in investor interest in both the stock market and the real estate sector, as expectations
(more accurately, extrapolations) of strong economic growth in the early 1990s prompted
investors and speculators alike to increase their exposure to these asset markets.
A common striking feature of previous financial crises is that the most seriously
affected economies often first experience a collapse in property prices and a consequent
weakening of banking systems before going on to experience an exchange rate crisis, a
financial crisis, and a business cycle bust. Although this sequence of events does not
necessarily imply a set of causal linkages, the collapse in real estate property prices is clearly
of central importance to recent financial crises in Japan, Indonesia, and Thailand.1 If the
banking systems in these countries had not been damaged by the speculative boom in real
estate markets followed by the collapse in real property prices, these foreign exchange crises
would likely have been less devastating, and the prospects for economic recovery would have
been faster.
Herring and Wachter (1999, 2002) show that in assets markets with no short sales and
a fixed or inelastic supply, optimists – those with reservation prices above the fundamental
1 See Mera and Renaud (2000) and Quigley (2001), which provide detailed accounts of the role played
by Asia’s real estate market in the financial crises of 1997-1998.
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value – will strongly influence prices. Moreover, the optimists are likely to remain in
business so long as the upward trend in asset prices continues even if their optimism, although
self-fulfilling, is unfounded by an analysis of fundamental value of the asset class. Herring
and Wachter (1999, 2002) show that optimists are also likely to be able to borrow against
their capital gains so long as lenders rely on market prices above the fundamental price when
determining the value of real estate properties that are used as collateral. In short, the
fundamental difficulty in engaging in short-sales of real estate, particularly considering its
heterogeneity, means that optimists prevail in the setting of real estate property prices.
In the case of Asia in the 1990s, market optimism was very much in evidence as the
Asia’s strong economic growth generated substantial investor interest in the region. There
was a surge in foreign capital inflow and banks and finance companies across Asia competed
to lend to the real estate sector even as the proportion of non-performing real estate loans
increased from 1994 onwards. The bursting of the real estate markets in Thailand and
Indonesia deepened the financial crisis and sparked the sudden and sharp withdrawal of
capital from East Asian markets. It was also the domino leading to the eventual collapse of
Asian currency and equity markets in late 1997. Even when the worst effects of the crisis
had passed by 1999 and Asian economies had stabilized and economic growth had tentatively
returned, the weakness in the real estate market remained a stress point in many Asian
economies, and it was governmental intervention to inject liquidity into the banking sector
that prevented another meltdown in the banking sector in some countries. Real estate prices
in most Asian economies remain depressed; in Hong Kong, residential property prices remain
at least 50% below the peak in the mid-1990s. In Japan commercial land prices are 50%
below their peak in 1991 and in Singapore, property prices are still 20-40% below the peak in
1996.
A large body of literature has examined the role of the banking sector in propagating
business cycles; see, for example Bernanke (1983), Bernanke and Gertler (1995), King (1994),
Kiyotaki and Moore (1997), and Allen and Gale (1997). These studies demonstrated that
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the workings of the financial sector can amplify the magnitude of the business cycle as
bank credit exposure moves procyclically. In the aftermath of the Asian financial crisis,
many researchers (including Krugman (1998), Wade (1998), Koichi and Renaud (2000), Tan
(2000) and Quigley (2001)) have examined the role played by the real estate sector and have
argued for reforms in the regulation of the real estate property markets and the treatment of
real property loans by financial institutions in order to prevent the recurrence of the kind of
bubble that contributed to the financial crisis.2
The objectives of this paper are two-fold. First, we review the genesis of the real-
estate bubble in the run-up to the Asian financial crisis and the role that it played in the
financial market stress experienced by the afflicted East Asian economies. With the benefit of
hindsight, it is generally agreed that the Asian financial crisis was not a problem brought on
by fiscal deficits, nor one brought on by macroeconomic mis-management, but rather one
brought one by financial excesses in the asset markets that led to a subsequent collapse.
The second objective of this paper is to examine the hypothesis, first developed in
Pavlov-Wachter (2002), that the buildup of the real estate exposure can be fuelled by
incentives to under price the put option of non-recourse loans. We shall use the predictions of
the model to test if such irrational exuberance did exist in Asia’s real estate markets in the
run-up to the financial crisis in 1997. The hypothesis can be explained as follows: In a
booming real estate market, banks may be overly optimistic regarding the collateral values of
properties (which is usually based on recent market transactions). Bank officers may also
compete to meet their quota of loans – particularly, if their compensation is tied to their
degree of success in generating new housing loans. These private incentives, coupled with
general market optimism, mean that the default risks of real estate loans may be underpriced.
If there are sufficiently large number of short-term players in the loan markets, Pavlov-
Wachter (2002) show that this can lead to an underpricing equilibrium in put options of non-
2 Krugman (1998) observes that to understand the Asian financial crisis, one must
focus on the role of financial intermediaries and the price of land and other assets.
5
recourse loans, as well as inflated prices in the asset markets. Importantly, these results hold
even when market participants in both the equity and debt markets are fully rational.
The rest of the paper is organized as follows. In Section 2, we review the main
events that caused the surge in foreign capital inflows into Asian economies in the early
1990s. In Section 3, we discuss the key developments in Asian real estate markets, focusing
on the expansion of bank credit and the impact on property prices and credit exposure to the
real estate sector. In Section 4, we review the growth in bank credit and its exposure to the
real estate sector in Asia. Section 5 reviews the role of lender optimism in credit expansion
across East Asian economies and test for the occurrence of an underpricing equilibrium in the
real estate markets in Hong Kong, Indonesia, Malaysia, Singapore and Thailand, in the run-up
to the Asian financial crisis. Section 6 concludes the paper with a summary of the empirical
findings in the paper and a discussion of the direction for future research.
2. The East Asian Miracle Years
With the benefit of hindsight, it is clear that the activities in the real estate markets in
East Asian economies in the early to mid-1990s were an important contributing factor to the
Asian financial crisis of 1997. As early as 1996, the risk that the real estate sector posed to the
overall stability of the financial sector was noted in the IMF World Economic Outlook
(December 1997 p.69 Box 1): “The investment in real estate was generated partly by
inflation in property values associated with the overheating of the economy, while the quality
of the banking system’s loan portfolio became increasingly dependent on the maintenance of
property prices, since real estate was the main collateral for loans to this sector.”
