From Hot and Cold Housing Markets: International Evidence
Jose Ceron, Omega Capital and Javier Suarez CEMFI, CEPR and ECGI
The studies by Englund and Ioannides (1997), Capozza et al. (2002), Tsatsaronis and Zhu (2003), and Borio and Mcguire (2004), among others, report significant correlations between real housing price growth and variables such as real GDP, unemployment, interest rates, and inflation, which suggests that property prices might feature a cyclical pattern, if only because of the convolution of the cyclicality of the other variables. Finally, swings in housing prices have been shown to be positively correlated with the volume of transactions (Stein, 1995) and negatively correlated with average selling times (Krainer, 2001).
Sunday, July 15, 2007
Saturday, July 14, 2007
Monday, July 9, 2007
Construction and Housing in Ireland
Construction and Housing in Ireland
Published by the Stationery Office, Dublin, Ireland.
Overview
This report presents an overview of the Irish construction industry. The information is sourced from statistics compiled by the Central Statistics Office, from other producers of construction statistics and from administrative data sources. The report aims to present a comprehensive picture of the Irish construction industry and also includes some international comparisons.
• In 2005, it was estimated that the value of output in the construction industry was almost €32 billion. This compares to €17.6 billion in 2000.
• In 2005 construction was estimated to have accounted for 20% of Gross Domestic Product or 23% of Gross National Product.
• Residential construction output more than doubled from €9.5 billion in 2000 to €20.9 billion in 2005.
• Average hourly earnings in construction increased from €11.44 per hour in the second quarter of 2000 to €17.31 per hour in the same period of 2005.
• The average number of hours worked in construction has decreased from 45.6 hours per week in the second quarter of 2000 to 43.8 hours per week in the same period of 2005.
• Employment in construction has grown by 46%, increasing from 166,200 in the second quarter of 2000 to more than 242,400 in the same period of 2005.
• Approximately 1 in 8 people (12.6%) employed in Ireland work in construction. This is the highest ratio in the European Union.
• Over 86,000 dwelling units were completed in Ireland in 2005. This compares to less than 20,000 completed in 1990 and 50,000 in 2000.
• New dwellings were completed at a rate of 21 units per 1,000 of population in 2005; and added over 5% to existing housing stock.
• Close to half of the units completed in Ireland in 2004, the latest year for which data is available, were semi-detached houses. This compares to about 30% in 2000.
• In the April 2006 Census of Population, the CSO identified a total of 1.8 million private residences and communal establishments throughout the State. Of these, about 275,000 were vacant at the time of the Census.
• The average price of a new house in Ireland was just over €272,000 in 2005. A secondhand hand house cost on average more than €330,000.
• More than a third (34.3%) of all dwellings sold in 2005 cost in excess of €300,000.
• In 2000, the cost of servicing a 90% mortgage over 20 years to buy a new house (based on the average national price of a new house and prevailing interest rates) would have been €1,021. The equivalent for a new house purchased in 2005 was a monthly repayment of €1,395.
• The cost of building and construction materials increased by 24% between 2000 and 2005. By comparison average house prices increased by 64% over the same period.
• The total value of mortgage debt has increased from less than €33 billion in 2000 to almost €100 billion at the end of 2005. Mortgage debt increased by almost €22 billion in 2005.
• The average size of a new mortgage has almost doubled from €102,300 in 2000 to €200,000 in 2005.
• Variable rate mortgages represented 83% of total outstanding mortgage debt in 2005.
• In 2000, less than 5% of new mortgages were for more than €200,000 but almost half of mortgages taken out in 2005 (46.9%) exceeded this value.
• In 2005, planning permission was granted for the construction of 55,000 multi-development houses, 21,000 one-off housing units and 24,000 apartments.
• The average floor size for houses granted planning permission in a multi-unit development was 125m2. For one-off houses the average floor area was 214m2.
• The amount of zoned serviced land for residential construction has increased from 10,800 hectares (with a potential for over 263,300 units) in 2000 to almost 14,800 hectares (with a potential of almost 460,000 units) in 2005. The potential housing density of this available land increased from 24 units per hectare in 2000 to more than 31 units per hectare in 2005.
• The Dublin region accounted for 34% of total construction output in 2000 and for less than 28% in 2004.
• In the second quarter of 2005 there were over 242,000 workers in the construction sector. Of these, almost 53,000 lived in Dublin while 37,500 lived in the South-West.
• According to the DEHLG, the average price of a new house in Dublin was €386,000 in 2005. A new house in Galway cost €275,000 and in Cork €265,000.
• Almost one in every three dwelling units completed in 2004 were located in Dublin or the Mid-East region.
• Ireland's house completion rate in 2005 (21 units per 1,000 of population) was four times the average for other European countries.
• In Ireland 77% of homes are owner-occupied. Hungary, Spain, Slovakia and Norway had higher ownership rates. In contrast to this, 45% of German homes and 35% of homes in Switzerland are owner-occupied.
• Construction output per capita is highest in Ireland at approximately €7,600 in 2005. This is more than double the corresponding figure for the United Kingdom.
The value of output in the construction industry increased from under €18 billion in 2000 to an estimated level of just under €32 billion in 2005. This was an increase of 79% over the five years or an annual average of over 12% per annum. The largest annual percentage increase was in 2004 when output increased by almost 16%. Over the period 2000-2005 the volume of activity increased by 30%, when price changes are excluded.
The primary growth areas in the industry have been the residential sector followed by infrastructure development. The value of residential construction output has more than doubled from €9.5 billion in 2000 to just under €21 billion in 2005. In the same period, the value of non-residential output had decreased by approximately 10%. Total output in productive and social infrastructure increased by €3 billion or 70% between 2000 and 2005. The increase in residential construction accounted for over 80% of the total growth in the value of construction output between 2000 and 2005.
By the first quarter of 2006 the construction industry employed in excess of 250,000 people. Many of these work in small enterprises or are self-employed. The structure of the industry makes it difficult to conduct a full census of building and construction firms. The CSO's annual census only covers firms with 20 or more persons engaged. There were 376 such firms in Ireland in 1997 and this number had grown by more than 80% to a total of 682 enterprises in 2003, the latest year for which data are available. The number of persons engaged by these firms grew by more than 90% from just over 29,200 in 1997 to more than 56,600 in 2003. Total turnover has almost trebled in the same period from just over €3.6 billion to more than €10.3 billion. The average turnover of these firms increased from just over €9.6 million in 1997 to more than €15 million in 2003.
In the second quarter of 2005, construction workers earned an average of €17.31 per hour. This was 51% higher than in the same period of 2000. The highest paid occupational groups were foremen & supervisors (earning €21.76 per hour in 2005) and skilled operatives (€20.24 per hour). Unskilled and semi-skilled workers on adult rates earned €15.92 per hour and apprentices earned €11.63 per hour.
Looking at average weekly earnings, which depend on hours worked and hourly wages, employees in the construction sector earned €758 per week in the second quarter of 2005. This was €236 per week higher than in 2000. Weekly earnings in construction were higher than in industry (€578 per week) but lower than in the public sector (€838 per week, excluding health). Between 2000 and 2005, average weekly earnings in construction increased by 45%, while weekly earnings in the public sector grew by 39% and in industry by 33%.
In the second quarter of 2005, there were 15.5 million people employed in construction in the European Union. As mentioned earlier, the construction sector accounted for one in every eight jobs (12.6%) in Ireland. This was the highest percentage in the EU. Across all 25 Member States, 7.9% of the workforce was involved in construction. In Spain, 12.4% of employment was in the construction sector, in Cyprus 11.8% and in Portugal 10.7%.
Construction as share of total employment 2005 - Q2
Much of the demand for labour in the construction sector in Ireland has been met by workers from the Accession States which joined the EU in May 2004. Tentative estimates from the QNHS indicate that there were 25,300 non-Irish nationals working in the construction sector in the fourth quarter of 2005. Of these, 5,000 were from the United Kingdom, 15,200 from the EU Accession States and 5,100 from other countries. About a quarter of persons from the EU Accession States working in Ireland were employed in the construction sector at the end of 2005. These estimates of the workforce by nationality are tentative, based on sample survey estimates which are subject to revision in the light of more comprehensive statistics which will be compiled from the 2006 Census of Population.
Ireland has a high level of house building relative to the size of its population. In 1990, just 5.6 houses and apartments were completed per 1,000 of population; by 2005 this ratio had increased to 20.9 per 1,000. Chapter 11 presents corresponding data for other European countries.
The Census of Population is one of the most important sources of information on households and on the stock of housing. During the course of the April 2006 census, the CSO enumerators identified a total of 1.8 million private residences and communal establishments throughout the State. They delivered blank census questionnaires to 1.5 million dwellings that were expected to be occupied on census night. Approximately 275,000 residences were vacant at the time of the census while in the remaining cases the household was either enumerated elsewhere or temporarily absent from the State.
The DEHLG also produces an estimate of the total housing stock in Ireland. The estimate which is derived by annual updating of the Census of Population figures, indicated that there were about 1.69 million dwelling units in the State in 2005. This figure is subject to revision by DEHLG in light of the April 2006 census figures.
In 2000, the average price of a new house was €166,200. By 2005, this had increased by 64% to €272,000. Over the same period, secondhand house prices increased by 74%, from €190,200 in 2000 to €330,300 in 2005. Between 2004 and 2005, new house prices increased by 11.1% and secondhand prices increased by 12%.
With the exception of 2001, new apartment prices have increased steadily in the past number of years. The average price of a new apartment in 2000 was €205,700. The corresponding figure in 2005 was €293,200, an increase of 43%. The average price of a secondhand apartment grew by 68% in the five years, from €196,900 in 2000 to €330,800 in 2005.
Taking the average new house price of €166,155 in 2000, a “typical” 90% mortgage over 20 years would have resulted in a monthly repayment of €1,021. This is an illustrative repayment figure generated by the CSO. Between 2000 and 2005, the average price of a new house increased to €272,034 while the average interest rate for the year changed from 5.4% to 3.3%. The combined effect of these changes was that a 90% mortgage on an average new house purchased in 2005 would have required a monthly repayment of €1,395. The corresponding monthly repayment figures on a 35-year 90% mortgage were €794 for a new house purchased in 2000 and €984 for an average new house bought in 2005.
The Wholesale Price Index (WPI) includes a sub-index measuring general price trends for building and construction materials. In addition the DEHLG also produces an index of house building costs. The WPI shows that the cost for all building materials has increased by 24% since 2000. Much of this increase took place in 2004 and 2005. Structural steel and reinforcing metal have shown a 56% increase between 2000 and 2005; while ready mixed mortar and concrete increased by 12% over the period. The house building cost index rose by almost 33% over the same five-year period while house prices increased by 64%.
The DEHLG affordability index aims to measure the percentage of net household income typically used to service a mortgage. The index is calculated on the basis of the monthly mortgage payment for a 90% loan on an average new house over twenty years, as a percentage of the net income of a two-earner household on average wages. A higher percentage indicates that home ownership is less affordable. In 1994, mortgage payments calculated on this basis represented 21% of monthly income for a two-earner household. In Dublin, mortgage payments represented 23% of income. By 2005, the national affordability indicator had increased to 27% of net household income. In Dublin, it had increased to 35% of income.
Published by the Stationery Office, Dublin, Ireland.
Overview
This report presents an overview of the Irish construction industry. The information is sourced from statistics compiled by the Central Statistics Office, from other producers of construction statistics and from administrative data sources. The report aims to present a comprehensive picture of the Irish construction industry and also includes some international comparisons.
• In 2005, it was estimated that the value of output in the construction industry was almost €32 billion. This compares to €17.6 billion in 2000.
• In 2005 construction was estimated to have accounted for 20% of Gross Domestic Product or 23% of Gross National Product.
