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Economic Watch Peru Lima, September 10, 2012

The real estate sector in Peru

Peru

Housing prices: deviated from their fundamental values?

Economic Analysis Hugo Perea Chief Economist – Peru [email protected] Francisco Grippa Principal Economist [email protected] Isaac Foinquinos Economist [email protected]

Housing prices in Metropolitan Lima have risen strongly over recent years, but they are supported by fundamental factors of supply and demand. However, the 8% average annual rate in real housing prices growth over recent years will be, according to our estimates, difficult to sustain in the future. An annual rate which does not exceed 5% would be more in line with market fundamentals.

The mechanisms that amplified recent real estate crises in some other countries are not present in Peru. This suggests that a strong downward correction in market prices would at present have a relatively limited impact at a macroeconomic level.

Periods of rapid growth in housing prices are not sufficient to justify the implementation of policy measures. This is because it is very difficult to

identify whether rising prices are due to fundamental factors or speculation. Hence, there is a risk of overreaction. However, in an uncertain environment, preventive action may be the correct one.

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Lima, September 10, 2012

Housing prices in Lima: evidence does not suggest a significant deviation from fundamentals The swift growth in housing prices in the metropolitan area of Lima has been attracting the attention of authorities and analysts alike. Concerns relate to the possibility that these prices may be above the equilibrium level suggested by their structural determinants. If this were the case, property prices would be reflecting a speculative behaviour. As a result, their levels would not be sustainable over time and could be subject to a sudden major downward correction. This concern is obviously greater if we extrapolate the negative impact on economic activity, employment, and welfare generated from the bursting of the real estate bubbles in the United States and Europe in the last five years. Evidence from abroad shows that such deviations in real-estate prices above those suggested by market fundamentals have usually occurred in environments featuring a prolonged extremely lax monetary policy, or major capital inflows. Abundant liquidity and low interest rates fed credit growth in an environment where banking regulation and supervision were poor. Credit was channeled into a variety of assets including real estate. Real-estate prices then began an upward trend. This trend later found additional support in an incorrect estimate of the future of the factors that were boosting the trend and their impact on it. Market participants therefore took on high risks and leverage from the financial system. This led to the creation of a bubble in the real-estate market. When the weakness of factors supporting price increases eventually became clear, they corrected downwards. The bubble burst. Because of the importance that the real-estate sector had acquired in the economy, and its close links to the financial system, economic activity slowed significantly, or even contracted for a number of years, with the negative effects that this implies on job creation and household income. Is there a bubble growing in the Peruvian real estate market? Are we now faced with the risk that in the future real-estate prices may correct downwards abruptly and substantially, affecting output and employment? To examine whether housing prices in Lima are out of line with their fundamental values, this report analyzes (i) what their movements have been over recent years; (ii) the changes in the fundamental factors of supply and demand that determine these prices; and (iii) the results of a statistical exercise we have used to estimate the equilibrium value, which we compare with observed prices.

Prices have risen quickly, but they have only recovered to their past levels, while they continue to be among the lowest in Latin America Evidence from abroad gives various examples of periods of a real-estate bubble. Chart 1 shows four of them: Japan, Ireland, the United States and Spain. These are some of the most recent. In three of the cases, the average price rise in real terms during the period that generated the bubble was 8% per year (4% per year in Japan). This upward trend extended over 10 to 15 years. As a result, prices doubled, or tripled in the case of Ireland. When the real-estate bubble burst, the downward price correction also took a few years. During this period costs were accumulated in terms of lower economic activity and employment. The rate at which housing prices in Lima have grown since 2006 is 8% in real terms. In other words, it is comparable with situations in which a bubble was created. This supports grounds for concern on the part of authorities and analysts. However, if the analysis is carried out from a broader time perspective the outlook is somewhat different. It shows that what has in fact occurred in recent years is a recovery of prices following a fall in the first half of the last decade. This process has not yet concluded (see Chart 2).