The bubble in the real estate sector was intimately linked to other factors that led to
the Asian financial crisis. In its assessment of the crisis, the first deputy managing director of
the IMF, Stanley Fischer, noted that the key domestic factors leading to the East Asian crisis
were: “first, the failure to dampen overheating pressures that had become increasingly evident
in Thailand and many other countries in the region and were manifested in large external
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deficits and property and stock market bubbles; second, the maintenance of pegged
exchange rate regimes for too long, which encouraged external borrowing and led to
excessive exposure to foreign exchange risk in both the financial and corporate sectors;
third, lax prudential rules and financial oversight which led to a sharp deterioration in the
quality of banks’ loan portfolios... Although the problems in these countries were mostly
homegrown, developments in the advanced economies and global financial markets
contributed significantly to the build-up of the imbalances that eventually led to the crises. In
many respects, Thailand, Indonesia, and Korea do face similar problems. They all have
suffered a loss of confidence, and their currencies are deeply depreciated,” Fischer (1998,
page 21).
These common factors identified by Stanley Fischer were key to the formation of the
real estate bubble in Asia and the eventual financial meltdown. The pegged or managed
exchange rate regimes, by encouraging external borrowings, led to a high ratio of external
debt, particularly short-term debt, to foreign exchange reserves. In the wake of the surge in
inflow of foreign capital to Asia during 1992-1996, domestic interest rates fell and cheap
financing for investment was readily available. A large portion of the banking credit was
extended to speculative investment projects and real estate transactions. (See Edison, et al
(2000) and Tan (2000) for further discussion on the subject.) The pegged exchange rate
regimes, by insulating businesses and financial institutions from short-term foreign exchange
volatility, led them to hold a significant part of their short-term debt in dollars on an
unhedged basis, thus exposing them to the risk of a sharp devaluation in the event of an
exchange rate regime shift. Below, we provide a brief account of the events in the run-up to
the Asian financial crisis.
2.1 The Surge in Foreign Capital Inflow
To trace the origins of the Asian real estate bubble, one has to start with the huge
capital inflows into emerging Asian economies in the early 1990s, during the days of the
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Asian Miracle years. In the early 1990s, emerging Asian economies3 were very much
admired for their high savings and investment rates, good macro-economic management and
strong GDP growth rates. A well-educated, trained and hardworking workforce was a
commonly-cited factor in sustaining the export competitiveness of many emerging Asian
economies. While Asia’s economic growth potential attracted the attention of investors, the
primary catalyst for the surge in foreign investment flows to emerging Asian economies can
be traced to the Plaza Accord of September 1985 – which devalued the U.S. dollar by close to
50% against the yen. Since most Asian currencies were pegged to the U.S. dollar or
managed against a basket of currencies (of which the U.S. dollar is the most significant
component), the Plaza Accord effectively also reduced the exchange rate of emerging Asian
economies. The enhanced export competitiveness fuelled subsequent economic growth.
Following the Plaza Accord, many East Asian economies benefited from the
relocation of many Japanese manufacturing firms seeking to lower their production costs as
they coped with a strong yen. The Japanese foreign direct investments were followed by
European and American investors. This first wave of foreign direct investments led to rising
rental rates and property rises, which triggered a first wave of real estate boom, as developers
began new projects to meet the increased demands. In its wake, financial investments in the
stock markets increased substantially. By 1993, Asian stock markets were among the top-
performing equity markets in the world. The East Asian Miracle phenomenon attracted
global investor attention and another wave of capital inflow, mostly short-term funds, was
channeled into the stock markets and real estate markets. This new wave of investor
exuberance was justified by market optimism that the strong economic growth performance
of Asian economies would continue and, more importantly, by the realization of high
investment returns in Asian economies in the preceding years.
3 In this paper, emerging Asian economies include China, Hong Kong, Indonesia, Malaysia,
Philippines, Singapore, South Korea, Taiwan and Thailand.
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Figure 1: Total External Debt (Current US$)
US$ billion
0
20
40
60
80
100
120
140
160
180
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China
Indonesia
South Korea
Malaysia
Philippines
Thailand
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 China 55.30 60.26 72.43 85.93 100.46 118.09 128.82 146.70 154.60 154.22 149.80 Indonesia 69.87 79.55 88.00 89.17 107.82 124.40 128.94 136.16 151.24 150.84 141.80 Malaysia 15.33 17.08 20.02 26.15 30.34 34.34 39.67 47.23 42.41 41.90 41.80 Philippines 30.58 32.45 33.01 35.94 39.41 37.83 40.15 45.68 48.27 53.02 50.06 South Korea 34.97 39.73 44.16 47.20 72.41 85.81 115.80 136.98 139.10 130.32 134.42 Thailand 28.09 37.70 41.78 52.64 65.53 100.04 107.74 109.70 104.92 96.77 79.68 Source: World Development Indicators, World Bank (2002)
A key factor in the surge of capital inflows into Asian economies was the system of
pegged or managed exchange rates. Since Asian currencies were managed tightly against the
U.S. dollar, the surge in capital inflows did not lead to sharp appreciation in the exchange rate.
Consequently, domestic liquidity increased and interest rates fell. Financing for investments
in real estate property and in the stock markets was readily available, often with loan quantum
and credit facilities of up to 90% of the collateral value. This flood of liquidity led to a sharp
price appreciation in the asset markets, inflated collateral value and prompted further credit
expansion as asset prices climbed. As shown in Figure 1, the surge in foreign capital inflows
9
was mirrored in the rise of the total external debt in emerging Asian economies (with the
exception of Singapore and Hong Kong).
Figure 2: Short-term Debt as Percentage of Total External Debt %
10
15
20
25
30
35
40
45
50
55
60
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China
Indonesia
South Korea
Malaysia
Philippines
Thailand
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 China 16.85 17.89 19.01 17.80 17.40 18.91 19.72 21.45 18.07 11.47 11.46 Indonesia 15.94 18.00 20.52 20.17 18.05 20.87 25.00 24.14 13.30 13.28 15.96 South Korea 30.89 28.19 27.00 25.85 43.65 54.32 57.50 39.27 20.23 26.66 30.10 Malaysia 12.44 12.14 18.18 26.58 20.40 21.18 27.90 31.63 19.97 14.35 11.10 Philippines 14.48 15.24 15.93 14.01 14.50 13.95 19.85 25.82 14.89 10.84 11.88 Thailand 29.62 33.13 35.25 43.00 44.53 44.08 39.55 34.49 28.27 24.20 18.68
Source: World Development Indicators, World Bank (2002)
In the case of Thailand, the creation of the offshore Bangkok International Banking
Facilities (BIBF) that allowed Thai corporations and banks to borrow in foreign currencies,
free of domestic regulation and taxation, spurred an increase in external debt, particularly
short-term debt. With a pegged exchange rate and ample liquidity at the shorter end of the
yield curve, (causing interest rates to be lower for loans of shorter tenures) it was attractive to
borrow ‘short’ and then invest ‘long’ in real estate projects or other types of investments. As
shown in Figure 2, short-term debt as a percentage of total debt rose from about 30% in 1990
10
to over 40% in 1996. However, this ratio was exceeded by South Korea, which saw its short-
term debt climbing to close to 65% of its total external debt.