• Residential construction output more than doubled from €9.5 billion in 2000 to €20.9 billion in 2005.
• Average hourly earnings in construction increased from €11.44 per hour in the second quarter of 2000 to €17.31 per hour in the same period of 2005.
• The average number of hours worked in construction has decreased from 45.6 hours per week in the second quarter of 2000 to 43.8 hours per week in the same period of 2005.
• Employment in construction has grown by 46%, increasing from 166,200 in the second quarter of 2000 to more than 242,400 in the same period of 2005.
• Approximately 1 in 8 people (12.6%) employed in Ireland work in construction. This is the highest ratio in the European Union.
• Over 86,000 dwelling units were completed in Ireland in 2005. This compares to less than 20,000 completed in 1990 and 50,000 in 2000.
• New dwellings were completed at a rate of 21 units per 1,000 of population in 2005; and added over 5% to existing housing stock.
• Close to half of the units completed in Ireland in 2004, the latest year for which data is available, were semi-detached houses. This compares to about 30% in 2000.
• In the April 2006 Census of Population, the CSO identified a total of 1.8 million private residences and communal establishments throughout the State. Of these, about 275,000 were vacant at the time of the Census.
• The average price of a new house in Ireland was just over €272,000 in 2005. A secondhand hand house cost on average more than €330,000.
• More than a third (34.3%) of all dwellings sold in 2005 cost in excess of €300,000.
• In 2000, the cost of servicing a 90% mortgage over 20 years to buy a new house (based on the average national price of a new house and prevailing interest rates) would have been €1,021. The equivalent for a new house purchased in 2005 was a monthly repayment of €1,395.
• The cost of building and construction materials increased by 24% between 2000 and 2005. By comparison average house prices increased by 64% over the same period.
• The total value of mortgage debt has increased from less than €33 billion in 2000 to almost €100 billion at the end of 2005. Mortgage debt increased by almost €22 billion in 2005.
• The average size of a new mortgage has almost doubled from €102,300 in 2000 to €200,000 in 2005.
• Variable rate mortgages represented 83% of total outstanding mortgage debt in 2005.
• In 2000, less than 5% of new mortgages were for more than €200,000 but almost half of mortgages taken out in 2005 (46.9%) exceeded this value.
• In 2005, planning permission was granted for the construction of 55,000 multi-development houses, 21,000 one-off housing units and 24,000 apartments.
• The average floor size for houses granted planning permission in a multi-unit development was 125m2. For one-off houses the average floor area was 214m2.
• The amount of zoned serviced land for residential construction has increased from 10,800 hectares (with a potential for over 263,300 units) in 2000 to almost 14,800 hectares (with a potential of almost 460,000 units) in 2005. The potential housing density of this available land increased from 24 units per hectare in 2000 to more than 31 units per hectare in 2005.
• The Dublin region accounted for 34% of total construction output in 2000 and for less than 28% in 2004.
• In the second quarter of 2005 there were over 242,000 workers in the construction sector. Of these, almost 53,000 lived in Dublin while 37,500 lived in the South-West.
• According to the DEHLG, the average price of a new house in Dublin was €386,000 in 2005. A new house in Galway cost €275,000 and in Cork €265,000.
• Almost one in every three dwelling units completed in 2004 were located in Dublin or the Mid-East region.
• Ireland's house completion rate in 2005 (21 units per 1,000 of population) was four times the average for other European countries.
• In Ireland 77% of homes are owner-occupied. Hungary, Spain, Slovakia and Norway had higher ownership rates. In contrast to this, 45% of German homes and 35% of homes in Switzerland are owner-occupied.
• Construction output per capita is highest in Ireland at approximately €7,600 in 2005. This is more than double the corresponding figure for the United Kingdom.
The value of output in the construction industry increased from under €18 billion in 2000 to an estimated level of just under €32 billion in 2005. This was an increase of 79% over the five years or an annual average of over 12% per annum. The largest annual percentage increase was in 2004 when output increased by almost 16%. Over the period 2000-2005 the volume of activity increased by 30%, when price changes are excluded.
The primary growth areas in the industry have been the residential sector followed by infrastructure development. The value of residential construction output has more than doubled from €9.5 billion in 2000 to just under €21 billion in 2005. In the same period, the value of non-residential output had decreased by approximately 10%. Total output in productive and social infrastructure increased by €3 billion or 70% between 2000 and 2005. The increase in residential construction accounted for over 80% of the total growth in the value of construction output between 2000 and 2005.
By the first quarter of 2006 the construction industry employed in excess of 250,000 people. Many of these work in small enterprises or are self-employed. The structure of the industry makes it difficult to conduct a full census of building and construction firms. The CSO's annual census only covers firms with 20 or more persons engaged. There were 376 such firms in Ireland in 1997 and this number had grown by more than 80% to a total of 682 enterprises in 2003, the latest year for which data are available. The number of persons engaged by these firms grew by more than 90% from just over 29,200 in 1997 to more than 56,600 in 2003. Total turnover has almost trebled in the same period from just over €3.6 billion to more than €10.3 billion. The average turnover of these firms increased from just over €9.6 million in 1997 to more than €15 million in 2003.
In the second quarter of 2005, construction workers earned an average of €17.31 per hour. This was 51% higher than in the same period of 2000. The highest paid occupational groups were foremen & supervisors (earning €21.76 per hour in 2005) and skilled operatives (€20.24 per hour). Unskilled and semi-skilled workers on adult rates earned €15.92 per hour and apprentices earned €11.63 per hour.
Looking at average weekly earnings, which depend on hours worked and hourly wages, employees in the construction sector earned €758 per week in the second quarter of 2005. This was €236 per week higher than in 2000. Weekly earnings in construction were higher than in industry (€578 per week) but lower than in the public sector (€838 per week, excluding health). Between 2000 and 2005, average weekly earnings in construction increased by 45%, while weekly earnings in the public sector grew by 39% and in industry by 33%.
In the second quarter of 2005, there were 15.5 million people employed in construction in the European Union. As mentioned earlier, the construction sector accounted for one in every eight jobs (12.6%) in Ireland. This was the highest percentage in the EU. Across all 25 Member States, 7.9% of the workforce was involved in construction. In Spain, 12.4% of employment was in the construction sector, in Cyprus 11.8% and in Portugal 10.7%.
Construction as share of total employment 2005 - Q2
Much of the demand for labour in the construction sector in Ireland has been met by workers from the Accession States which joined the EU in May 2004. Tentative estimates from the QNHS indicate that there were 25,300 non-Irish nationals working in the construction sector in the fourth quarter of 2005. Of these, 5,000 were from the United Kingdom, 15,200 from the EU Accession States and 5,100 from other countries. About a quarter of persons from the EU Accession States working in Ireland were employed in the construction sector at the end of 2005. These estimates of the workforce by nationality are tentative, based on sample survey estimates which are subject to revision in the light of more comprehensive statistics which will be compiled from the 2006 Census of Population.
Ireland has a high level of house building relative to the size of its population. In 1990, just 5.6 houses and apartments were completed per 1,000 of population; by 2005 this ratio had increased to 20.9 per 1,000. Chapter 11 presents corresponding data for other European countries.
The Census of Population is one of the most important sources of information on households and on the stock of housing. During the course of the April 2006 census, the CSO enumerators identified a total of 1.8 million private residences and communal establishments throughout the State. They delivered blank census questionnaires to 1.5 million dwellings that were expected to be occupied on census night. Approximately 275,000 residences were vacant at the time of the census while in the remaining cases the household was either enumerated elsewhere or temporarily absent from the State.
The DEHLG also produces an estimate of the total housing stock in Ireland. The estimate which is derived by annual updating of the Census of Population figures, indicated that there were about 1.69 million dwelling units in the State in 2005. This figure is subject to revision by DEHLG in light of the April 2006 census figures.
In 2000, the average price of a new house was €166,200. By 2005, this had increased by 64% to €272,000. Over the same period, secondhand house prices increased by 74%, from €190,200 in 2000 to €330,300 in 2005. Between 2004 and 2005, new house prices increased by 11.1% and secondhand prices increased by 12%.
With the exception of 2001, new apartment prices have increased steadily in the past number of years. The average price of a new apartment in 2000 was €205,700. The corresponding figure in 2005 was €293,200, an increase of 43%. The average price of a secondhand apartment grew by 68% in the five years, from €196,900 in 2000 to €330,800 in 2005.
Taking the average new house price of €166,155 in 2000, a “typical” 90% mortgage over 20 years would have resulted in a monthly repayment of €1,021. This is an illustrative repayment figure generated by the CSO. Between 2000 and 2005, the average price of a new house increased to €272,034 while the average interest rate for the year changed from 5.4% to 3.3%. The combined effect of these changes was that a 90% mortgage on an average new house purchased in 2005 would have required a monthly repayment of €1,395. The corresponding monthly repayment figures on a 35-year 90% mortgage were €794 for a new house purchased in 2000 and €984 for an average new house bought in 2005.
The Wholesale Price Index (WPI) includes a sub-index measuring general price trends for building and construction materials. In addition the DEHLG also produces an index of house building costs. The WPI shows that the cost for all building materials has increased by 24% since 2000. Much of this increase took place in 2004 and 2005. Structural steel and reinforcing metal have shown a 56% increase between 2000 and 2005; while ready mixed mortar and concrete increased by 12% over the period. The house building cost index rose by almost 33% over the same five-year period while house prices increased by 64%.
The DEHLG affordability index aims to measure the percentage of net household income typically used to service a mortgage. The index is calculated on the basis of the monthly mortgage payment for a 90% loan on an average new house over twenty years, as a percentage of the net income of a two-earner household on average wages. A higher percentage indicates that home ownership is less affordable. In 1994, mortgage payments calculated on this basis represented 21% of monthly income for a two-earner household. In Dublin, mortgage payments represented 23% of income. By 2005, the national affordability indicator had increased to 27% of net household income. In Dublin, it had increased to 35% of income.
Saturday, July 7, 2007
House Prices, Interest Rates and Macroeconomic Fluctuations: International Evidence Christopher Otrok and Marco E. Terrones
This paper studies the dynamic properties of international house prices, stock prices, interest rates and macroeconomic aggregates in industrial countries. While the dynamics of stock market returns and interest rates have been studied previously, we use a new dataset to gain insight into both the comovement of house price across industrial countries and the relationship between the fluctuations of house price with the fluctuations of financial asset returns and macroeconomic aggregates. Despite the fact that housing is the quintessential nontradable asset, we find a large degree of synchronization or comovement in the growth rate of real house prices in industrialized countries. We then show that much of this comovement can be related to a common dynamic component in interest rates across these countries. While we confirm the existence of a great degree of comovement in macroeconomic aggregates (namely, real output, consumption, and residential investment), we find little evidence that these aggregates are important sources of house price fluctuations. Instead, we find that house prices have an effect on macroeconomic aggregates. Given the important role that interest rates play for asset prices and macroeconomic fluctuations in industrial countries, we examine the role of monetary policy shocks--both domestic and global--in driving movement in these variables using an identified VAR augmented with our latent factors. We find evidence of a strong but delayed impact of U.S. monetary shocks on housing price growth both in the U.S. and internationally. We also document differences in the response of the U.S. economy and the global economy to these shocks.
rates. In this paper we contribute to the effort of bridging these two strands of literature and study the inter-relationships in the degree and nature of comovement across both macroeconomic aggregates and asset returns.2 Included in our list of asset returns is the growth rate of real residential house prices.
Housing activities account for a large fraction of GDP and households’ expenditures in industrial countries. Moreover, housing is the main asset5 and mortgage debt the main liability held by households in these countries, and therefore large house price movements, by affecting households’ net wealth and their capacity to borrow and spend may have important macroeconomic implications. From a global perspective, housing is the quintessential nontraded asset yet, as we document in this paper, there is a surprising degree of synchronization in the changes in the price of this asset across industrial countries. In fact, the degree of comovement is on par with the magnitude of comovement in both financial asset returns (essentially frictionless) and macroeconomic aggregates (slowed only by trade frictions).