REFER TO IMPORTANT DISCLOSURES ON PAGE 13 OF THIS REPORT

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Chart 1

Chart 2

400

120

Annual behaviour of housing prices in different countries (in real terms, index)

Average housing prices in Lima in real terms (constant PEN, 1998=100) 110

300

100 90

200

80 100

70 60

0

50

1 4 7 10 13 16 19 22 25 28 31 34 37 40

40

Japan (1977=100) Ireland (1992=100)

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Spain (1997=100) USA (1997=100) Peru (2006=100)

Source: Bloomberg, Haver, CAPECO, BBVA Research

Source: CAPECO

Another point to highlight is that despite the swift rise in housing prices in Lima over recent years, with an accumulated increase of over 40% in real terms since 2006, in comparison with the rest of Latin America these price levels do not appear to be very high. For example, after correcting for differences in purchasing power, the average price per square meter in Lima is lower than in the other main cities of Latin America (see Chart 3). Chart 3

LatAm: price of a 100m2 home, adjusted for purchasing power (index Peru = 100) 293

206

204

174

172 125 100

Argentina

Brazil

Panama

Mexico

Colombia

Chile

Peru

Source: CAPECO, IMF, Global Property Guide

Lastly, it is important to point out that in some districts of the Peruvian capital city, above all in those with middle-income residents, the rise in housing prices over the last five years has been more pronounced, at an annual average of 12% in real terms. However, even here it can be seen that these prices have basically recovered the levels of the 1990s. Since 2000, for example, the accumulated increase to date in the districts in which prices increased most has been 33%. Other Peruvian assets, such as shares of publicly listed companies, have gained substantially more over the same period (see Chart 4).


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Chart 4

Selected Peruvian asset prices (in real terms, 2000 = 100) 1800 1600 1400 1200 1000 800 600 400 200 0

1229

Housing prices*

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

133

Lima General Stock Exchange Index

* Prices in districts that recorded the biggest price rises over the period. Source: BCRP

To sum up, if we compare housing price movements in Lima with real estate bubbles in other countries, it is true that they show some similarity to the initial phases of these processes. However, an analysis from a broader perspective indicates that what has occurred is mainly a price recovery to previous levels; and this recovery has actually been less pronounced than in other Peruvian assets. In addition, the levels reached are still relatively low in terms of the region.

The trend for rising prices is basically supported by demand fundamentals... On the demand side, the increase in household purchasing power has been a factor that has boosted the real-estate market. There has been a sustained increase in employment over recent years (see Chart 5), even during the international crisis. Since 2006 jobs have been created at an average rate of 5.5% per year. And these jobs are of better quality. Over the last five years, the adequate labor force has increased by 14 percentage points to around 53% of the total. In these conditions, the household income trend has been very positive, with a per capita GDP that in purchasing-parity terms has increased at an average rate of over 7% per year in the last five years. As a result, the middle class has grown. What is more, its income has become more stable and predictable, not only because the quality of jobs is greater, but also because the resistance of Peru's economy to negative events and its capacity for response suggest that fluctuations in output (and income) can be mitigated in the future. To sum up, a swift and lasting increase in purchasing power has led to the purchase of durable goods. In this context, effective demand for housing, which includes all those households who are interested in acquiring a property and have the resources to access a mortgage loan1, has increased steadily (see Chart 6), supporting the rise in property prices.

1: In rigorous terms, effective demand for housing includes households that are interested in buying a home in the property market in the zone, have sufficient resources to pay an initial deposit and the income necessary to make the monthly loan repayments, in accordance with current market regulations for the long-term finance of homes in the banking system and in the institutions that operate with different resources and systems. This estimate of effective demand takes into account that the household's capacity for final payment corresponds to its socioeconomic level, which is determined by the current place of residence.