Although the buildup in real estate exposure was most dramatic in Thailand, it was
not the only country that suffered from the problem. In Malaysia, major companies also
borrowed heavily from abroad until 1994 when restrictions on foreign borrowings were
enacted. Even so, total external debt continued to climb (see Figure 1). However, compared
to Thailand and Indonesia, a lower share of foreign borrowing was of a short-term nature and
a higher proportion was hedged. From 1992-96 more than 70 percent of bank lending in
Malaysia was channeled into real estate and stock-market investments.
In South Korea too, the conglomerates invested a substantial amount of real estate
and speculated heavily on the stock market, mostly financed with short-term debt. By 1996,
total bank exposure to real estate reached 25%, higher than either Thailand or Indonesia. The
share of Korea’s short-term debt in total debt rose to over 58 % in 1996. By 1996, the top 20
listed South Korean companies were earning a mere 3 % on assets, while the average cost to
borrowing had risen to 8.2 %, and the average debt to equity ratio had risen to 220 % (see
Bullard et al., 1998).
In early 1996, the United States tightened its monetary policy. This led to the
appreciation of the U.S. dollar against the yen and eroded the competitiveness of Asian
exports. As a result, the current account balance of emerging Asian economies deteriorated.
However, the maintenance of the pegged exchange rate regimes meant that the exchange rates
had to be supported even as the current account deficits widened and short-term external
debts climbed. As foreign exchange reserves continued to deplete, investor concerns over the
ability of the central banks to support the currency pegs were heightened and this accelerated
capital withdrawals. In its wake, the rising ratio of short-term debt to total reserves (see
Figure 3) – an indicator of the downward pressure on the currency peg – led to market
speculation over possible currency devaluations.
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Figure 3: Short-term Debt as Percentage of Total Reserves
%
0
40
80
120
160
200
240
280
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China
Indonesia
South Korea
Malaysia
Philippines
Thailand
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 China 27.02 22.38 55.39 55.93 30.26 27.81 22.74 21.48 18.28 10.95 10.00Indonesia 128.63 138.20 157.26 144.20 146.06 174.18 166.17 187.94 85.20 73.25 77.11South Korea 72.40 81.07 69.19 59.94 122.70 142.09 194.92 262.85 54.01 46.88 42.04Malaysia 17.89 17.70 20.19 24.66 23.50 29.45 39.68 69.58 32.28 19.44 15.55Philippines 217.42 111.45 98.51 84.85 80.22 68.05 67.84 135.35 66.60 38.23 39.56Thailand 58.37 67.92 69.52 88.97 96.36 119.37 110.27 140.67 100.42 67.33 45.55
Source: World Development Indicators, World Bank (2002)
The withdrawal of foreign capital and speculative shorting of the currencies in the
forward market led to a tightening of domestic credit and rising interest rates, which hurt the
asset markets. As loan defaults by corporations and investors in the real estate market
increased, capital outflows swelled. When Thailand announced a devaluation of the Thai baht
on 2 July 1997, it signaled a full-blown stampede to get out of emerging Asia. Table 1 below
provides a snapshot of the external debt, current account and foreign exchange reserves
positions of the Asian economies in 1996. On the eve of the Asian financial crisis, Thailand,
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Indonesia and South Korea had significantly higher short-term debt (less than 12 months in
maturity) than could be supported by the foreign exchange reserves.
Table 1:
External Debt, Foreign Reserves and Current Account Balance in 1996, and the
Subsequent Currency Crisis in 1997-98
Economy Total External
Debt (US$ billion)
Short-term Debt
(US$ billion)
Total Foreign Reserves
(US$ billion)
Current Account Balance
(% of GDP)
Change in Foreign Exchange Rate
(%, Jul 97 to Feb98)
China 129 34 107 0.88 -
Hong Kong - - 63 -1.33 -
Indonesia 129 41 24 -3.4 -76
Malaysia 40 11 27 -4.43 -39
Philippines 40 13 10 -4.77 -36
Singapore - - 76 14.05 -16
South Korea 116 102 34 -4.42 -43
Taiwan 46 29 88 4.00 -17
Thailand 107 42 37 -8.05 -49
Source: Asian Financial Markets: 4th Quarter 1998, published by J.P. Morgan Inc.
3. The Real Estate Boom in Asia
In the preceding section, we traced the origins of the Asian financial crisis to the
surge of capital inflows in the early 1990s, as spectacular gains in Asian stock markets and
real estate markets attracted further inflows. In this section, we discuss the buildup in the real
estate bubble and the role played by financial institutions in fueling the real estate market
across Asia. Although the beginning of the Asian financial crisis is usually cited as 2 July
1997, the first signs of the financial crisis were evident in late 1996. The real estate bubble
began to burst across Asia as concerns mounted over loan defaults and talk that many banks
and finance companies had overextended their lending and were faced with huge bad debts.
Expectations play a key role in the creation and the collapse of an asset bubble. A
bubble in an asset market occurs when an investor believes that future investments will
continue to yield high returns, by extrapolating from past experience. A strong growing
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economy, as was the case in Asian countries during the Miracle Years in the early 1990s,
raises expectations about future growth prospects and thus increases the willingness of firms
to increase their debt leverage and invest in future capacity. At the same time, banks are also
more willing to increase their credit exposure in light of appreciated collateral value. The
increase in market liquidity helps to propel asset prices higher. Conversely, when market
conditions deteriorate and collateral values fall, bank loans are recalled and credit lines
curtailed as banks and financial institutions seek to limit their exposure. The ensuing credit
constraints and loan defaults further exacerbates the market decline and may eventually tip
the economy into a recession.
With hindsight, the incentives and opportunities to adopt this extrapolation of past
growth performance appeared to be unusually strong in the booming asset markets in Asia in
the early 1990s, as Mera and Renaud, (2000), Quigley (2001), Tan (2000) and other
researchers have argued. Asian corporations and investors mistakenly took the view of
continued robust export demand in Asian economies in the mid-1990s. Many of them
increased their leverage by borrowing against the collateral value of their assets for business
expansion.