This paper studies the dynamic properties of international house prices, stock prices, interest rates and macroeconomic aggregates in industrial countries. While the dynamics of stock market returns and interest rates have been studied previously, we use a new dataset to gain insight into both the comovement of house price across industrial countries and the relationship between the fluctuations of house price with the fluctuations of financial asset returns and macroeconomic aggregates. Despite the fact that housing is the quintessential nontradable asset, we find a large degree of synchronization or comovement in the growth rate of real house prices in industrialized countries. We then show that much of this comovement can be related to a common dynamic component in interest rates across these countries. While we confirm the existence of a great degree of comovement in macroeconomic aggregates (namely, real output, consumption, and residential investment), we find little evidence that these aggregates are important sources of house price fluctuations. Instead, we find that house prices have an effect on macroeconomic aggregates. Given the important role that interest rates play for asset prices and macroeconomic fluctuations in industrial countries, we examine the role of monetary policy shocks--both domestic and global--in driving movement in these variables using an identified VAR augmented with our latent factors. We find evidence of a strong but delayed impact of U.S. monetary shocks on housing price growth both in the U.S. and internationally. We also document differences in the response of the U.S. economy and the global economy to these shocks.
rates. In this paper we contribute to the effort of bridging these two strands of literature and study the inter-relationships in the degree and nature of comovement across both macroeconomic aggregates and asset returns.2 Included in our list of asset returns is the growth rate of real residential house prices.
Housing activities account for a large fraction of GDP and households’ expenditures in industrial countries. Moreover, housing is the main asset5 and mortgage debt the main liability held by households in these countries, and therefore large house price movements, by affecting households’ net wealth and their capacity to borrow and spend may have important macroeconomic implications. From a global perspective, housing is the quintessential nontraded asset yet, as we document in this paper, there is a surprising degree of synchronization in the changes in the price of this asset across industrial countries. In fact, the degree of comovement is on par with the magnitude of comovement in both financial asset returns (essentially frictionless) and macroeconomic aggregates (slowed only by trade frictions).
Thursday, July 5, 2007
The Baby Boom: Predictability in House Prices and Interest Rates
The Baby Boom: Predictability in House Prices and Interest Rates
Robert F. Martin
Abstract: This paper explores the baby boom's impact on U.S. house prices and interest rates in the post-war 20th century and beyond. Using a simple Lucas asset pricing model, I quantitatively account for the increase in real house prices, the path of real interest rates, and the timing of low-frequency fluctuations in real house prices. The model predicts that the primary force underlying the evolution of real house prices is the systematic and predictable changes in the working age population driven by the baby boom. The model is calibrated to U.S. data and tested on international data. One surprising success of the model is its ability to predict the boom and bust in Japanese real estate markets around 1974 and 1990.
This paper explores the extent to which the baby boom has impacted U.S. house prices and interest rates over the latter half of the 20th century. Without question, the baby boom has had a direct and large impact on the dynamics of the U.S. age profile. These dynamics have manifested themselves in changes to the proportion of the population that is of working age. The boomers entered the labor force en masse between 1967 and 1973 and, over the subsequent 35 years, they increased both the size and the growth rate of the potential labor force. The baby boomers are now about to leave the workforce. As they retire, the size of the working age population will fall as will output per person.
These changes in the working age population and the associated impact on output have had and will continue to have a first order effect on house prices and interest rates in the United States. This paper builds on the intuition of the well known paper by Mankiw and Weil (1988). That paper predicted that the baby boom would lead to a peak in house prices in 1989 (they were right) and then to a large permanent fall in the real price of housing from that point forward (obviously wrong). The intuition for this result is simple. If households exhibit hump-shaped demand for housing over the life-cycle and if housing is relatively difficult to build, then house prices should exhibit a peak at the time that the baby boomers reach their peak demand and should decline as the boomer’s demand for housing wanes. The obvious gulf between their predictions and the increases in house prices between 1995 and the present have caused many to dismiss both the Mankiw and Weil paper and the impact of the baby boom on house prices in toto.
This paper will resurrect their intuition. Mankiw and Weil missed the upturn only because they worked in a partial equilibrium environment and over the course of the 1990s general equilibrium effects began to dominate the contemporaneous demand effects. In other words, they neglected both the impact of discount rates on house prices and the impact of the baby boom on the discount rate. By working in a structural model, this paper is able to consider the general equilibrium effects without neglecting the demand effects which are so important in the work of Mankiw and Weil. Indeed, I will show that, if the interest rate effect is shut down in my model, the model will replicate the predictions of Mankiw and Weil.
Using a parsimonious and standard Lucas asset pricing framework, the model demonstrates that the demographic profile in the United States is a likely driver of both house prices and interest rates in the post-war era. In this paper, changes in the size of the working age population determine the labor input into a neoclassical production function. The model takes as given the endowment of capital, labor, and the stock of housing. As I work in an endowment economy, the model will not replicate the time series of capital accumulation — neither business nor residential. Since both of these stocks are assumed fixed, the model also misses the increase in consumption of both goods and housing services observed in the data. However, the model exactly replicates the increase in the ratio of consumption of goods and services to the consumption of housing services as reported in the National Income and Product Accounts. That is, the ratio of consumption to housing services increases by 18 percent in both the model and in the NIPA data over the period 1974 to 2004.
When the size of the working age population is temporarily high as it is now, output is temporarily high and households wish to transfer assets to the future. Because ability to do so is limited2 , there is upward pressure on real asset prices — house prices rise, interest rates fall.3 The increase in house prices occurs now despite the certain knowledge that once the baby boomers retire real house prices will fall.
Without changing the parameters of the model, I test the model’s ability to replicate the pattern of long-term real interest rates.6 Ignoring high frequency movement in the real rate, the model is consistent with interest rates over the period 1950 to 1972 during which interest rates rose and then fell and over the period 1990 to 2005 during which interest rates fell. In the intervening period, the model interest rate is too high relative to the data in the 1970s and too low relative to the data in the early 1980s. To restate this result, using the parameters which are designed to replicate house prices, the model exactly matches long-term interest rates for 37 of the past 55 years.
The question remains “How rational do agents have to be in order to incorporate the output increases observed in the 1990s into the price of bonds being traded in the 1970s?” Do the agents need to have a demographic model like the one presented in this paper in order to anticipate the change in output? The answer is no. Individual agents simply looks forward to their own path of lifetime labor income. The agents in the model know their life time working hours and realize that their highest output years are yet to come. They realize that in the future their own household output per person will rise (their children becoming adults). Therefore, each agent wishes to borrow against these future increases in wealth. Unfortunately for them, the shock that they face turns out to be aggregate — their cohort goes to the bond market with them and interest rates rise. This is simply the flip side of why interest rates are low now.
One of the most surprising results of this paper is its ability to replicate the decline in output volatility in 1984. The volatility in output implied by our model falls by half in the post-1984 world. McConnell et al. (1999) identify a decline in the volatility of U.S. real GDP in 1984. This decline has been attributed alternatively to improved monetary policy (Clarida et al (2000)), improved business practices (McConnell et al. (1999), improved mortgage markets associated with regulation Q (Dynan et al (2005), or simply to a reduction in the volatility of macroeconomic shocks (Stock and Watson (2003)). The demographic model has none of these channels, implying that the good luck noted by Ahmed et al (2002) can simply be named predictable demographic changes. As the baby boom moderated so did the economy.
While it is a success in itself to match both house prices and interest rates in a such a parsimonious model, we further test the model’s ability to match house prices in other industrialized countries. I test the model on data for the United Kingdom, Japan, and Ireland. The model succeeds in each case in matching both the trend in house prices and most of the major peaks in each country. Japan is the most remarkable case.
Between 1970 and 2005, Japanese real house prices exhibited peaks in 1974 and 1990. Since 1990, real house prices have fallen around 34 percent. The sharp increase in real estate prices in the 1980s followed by a fifteen-plus year fall in prices has led many to refer to 1980s Japan as the original bubble economy (Bayoumi and Collyns (2003)). This simple model, using Japanese demographic data, successfully predicts the 1974 and the 1990 house price peaks. Strikingly, the model also predicts a 30 percent decline in real house prices over the fifteen years following the 1990 peak.
The economy consists of a single representative agent. While more complicated demographics could easily have been implemented in the model, this framework ensures the absence of the life-cycle type savings behavior which is the focus of so much of the previous work. That is, the dynamics in this model are not driven by dissaving on the part of some sub-set of agents but rather by aggregate fluctuations in output.
Japan
Japan makes an excellent test case for the model. Japanese real house prices rose almost 40 percent between 1986 and 1990. After the 1990 peak, real house prices have fallen around 34 percent, nominal house prices have fallen even further.20 Japan is widely thought to have experienced an asset price bubble in the late 1980s, with a primary affected asset class being real estate (see for example Bayoumi and Collyns (2000), Ahearne et al. (2002), and Charkaborty (2005)). These papers give many reasons why the bubble occurred and subsequently collapsed mainly associated, in one form or another, with imperfections in the banking system. Hayashi and Prescott (2005) dispute the finding that a breakdown in the financial system caused the decade long stagnation. Instead they attribute the decline to a decade long slowdown in total productivity growth.
Demographics, if not the only driver, appears to have played a significant role in the run-up in house prices in Japan in the 1980s and appears linked to the decline in house prices over the 1990s. Figure 13 shows the time path of real house prices (dashed black line) and the data output by the model (the bold solid line). The model is capable of replicating both the 1974 peak in real house prices and the 1990 peak, albeit the model predicts the peak to occur in 1992 rather than 1990. The model, surprisingly, also predicts the fall in house prices over the last fifteen years. From the model peak year, the model predicts a 30 percent decline in house prices over fifteen years, remarkably close to the actual fall.
Ireland
The model is applied to Ireland. I wanted to end with Ireland because it is a country without a dire prediction for house prices going forward because Ireland has a very young population . One result of the very young population is that the model does not predict a decline in house prices until the year 2033. Figure 17 shows real house prices and simulated house prices from the model. Among the countries examined in this paper, Ireland has the smoothest predicted price of housing. The model comes close to predicting the stagnant housing market between 1970 and 1994 and is able to make the turn to high house price growth from 1994 forward. The model exactly matches house prices from 2002 to 2005. The model’s predictions for house prices between now and 2010 are remarkable. Over this time period, the model predicts a further doubling of house prices.
The model predicts such different house price growth in Ireland because the Irish baby boom was quite different from the other countries. Irish population data is available beginning in 1950. Inferring from the growth rate of the 20 to 24 year old population, the original “post-war” baby boom in Ireland occurred quite late. The birth rate may have begun to pick-up in 1940 but did not substantially peak until 1960. More importantly for our result is that Ireland had a baby boom quite recently in the very late 1970s. This cohort enters the workforce around 1994 implying that most of the current run-up in house prices in Ireland is a result of increased output as the labor supply increases. (Note, this is also the reason the model predicts a slight decline in house prices earlier.) That same cohort does not begin to retire until around 2033. But for Ireland, even in 2033, the case for house prices is not so dire. This results from the fact that Ireland is currently in the middle of a sizable baby boomlet (the boomlet causes the change in slope of prices around 2000). This second cohort does not enter the labor force until between 2025 and 2030, somewhat cushioning the falling prices later. This cohort retires around 2065 to 2070.