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Chart 5

Chart 6

Employment and National disposable income in real terms (index 2006=100)

Effective demand for homes (thousands of homes) 450 140

400

130

350 300

100 2006

2007

2008

2009

2010

250

2011

Urban employment Domestic disposable income

200

2006 2007 2008 2009 2010 2011

Source: BCRP

Source: CAPECO

The population's increased income and its positive impact on effective demand for housing is also included in the affordability ratio. This ratio measures how long an average household would take to generate the income that covers the price of a home of 100 square meters. The effort that has to be made in Lima is among the lowest in the region (see Chart 7). This suggests that housing prices in this city are more in line with the purchasing power of those looking for a home. Chart 7

LatAm: affordability ratio (index Peru=100)* 176

169

168 146

120 100 73

Brazil

Colombia

Argentina

Panama

Mexico

Peru

Chile

* Is the ratio between the house price of 100 square meters to GDP per capita Source: BBVA Research Peru, BCRP, Global Property Guide and IMF

Another factor on the demand side that supports increased housing prices is the demographic composition change. Segments of the population with ages of more than 25 years, which are those that may potentially want housing, have increased their relative proportion. This trend will continue in the coming years (see Chart 8). In other words, more people will be looking for homes, not only because of the increase in population (the annual growth rate is 1%), but also because the proportion of people who are looking for homes will be greater. And these families will have increased resources to access housing.


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Chart 8

Population pyramid (millions of people, by age group) 80 and over 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4

Men

Women Potential housing demand

2.0

1.5

1.0

0.5

0.0

2025

0.5

1.0

1.5

2.0

2010

Source: INEI

... and by supply fundamentals On the supply side, the rising trend in housing prices also includes increased construction costs, i.e. wages, materials and, in particular, land. The availability of adequate land is reducing, either because there is no room in the city areas with higher purchasing power, or because in outlying areas the land is not prepared or does not have access to public services (water, sewerage, and electricity). Excluding the cost of land, the rise in property prices over the last five years would have nearly doubled the rise in wage and material costs. However, taking into account the cost of land, this difference is reduced to a notable extent (see Chart 9)): in this case the price increased around 25% more than the total cost of housing. This figure is more reasonable, and may find support in the demand factors mentioned earlier. Chart 9

Housing price / cost (index 1Q07 = 100) 188

124

1Q12

4Q11

3Q-11

2Q11

1Q11

4Q10

3Q-10

2Q10

1Q10

4Q09

3Q-09

2Q09

1Q09

4Q08

3Q-08

2Q08

1Q08

4Q07

3Q-07

2Q07

1Q07

100

Price/ construction cost* Price / Total home cost (includes cost of land) * The cost of construction only includes materials and wages, not land. Source: BCRP

The supplied quantity of houses has been quite strong, with an average annual growth over the last five years of 5.5%. However, this rate is not sufficient to meet the increasing effective demand. The neighboring countries of Chile and Colombia saw around 4 homes constructed


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per 1,000 inhabitants, twice the figure in Peru. As a result, the unsatisfied demand2, which was already significant, has increased still further (see Chart 10), and this has supported prices. Chart 10

Unsatisfied demand*: total and by USD thousands value of home (thousands of homes) 450 400

350 300

250 200 150 100 50

0 Total 2005

60

2011

* Unsatisfied demand is defined as excess effective demand over the immediate supply of homes. Source: CAPECO

Empirical evidence suggests that current prices are not far from their fundamental values Beyond a qualitative discussion about the support that supply and demand factors are providing for prices, we have tried to quantify this support to obtain an equilibrium price and evaluate whether it is similar to that observed in the market. One indicator usually used for this assessment is the price-earnings ratio (PER), which is the ratio between the price of the home and income from its annual rental. The PER thus reflects the number of years that a property would have to be rented to recover its value. According to the Global Property Guide, if the PER is at levels of under 12.5, prices are undervalued, while if it is above 25.0, prices are overvalued. Levels between 12.5 and 25.0 suggest that prices are close to equilibrium and are supported by fundamental market factors. Data published by the Central Bank of Peru suggest that in Lima overall (see Chart 11), and in most districts in the city, the PER has been rising in recent years. However, in all cases the PER is under 19, so that it remains comfortably within its normal levels. Housing prices are thus at around their equilibrium level.