In a booming market, both the borrower and the lender have an incentive to provide as
high an estimate as possible of the collateral value of the asset. For the borrower, it is to
maximize the quantum of loan facility; while for the lender, it is to compete for a bigger slice
of the loanable funds market. Herring and Wachter (1999) point to the common reliance on
appraisals, which even if reflective of current market value, results in underpricing of the put
option (of a default) when cash flows are expected to decline after an initial increase, as is the
case when supply adjusts to an initial demand shock. Moreover, appraisals are based on past
transactions and, as such, are backward-looking and susceptible to disaster myopia, which
refers to a lower than warranted assessment of the risk of default on loans. Hendershott and
Kane (1995) present econometric evidence of appraisal bias of over 50 percent in the late
1980’s U.S. commercial office market.
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In Asia’s real estate market in the early 1990s, these incentive problems inherent in
asset appraisal and valuation were particularly severe. It has been widely reported that the
close linkages and reciprocal business relationships among the business elites in Asian
economies made it easy to mortgage real estate assets at inflated assessed values in order to
secure funding for new business ventures or to expand existing businesses. It is also
important to note that the early 1990s, the domestic bond markets were undeveloped in most
Asian economies. The absence of domestic long-term funding meant that most companies
had to rely on short-term loans to finance long-term investments.
In Thailand’s case, the short-term loans from the Bangkok International Banking
Facility (BIBF) were cheaper as the interest rates were lower than domestic loans in Thai baht.
Thai banks would borrow from the offshore market and then offer loan packages to
developers to finance construction projects as well as individual housing loans to potential
buyers. This arrangement suited the Thai banks as they had control over the valuation of the
collateral (the housing project) and also generated more interest income. The housing loans
market was so lucrative that it was reported that banks would also compete with one another
by offering loan-to-value ratios of 90 per cent and even extending renovation loans to include
the purchase of furniture (Mera and Renaud, 2000).
The surge in foreign capital inflows in the early 1990s fuelled a real estate and stock
market boom not just in Thailand, but in almost all the Asian stock markets and property
markets. As shown in Figures 4A to 4E (for Thailand, Indonesia, Singapore, Hong Kong and
Malaysia, respectively), the real estate markets and the stock markets tracked closely in both
the ascent and the subsequent collapse.
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Figure 4A:
Stock Market Capitalization and Real Estate Property Index - Thailand
US$ billion
0
500
1000
1500
2000
2500
Dec-92 Dec-93 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-000
20
40
60
80
100
120
140
160
SET Property Index
(left scale)
Stock Market Capitalization(right scale)
Note: The SET Property Index is a subindex of the Stock Exchange of Thailand (SET) Index. (Source: Bloomberg) Stock Market Capitalization data is taken from WDI, 2002.
Figure 4B:
Stock Market Capitalization and Real Estate Property Index- Indonesia
US$ billion
0
20
40
60
80
100
120
140
160
180
200
Dec-92 Dec-93 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-000
10
20
30
40
50
60
70
80
90
100
Jarkarta Stock Market
Construction Property Index
(left scale)
Stock Market Capitalization(right scale)
Note: The Jakarta Stock market Construction and Property Index is a subindex of the Jakarta Stock Market Index (JSI). (Source: Bloomberg) Stock Market Capitalization data is taken from WDI, 2002.
16
Figure 4C:
Stock Market Capitalization and Real Estate Property Index - Singapore US$ billion
40
60
80
100
120
140
160
180
200
Dec-90 Dec-91 Dec-92 Dec-93 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-000
50
100
150
200
250URA Property Price Index of
residential properties (left
scale)
Stock Market Capitalization(right scale)
Note: The URA property Index is reported on a quarterly basis (Source: Urban Redevelopment Authority, Singapore). Stock Market Capitalization data is taken from WDI, 2002.
Figure 4D:
Stock Market Capitalization and Real Estate Property Price Index - Hong Kong
HKD per sq ft US$ billion
60
1060
2060
3060
4060
5060
6060
7060
8060
9060
Dec-90 Dec-91 Dec-92 Dec-93 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-000
100
200
300
400
500
600
700
Property Price Index (left scale)
Stock Market Capitalization(right scale)
Note: The Property Price Index is the average of the residential property value per square foot. (Source: Vigers Hong Kong Limited). Stock Market Capitalization data is taken from WDI, 2002.
17
Figure 4E
Stock Market Capitalization and Real Estate Property Index - Malaysia
US$ billion
0
500
1000
1500
2000
2500
3000
3500
4000
Dec-92 Dec-93 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-000
50
100
150
200
250
300
350
KLSE Property
Index(left scale)
Stock Market Capitalization(right scale)
Note: The KLSE Price Index is the subindex of the Kuala Lumpur Stock Exchange Index. (Source: Bloomberg). Stock Market Capitalization data is taken from WDI, 2002.
As early as 1994, early warning signs suggested that the real estate market was
overheating and further increases in property values was not supported by both economic
fundamentals (as current account deficits widened and export competitiveness eroded) and
the pipeline of supply of new properties. This apparent imbalance between new supply and
vacancy rates was evident in both the residential property market and the commercial
property market. Across many Asian cities, the supply of new residential dwellings in urban
areas reached record levels by 1995. In the case of Thailand, property prices had peaked in
late 1992 and steadily declined thereafter. Thailand’s stock market peaked in 1994, but
continued to attract foreign investor interest given the wide differentials between domestic
baht interest rates and U.S. dollar interest rates.
By 1996 the stock of newly built office supply was large, by absolute and relative
standards to recent historical trends, throughout many Asian cities. Vacancy rates rose
18
substantially despite the ratio of asset prices to market rents for commercial and office real
estate, as well as residential properties, reached historic highs well (Source: Morgan Stanley
research reports). As reported by Morgan Stanley Dean Witter in June 1996, the new supply
forecast for 1997 in the Kuala Lumpur office market was almost 4.5 million square feet,
almost twice the increase expected in 1996. Estimates of new supply created during the 5-
year period 1993–1998 were about five times as large as had been produced during the
previous 5-year period. Similar increases in supply were observed and forecast for Singapore
– a steady increase in net supply from a million square feet in 1993 to 2.5 million in 1994, to
3 million in 1995, to 5 million in 1996, to 6.5 million estimated for 1997. During this period,
vacancy rates almost doubled. Elsewhere, in Bangkok, Jakarta, Manila, and Singapore, a
similar pattern of oversupply was also reported (see Quigley (2001) for details).