Robert F. Martin
Abstract: This paper explores the baby boom's impact on U.S. house prices and interest rates in the post-war 20th century and beyond. Using a simple Lucas asset pricing model, I quantitatively account for the increase in real house prices, the path of real interest rates, and the timing of low-frequency fluctuations in real house prices. The model predicts that the primary force underlying the evolution of real house prices is the systematic and predictable changes in the working age population driven by the baby boom. The model is calibrated to U.S. data and tested on international data. One surprising success of the model is its ability to predict the boom and bust in Japanese real estate markets around 1974 and 1990.
This paper explores the extent to which the baby boom has impacted U.S. house prices and interest rates over the latter half of the 20th century. Without question, the baby boom has had a direct and large impact on the dynamics of the U.S. age profile. These dynamics have manifested themselves in changes to the proportion of the population that is of working age. The boomers entered the labor force en masse between 1967 and 1973 and, over the subsequent 35 years, they increased both the size and the growth rate of the potential labor force. The baby boomers are now about to leave the workforce. As they retire, the size of the working age population will fall as will output per person.
These changes in the working age population and the associated impact on output have had and will continue to have a first order effect on house prices and interest rates in the United States. This paper builds on the intuition of the well known paper by Mankiw and Weil (1988). That paper predicted that the baby boom would lead to a peak in house prices in 1989 (they were right) and then to a large permanent fall in the real price of housing from that point forward (obviously wrong). The intuition for this result is simple. If households exhibit hump-shaped demand for housing over the life-cycle and if housing is relatively difficult to build, then house prices should exhibit a peak at the time that the baby boomers reach their peak demand and should decline as the boomer’s demand for housing wanes. The obvious gulf between their predictions and the increases in house prices between 1995 and the present have caused many to dismiss both the Mankiw and Weil paper and the impact of the baby boom on house prices in toto.
This paper will resurrect their intuition. Mankiw and Weil missed the upturn only because they worked in a partial equilibrium environment and over the course of the 1990s general equilibrium effects began to dominate the contemporaneous demand effects. In other words, they neglected both the impact of discount rates on house prices and the impact of the baby boom on the discount rate. By working in a structural model, this paper is able to consider the general equilibrium effects without neglecting the demand effects which are so important in the work of Mankiw and Weil. Indeed, I will show that, if the interest rate effect is shut down in my model, the model will replicate the predictions of Mankiw and Weil.
Using a parsimonious and standard Lucas asset pricing framework, the model demonstrates that the demographic profile in the United States is a likely driver of both house prices and interest rates in the post-war era. In this paper, changes in the size of the working age population determine the labor input into a neoclassical production function. The model takes as given the endowment of capital, labor, and the stock of housing. As I work in an endowment economy, the model will not replicate the time series of capital accumulation — neither business nor residential. Since both of these stocks are assumed fixed, the model also misses the increase in consumption of both goods and housing services observed in the data. However, the model exactly replicates the increase in the ratio of consumption of goods and services to the consumption of housing services as reported in the National Income and Product Accounts. That is, the ratio of consumption to housing services increases by 18 percent in both the model and in the NIPA data over the period 1974 to 2004.
When the size of the working age population is temporarily high as it is now, output is temporarily high and households wish to transfer assets to the future. Because ability to do so is limited2 , there is upward pressure on real asset prices — house prices rise, interest rates fall.3 The increase in house prices occurs now despite the certain knowledge that once the baby boomers retire real house prices will fall.
Without changing the parameters of the model, I test the model’s ability to replicate the pattern of long-term real interest rates.6 Ignoring high frequency movement in the real rate, the model is consistent with interest rates over the period 1950 to 1972 during which interest rates rose and then fell and over the period 1990 to 2005 during which interest rates fell. In the intervening period, the model interest rate is too high relative to the data in the 1970s and too low relative to the data in the early 1980s. To restate this result, using the parameters which are designed to replicate house prices, the model exactly matches long-term interest rates for 37 of the past 55 years.
The question remains “How rational do agents have to be in order to incorporate the output increases observed in the 1990s into the price of bonds being traded in the 1970s?” Do the agents need to have a demographic model like the one presented in this paper in order to anticipate the change in output? The answer is no. Individual agents simply looks forward to their own path of lifetime labor income. The agents in the model know their life time working hours and realize that their highest output years are yet to come. They realize that in the future their own household output per person will rise (their children becoming adults). Therefore, each agent wishes to borrow against these future increases in wealth. Unfortunately for them, the shock that they face turns out to be aggregate — their cohort goes to the bond market with them and interest rates rise. This is simply the flip side of why interest rates are low now.
One of the most surprising results of this paper is its ability to replicate the decline in output volatility in 1984. The volatility in output implied by our model falls by half in the post-1984 world. McConnell et al. (1999) identify a decline in the volatility of U.S. real GDP in 1984. This decline has been attributed alternatively to improved monetary policy (Clarida et al (2000)), improved business practices (McConnell et al. (1999), improved mortgage markets associated with regulation Q (Dynan et al (2005), or simply to a reduction in the volatility of macroeconomic shocks (Stock and Watson (2003)). The demographic model has none of these channels, implying that the good luck noted by Ahmed et al (2002) can simply be named predictable demographic changes. As the baby boom moderated so did the economy.
While it is a success in itself to match both house prices and interest rates in a such a parsimonious model, we further test the model’s ability to match house prices in other industrialized countries. I test the model on data for the United Kingdom, Japan, and Ireland. The model succeeds in each case in matching both the trend in house prices and most of the major peaks in each country. Japan is the most remarkable case.
Between 1970 and 2005, Japanese real house prices exhibited peaks in 1974 and 1990. Since 1990, real house prices have fallen around 34 percent. The sharp increase in real estate prices in the 1980s followed by a fifteen-plus year fall in prices has led many to refer to 1980s Japan as the original bubble economy (Bayoumi and Collyns (2003)). This simple model, using Japanese demographic data, successfully predicts the 1974 and the 1990 house price peaks. Strikingly, the model also predicts a 30 percent decline in real house prices over the fifteen years following the 1990 peak.
The economy consists of a single representative agent. While more complicated demographics could easily have been implemented in the model, this framework ensures the absence of the life-cycle type savings behavior which is the focus of so much of the previous work. That is, the dynamics in this model are not driven by dissaving on the part of some sub-set of agents but rather by aggregate fluctuations in output.
Japan
Japan makes an excellent test case for the model. Japanese real house prices rose almost 40 percent between 1986 and 1990. After the 1990 peak, real house prices have fallen around 34 percent, nominal house prices have fallen even further.20 Japan is widely thought to have experienced an asset price bubble in the late 1980s, with a primary affected asset class being real estate (see for example Bayoumi and Collyns (2000), Ahearne et al. (2002), and Charkaborty (2005)). These papers give many reasons why the bubble occurred and subsequently collapsed mainly associated, in one form or another, with imperfections in the banking system. Hayashi and Prescott (2005) dispute the finding that a breakdown in the financial system caused the decade long stagnation. Instead they attribute the decline to a decade long slowdown in total productivity growth.
Demographics, if not the only driver, appears to have played a significant role in the run-up in house prices in Japan in the 1980s and appears linked to the decline in house prices over the 1990s. Figure 13 shows the time path of real house prices (dashed black line) and the data output by the model (the bold solid line). The model is capable of replicating both the 1974 peak in real house prices and the 1990 peak, albeit the model predicts the peak to occur in 1992 rather than 1990. The model, surprisingly, also predicts the fall in house prices over the last fifteen years. From the model peak year, the model predicts a 30 percent decline in house prices over fifteen years, remarkably close to the actual fall.
Ireland
The model is applied to Ireland. I wanted to end with Ireland because it is a country without a dire prediction for house prices going forward because Ireland has a very young population . One result of the very young population is that the model does not predict a decline in house prices until the year 2033. Figure 17 shows real house prices and simulated house prices from the model. Among the countries examined in this paper, Ireland has the smoothest predicted price of housing. The model comes close to predicting the stagnant housing market between 1970 and 1994 and is able to make the turn to high house price growth from 1994 forward. The model exactly matches house prices from 2002 to 2005. The model’s predictions for house prices between now and 2010 are remarkable. Over this time period, the model predicts a further doubling of house prices.
The model predicts such different house price growth in Ireland because the Irish baby boom was quite different from the other countries. Irish population data is available beginning in 1950. Inferring from the growth rate of the 20 to 24 year old population, the original “post-war” baby boom in Ireland occurred quite late. The birth rate may have begun to pick-up in 1940 but did not substantially peak until 1960. More importantly for our result is that Ireland had a baby boom quite recently in the very late 1970s. This cohort enters the workforce around 1994 implying that most of the current run-up in house prices in Ireland is a result of increased output as the labor supply increases. (Note, this is also the reason the model predicts a slight decline in house prices earlier.) That same cohort does not begin to retire until around 2033. But for Ireland, even in 2033, the case for house prices is not so dire. This results from the fact that Ireland is currently in the middle of a sizable baby boomlet (the boomlet causes the change in slope of prices around 2000). This second cohort does not enter the labor force until between 2025 and 2030, somewhat cushioning the falling prices later. This cohort retires around 2065 to 2070.
Why Have Housing Prices Gone Up?
Why Have Housing Prices Gone Up?
Edward L. Glaeser and Joseph Gyourko
Since 1950, housing prices have risen regularly by almost two percent per year. Between 1950 and 1970, this increase reflects rising housing quality and construction costs. Since 1970, this increase reflects the increasing difficulty of obtaining regulatory approval for building new homes. In this paper, we present a simple model of regulatory approval that suggests a number of explanations for this change including changing judicial tastes, decreasing ability to bribe regulators, rising incomes and greater tastes for amenities, and improvements in the ability of homeowners to organize and influence local decisions. Our preliminary evidence suggests that there was a significant increase in the ability of local residents to block new projects and a change of cities from urban growth machines to homeowners’ cooperatives.
Too often, analysts attempt to understand housing prices only by attending to demand-side factors such as interest rates or per capita income, while ignoring the supply-side of the market. Rising prices require not only rising demand, but also limits on supply. The supply of housing includes three elements: land, a physical structure, and government approval to put the structure on the land. Thus, rising prices must reflect rising physical costs of construction, increasing land prices or regulatory barriers to new construction.
Even in booming markets, construction cost increases have been modest. Between 1970 and 2000, real construction costs in San Francisco and Boston rose by 4.6 percent and 6.6 percent, respectively. Over the same 30 years, real mean house prices rose by 270 percent in the San Francisco primary metropolitan statistical area (PMSA) and 127 percent in the Boston metropolitan area.
Rising structure costs still could explain the post-1970 growth in housing prices if structural size and quality were increasing rapidly. To assess the importance of housing quality, we can compare the overall rise in housing prices with the rise in prices measured by repeat-sales indices that hold housing structure constant. In the United States as a whole, the real median value of owner-occupied housing rose by 1.20 percent per year from 1980 to 2000. Over this same period, real appreciation of the repeat-sales index published by the Office of Federal Enterprise Housing Oversight (OFHEO) was 0.93 percent per year, which suggests that changes in the quality of housing account for no more than one quarter of the average increase in housing values. The same methodology in high-price areas shows that quality growth is even less important in those places.
It is only since 1980, and only in a relatively few metropolitan areas, that there has been a widening gap between price and construction cost. Almost all of the markets in which housing prices became substantially higher than physical production costs during the 1970s were part of the three big coastal metropolises in California—the Los Angeles-centered CMSA, the San Francisco-centered CMSA, and the San Diego MSA.
A decade later, gaps between prices and construction costs on the West Coast had grown and had spread to interior markets in California. For example, structure represented only 53 percent of average house value in Sacramento in 1990. High prices relative to construction costs had also spread to other West Coast markets such as Seattle. The non-structure component of house value also exceeded 40 percent across a swath of the east coast roughly approximated by Amtrak’s Northeast Corridor.
By the year 2000, there were 27 metropolitan areas in which structure could account for no more than 60 percent of total house value.
