Aoki, Kosuke, James Proudman, and Gertjan Vlieghe, 2002, “House Prices, Consumption, and Monetary Policy: A Financial Accelerator Approach,” Bank of England Working Paper No. 169 (London: Bank of England).
Attanasio, O, Blow, L, Hamilton, R and Leicester, A (2005), “Consumption, House Prices and Expectations,” Bank of England Working Paper No. 271.
Bank for International Settlements (BIS), 2006, “Housing Finance in the Global Financial Market,” CGFS Publication No. 26 (Basel: Committee on the Global Financial System).
Benito, Andrew, Jaime N.R. Thompson, Matt Waldron, and Rob Wood, 2006, “House prices and Consumer Spending”, Bank of England Quarterly Bulletin (Summer).
Bernanke, Ben S., and 2007, “Housing, Housing Finance, and Monetary Policy,” opening speech at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
- Search Google Scholar
- Export Citation
)| false Bernanke, Ben S., and 2007, “ Housing, Housing Finance, and Monetary Policy,” opening speech at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “ Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
Bernanke, Ben S., and Mark Gertler, 1995, “Inside the Black Box: The Credit Channel of Monetary Policy Transmission,” Journal of Economic Perspectives, Vol. 9 (Autumn), pp. 27–48.
Bernanke, Ben S., and Simon Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” in Handbook of Macroeconomics, Vol. 1C, ed. by J.B. Taylor and M. Woodford (Amsterdam: North-Holland), Ch. 21.
Billmeier, Andreas, and Isabella Massa, 2007, “What Drives Stock Market Development in the Middle East and Central Asia—Institutions, Remittances, or Natural Resources?” IMF Working Papers No. 07/157 (Washington: International Monetary Fund).
Bordo, Michael D., and Olivier Jeanne, 2002, “Boom-Busts in Asset Prices, Economic Instability, and Monetary Policy,” NBER Working Paper No. 8966 (Cambridge, Massachusetts: National Bureau of Economic Research).
Calza, Alessandro, Tommaso Monacelli, and Livio Stracca, 2007, “Mortgage Markets, Collateral Constraints, and Monetary Policy: Do Institutional Factors Matter?” CEPR Discussion Paper No. 6231 (London: Centre for Economic Policy Research).
Case, Karl E. and Robert J. Shiller, 1989, “The Efficiency of the Market for Single Family Homes,” American Economic Review 79, pp. 125–37.
Chiquier, Loïc, Olivier Hassler, and Michael Lea, “Mortgage Securities in Emerging Markets,” World Bank Group, Working Paper 3370 August 2004.
Collyns, Charles, and Abdelhak Senhadji, 2002, Lending Booms, Real Estate Bubbles and The Asian Crisis, IMF Working Papers No. 02/20 (Washington: International Monetary Fund).
Debelle, Guy, 2004, “Macroeconomic Implications of Rising Household Debt,” BIS Working Paper No. 153 (Basel: Bank for International Settlements).
Dynan, Karen E., Douglas W. Elmendorf, and Daniel E. Sichel, 2006, “Can Financial Innovation Help to Explain the Reduced Volatility of Economic Activity?” Journal of Monetary Economics, Vol. 53 (January), pp. 123–50.
Englund, Peter and Yannis M. Ioannides, 1997, “House Price Dynamics: An International Empirical Perspective,” Journal of Housing Economics, 6, pp. 119-136.
Fisher, Jonas D. M., 2007, “Why Does Household Investment Lead Business Investment Over the Business Cycle?” Journal of Political Economy, Vol. 115, No. 1.
Green, Richard K., and Susan M. Wachter, 2007, “The Housing Finance Revolution,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
- Search Google Scholar
- Export Citation
)| false Green, Richard K., and Susan M. Wachter, 2007, “ The Housing Finance Revolution,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “ Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
Hilbers, Paul, Alexander W. Hoffmaister, Angana Banerji, and Haiyan Shi, 2008, “House Price Developments in Europe: A Comparison, IMF Working Papers No. 08/211 (Washington: International Monetary Fund).
International Monetary Fund, 2008a, World Economic Outlook, April 2008, Chapter 3, “The Changing Housing Cycle and the Implications for Monetary Policy,” pp. 103-132 (Washington: International Monetary Fund).
International Monetary Fund, 2009b, World Economic Outlook, October 2009, Chapter 3, “Lessons for Monetary Policy from Asset Price Fluctuations,” (Washington: International Monetary Fund).
International Finance Corporation, 2008, May, http://www.ifc.org/ifcext/economics.nsf/Content/CON_Housing-Global_Conference_on_Housing_Finance_in_Emerging_Markets_May2008?OpenDocument&TableRow=1.1#1. (Washington: World Bank Group).