As shown in Table 2, the commercial real estate markets collapsed across Asian cities
during 1997-1998. Rental yields fell by an average of 34%, while prices fell by an average of
40%. Similar declines were recorded for the residential real estate property markets. Even as
prices and rental rates fell, office vacancy rates for commercial rates in the central business
districts of major Asian cities continued to climb in 1998, as shown in Table 3.
Table 2: Average Rental Rates and Property Prices of Commercial Real Estate in Asian
Cities, 1997 to 1998
1997 Rental
rates (US$/sq m, p.a.)
1997 Property prices
(US$/sq m)
Rental yield in 1997 (% p.a.)
% Change in rental rate,
1997 to 1998
% Change in property prices, 1997 to 1998
% Change in rental yield,
1997 to 1998
Bangkok 35 453 7.78 -60 -50 -1.92 Hong Kong 847 12309 6.88 -13 -18 0.39 Jakarta 36 350 10.25 -63 -66 0.83 Kuala Lumpur 54 593 9.03 -47 -54 1.11 Manila 154 1068 14.43 -36 -43 1.68 Seoul 250 2159 11.58 -34 -40 1.04 Shanghai 248 1265 19.62 -35 -56 6.29 Singapore 334 8916 3.74 -31 -23 -0.40 Taipei 395 5792 6.82 -6 -21 1.05 Tokyo 466 9888 4.71 -18 -30 0.71
Source: Asian Financial Markets: 4th Quarter 1998, published by J.P. Morgan
19
Table 3: Vacancy Rates and New Supply of Offices in Asian Cities, 1997 to 1998
Vacancy rate in June 1997
Vacancy rate in June 1998
New supply, 1998 to 1999 (,000 sq m)
New supply as % of June 1998 stock
Bangkok 17.7 27.0 250.0 11.0 Hong Kong 6.4 9.7 250.0 14.2 Jakarta 13.1 16.0 150.0 6.2 Kuala Lumpur 10.3 16.8 300.0 13.7 Manila 2.1 5.7 200.0 9.9 Seoul n.a. 15.0 500.0 3.9 Shanghai 40.3 48.4 900.0 26.1 Singapore 9.3 11.1 300.0 8.0 Taipei 3.0 2.5 50.0 5.3 Tokyo 5.0 4.5 700.0 1.0
Source: Asian Financial Markets: 4th Quarter 1998, published by J.P. Morgan
4. Bank Lending to Real Estate Sector
In this section, we review the growth in bank credit and its exposure to the real estate
sector in Asia. From 1990 to 1996, spurred by the inflow of foreign funds, bank credit
growth rates in Southeast Asian countries had substantially exceeded GNP growth rates.
Barth et al. (1998) estimate that the expansion in bank credit to the private sector, relative to
GDP growth, was 48% in Hong Kong during the 1990–1996 period; the corresponding
figures were 62% in Indonesia, 40% in Malaysia, 115% in the Philippines, and 70% in
Thailand. By comparison, the growth was 19% in Germany, 3% in Japan, 16% in the United
Kingdom, and 21.5% in the United States.
In the case of Thailand, the financial liberalization in 1992 enabled commercial banks
to borrow more freely in foreign currencies from abroad. By 1997, foreign debt totaled
US$90 billion, of which US$20 billion was due by end-1997. Loans from banks to property
developers tripled between 1992 and 1996. The market was flush with so much liquidity that
funding was available for almost any real estate project. In fact, Thai financial institutions
often competed with one another for customers by increasing loan amounts and reducing
interest rates. There was also an incentive for corporate borrowers to borrow in U.S.
dollars; they paid interest rates of 8% compared to over 13% if they borrow in Thai baht.
20
By mid-1996, the loan exposure of the real estate sector in Thailand was estimated at 30-40%
of total loans with a value of US$160 billion. On average, loans to the real estate sector
amounted to 10.2 % of all outstanding loans of the commercial banks. The exposure of the
finance companies was higher, with an estimated 25-30 % of all outstanding loans was
extended to the real estate sector (Source: Bank of Thailand).
Figure 5: Domestic Credit Provided by the Banking Sector (as % of GDP)
0
20
40
60
80
100
120
140
160
180
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China Hong KongIndonesia South KoreaMalaysia PhilippinesSingapore Thailand
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 China 89.98 92.64 91.97 103.23 92.18 91.18 97.85 106.77 121.80 130.35 132.73 Hong Kong 156.29 132.13 124.17 130.42 144.73 147.50 157.32 168.08 150.21 141.37 141.42 Indonesia 45.48 45.61 46.05 47.73 50.61 51.78 54.23 57.82 58.37 61.00 66.22 Malaysia 75.67 79.02 114.61 112.50 112.22 126.71 142.91 161.81 160.47 151.59 143.38 Philippines 26.86 23.86 26.60 51.73 55.66 64.27 73.95 84.47 75.63 69.17 67.97 Singapore 75.64 76.55 74.88 72.64 72.94 76.45 80.36 86.34 100.32 95.90 89.61 South Korea 65.65 66.39 65.35 65.31 65.95 64.74 69.50 80.01 91.49 96.82 104.00 Thailand 91.05 92.74 99.36 111.57 125.43 135.33 142.19 162.39 164.02 144.61 121.72
Source: World Development Indicators, World Bank, 2002
21
Figure 5 shows the expansion of domestic credit as a percentage of GDP for Asian
economies in the 1990s. A significant portion of the credit expansion was directed to the real
estate sector, estimated to account for between 15% and 55% of the total bank loans. By the
mid-1990s the size of the real estate sector was substantial relative to GNP. For example, it
was estimated that in 1996-1997 the value of real estate in the Bangkok metropolitan region
was almost half as large as the GNP of the entire economy of Thailand (see, Mera and
Renaud, 2000). Across all the East Asian economies, real estate debt, as a percentage of GNP,
averaged 13 %. Table 4 provides the breakdown across the various Asian economies.
The rapid expansion in bank credit to the real estate sector continued in 1995 and 1996
(see Figure 5) even as the ratio of nonperforming real estate loans to total loans rose. In 1995,
nonperforming loans were 10.4% of all bank loans in Indonesia, 7.7% in Thailand, and almost
6% in Malaysia, as shown in Table 4.