It is no longer the case that high prices relative to construction costs generally lead to a surge in new construction.
These results strongly suggest that restrictions on new supply have become increasingly important in preventing suppliers from responding to high prices by building additional units. But are these limits on new construction the result of a dwindling supply of land or other barriers to new construction?
Beyond physical structure, the cost of supplying a house includes both the cost of the land and the cost of the right to build. If the costs associated with the right to build were small, then the non-structure value of the property would include only the cost of the land. A completely free market for land would lead land to be worth the same amount on both the intensive and extensive margins. Stated differently, a quarter acre would be valued the same if it sits under one house or if it extends the lot of another house. Using this insight, Glaeser and Gyourko (2003) and Glaeser, Gyourko and Saks (2005) use hedonic price estimation to estimate the price of land when it extends the lot of an existing house. We find that such land is not all that valuable; generally a quarter acre is worth about ten times more if it sits under a house than if it extends the lot of another house. The fact that land is worth much more when it is bundled together with the right to build provides further evidence that the right to build is worth a great deal.
In sum, the evidence points toward a man-made scarcity of housing in the sense that the housing supply has been constrained by government regulation as opposed to fundamental geographic limitations.8 The growing dispersion of housing prices relative to construction costs suggests that these regulations have spread into a larger number of local markets over time. Moreover, they appear to have become particularly severe in the past 2-3 decades.
Given these assumptions, there is a unique amount of development that will maximize the average discounted lifetime utility of all current residents of the town. In order to achieve this social optimum, it is necessary to allow for the possibility of sidepayments between developers (who gain from additional residential construction) and homeowners (who lose from additional development through lower future housing values). It is straightforward to show that a higher fraction of homeowners will lead to less development. Moreover, because a shorter lifespan makes the resale value of homes more salient to homeowners, shorter life spans also curtail the optimal amount of development.
There are two reasons why the level of development that maximizes the welfare of current residents will not be socially optimal. First, higher population density has a negative impact on the utility of future residents of the town and of the reservation locale that current residents will not internalize. Second, current homeowners have an incentive to increase the value of their homes, and do not internalize the impact that higher housing prices have on non-homeowners who would like to live in the town.
The second comparative static suggests that the explanation lies in the rise of homeownership and the success of community organization. Increases in both the share of homeowners and the political organization of homeowners’ groups should lead to less development. In the past 40 years, the fraction of homeownership has risen from about 59 to 68% (Federal Reserve Board, 1964 and Aizcorbe et. al., 2003). Moreover, political participation of homeowners groups has been rising (Nelson, 2004, Freund, 1974). Not only should this trend restrict residential development, but Altshuler and Luberoff (2002) suggest that these groups have been increasingly able to restrict large-scale nonresidential development projects as well.
In 1977, Robert Ellickson noted that “suburban governments are becoming ever more adventuresome in their efforts to control housing development.” (p. 388). Ellickson does not explain this change, but points to judicial decisions such as Nectow v. City of Cambridge which have made it difficult for landowners to stop municipalities from restricting new construction on their land. Fischel (2004) points to the ideology of judges: “Courts, whose judges share the same environmental attitudes as middle class homeowners (just as 1920s judges shared the ideology of hearth and home), were more sympathetic to claims that the local decision had failed to account for environmental impacts than they had been to seemingly selfish claims that neighbors’ home values were at risk.” (pp. 332-333) Other cases such as Mt. Laurel that demanded low income housing have simultaneously allowed growth controls: "once a community has satisfied its fair share obligation [a fraction of the region’s low-income housing], the Mount Laurel Doctrine will not restrict other measures, including large-lot and open area zoning, that would maintain its beauty and communal character"(Mount Laurel II, 456 A.2d at 421 cited in Fischel (2004), p. 331).
While the influence of developers may or may not have declined, many observers have noted a sizable increase in the organization and political impact of local residents. Altshuler and Luberoff (2002) examine the history of large scale government projects (“Mega Projects”) and describe changes that began in the 1960s, when citizens became better able to challenge large scale projects that would impact their neighborhood. One early and striking example was Jane Jacobs’ leadership of the Greenwich Village movement that stopped Robert Moses’ West Side highway project in New York. Through increasingly sophisticated use of the media, local groups learned how turn mega-projects into public relations disasters.
Another way to think about the effect of income is to consider the zoning environment of very rich places in 1960. If the income hypothesis is correct, then permitting in these places should have been as restrictive in 1960 as the entire metropolitan areas of Boston or New York in more recent years. However, places like New Rochelle, NY, San Mateo, CA and West Orange, NJ, each allowed at least 10 times as much development in the 1950s as metropolitan areas with comparable incomes today. Again, this analysis suggests that the complete story goes well beyond the explanation that homeowners became richer.
A final hypothesis is that the impact of new construction on housing prices has changed over time. In the 1950s, housing costs were low, lower incomes made people less concerned about environmental amenities, and an absence of construction in previous decades may have meant that the quality of new housing was significantly higher than older units. For these reasons, new construction may not have led to major reductions in housing prices for existing units and as such, homeowners had much weaker incentives to fight new construction. In 2004, however, homeowners appear to believe that new construction will significantly reduce housing prices. Certainly, the evidence in this paper linking rising housing prices to reductions in construction suggests that they are right. As in the case of the previous theories, we have little evidence on the relevance of this theory and we look to further research to examine this hypothesis more thoroughly.
Edward L. Glaeser and Joseph Gyourko
Since 1950, housing prices have risen regularly by almost two percent per year. Between 1950 and 1970, this increase reflects rising housing quality and construction costs. Since 1970, this increase reflects the increasing difficulty of obtaining regulatory approval for building new homes. In this paper, we present a simple model of regulatory approval that suggests a number of explanations for this change including changing judicial tastes, decreasing ability to bribe regulators, rising incomes and greater tastes for amenities, and improvements in the ability of homeowners to organize and influence local decisions. Our preliminary evidence suggests that there was a significant increase in the ability of local residents to block new projects and a change of cities from urban growth machines to homeowners’ cooperatives.
Too often, analysts attempt to understand housing prices only by attending to demand-side factors such as interest rates or per capita income, while ignoring the supply-side of the market. Rising prices require not only rising demand, but also limits on supply. The supply of housing includes three elements: land, a physical structure, and government approval to put the structure on the land. Thus, rising prices must reflect rising physical costs of construction, increasing land prices or regulatory barriers to new construction.
Even in booming markets, construction cost increases have been modest. Between 1970 and 2000, real construction costs in San Francisco and Boston rose by 4.6 percent and 6.6 percent, respectively. Over the same 30 years, real mean house prices rose by 270 percent in the San Francisco primary metropolitan statistical area (PMSA) and 127 percent in the Boston metropolitan area.
Rising structure costs still could explain the post-1970 growth in housing prices if structural size and quality were increasing rapidly. To assess the importance of housing quality, we can compare the overall rise in housing prices with the rise in prices measured by repeat-sales indices that hold housing structure constant. In the United States as a whole, the real median value of owner-occupied housing rose by 1.20 percent per year from 1980 to 2000. Over this same period, real appreciation of the repeat-sales index published by the Office of Federal Enterprise Housing Oversight (OFHEO) was 0.93 percent per year, which suggests that changes in the quality of housing account for no more than one quarter of the average increase in housing values. The same methodology in high-price areas shows that quality growth is even less important in those places.
It is only since 1980, and only in a relatively few metropolitan areas, that there has been a widening gap between price and construction cost. Almost all of the markets in which housing prices became substantially higher than physical production costs during the 1970s were part of the three big coastal metropolises in California—the Los Angeles-centered CMSA, the San Francisco-centered CMSA, and the San Diego MSA.
A decade later, gaps between prices and construction costs on the West Coast had grown and had spread to interior markets in California. For example, structure represented only 53 percent of average house value in Sacramento in 1990. High prices relative to construction costs had also spread to other West Coast markets such as Seattle. The non-structure component of house value also exceeded 40 percent across a swath of the east coast roughly approximated by Amtrak’s Northeast Corridor.
By the year 2000, there were 27 metropolitan areas in which structure could account for no more than 60 percent of total house value.
It is no longer the case that high prices relative to construction costs generally lead to a surge in new construction.
These results strongly suggest that restrictions on new supply have become increasingly important in preventing suppliers from responding to high prices by building additional units. But are these limits on new construction the result of a dwindling supply of land or other barriers to new construction?
Beyond physical structure, the cost of supplying a house includes both the cost of the land and the cost of the right to build. If the costs associated with the right to build were small, then the non-structure value of the property would include only the cost of the land. A completely free market for land would lead land to be worth the same amount on both the intensive and extensive margins. Stated differently, a quarter acre would be valued the same if it sits under one house or if it extends the lot of another house. Using this insight, Glaeser and Gyourko (2003) and Glaeser, Gyourko and Saks (2005) use hedonic price estimation to estimate the price of land when it extends the lot of an existing house. We find that such land is not all that valuable; generally a quarter acre is worth about ten times more if it sits under a house than if it extends the lot of another house. The fact that land is worth much more when it is bundled together with the right to build provides further evidence that the right to build is worth a great deal.
In sum, the evidence points toward a man-made scarcity of housing in the sense that the housing supply has been constrained by government regulation as opposed to fundamental geographic limitations.8 The growing dispersion of housing prices relative to construction costs suggests that these regulations have spread into a larger number of local markets over time. Moreover, they appear to have become particularly severe in the past 2-3 decades.
Given these assumptions, there is a unique amount of development that will maximize the average discounted lifetime utility of all current residents of the town. In order to achieve this social optimum, it is necessary to allow for the possibility of sidepayments between developers (who gain from additional residential construction) and homeowners (who lose from additional development through lower future housing values). It is straightforward to show that a higher fraction of homeowners will lead to less development. Moreover, because a shorter lifespan makes the resale value of homes more salient to homeowners, shorter life spans also curtail the optimal amount of development.
There are two reasons why the level of development that maximizes the welfare of current residents will not be socially optimal. First, higher population density has a negative impact on the utility of future residents of the town and of the reservation locale that current residents will not internalize. Second, current homeowners have an incentive to increase the value of their homes, and do not internalize the impact that higher housing prices have on non-homeowners who would like to live in the town.
The second comparative static suggests that the explanation lies in the rise of homeownership and the success of community organization. Increases in both the share of homeowners and the political organization of homeowners’ groups should lead to less development. In the past 40 years, the fraction of homeownership has risen from about 59 to 68% (Federal Reserve Board, 1964 and Aizcorbe et. al., 2003). Moreover, political participation of homeowners groups has been rising (Nelson, 2004, Freund, 1974). Not only should this trend restrict residential development, but Altshuler and Luberoff (2002) suggest that these groups have been increasingly able to restrict large-scale nonresidential development projects as well.
In 1977, Robert Ellickson noted that “suburban governments are becoming ever more adventuresome in their efforts to control housing development.” (p. 388). Ellickson does not explain this change, but points to judicial decisions such as Nectow v. City of Cambridge which have made it difficult for landowners to stop municipalities from restricting new construction on their land. Fischel (2004) points to the ideology of judges: “Courts, whose judges share the same environmental attitudes as middle class homeowners (just as 1920s judges shared the ideology of hearth and home), were more sympathetic to claims that the local decision had failed to account for environmental impacts than they had been to seemingly selfish claims that neighbors’ home values were at risk.” (pp. 332-333) Other cases such as Mt. Laurel that demanded low income housing have simultaneously allowed growth controls: "once a community has satisfied its fair share obligation [a fraction of the region’s low-income housing], the Mount Laurel Doctrine will not restrict other measures, including large-lot and open area zoning, that would maintain its beauty and communal character"(Mount Laurel II, 456 A.2d at 421 cited in Fischel (2004), p. 331).