2. Unsatisfied demand is defined as excess of effective demand. It includes those families that are interested in acquiring a home and have the resources to take on a mortgage loan, compared with the immediate supply of homes.


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Chart 11

PER in Lima and in selected districts 18.4 17.4 15.8 14.4 13.3

10.9 2Q10

3Q10

4Q10

Lima (promedio)

1Q11

2Q11

San Isidro

3Q11

4Q11

1Q12

Miraflores

Source: BCRP, BBVA Research Peru

Another way of calculating the equilibrium price of housing is through an econometric model that considers the fundamentals of supply and demand in the real estate market. In the model we have estimated (see the Appendix for details), the underlying factors are real income growth (using GDP growth as a proxy), supplied quantity of homes, and construction costs. However, the model does not include prospective variables such as expected future income (permanent income) and expected returns on investment in housing. It may be that in the absence of these kinds of variables and given the limited nature of our sample there is some bias in the estimated equilibrium prices. Our results are therefore of referential value. In any event, they indicate that currently prices are supported mainly by fundamental factors (see Chart 12). They are in line with the conclusions of a recent study by the International Monetary Fund3 for a sample of Latin American countries including Peru, which suggests that there are few signs of misalignments in the mortgage and real estate sectors, and that housing prices in most markets are close to their equilibrium levels. Chart 12

Price per m2 in Metropolitan Lima and Callao areas (USD) 1,700

1,500

Forecast

1,300

1,100 900 700 500

Observed

Equilibrium

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

300

Standard deviation

Source: CAPECO and BBVA Research Peru

3: Cubeddu, Tovar and Tsounta (2012), “Latin America: vulnerabilities under construction?”, IMF WP 2012/193, International Monetary Fund


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We have gone a little further and projected the equilibrium price, based on some assumptions that are consistent with our medium-term forecasts. Once this has been done, we have used the standard deviation of the estimate to construct an interval of confidence. This suggests that an average increase in housing prices of not more than 5% per year (in real terms) in the medium term is consistent with market fundamentals. The moderation of the rate at which this variable could go up compared with the figure recorded in recent years (8% per year) is due to the fact that prices have already nearly recovered from the slump they recorded in the first half of the last decade. In some districts price rises have even exceeded those at the end of the 1990s, supported by the supply and demand factors described above. In addition, the expansion of economic activity will moderate somewhat in the medium term. Naturally, if there are changes in the above assumptions, our estimates will be affected. Specifically, stronger GDP growth would result in higher equilibrium prices. In contrast, if housing supply grows at a faster pace, the result will be lower equilibrium prices. The results of our model are particularly sensitive to GDP as this is the variable with the greatest explanatory power.

Mortgage finance has boosted the real estate market, but it is still relatively small in size Evidence shows that a sharp rise in housing prices not aligned with market fundamentals is usually supported by mortgage finance. In Peru, loans granted by the financial system to the private sector for the purchase of housing grew by around 170% over the last five years, i.e. at an average annual rate of 22%. This rate of expansion suggests that lending could be supporting a misalignment between housing prices and their fundamental value. However, the total balance of these loans is currently equivalent to 4.5% of GDP. In Latin America, this level is comparable to that in Colombia (which has a similar income per capita) and Brazil, and far lower than Chile and Mexico. Its limited size becomes clear if we compare it to that of countries that experienced major deviations of housing prices with respect to their fundamental values (see Chart 13). Even if we add finance for developers to these loans, the level is still under 7% of GDP. The limited importance that mortgage loans have at present as a proportion of output implies two things. First, that this type of finance only reaches a small part of the population. Its strong growth is therefore natural, and finds additional support in the higher income of the population. Together with the fact that the bulk of these loans finance the acquisition of first homes (according to one of the biggest financial institutions in the country, 90% of the lending is to finance the borrower's first home), this reduces the probability of speculation on the part of people requesting mortgage loans. Second, if there is a real-estate bubble and it explodes, its negative impacts would be limited at an aggregate level. Chart 13