Kholodilin, Konstantin A., Jan-Oliver Menz, Boriss Siliverstovsx, 2007, “What drives housing prices down? Evidence from an international panel,” DIW Berlin, German Institute for Economic Research, Discussion Paper No. 758.
Leamer, Edward, 2007, “Housing Is the Business Cycle,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31– September 1.
Merrill Lynch, 2007, Guide to Emerging Mortgage and Consumer-Credit Markets, Vol 2: Central and Eastern Europe, Middle East and Africa.
Miles, David, 1992, “Housing Markets, Consumption and Financial Liberalisation in the Major Economies”, European Economic Review, 36 (1992) 1093-1136, North-Holland
Muellbauer, John, 2007, “Housing, Credit and Consumer Expenditure,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
Ortalo-Magne, F, and Sven Rady, 2006, “Housing Market Dynamics: On the Contribution of Income Shocks and Credit Constraints”, Review of Economic Studies, Vol. 73, pp. 459-485, April 2006
Pesaran, M. Hashem, Yongcheol Shin, Ron P. Smith, 1999, “Pooled Mean Group Estimation of Dynamic Heterogeneous Panels,” Journal of the American Statistical Association, Vol. 94, No. 446., pp. 621-634.
Poterba, J., 1991, “House Price Dynamics: the Role of Tax Policy and Demography,” Brooking Papers on Economic Activity: 2, Brookings Institution, pp. 142-203.
Schnure, Calvin, 2005, “Boom-Bust Cycles in Housing: The Changing Role of Financial Structure,” IMF Working Paper 05/200 (Washington: International Monetary Fund).
Shiller, Robert J., 2003, “From Efficient Markets Theory to Behavioural Finance,” Journal of Economic Perspectives, Volume 17, No. 1, Winter, 84-104.
Shiller, Robert J., 2007 “Understanding Recent Trends in House Prices and Home-ownership,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
- Search Google Scholar
- Export Citation
)| false Shiller, Robert J., 2007“ Understanding Recent Trends in House Prices and Home-ownership,” paper presented at the Federal Reserve Bank of Kansas City 31st Economic Policy Symposium, “ Housing, Housing Finance and Monetary Policy,” Jackson Hole, Wyoming, August 31–September 1.
Tsatsaronis, Kostas, and Zhu, Haibin, 2004, “What drives Housing Price Dynamics: Cross-Country Evidence,” BIS Quarterly Review, March 2004 (Basel: Bank for International Settlements).
World Bank, 2005, The Macroeconomic and Sectoral Performance of Housing Supply Policies in Selected MENA Countries: A Comparative Analysis, April 2005, (Washington: World Bank Group).
Zhu, Haibin, 2005, “The Importance of Property Markets for Monetary Policy and Financial Stability,” BIS Working Paper No. 21 (Basel: Bank for International Settlements).
The authors are grateful to Ralph Chami, Maher Hasan, Patrick Imam, Tigran Poghosyan and Pau Rabanal for useful comments on an earlier draft, and seminar participants for comments made at the MCD discussion forum. Thanks also to Amar Finance and Leasing, the Arab Monetary Fund, the International Finance Corporation, Merrill Lynch, and the World Bank for kindly providing some data used in this study. The usual disclaimer applies.
The EMCD region comprises the following 16 economies: Algeria, Bahrain, Egypt, Iran, Jordan, Kazakhstan, Kuwait, Lebanon, Libya, Morocco, Oman, Qatar, Tunisia, Saudi Arabia, Syria, and the United Arab Emirates. However, data are not available for all 16.
Down payments for homeownership have ranged between 20–100 percent, implying that the younger generation (21–35 year-olds) and members of low-income households have been, for the most part, deprived of ownership. As a result, a large segment of these populations have tended to live with their parents until they are able to purchase a home, while a smaller fraction rent. Moreover, and until recently, bank and nonbank lending to these particular groups has been limited.
The state is a majority owner of land in Algeria, Egypt, Iran, and Morocco. In Egypt and Morocco, only 25 percent of land is titled. By contrast, in Saudi Arabia, the state offers families free plots of land to build their new homes—although more recently this has been limited to low-income households. Several other economies in the region shared this problem prior to 2001, but structural reforms introduced in 2002—particularly in Egypt and Morocco—began to relax this constraint.
The house-price-to-income ratio is high in both Bahrain and the UAE despite the absence of a supply gap. This may be due to building and demand-push associated with expatriates’ luxury houses in these countries.
Home improvement is needed in the latter to avoid any erosion in value of housing stock.
This is the real estate industry’s profitability yard stick.
Registration, transfer, foreclosure, construction quality, and tax regimes.
To be specific, it was by and large the GCC (and, in particular, the UAE) nonbanks that contributed to this profound change. In Egypt and Morocco, for example, banks actually extend less than half the total of mortgage loans, given a rich nonbank lending environment—which nonetheless has many problems and is undergoing significant reform. The change in the role of the state, as a specialized lender and market enabler, was the other contributing factor—see below.