While the influence of developers may or may not have declined, many observers have noted a sizable increase in the organization and political impact of local residents. Altshuler and Luberoff (2002) examine the history of large scale government projects (“Mega Projects”) and describe changes that began in the 1960s, when citizens became better able to challenge large scale projects that would impact their neighborhood. One early and striking example was Jane Jacobs’ leadership of the Greenwich Village movement that stopped Robert Moses’ West Side highway project in New York. Through increasingly sophisticated use of the media, local groups learned how turn mega-projects into public relations disasters.
Another way to think about the effect of income is to consider the zoning environment of very rich places in 1960. If the income hypothesis is correct, then permitting in these places should have been as restrictive in 1960 as the entire metropolitan areas of Boston or New York in more recent years. However, places like New Rochelle, NY, San Mateo, CA and West Orange, NJ, each allowed at least 10 times as much development in the 1950s as metropolitan areas with comparable incomes today. Again, this analysis suggests that the complete story goes well beyond the explanation that homeowners became richer.
A final hypothesis is that the impact of new construction on housing prices has changed over time. In the 1950s, housing costs were low, lower incomes made people less concerned about environmental amenities, and an absence of construction in previous decades may have meant that the quality of new housing was significantly higher than older units. For these reasons, new construction may not have led to major reductions in housing prices for existing units and as such, homeowners had much weaker incentives to fight new construction. In 2004, however, homeowners appear to believe that new construction will significantly reduce housing prices. Certainly, the evidence in this paper linking rising housing prices to reductions in construction suggests that they are right. As in the case of the previous theories, we have little evidence on the relevance of this theory and we look to further research to examine this hypothesis more thoroughly.
Are House Prices Nearing a Peak?
Are House Prices Nearing a Peak? A Probit Analysis for 17 OECD Countries
House prices have been moving up strongly in real terms since the mid-1990s in the majority of OECD countries, with the ongoing upswing the longest of its kind in the OECD area since the 1970s. If interest rates were to rise significantly, real house prices may be at risk of nearing a peak. The historical record suggests that the subsequent drops in prices in real terms might be large and that the process could be protracted. To quantify the probability that a peak is nearing in the current situation a probit model was estimated for the period 1970-2005 on a restricted set of what are generally agreed to be the main explanatory variables. Aside from interest rates, these include measures of overheating, such as the gap between real house prices and their long-run trend and the rate of change in real house prices in the recent past. The main finding is that an increase in interest rates by about 1 to 2 percentage points would result in probabilities of a peak nearing of 50% or more in the United States, France, Denmark, Ireland, New Zealand, Spain and Sweden.
House prices have been moving up strongly in real terms since the mid-1990s in the majority of OECD countries, with the ongoing upswing the longest of its kind in the OECD area since the 1970s. As reported in Girouard et al. (2006), several measures, such as the user cost of owner-occupied housing and affordability indicators, suggest that house prices are not that much out of line with the fundamentals in most markets. However, the extent to which real house prices look to be fairly valued depends critically on interest rates remaining at or close to their recent historical lows. Interest rates have already edged up since late 2005, and, if they were to rise significantly further, real house prices may be at risk of nearing a peak. The historical record suggests that the subsequent drops in prices in real terms might be large and that the process could be protracted. This would have negative implications for activity, which in turn could necessitate a monetary policy response.
Since the 1970s, house prices in real terms (the ratio of actual house prices to the consumer price index) in the OECD have been on a secular upward trend, rising by on average 3% per annum in the area as a whole (Table 1). This is generally attributed to rising demand for housing space linked to increasing per capita income, growing populations, supply factors such as land scarcity and restrictiveness of zoning laws, quality improvement that is not properly taken into account in the price index and comparatively low productivity growth in construction.
This suggests that global factors have been at work to sustain the current housing boom. These factors include the easing of monetary policy stances in the wake of the 2000-01 downturn and the associated massive injection of liquidity, the exceptionally low levels of term premiums on longer-term bond yields and easier access to credit owing to the liberalisation of mortgage markets.
For example, the general increase in indebtedness, which is another striking feature of the current upswing, has been mostly offset by the decline in borrowing rates. As a result, households do not seem to devote a greater share of their income to debt service than in the not-too-distant past. A comparison of price-to-rent ratios with the inverse of the imputed user cost of housing over the past ten years also does not suggest that real house prices are greatly overvalued in most markets, and where they do, it can be explained by features that are particular to those markets, such as restrictions on the availability of land for residential housing development becoming more acute due to tough zoning rules, cumbersome building regulations and slow administrative procedures.
However, the extent to which real house prices look to be fairly valued depends critically on interest rates remaining at or close to their current historical lows. If interest rates were to rise significantly, house prices would come under downward pressure as the user cost would fall out of sync with the prevailing price-to-rent ratios or because affordability constraints kick in. Real house prices would have to adjust downwards, but with inflation lower than in previous episodes, a bigger share of the burden of the adjustment will need to be borne by nominal house price decreases. However, nominal house prices tend to exhibit downward stickiness: when overall conditions weaken, owners of existing homes tend to withdraw from the market rather than suffer a capital loss, while builders will develop fewer new properties. As a result, in a low inflation environment the adjustment of real prices will be drawn-out. This is illustrated by the negative cross-country correlation observed between the level of inflation and the duration of houseprice- contraction phases, although there is also a tendency for real prices to fall less at low inflation (Figure 2). The upshot is that the effects of the adjustment may be less disruptive than in past episodes of contraction but may also depress economic activity for a longer period.
To estimate the individual country models, the following procedure was used. As a first step, the model as presented in Equation (1) was re-estimated for each individual country. Subsequently, experiments were carried out with a view to improving the performance of each individual country model. There were a few cases where the specification used in the pooled model also proved optimal for the individual country models (Spain and Switzerland). In all other cases the specification was changed in a number of ways (Table 5):
• In several cases entering the inflation rate as an additional explanatory variable improved the equation significantly (United States, France, Denmark, New Zealand and Sweden). This variable enters the equation with a negative sign, suggesting that higher inflation eases the financing constraint facing households and therefore makes a peak less likely.
Both sets of estimates (pooled and individual) point to the same group of countries as being at risk of nearing a peak if interest rates significantly increase from their levels observed in the fourth quarter of 2005: the United States, France, Denmark, Ireland, New Zealand, Spain and Sweden. This prediction is conditional on the development of interest rates and it also depends on the validity of the historical relationships as estimated.
House prices have been moving up strongly in real terms since the mid-1990s in the majority of OECD countries, with the ongoing upswing the longest of its kind in the OECD area since the 1970s. If interest rates were to rise significantly, real house prices may be at risk of nearing a peak. The historical record suggests that the subsequent drops in prices in real terms might be large and that the process could be protracted. To quantify the probability that a peak is nearing in the current situation a probit model was estimated for the period 1970-2005 on a restricted set of what are generally agreed to be the main explanatory variables. Aside from interest rates, these include measures of overheating, such as the gap between real house prices and their long-run trend and the rate of change in real house prices in the recent past. The main finding is that an increase in interest rates by about 1 to 2 percentage points would result in probabilities of a peak nearing of 50% or more in the United States, France, Denmark, Ireland, New Zealand, Spain and Sweden.
House prices have been moving up strongly in real terms since the mid-1990s in the majority of OECD countries, with the ongoing upswing the longest of its kind in the OECD area since the 1970s. As reported in Girouard et al. (2006), several measures, such as the user cost of owner-occupied housing and affordability indicators, suggest that house prices are not that much out of line with the fundamentals in most markets. However, the extent to which real house prices look to be fairly valued depends critically on interest rates remaining at or close to their recent historical lows. Interest rates have already edged up since late 2005, and, if they were to rise significantly further, real house prices may be at risk of nearing a peak. The historical record suggests that the subsequent drops in prices in real terms might be large and that the process could be protracted. This would have negative implications for activity, which in turn could necessitate a monetary policy response.
Since the 1970s, house prices in real terms (the ratio of actual house prices to the consumer price index) in the OECD have been on a secular upward trend, rising by on average 3% per annum in the area as a whole (Table 1). This is generally attributed to rising demand for housing space linked to increasing per capita income, growing populations, supply factors such as land scarcity and restrictiveness of zoning laws, quality improvement that is not properly taken into account in the price index and comparatively low productivity growth in construction.
This suggests that global factors have been at work to sustain the current housing boom. These factors include the easing of monetary policy stances in the wake of the 2000-01 downturn and the associated massive injection of liquidity, the exceptionally low levels of term premiums on longer-term bond yields and easier access to credit owing to the liberalisation of mortgage markets.
For example, the general increase in indebtedness, which is another striking feature of the current upswing, has been mostly offset by the decline in borrowing rates. As a result, households do not seem to devote a greater share of their income to debt service than in the not-too-distant past. A comparison of price-to-rent ratios with the inverse of the imputed user cost of housing over the past ten years also does not suggest that real house prices are greatly overvalued in most markets, and where they do, it can be explained by features that are particular to those markets, such as restrictions on the availability of land for residential housing development becoming more acute due to tough zoning rules, cumbersome building regulations and slow administrative procedures.
However, the extent to which real house prices look to be fairly valued depends critically on interest rates remaining at or close to their current historical lows. If interest rates were to rise significantly, house prices would come under downward pressure as the user cost would fall out of sync with the prevailing price-to-rent ratios or because affordability constraints kick in. Real house prices would have to adjust downwards, but with inflation lower than in previous episodes, a bigger share of the burden of the adjustment will need to be borne by nominal house price decreases. However, nominal house prices tend to exhibit downward stickiness: when overall conditions weaken, owners of existing homes tend to withdraw from the market rather than suffer a capital loss, while builders will develop fewer new properties. As a result, in a low inflation environment the adjustment of real prices will be drawn-out. This is illustrated by the negative cross-country correlation observed between the level of inflation and the duration of houseprice- contraction phases, although there is also a tendency for real prices to fall less at low inflation (Figure 2). The upshot is that the effects of the adjustment may be less disruptive than in past episodes of contraction but may also depress economic activity for a longer period.
To estimate the individual country models, the following procedure was used. As a first step, the model as presented in Equation (1) was re-estimated for each individual country. Subsequently, experiments were carried out with a view to improving the performance of each individual country model. There were a few cases where the specification used in the pooled model also proved optimal for the individual country models (Spain and Switzerland). In all other cases the specification was changed in a number of ways (Table 5):
• In several cases entering the inflation rate as an additional explanatory variable improved the equation significantly (United States, France, Denmark, New Zealand and Sweden). This variable enters the equation with a negative sign, suggesting that higher inflation eases the financing constraint facing households and therefore makes a peak less likely.
Both sets of estimates (pooled and individual) point to the same group of countries as being at risk of nearing a peak if interest rates significantly increase from their levels observed in the fourth quarter of 2005: the United States, France, Denmark, Ireland, New Zealand, Spain and Sweden. This prediction is conditional on the development of interest rates and it also depends on the validity of the historical relationships as estimated.
Notes 2
The following notes come from this paper:
Ireland’s housing boom: what has driven it and have prices overshot?
David Rae and Paul van den Noord
OECD Economics Department working paper No 492
Abstract
The Irish housing market is very buoyant. The housing boom is driven by strong economic growth, dynamic demographics and low interest rates. However, large tax advantages and relatively lenient credit policies by banks have also played their part, and prices may have become overvalued. To the extent that high house prices reflect favourable tax treatment, they may lead to economic inefficiencies by drawing excessive resources into residential construction. While a soft landing appears the most likely prospect, a disorderly correction of house prices would pose risks for macroeconomic and possibly financial stability. In this context, one policy lever available to the government would be a phased removal of the tax advantages associated with housing. In addition, banks should remain cautious in their lending and provisioning policies.