Table 4: Exposure of the Banking Sector to Real Estate, 1996
Real estate, as % of bank
loans
Private bank credit (US$
billion)
Average loan exposure to real
estate as % of GNP
Non-performing real estate loans (% of
total loans)1
Moody's rating of the banking
sector
1996 GNP (US$ billion)
China 35-40 930 9 n.a. D 812 Hong Kong 40-55 300 76 3.0 C 154 Indonesia 25-30 54 7 18.0 - 197 Malaysia 30-40 120 58 6.0 D+ 94 Philippines 15-25 40 17 8.0 D+ 87 Singapore 30-40 130 30 4.5 C+ 94 South Korea 15-25 440 17 18.0 D 480 Taiwan 35-45 400 58 5.0 D 274 Thailand 30-40 160 44 16.0 E+ 176
1. Estimates, based on Asian Financial Markets, 1998 issues, published by J.P. Morgan Inc.
What accounted for the sizable amounts of credit that was channeled to the real estate
sector in Asia? Previous studies on this subject (surveyed in Mera and Renaud, 2000) had
identified a number of weaknesses in Asia’s banking sector, such as unsophisticated credit
risk management system, relatively lax regulation that enabled banks to lend at loan-to-
22
(collateral) values as well as the implicit support of financial institutions by the government.
Many financial markets were characterized by weak foreclosure and property rights laws, as
well as a lack of transparency of lending relationships.
Perhaps one of the biggest contributing factors to the real estate bubble buildup was
the belief by many financial institutions of the implicit support provided by the government.
This belief was not misplaced, as in the aftermath of the Asian Financial Crisis, many
financial institutions in Thailand were bailed out by the government and protected from losses.
As some observers noted, the problem of certain banks in Thailand is not that they were too
big to fail, but that they were too political to fail. Elsewhere, in Indonesia and Malaysia, the
strong political connections of those directing financial institutions also led many creditors to
hold the view they had protection from excessive risk. This belief of an implicit guarantee by
the government – as borne out in the case of Thailand – led many banks to underinvest in risk
management technologies and implement less than adequate risk management measures and
credit approval processes to limit their exposures.
Figure 6 is a scatter-plot of the domestic credit provision by banks (as % of GDP)
against the differentials of lending rates and deposit rates. While the interest rate differentials
in Singapore remained broadly stable from 1990 to 2000, bank credit expansion climbed
steadily. Similarly, in the case of Hong Kong, its interest rate differentials remained stable
(tracking those of the U.S. dollar, to which it is tightly pegged), but credit expansion rose
sharply until 1997, before contracting severely from 1998 to 2000. In both economies, the
government had tight control over the monetary policy and domestic credit expansion. In the
case of Thailand, the differentials between lending and borrowing rates were much more
variable, and credit expansion rose sharply from 1993 to 1997, even as the interest rate
spreads widened. As for Indonesia, the spread between lending and borrowing rates were
more volatile and wider than in the case of Thailand, but domestic credit expansion was
significantly lower.
23
Figure 6: Domestic Bank Credit Expansion and Interest Rate Spread
Domestic Credit Provided by Banks (as % of GDP)
ID90 ID91 ID93
HK91
HK92
HK93
HK97
HK98HK99
HK00
TH90
TH92
TH94
TH95
TH00
SG96
SG97
SG98
SG99
ID92
ID94
ID95
ID96 ID97
ID99
HK90
HK94HK95
HK96
TH91
TH93
TH96
TH97 TH98
TH99
ID00
SG90SG91SG92SG93 SG94
SG95
SG00
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150
155
160
165
170
175
1 2 3 4 5 6 7
Spread between Lending and Deposit Interest Rates (%)
Legend : HK Hong Kong SG Singapore ID Indonesia TH Thailand The number next to the country tag refers to the year.
24
5. Lender Optimism, Disaster Myopia in Asset Markets
While governance issues and implicit government support were key factors that
accounted for the sharp expansion in bank credit to the financial sector in Thailand, it has
been argued by some researchers that disaster myopia and lender optimism were also factors
that fuelled the credit expansion across East Asian economies.
In Herring and Wachter (1999, 2002), it is shown that real estate markets are
particularly vulnerable to waves of optimism by both lenders and borrowers. In such markets
with no possibility of short sales and a fixed or inelastic supply (in the short-run), optimists –
those with reservation prices above the fundamental value – will strongly influence prices.
They are also likely to remain in business so long as the upward trend in prices continues
even if their optimism is unfounded by an analysis of fundamental value. Optimists are likely
to be able to borrow against their capital gains so long as lenders rely on market prices above
the fundamental price when determining the value of real estate as collateral. The primary
difficulty in selling real estate short, given its heterogeneity, means that optimists exert
significant influence in the setting of real estate property prices.
The magnitude of the resultant rise in real estate property price will be greater, and
the duration longer, so long as banks continue to augment the financial resources of the
optimists. Historically, the willingness of banks to increase their exposure to real estate
lending is likely to increase when economic conditions are favorable, as was the case during
the Asian Miracle years of the early 1990s. Lender/Investor optimism is a common
phenomenon as the extrapolation of past positive price trends, and the low-frequency or non-
observation of negative events, lead to underpricing of the default risk. Poor information and
inadequate analysis may further perpetuate the lending optimism.
Lenders may have a further incentive to underprice the put option of the real estate
loans, so that the risk of loan default, and other associated risks (e.g. exchange rate risk), are
not adequately priced. Pavlov and Wachter (2004) construct a model to show that the
presence of short-term players in the debt market may induce the underpricing of the put
25
option in equilibrium, when certain conditions hold. In turn, this will lead to inflated asset
prices. This phenomenon may occur even when market participants in both the equity and
debt markets are fully rational. The implications of the Pavlov-Wachter model is that lower
lending rates in an environment of asset price appreciation may not fully reflect the value of
the default risk and higher deposit rates may result due to increased demand for deposits.
This, in turn, leads to inflated asset prices above their fundamental levels (Result 3 of Pavlov
and Wachter, 2004).
While the divergence between market and fundamental value of real estate assets are
not directly testable, if the Pavlov-Wachter hypothesis holds, the differential of the loan rate
over the deposit rate can be used as a proxy for the extent of underpricing. This spread
compensates the lender for providing the put option embedded in loans. During a bubble, if
due to widespread lender underpricing, lenders will require little or no compensation for the
put option. Thus, the spread of lending rates over deposit rates is narrowed, and is correlated
with higher prices of the underlying asset.
At the same time, periods of widespread underpricing are associated with increased
lending activity. In order for lenders to raise enough capital to support the increased loan
activities, they will need to increase the deposit rates. This then leads to the testable
implication that deposit rates are positively correlated with asset prices. Therefore, we may
test for the occurrence of an underpricing equilibrium with the following hypothesis:
Result 4 of Pavlov and Wachter, 2004: The spread between lending rates and deposit rates is
negatively correlated with asset prices. Deposit rates are positively correlated with asset
prices.