Mortgage loans (% GDP) 76

70

58 45 36 25

19

14

Ireland 1990

Japan

2006

Source: IMF, World Economic Outlook, April 2008


Spain

USA

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It is worth mentioning that the rise in mortgage lending has been similar to that of corporate lending and consumer finance (around 20% as an annual average in each case). This reduces the probability that the greater demand for housing loans has been sustained mainly by speculative factors, as a similar effect would have to be produced in corporate lending and consumer finance, which does not make much sense. It is more reasonable that the greater demand for the three types of finance is supported by factors such as the growing purchasing power of the population, the steady increase in the level of formality in the economy, and the reduction in the level of monthly repayments (due to lower interest rates and the extension of loan periods).

We consider that if there is a downward correction in housing prices, the macroeconomic impact would be limited Although there is insufficient evidence to state that housing prices in Lima are out of line with their fundamental factors, history shows us that it has usually been difficult to identify such misalignments in advance. It is therefore also probably worth asking what would happen if the trend in real estate prices reversed. Would the impact at an aggregate level be as severe as observed in other countries? We consider that in this scenario the negative effects on the economy would be relatively limited, as the amplification mechanisms present in recent real-estate crises in other countries are not evident in Peru. First, some of these recent experiences included a process of financial innovation and sophistication that encouraged the leveraging of households, companies and banks. This helped feed the trend of rising real-estate prices and made the subsequent adjustment more painful. This has not been the case in Peru. For example, it is rare for Peruvian families to use a home as collateral for other financial transactions. Although a downward correction of the property's price would harm their equity, it would thus not cause them to default on payments or restrict their consumption; at the aggregate level, the negative impact on demand would therefore be limited. Second, there are aspects of the institutional framework in Peru that reduce the negative impact of a potential downward correction in real-estate prices. For example, in some countries that have experienced a bubble, borrowers have an incentive to allow the bank to foreclose on their property if its price drops below the value of the loan. This is because their obligation to the bank ends at that point. The financial institution thus suffers an equity loss that then reduces its capacity to lend. At the aggregate level, this negatively affects expenditure. This is not the case in Peru. Here, regardless of whether the home was foreclosed or not, the obligation to the financial system remains (amounting to the difference between the value of the loan and that of the property). Thus the financial institution does not suffer losses beyond those of the provisions it will have to make. Finally, the financial system is less exposed to the real-estate sector in Peru than in other countries that have experienced bubbles in this market. The sector accounts for 20% of the total balance of bank loans in Peru, including loans to project developers. In Spain, for example, exposure was much bigger, at 60%. Given this, a downward revision of prices would be easier to digest by the Peruvian banking system. Finally, it is important to acknowledge that regardless of whether the macroeconomic impacts of a possible slump in real-estate prices are limited, it is desirable to monitor closely what is happening in housing market because any sudden and abrupt price correction would affect the strength of construction (a key sector), employment and credit supply.


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Does the increase in property prices justify the implementation of preventive measures? Concerns about a possible speculative bubble in the real-estate market are due to the fact that prices do not respond to fundamental factors. They therefore represent an unsustainable increase that at some time will reverse and have a negative effect on the economy, such as a recession or undesired distribution of wealth. However, periods of rapid growth in real-estate prices, or prices of any other asset in general, are not sufficient to justify the implementation of policy measures. This is because it is very difficult to identify whether the price rise is due to fundamental factors or is speculative in nature, as it reflects purchase and sale decisions that incorporate expectations regarding the future. The risk here is that if there is no bubble, the authorities may end up overreacting. This would inhibit potentially sustainable demand and delay the closure of the large housing deficit. On the monetary policy side, it is worth asking whether central banks should try to stabilize asset prices, in particular those of property. If it is determined that these prices do not affect compliance with the inflation target, in principle the answer would be negative. However, the central bank could have an additional objective of ensuring financial stability in order to prevent crises that extend output fluctuations by weakening the financial position of households, banks and companies, and thus notably affect the welfare of society as a whole. In this case, monetary policy would have a role in preventing the appearance of a bubble and in handling the situation when it bursts. In the context of the recent financial crises, a debate is currently raging about how to incorporate the objective of financial stability within the institutional framework of central banks. One proposal has been to extend their mandate to include this objective explicitly; another has been to consider changes in the financial markets as only part of their balance of risks with respect to inflation and economic activity. In recent years some Asian countries that have recorded major increases in housing prices have implemented preventive measures to contain the risks of property bubbles (see Table 1). Table 1

Macroprudential housing measures in selected countries Loan to Value (LTV) limit Luxury homes.