House prices across the industrialised world have surged since the mid 1990s – with the notable exceptions of Germany and Japan which are both still grappling with the aftermath of real estate busts in the early 1990s. In many countries, housing demand is underpinned by an easy monetary stance (Otrok and Terrones, 2005), while over a longer period tight zoning regulations have exacerbated the upward movement in property prices in and around growth centres (Glaeser et al., 2005).
This paper argues that most of the increase in Irish house prices is justified by the economic and demographic driving forces. It should be remembered that in 1993 the average Irish house cost a mere € 75 000, which was extraordinarily low for a European country. Since then, remarkable growth in incomes, low interest rates, strong population growth, especially among the younger house-forming age groups, a surge in immigration and changing living patterns have all contributed to the boom.
Ireland’s house prices have risen dramatically since the mid 1990s. From 1995 to 2005 the price of second-hand houses more than tripled in real terms (Figure 1, left panel). House price inflation eased temporarily in 2001 but it has reignited since. Compared with other countries, the Irish housing boom has been extraordinarily vigorous: both in real and nominal terms the increase in house prices since the mid 1990s has been the highest in the OECD, with the United Kingdom and Spain ranking second and third respectively.
More favourable demand factors in comparison with developments elsewhere have surely played a role in shaping the buoyant price developments in Ireland. Growth in real disposable income since the mid 1990s has been stronger than in any other industrial country and real interest rates were among the lowest (Figure 2). The decline in inflation has also contributed by front-loading mortgage repayments. Furthermore, demographic trends were particularly favourable to housing demand in the 1990s, including strong population growth, a sharp fall in household size from a high level, a rapid acceleration in the growth of population in the household formation cohort and sizeable net immigration. Other demographic developments include the increase in the number of double income households and higher divorce rates. Another factor is the number of baby boomers investing in the buy-to-let market because of increasing worries about inadequate pension provisions for retirement.
In addition, the tax treatment of housing in Ireland has been more favourable for home ownership than in most other EU countries (van den Noord, 2005). This is reflected in a low user cost of capital. The user cost for homeowners is analogous to the cost of rental accommodation for tenants. It includes the after-tax mortgage interest rate net of capital gains, the opportunity cost associated with equity financing (usually the after-tax deposit rate), property tax (if any) and depreciation. There have been extended periods when the user cost has been negative, in particular in the late-1970s and from the mid 1990s onwards, implying a strong incentive to invest in housing. The main driving factor keeping the user cost negative has been the untaxed capital gains (on owner-occupied homes), whereas the importance of income tax deductions has diminished with the gradual decline in marginal income tax rates and a series of other tax reforms (Box 1). Since taxation of capital gains has an important negative influence on the user cost, its absence could have acted as a catalyst for the upward spiral in house prices.
Finland, Portugal and Spain are the only other countries which, like Ireland, give a tax deduction for mortgage interest payments but do not tax imputed rent or capital gains on the principal owner-occupied dwelling. However, all three have municipal taxes on property values ranging from 0.4% to 1%. The size of the tax bias in Ireland has been reduced over time as the ceiling on mortgage interest deductibility has not kept pace with the increase in house prices. Updating the estimates by van den Noord (2005) shows an overall tax wedge of –0.57% for the first seven years and –0.36% thereafter, giving Ireland the fifth-largest tax bias in the EU15.
The rise in housing demand triggered a strong response in supply, which again is unprecedented by international standards (Figure 3). House construction and residential permits per capita are among the highest in the OECD. Around a third of the housing stock is younger than ten years old. Half of the stock is detached houses, with apartments accounting for just 6%. The enormous increase in housing supply was accompanied by significant increases in real construction costs and land prices. The significant cost increases did not deter the supply of housing, which was aided by more relaxed zoning rules. Yet, despite the massive increase in the housing stock, it will almost certainly increase further in the medium term (even ignoring the effect of population growth) given that in Ireland there are significantly more adults per dwelling than in other OECD countries. If preferences in Ireland were similar to those in other EU countries, this would, ceteris paribus, lead to falling numbers of (adult) persons per dwelling. This gap has undoubtedly been a factor in the buoyant demand for housing and a driving force behind the escalation of house prices, and is likely to act for several more years. Indeed, the high cost of accommodation in Ireland may be discouraging people from forming an independent household (Fitz Gerald, 2005).
The demographic variable (the share of the population that is around the household-formation age) is included to capture the hypothesis that a younger population is likely to put extra pressure on the housing market.
It is difficult to compare prices across countries because the size, quality, location and amenities of houses can differ substantially. Comparisons are a little easier if they are restricted to the major cities, but this does not solve the problem entirely. Bearing this in mind, the available evidence suggests that average prices in Dublin are higher than in comparable cities. In a comparison of average sale prices in 2004 across a dozen European cities, the price per square metre was higher in Dublin that everywhere else (Figure 7, left panel). Some further evidence comes from cost-of-living comparisons conducted by various private-sector consultancies. These usually focus on prices or rents of inner-city apartments typically bought or rented by business executives. Here Dublin does not stand out so dramatically (Figure 7, right panel). This may be because rents are not especially high in Ireland but it may also reflect urban sprawl. Anecdotally at least, there is not a great deal of diversity in the housing stock. The centres of the main cities have not been taken over by apartment complexes and there is relatively little high-density in-fill housing. If preferences change and Irish people become more comfortable living in downtown apartments or in higher-density housing with no garden, then the distribution of prices may become more uneven: house prices in the central city may rise significantly relative to prices in the suburbs and city fringes. There is some evidence this may be happening already (Policy Exchange, 2005).
In a majority of countries, the ratios of prices to rents and prices to disposable income do not have strong trends when considered over long periods of time. The ratios may rise sharply during housing booms, but they usually fall back again through a combination of falling real house prices (i.e. a lower numerator) and rising rents or incomes (the denominator rising to catch up). In Ireland’s case, the increase in these two ratios far outstrips the cycles that have been seen in other countries before the most recent global housing boom (Figure 9), although the increase in the price-to-income ratio is in line with some other countries that have also enjoyed booming house prices in the last five years.
Affordability
The concept of housing “affordability” is popular in public discussions and with the real estate industry, perhaps because of its simplicity. While it is not particularly useful for assessing house price over-valuation, it is a useful measure of cash flow pressures. In 2005, the average mortgage repayment burden for a first time buyer was estimated to be 30% of disposable income (Central Bank, 2005), which is higher than in 1994/95, but is actually slightly lower than it was in 1991, when interest rates were much higher (Figure 10). Thus, the repayment burden is not out of line with past levels – provided, of course, that interest rates remain low.
The effects of increased housing wealth and equity withdrawal on household saving have never been strong in Ireland. The savings rate has been fluctuating around 9% throughout the housing boom. However, this does not imply that no housing equity is released, but rather that it may be recycled back into the housing market. This shows up especially in the buy-to-let market and in the rapid growth in the number of secondary or otherwise mostly vacant homes. This suggests that demand is driven, at least in part, by expectations of capital gains, which may confirm the impression of over valuation emerging from some of the quantitative indicators.
The buy-to-let market is small but has been growing fast. New buy-to-let mortgages constituted 20% of all mortgage transactions in 2004 while 30% of second-hand dwellings sold during the first half of 2004 were previously held as investment properties. The buy-to-let market is dominated by small, mostly inexperienced investors, whose primary objective is to provide for retirement. With property investors taking such an active part in the market, the question is to what extent they have driven up house prices. Attracted by the substantial capital gains and small carrying costs, many investors have entered the buy-to-let market, possibly displacing first time buyers and contributing significantly to housing demand and house prices. The main concern – and another indication of overshooting prices – is the growing divergence between property prices and rental income. Indeed, rents actually fell from 2002 to early 2005. The position of those in the buy-to-let segment of the market will continue to be sustainable only if interest rates stay low. However, if mortgage rates were to rise many of these investment positions would be loss making.
Demand for second homes appears to be another important factor in the housing market. Although housing supply has risen tremendously in recent years, a surprisingly large proportion of it appears to be satisfying demand for second-home properties (in 2005, around 15% of homeowners aged 35-54 owned a second home). As in the case of the buy-to-let market, some properties may have been acquired with the expectation that house prices would continue to grow at a fast pace for the indefinite future. More generally, an important element of the boom over the last decade has been the growth in the number of dwellings that are vacant, for whatever reasons, for most of the year. Fitz Gerald et al. (2003) calculated that the number of vacant dwellings in Ireland had increased by 80 000 from 2000 to 2003, which is equivalent to half the houses constructed over that period. On the basis of modelling work in that paper it was estimated that this additional demand would have added between 15 and 20% to house prices over the same period, which roughly corresponds to the overvaluation estimated in the econometric model above.
An over-valued housing market may have implications for financial stability, but that depends on many factors. The first point to note is that an overvaluation does not imply that prices will drop, at least if the degree of overvaluation is moderate. The housing market is unlike other asset markets in that house price dynamics are not symmetric. Prices rise quickly during booms, but in a market slump most people prefer to take their house off the market rather than sell at a loss. Hence, a small fall in prices followed by several years of a flat market is more likely than a sharp drop in house values. Put another way, the price level may remain fairly high as the market waits for the underlying fundamentals to catch up.
Even if house prices level off, there is a potential macroeconomic and financial stability issue that could arise from decline in residential construction. As noted in Chapter 1, the rate of house building will need to fall to some extent to return to its sustainable long-run level. International experience shows that this process is seldom smooth: when the investment rate turns down, it usually falls sharply (Box 3).
Definition of "booms"
Between 1960 and 2004, 49 residential construction booms have occurred in 23 countries for which data is available. A boom is defined (rather generously) as a rise in the level of real per capita residential investment of at least 15% over a five year period. In order to avoid identifying false peaks and data blips, a peak is defined as the highest point in a window of the preceding four years and the subsequent three years. By construction, the latest peak that can be identified is 2002; the analysis therefore omits the housing booms that are currently underway. In the cycles that have been identified, the average increase in real per capita residential investment from trough to peak is around 40%. The largest occurred in Korea from 1973 to 1978 (where investment rose by 160%). The trough to peak increase has exceeded 50% in 16 cases.
How common are soft landings? If a soft landing is defined as a relatively small reduction in the investment rate, they are not especially common. There have been only four cases where the decline in per capita residential investment has been smaller than one third of the increase that occurred during the boom years (these are the Netherlands after 1978, Belgium after 1990, the United Kingdom after 1998 and Finland after 2000). Soft landings are more common if they are defined as gradual declines, i.e. where it takes at least three years to hit the trough. There have been around 20 examples of these. But all of these were comparatively deep declines. If a soft landing is defined as something that is both mild and gradual, there has not been a single case out of the 49 boom bust cycles.
Ireland’s housing boom: what has driven it and have prices overshot?
David Rae and Paul van den Noord
OECD Economics Department working paper No 492
Abstract
The Irish housing market is very buoyant. The housing boom is driven by strong economic growth, dynamic demographics and low interest rates. However, large tax advantages and relatively lenient credit policies by banks have also played their part, and prices may have become overvalued. To the extent that high house prices reflect favourable tax treatment, they may lead to economic inefficiencies by drawing excessive resources into residential construction. While a soft landing appears the most likely prospect, a disorderly correction of house prices would pose risks for macroeconomic and possibly financial stability. In this context, one policy lever available to the government would be a phased removal of the tax advantages associated with housing. In addition, banks should remain cautious in their lending and provisioning policies.
House prices across the industrialised world have surged since the mid 1990s – with the notable exceptions of Germany and Japan which are both still grappling with the aftermath of real estate busts in the early 1990s. In many countries, housing demand is underpinned by an easy monetary stance (Otrok and Terrones, 2005), while over a longer period tight zoning regulations have exacerbated the upward movement in property prices in and around growth centres (Glaeser et al., 2005).