In the context of Asian markets in the 1990s, the high deposit rates served to attract
further capital inflows, even as the spread between lending rates and deposit rates narrowed.
In light of the significant surge in foreign capital inflows, there may not be any noticeable
surge in deposit rates, at least not till the eve of the financial crisis in mid-1997.
26
In order to test the above hypothesis in the case of the Asian real estate bubble in the
1990s, we compiled the data from various sources, including The World Bank’s World
Development Indicators (2002), Bloomberg and the data released by the Asian central banks
and the statistical bureaus on their websites.
Table 5: Lending Interest Rates, Deposit Rate and Interest Rate Spread (%)
Lending Rates
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China 9.36 8.64 8.64 10.98 10.98 12.06 10.08 8.64 6.39 5.85 5.85
Hong Kong 10.00 8.50 6.50 6.50 8.50 8.75 8.50 9.50 9.00 8.50 9.50
Indonesia 20.83 25.53 24.03 20.59 17.76 18.85 19.22 21.82 32.15 27.66 18.45
Malaysia 7.17 8.13 9.31 9.05 7.61 7.63 8.89 9.53 10.61 7.29 6.77
Philippines 24.12 23.07 19.48 14.68 15.06 14.68 14.84 16.28 16.78 11.78 10.91
Singapore 7.36 7.58 5.95 5.39 5.88 6.37 6.26 6.32 7.44 5.80 5.83
South Korea 10.00 10.00 10.00 8.58 8.50 9.00 8.84 11.88 15.28 9.40 8.55
Thailand 14.42 15.40 12.17 11.17 10.90 13.25 13.40 13.65 14.42 8.98 7.83
Deposit Rates
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China 8.64 7.56 7.56 10.98 10.98 10.98 7.47 5.67 3.78 2.25 2.25
Hong Kong 6.67 5.46 3.07 2.25 3.54 5.63 4.64 5.98 6.62 4.50 4.80
Indonesia 17.53 23.32 19.60 14.55 12.53 16.72 17.26 20.01 39.07 25.74 12.50
Malaysia 5.90 7.18 7.97 7.04 4.94 5.93 7.09 7.78 8.51 4.12 3.36
Philippines 19.54 18.80 14.27 9.61 10.54 8.39 9.68 10.19 12.11 8.17 8.31
Singapore 4.67 4.63 2.86 2.30 3.00 3.50 3.41 3.47 4.60 1.68 1.71
South Korea 10.00 10.00 10.00 8.58 8.50 8.83 7.50 10.81 13.29 7.95 7.94
Thailand 12.25 13.67 8.88 8.63 8.46 11.58 10.33 10.52 10.65 4.73 3.29
Interest Rate Spreads
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
China 0.72 1.08 1.08 0.00 0.00 1.08 2.61 2.97 2.61 3.60 3.60
Hong Kong 3.33 3.04 3.43 4.25 4.96 3.12 3.86 3.52 2.38 4.00 4.70
Indonesia 3.30 2.21 4.43 6.04 5.23 2.13 1.96 1.81 -6.92 1.92 5.95
Malaysia 1.26 0.94 1.35 2.01 2.67 1.70 1.81 1.75 2.10 3.16 3.41
Philippines 4.58 4.27 5.20 5.08 4.52 6.29 5.16 6.08 4.67 3.61 2.60
Singapore 2.69 2.95 3.09 3.09 2.88 2.86 2.85 2.85 2.84 4.12 4.12
South Korea 0.00 0.00 0.00 0.00 0.00 0.17 1.34 1.07 1.99 1.45 0.61
Thailand 2.17 1.73 3.29 2.54 2.44 1.67 3.06 3.13 3.77 4.25 4.54 Source: World Development Indicators, World Bank, 2002
27
Table 5 reports the lending interest rates, the deposit interest rates, and the spread
between the two rates for eight Asian countries. Note that both the lending and deposit rates
fell in the early 1990s in the wake of the massive inflow of foreign capital into Asia. The
interest rate spreads also appeared to have either remained stable or narrowed in the years
preceding 1997. We test the hypothesis of Pavlov and Wachter (2004) on the real estate
market in Hong Kong, Indonesia, Malaysia, Singapore and Thailand.
In Thailand’s case, the property index we use for the analysis is the Stock Exchange
of Thailand Property sub-index (see Figure 4A), while the lending interest rates and deposit
interest rates used are the minimum lending rates (MLR) and the 3 month deposit rates
(Source: Bank of Thailand). The correlation analysis, for the period 1993 to 1997, is based
on the levels in the property price index and the levels of the deposit rates and interest rate
spreads. The correlation coefficients, reported in Table 6, are of the right signs, consistent
with the Pavlov-Wachter hypothesis. Changes in real estate prices were positively correlated
with changes in deposit rates and negatively correlated with the changes in interest rate
spreads. Note that minimum lending rates and deposit rates do not change frequently.
Actual lending rates, however, particularly mortgage rates, may be adjusted downwards for
individual transactions. More importantly, generous loan-to-value ratios and higher appraised
collateral values were used to compete in the real estate loans market.
Likewise, we ran the same correlation analysis for Malaysia and Indonesia. The
property price indices we used are those shown in Figure 4B and 4E. In the case of Malaysia,
the correlation coefficients are of the right signs, again supporting the Pavlov-Wachter
hypothesis. For Indonesia, the correlation coefficient between the property price index and
the interest rate spread is negative, in line with the hypothesis. However, the correlation
between the property price index and the deposit rates is also negative. One possible
explanation for the negative correlation is the fact that Indonesia saw very strong inflows of
foreign capital in the 1990s.
28
Table 6: Correlation between Property Prices and Interest Rates
Correlation Coefficient
Real Estate Prices Spread of Lending rates
over deposit rates Deposit rates (3-month rate at
commercial banks)
Model prediction of Pavlov and Wachter (2002)
Negative Positive
Thailand (level monthly, from Jan 1992 to May 2003) -89.37% 50.97%
Malaysia (level, monthly, from Dec 1992 to May 2003) -64.75% 34.66%
Indonesia (level, monthly from Dec 1995 to Dec 2000) -40.33% -44.32%
Singapore (level, quarterly, from 1983Q1 to 2003Q1) 23.53% -41.85%
Hong Kong (level, quarterly, from 1990 Q1 to 1997Q4) 3.99% -30.46%
We replicated the analysis for Singapore and Hong Kong. In both cases, the signs of
the correlation coefficients were opposite to those that were predicted by the Pavlov-Wachter
hypothesis and noticeably smaller in absolute value. For the case of Singapore, only quarterly
data for the residential property price index was available. As for Singapore interest rates, we
use the 3-month deposit rates and bank prime lending rates (Source: Monetary Authority of
Singapore). The Monetary Authority of Singapore (the de-facto central bank) also intervened
actively to smooth the fluctuations in interest rates. The results are not consistent with the
Pavlov – Wachter underpricing phenomena. In Singapore’s case, the government exercised
tight control over land sales and such sales were accelerated in the 1990s to dampen the
property market as real estate prices rose. At the same time, guidelines for property loans
were tightened in 1996 to curb speculation in property4. Together with tighter guidelines on
bank loans to the real estate sector, Singapore banks were less exposed to the real estate 4 Among the measures introduced was to treat capital gains of real estate transactions as taxable
income if the sale of the property took place within three years of purchase. The maximum loan
quantum was also fixed at 80% of the appraised real estate value.