Tax treatment Increase in tax rate for sales of residences.

China

Applied to first homes above a certain size, and to second homes.

Tax on resale of recently purchased homes.

Korea

Depends on the city.

Hong Kong

Source: IMF

Among the most commonly used measures are imposing a maximum limit on the ratio between the loan granted and the value of the home, known as the loan-to-value (LTV) ratio. However, empirical evidence is not conclusive in terms of the role of the level of this ratio in real-estate crises, or the effectiveness of the limits set in maintaining financial stability. The IMF's Global Financial Stability Report in April 2011 states that "Maximum LTV ratios do not help explain crisis outcomes or the pre-crisis boom... neither [do they] explain the depth of the house price downturn... Furthermore, threshold effects of high LTV ratios (for instance, above 80%) were found to be important for the outcome on financial sustainability." Although the IMF does not rule out the use of limits to the LTV ratio (and also to the debt/income ratio) as a prudential measure, it recommends using them with caution. To sum up, there is no clear room for implementing measures when significant increases in housing prices are observed, because it is difficult to identify whether the process reflects fundamental or speculative factors. This means that there is a risk of overreaction. However, in an environment of uncertainty, preventive action may be the best response to contain the possible accumulation of any financial imbalances that could have severe ex-post negative impacts on the economy.


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Appendix The estimate of the equilibrium price (p) has been carried out based on an econometric cointegration model similar to that used by Leung, Chow and Han (2008), which aims to explain housing prices in real terms:

pt

α

k

βPBIt i

Δpt

α ( pt

1

βi ΔPBIt k

pp* 1 )

k

δOferta t j

n j 1

φ j Δpt

n j

δ j ΔOferta t

εt

k

β j ΔPBIt

n j

j 1

γ j ΔIPMCt

j

εt

j 1

The fundamentals of market supply and demand are included through three variables: growth in economic activity (GDP); the available supply of housing (Supply, in square meters) and construction costs approximated by the index of construction material prices (IPMC). The estimate constructed presents the expected signs for the coefficients associated with supply and demand factors in the housing market. Price-income elasticity is around 1.4, while the coefficient of correction is 0.9, which suggests that observed prices have tended to correct relatively quickly toward their equilibrium levels (the levels that are sustained by market fundamentals). The results show that currently the observed price is similar to the equilibrium price (see Chart 11). This supports the previous conclusion that the current price is at reasonable levels, despite the rising trend recorded in recent years. The projection has used our GDP growth forecasts, and an increase in supply and in the costs of construction that are similar to the average rate for the last five years. The lack of a broader sample of data certainly limits the reliability of the inferences, but if we consider the standard historical deviation the model suggests that an average growth of not more than 10% in the medium term is coherent with market fundamentals.

References BBVA Research (2010, 2011). China Real Estate Watch. International Monetary Fund (2003). When Bubbles Burst, World Economic Outlook, Spring. McCarthy and Peach (2004), Are home prices the next "bubble"? Economic Policy Review, Federal Reserve Bank of New York. Leung, Chow and Han (2008) Long-term and short term determinants of property prices in Hong Kong, Hong Kong Monetary Authority Poterba, J. M. 1984. “Tax Subsidies to Owner-Occupied Housing: An Asset-Market Approach.” Quarterly Journal of Economics 98, No. 4 (November): 731-52. Jorgenson, D. W. 1963. “Capital Theory and Investment Behavior.”American Economic Review 53, No. 2 (May): 247-59.


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