The main Islamic (shari’a-compliant) housing finance products are: Ijara (akin to a lease), Musharaka mutanaqisa (akin to a declining-balance mortgage), Murabaha (akin to cost-plus mortgage), Furijat (shorter-duration mortgage) and Yusur (an adjustable repayment mortgage). See Appendix Box A.2 for more details on Islamic mortgage products. Box 3 and Box 1 of the Bahrain and Kuwait 2009 Article IV consultation staff reports, respectively, also shed some light on investment companies and wholesale banks’ exposure to the real estate sector.
For example, in Egypt the effective interest rate reached over 20 percent a few years ago, falling to about 12 percent in 2007/08—with the rate applied to low-income households capped at about 6 percent (or 2-4 percent above the central bank rate), and in Jordan the rate was about 9-10 percent, down from 14-15 percent a few years earlier.
At one end, Morroco is an exception, since it has the most advanced mortgage market in the region. At the other end is Egypt, whose mortgage market suffers from high barriers to entry and very conservative lending practices (e.g. the highest, double digit “effective” interest rates, the most regressive subsidies, and the weakest property rights) despite a very rich micro finance history of more than a century. As whole, NOI have increased in the number of lenders and products, while upgrading property rights and regulatory capacity as well as making social housing policies less regressive.
The exception being Saudi Arabia, which has a more rudimentary mortgage market, albeit a rapidly developing one in the past two years.
One of these, typical LTV ratios, was included in WEO (2008a). The other three are unique to this paper.
This is done for two reasons. First, loose lending practices in some advanced countries are considered as contributing factors which partly triggered the current financial crisis. Hence, high LTV ratios are not deemed an advancement or innovation without supporting regulatory capacity to ensure adequate risk analysis is being undertaken by both lenders and regulators. Second, there are large cross-country differences in EMCD in terms of property rights and the adequacy of legal proceedings (including court foreclosures).
Examples include direct limits on banks’ real estate credit concentration ratios, limits on indirect exposure to the sector either through owned companies or SPVs, prevention of the purchase of underdeveloped real estate property for speculative purposes, and specific residential and corporate mortgage leverage ratios.
It should be noted that not only do some countries not distinguish between residential (household) and business (corporate) mortgage loans, but more importantly in recent years, the mortgage-to-GDP data in this paper captures bank only loans and credit to households. The nonbank share is absent in this paper due to data limitations, as is the corporate sector’s mortgage leverage ratio. That is not to suggest that nonbank and corporate mortgage lending are is insignificant. Quite the contrary, these have been rising very rapidly in the past three to four years and are most likely to be larger than bank lending to households in the GCC, Egypt and Morocco. Moreover, these are presumed to be key drivers of Dubai’s real estate boom, along with the demand push from expatriate workers.
Qatar has a lower MMI than other GCCs reflecting its relatively limited range of mortgage lenders and loan features (i.e. its score generated from the first three and fifth columns of Table 2). However, (as shown by the latter columns of Table 2) it is well-advanced in terms state of the art institutional housing finance infrastructure. Thus its MMI is likely to improve in the near future.
Two forms of securitization have begun to emerge (Table 2): mortgage backed assets (MBS) converted to bonds, which are fully sold to institutional investors (i.e. off the balance sheet of banks), and to a lesser extent covered bond issuance (which remain on banks’ balance sheets). For example, the inception of the Algerian Mortgage Refinance Company in 2007 finances unsecured debt securities (mortgage backed bonds); the Egyptian company of mortgage refinance is embarking on the development of the secondary market MBS; the Jordanian Mortgage Refinance Company, a PPP, is a liquidity facility to commercial banks backing residential mortgage loans with a maximum LTV ratio of 80 percent (since 1997); in Morocco securitization was initially limited to transactions involving first-ranking mortgage receivables but more recently a SPV has been set up to purchase all mortgage receivables, expanding to include various products such as RMBS, CMBS, ABCP, and offshore securitization; in Saudi Arabia Dar Al-Arkan, a PPP, commenced issuance of Islamic MBS in 2008; in Tunisia the first MBSs were issued in 2006 for loans with a LTV ratio of 55 percent; the UAE was the first EMCD country to issue MBS.
Appendix Table A.1 lists the definition of these house prices. For Oman, CPI rents could be the imputed rental value of owner-occupied housing, which could explain why house and rental price dynamics co-move.
It should be noted that the house price index of Dubai is used as a proxy for the UAE. See Appendix Table A.1 for further details.
Since quarterly data is employed for the co-integration tests, rent could be sensitive to the overall monthly CPI. However, if that were true, the two variables of the UAE and Kazakhstan would have to also be co-integrated, which they are not. Thus the co-integration results reject this possibility.