29
market than other countries, such as Indonesia and Thailand. Moreover, the Singapore
government, through the Housing Development Board, had exclusively provided mortgage
loans for the purchase of public housing until 2002.
In the case of Hong Kong, the currency was pegged to the U.S. dollar at HK$7.8 to
one U.S. dollar. This meant that the Hong Kong interest rates moved in line with the U.S.
interest rates. The capital inflows were largely sterilized to keep Hong Kong interest rates in
line with the U.S. rates. As in the case of Singapore, the boom in the real estate sector
appeared to be fuelled more by the boom in the stock markets. From Figures 4C and 4D, the
stock markets peaked ahead of the real estate markets, as reflected in the property price
indices. The wealth effect resulting from the stock market boom was an important factor
propelling property prices higher in both economies. As a result, the real estate markets were
also less sensitive to movements in the interest rates.
By any measure, all five real estate markets experienced a substantial negative
demand shock. However, the magnitude of price declines was very different. Relative to
their peak the real estate markets in Thailand, Malaysia, and Indonesia declined by shocking
95, 86, and 81 percentage points, respectively, while Singapore and Hong Kong saw
relatively more tampered declines of 33 and 38 percentage points. Interestingly, it was
Singapore and Hong Kong that had tight government controls over the real estate lending
market before the crash. All this evidence points in one direction: underpricing was
widespread in Thailand, Malaysia, and Indonesia, and limited in Singapore and Hong Kong,
likely thanks to tight government controls.
According to Pavlov and Wachter (2004), underpricing results in inflated asset prices
above their fundamental level. After a crash, underpricing is eliminated and prices return to
their fundamental level. Thus, underpricing compounds the effect of a negative demand
shock and produces massive price declines. Therefore, countries that experience severe
underpricing in the landing market, such as Thailand, Malaysia, and Indonesia, experience
otherwise unexplained excessive price drops following a negative demand shock. Countries
30
that prevent underpricing during periods of economic growth tend to experience relatively
smaller price declines during economic stagnation.
The relationship between the property price index and the interest rate differentials is
illustrated in Figures 7A to 7E.
Figure 7A: Property Price Index and Interest Rate Spread – Thailand
%
0
500
1000
1500
2000
2500
1993 1994 1995 1997 1998 1999 2000 2001 2001 2002 2003
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
Spread between minimum lending rate and 3-month deposit rate(right scale, inverted)
Price Index of Residential Real Estate Property(left scale)
Figure 7B: Property Price Index and Interest Rate Spread - Singapore
Property Price Index 1998, Q4 = 100 %
0
20
40
60
80
100
120
140
160
180
200
1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Spread betw een prime lending rate and 3-month deposit rate(right scale, inverted)
Price Index of Residential Real Estate Property(left scale)
31
Figure 7C: Property Price Index and Interest Rate Spread - Malaysia %
0
500
1000
1500
2000
2500
3000
3500
4000
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Spread betw een prime lending rate and 3-month deposit rate(right scale, inverted)
Price Index of Real Estate Property(left scale)
Figure 7D: Property Price Index and Interest Rate Spread - Indonesia %
0
20
40
60
80
100
120
140
160
180
200
1995 1996 1997 1998 1999 2000 2001 2002
0
10
20
30
40
50
60
70
Spread betw een lending rate and 1-month deposit rate(right scale, inverted)
Jakartal Real Estate Property(left scale)
32
Figure 7E: Property Price Index and Interest Rate Spread – Hong Kong
%
1500
2500
3500
4500
5500
6500
7500
8500
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
-3.5
-2.5
-1.5
-0.5
0.5
1.5
2.5
3.5
4.5
5.5
Spread betw een prime lending rate and 1-month deposit rate(right scale, inverted)
Property Price Index(left scale)
6. Summary and Discussion
In this paper, we have reviewed the genesis of the real-estate bubble in the run-up to
the Asian financial crisis, and the role that it played in the financial market stress experienced
by the afflicted East Asian economies. We also examined the hypothesis, developed in
Pavlov-Wachter (2004), that the buildup of the real estate exposure might be fuelled by
incentives to under price the put option real estate loans. Our preliminary analysis shows
that Thailand, Malaysia, and Indonesia appeared to have experienced the Pavlov-Wachter
underpricing phenomena, which, in turn, resulted in massive price declines following the
negative demand shock of 1997. Singapore and Hong Kong, on the other hand, seem to have
successfully controlled underpricing in the early 1990s, perhaps due to strong and decisive
government intervention. Consistent with this hypothesis, Singapore and Hong Kong
experienced relatively smaller price declines which were very likely due to fundamental shifts
in demand.
33
There are a number of directions in which we can refine the research in this paper.
Firstly, we will use alternative data series on real estate property prices to conduct the
correlation analysis. Our current analysis using the property sub-indices of the stock market
indices had its limitations, in that the price series may be more significantly correlated with
overall stock market movements, than with the price movements in the real estate market.
Nonetheless, the correlation should be positive between the property sub-indices and the real
estate market. Unfortunately, good data on such series are not readily available. Further
analysis with more comprehensive data should improve the results.
Secondly, we briefly mentioned that in the case of Asia, foreign capital inflow was a
significant driver of the stock market boom and real estate market boom. Thus, deposit rates
may not need to rise, even as banks continue to increase their lending to the real estate sector.
At the same time, the system of pegged exchange rates meant that besides loan default risk,
exchange rate risk (specifically, devaluation risk) was a significant factor in the underpricing
of the embedded put option of real estate loans. By incorporating these aspects into an
expanded theoretical model described in Pavlov-Wachter (2004) will enrich the analysis and
could yield additional predictions that we can test empirically.
34
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