One could argue that if rent is more sensitive to the interest rate than aggregate inflation through its effect on user costs then rent could be more flexible than the aggregate price level in the face of shocks. The estimation results of Section VI.B below suggest that in the EMCD region the rental market is more driven by expatriate workers’ demand for housing (proxied by remittances) and the population size of expatriate workers, in addition to the aggregate price level. For this reason, rental growth does not closely follow the change in CPI. Moreover, firms’ investment decisions, which may be correlated with the employment of expatriate workers, could be more sensitive to aggregate shocks (e.g. technology shocks, liquidity shocks, etc.) rather than the aggregate price level. Thus, one could say that shocks influencing the demand in the rental market may not be sector-specific shocks but could be aggregate shocks. Further research would be needed to corroborate this point.
This is particularly relevant to the GCC economies with a large number of expatriate workers and a higher share of rentals.
These latter two points are of importance for EMCD given its particularly youthful workforce (as a ratio of total work force) and, in some of its economies, a significant rental segment.
Although they note that correlations seem to have strengthened at the beginning of this decade.
This mixed data set of countries across diverse regions implies abundant heterogeneity. To address this concern, the analysis runs regressions for the full sample of all 33 EME and then separately for EMCD alone. Moreover, additional techniques are used to address this problem while exploiting its richness—see Sections C and footnote 43 below.
EMCD economies are in italics.
This is corroborated by adding two proxies of supply rigidity.
Since not all channels may be controlled for, it is possible that no co-integrated relationship between the rental price and the right hand side variables of the regression function exists.
The long-term (LT) lending rate is considered to be a proxy for the mortgage lending rate, since the latter is only available for a few EME. For those which are available, the mortgage rate was found to mirror the LT lending rate. Using such a rate could capture the impact of better housing finance access, since the MMI developed in Section III is time invariant.
An affordability ratio is also usually employed in advanced-economy empirical models of house price determinants, to capture the dynamic feedback from higher prices and income. While this ratio—defined as lagged real-CPI-rents-to-real-per-capita-income ratio, unlike advanced economies’—was included in several rounds of the estimation, it was not found to be a significant fundamental determinant of EMCD rental price dynamics—i.e. its coefficient was naught (0.00).
This is consistent with Collyns and Senhadji (2002), who also find that property price inflation in emerging Asia was procyclical with credit growth.
Since GDP rather than GNP was used to measure income, the estimation results therefore apply to citizens and non-citizens alike. However, given that the influx of expatriate workers is sensitive to economic conditions and the luxury end of the rental market is predominately occupied by foreign high-income workers, factors relating to non-citizens could drive the results—a point verified by the estimation results and thus implying that EMCDs are different from the standard empirical models of house price determinants.
Mortgage credit has recently been extended (indirectly) to expatriates in a few EMCD economies (Dubai and Qatar, to be specific) via construction developers (corporates) who borrow from banks. Other types of credit, however, are extended directly to expatriates including for the purchase of durables.
Since the coefficients obtained in this regression do not go hand in hand with theory, one might conclude that population growth dominates (as per a few advanced-country empirical studies), rendering all other coefficients insignificant. It should be noted, however, that this is not the case in EMCD. In particular, for three GCC countries, the dominance of the working-age population regressor appears to be due to the large share of expatriate workers in total population. In these countries, without expatriate workers population growth does not dominate the regression.
The price of steel, a key construction input, is insignificant.
This methodology has an advantage when slope coefficients are heterogeneous across countries (as is likely to be the case here) of providing consistent estimates of the sample mean of the heterogeneous cointegrating vectors. Pooled-within-dimension (fixed effects) estimators do not have this advantage. Moreover, this estimation method provides a single-equation—correcting for the small sample effects of serial autocorrelation and endogeneity—to estimate a long-run (cointegrating) model. The estimated model is described by the following
The intuition of the model is that in the long run, quantity variables such as real per capita income, working-age population and credit growth are co-integrated with the growth rate of the real rental price. The term in the parentheses of (2) measures the deviation from the long run equilibrium and λ is the speed of convergence. Concurrently, the short run relationships between the real rental price and these variables are provided. Since annual data do not provide much room to explore heterogeneity across countries, the assumption here is that all long and short run coefficients are identical across countries. The model is estimated for the full sample of EME and then separately for EMCD.
IMF (2009b) finds that in advanced economies monetary policy was not the smoking gun for the recent house price boom-bust cycle. In other words, it could well be that in some countries interest rates were too low (the United States) but in other countries despite high interest rates there was a house price boom (Australia, the United Kingdom, and New Zealand), and in other countries interest rates were low but no boom occurred (Germany). So from an advanced cross-country perspective one cannot conclude that monetary policy was the main fundamental factor driving house prices.