This paper argues that most of the increase in Irish house prices is justified by the economic and demographic driving forces. It should be remembered that in 1993 the average Irish house cost a mere € 75 000, which was extraordinarily low for a European country. Since then, remarkable growth in incomes, low interest rates, strong population growth, especially among the younger house-forming age groups, a surge in immigration and changing living patterns have all contributed to the boom.
Ireland’s house prices have risen dramatically since the mid 1990s. From 1995 to 2005 the price of second-hand houses more than tripled in real terms (Figure 1, left panel). House price inflation eased temporarily in 2001 but it has reignited since. Compared with other countries, the Irish housing boom has been extraordinarily vigorous: both in real and nominal terms the increase in house prices since the mid 1990s has been the highest in the OECD, with the United Kingdom and Spain ranking second and third respectively.
More favourable demand factors in comparison with developments elsewhere have surely played a role in shaping the buoyant price developments in Ireland. Growth in real disposable income since the mid 1990s has been stronger than in any other industrial country and real interest rates were among the lowest (Figure 2). The decline in inflation has also contributed by front-loading mortgage repayments. Furthermore, demographic trends were particularly favourable to housing demand in the 1990s, including strong population growth, a sharp fall in household size from a high level, a rapid acceleration in the growth of population in the household formation cohort and sizeable net immigration. Other demographic developments include the increase in the number of double income households and higher divorce rates. Another factor is the number of baby boomers investing in the buy-to-let market because of increasing worries about inadequate pension provisions for retirement.
In addition, the tax treatment of housing in Ireland has been more favourable for home ownership than in most other EU countries (van den Noord, 2005). This is reflected in a low user cost of capital. The user cost for homeowners is analogous to the cost of rental accommodation for tenants. It includes the after-tax mortgage interest rate net of capital gains, the opportunity cost associated with equity financing (usually the after-tax deposit rate), property tax (if any) and depreciation. There have been extended periods when the user cost has been negative, in particular in the late-1970s and from the mid 1990s onwards, implying a strong incentive to invest in housing. The main driving factor keeping the user cost negative has been the untaxed capital gains (on owner-occupied homes), whereas the importance of income tax deductions has diminished with the gradual decline in marginal income tax rates and a series of other tax reforms (Box 1). Since taxation of capital gains has an important negative influence on the user cost, its absence could have acted as a catalyst for the upward spiral in house prices.
Finland, Portugal and Spain are the only other countries which, like Ireland, give a tax deduction for mortgage interest payments but do not tax imputed rent or capital gains on the principal owner-occupied dwelling. However, all three have municipal taxes on property values ranging from 0.4% to 1%. The size of the tax bias in Ireland has been reduced over time as the ceiling on mortgage interest deductibility has not kept pace with the increase in house prices. Updating the estimates by van den Noord (2005) shows an overall tax wedge of –0.57% for the first seven years and –0.36% thereafter, giving Ireland the fifth-largest tax bias in the EU15.
The rise in housing demand triggered a strong response in supply, which again is unprecedented by international standards (Figure 3). House construction and residential permits per capita are among the highest in the OECD. Around a third of the housing stock is younger than ten years old. Half of the stock is detached houses, with apartments accounting for just 6%. The enormous increase in housing supply was accompanied by significant increases in real construction costs and land prices. The significant cost increases did not deter the supply of housing, which was aided by more relaxed zoning rules. Yet, despite the massive increase in the housing stock, it will almost certainly increase further in the medium term (even ignoring the effect of population growth) given that in Ireland there are significantly more adults per dwelling than in other OECD countries. If preferences in Ireland were similar to those in other EU countries, this would, ceteris paribus, lead to falling numbers of (adult) persons per dwelling. This gap has undoubtedly been a factor in the buoyant demand for housing and a driving force behind the escalation of house prices, and is likely to act for several more years. Indeed, the high cost of accommodation in Ireland may be discouraging people from forming an independent household (Fitz Gerald, 2005).
The demographic variable (the share of the population that is around the household-formation age) is included to capture the hypothesis that a younger population is likely to put extra pressure on the housing market.
It is difficult to compare prices across countries because the size, quality, location and amenities of houses can differ substantially. Comparisons are a little easier if they are restricted to the major cities, but this does not solve the problem entirely. Bearing this in mind, the available evidence suggests that average prices in Dublin are higher than in comparable cities. In a comparison of average sale prices in 2004 across a dozen European cities, the price per square metre was higher in Dublin that everywhere else (Figure 7, left panel). Some further evidence comes from cost-of-living comparisons conducted by various private-sector consultancies. These usually focus on prices or rents of inner-city apartments typically bought or rented by business executives. Here Dublin does not stand out so dramatically (Figure 7, right panel). This may be because rents are not especially high in Ireland but it may also reflect urban sprawl. Anecdotally at least, there is not a great deal of diversity in the housing stock. The centres of the main cities have not been taken over by apartment complexes and there is relatively little high-density in-fill housing. If preferences change and Irish people become more comfortable living in downtown apartments or in higher-density housing with no garden, then the distribution of prices may become more uneven: house prices in the central city may rise significantly relative to prices in the suburbs and city fringes. There is some evidence this may be happening already (Policy Exchange, 2005).
In a majority of countries, the ratios of prices to rents and prices to disposable income do not have strong trends when considered over long periods of time. The ratios may rise sharply during housing booms, but they usually fall back again through a combination of falling real house prices (i.e. a lower numerator) and rising rents or incomes (the denominator rising to catch up). In Ireland’s case, the increase in these two ratios far outstrips the cycles that have been seen in other countries before the most recent global housing boom (Figure 9), although the increase in the price-to-income ratio is in line with some other countries that have also enjoyed booming house prices in the last five years.
Affordability
The concept of housing “affordability” is popular in public discussions and with the real estate industry, perhaps because of its simplicity. While it is not particularly useful for assessing house price over-valuation, it is a useful measure of cash flow pressures. In 2005, the average mortgage repayment burden for a first time buyer was estimated to be 30% of disposable income (Central Bank, 2005), which is higher than in 1994/95, but is actually slightly lower than it was in 1991, when interest rates were much higher (Figure 10). Thus, the repayment burden is not out of line with past levels – provided, of course, that interest rates remain low.
The effects of increased housing wealth and equity withdrawal on household saving have never been strong in Ireland. The savings rate has been fluctuating around 9% throughout the housing boom. However, this does not imply that no housing equity is released, but rather that it may be recycled back into the housing market. This shows up especially in the buy-to-let market and in the rapid growth in the number of secondary or otherwise mostly vacant homes. This suggests that demand is driven, at least in part, by expectations of capital gains, which may confirm the impression of over valuation emerging from some of the quantitative indicators.
The buy-to-let market is small but has been growing fast. New buy-to-let mortgages constituted 20% of all mortgage transactions in 2004 while 30% of second-hand dwellings sold during the first half of 2004 were previously held as investment properties. The buy-to-let market is dominated by small, mostly inexperienced investors, whose primary objective is to provide for retirement. With property investors taking such an active part in the market, the question is to what extent they have driven up house prices. Attracted by the substantial capital gains and small carrying costs, many investors have entered the buy-to-let market, possibly displacing first time buyers and contributing significantly to housing demand and house prices. The main concern – and another indication of overshooting prices – is the growing divergence between property prices and rental income. Indeed, rents actually fell from 2002 to early 2005. The position of those in the buy-to-let segment of the market will continue to be sustainable only if interest rates stay low. However, if mortgage rates were to rise many of these investment positions would be loss making.
Demand for second homes appears to be another important factor in the housing market. Although housing supply has risen tremendously in recent years, a surprisingly large proportion of it appears to be satisfying demand for second-home properties (in 2005, around 15% of homeowners aged 35-54 owned a second home). As in the case of the buy-to-let market, some properties may have been acquired with the expectation that house prices would continue to grow at a fast pace for the indefinite future. More generally, an important element of the boom over the last decade has been the growth in the number of dwellings that are vacant, for whatever reasons, for most of the year. Fitz Gerald et al. (2003) calculated that the number of vacant dwellings in Ireland had increased by 80 000 from 2000 to 2003, which is equivalent to half the houses constructed over that period. On the basis of modelling work in that paper it was estimated that this additional demand would have added between 15 and 20% to house prices over the same period, which roughly corresponds to the overvaluation estimated in the econometric model above.
An over-valued housing market may have implications for financial stability, but that depends on many factors. The first point to note is that an overvaluation does not imply that prices will drop, at least if the degree of overvaluation is moderate. The housing market is unlike other asset markets in that house price dynamics are not symmetric. Prices rise quickly during booms, but in a market slump most people prefer to take their house off the market rather than sell at a loss. Hence, a small fall in prices followed by several years of a flat market is more likely than a sharp drop in house values. Put another way, the price level may remain fairly high as the market waits for the underlying fundamentals to catch up.
Even if house prices level off, there is a potential macroeconomic and financial stability issue that could arise from decline in residential construction. As noted in Chapter 1, the rate of house building will need to fall to some extent to return to its sustainable long-run level. International experience shows that this process is seldom smooth: when the investment rate turns down, it usually falls sharply (Box 3).
Definition of "booms"
Between 1960 and 2004, 49 residential construction booms have occurred in 23 countries for which data is available. A boom is defined (rather generously) as a rise in the level of real per capita residential investment of at least 15% over a five year period. In order to avoid identifying false peaks and data blips, a peak is defined as the highest point in a window of the preceding four years and the subsequent three years. By construction, the latest peak that can be identified is 2002; the analysis therefore omits the housing booms that are currently underway. In the cycles that have been identified, the average increase in real per capita residential investment from trough to peak is around 40%. The largest occurred in Korea from 1973 to 1978 (where investment rose by 160%). The trough to peak increase has exceeded 50% in 16 cases.
How common are soft landings? If a soft landing is defined as a relatively small reduction in the investment rate, they are not especially common. There have been only four cases where the decline in per capita residential investment has been smaller than one third of the increase that occurred during the boom years (these are the Netherlands after 1978, Belgium after 1990, the United Kingdom after 1998 and Finland after 2000). Soft landings are more common if they are defined as gradual declines, i.e. where it takes at least three years to hit the trough. There have been around 20 examples of these. But all of these were comparatively deep declines. If a soft landing is defined as something that is both mild and gradual, there has not been a single case out of the 49 boom bust cycles.
Wednesday, July 4, 2007
House Investment and Population Cycles
Housing Investment and Population Cycles in Euro Area Countries
Changes in Population Over Previous Year and 5-Year-Moving-Average of Changes in Gross Fix Capital Formation in Housing
Changes in Population Over Previous Year and 5-Year-Moving-Average of Changes in Gross Fix Capital Formation in Housing
Notes One
EXPLAINING GROWTH DIVERGENCES IN THE EURO AREA: THE ROLE OF RESIDENTIAL INVESTMENT
Klaus - Jürgen Gern and Carsten - Patrick Meier
IfW, Kiel Institute for the World Economy
In our econometric analysis of housing investment in the euro area we, as a first step, distinguish between Germany and the rest of the euro area. This distinction is motivated by the fact that German developments have been special in several respects over the past 20 years and, given the large size of the Germany as a proportion of the euro area economy, influence the developments on an aggregate euro area level significantly (as opposed to, e.g., Austria where housing investment—and population growth—was rather similar to German patterns).
Since swings in housing investment in Germany over the recent two decades have been associated with pronounced changes in population growth, special emphasis is given to the importance of demographic developments in explaining diverging trends in housing investment. Population growth and demographic developments that affect the number of households, such as shifts in the share of population in household formation age and falls in the average size of households, all have potentially important implications for housing demand.
We estimate functions for Germany and the rest of the euro
area where residential investment depends on the existing level of housing
stock, real income, the user cost of capital (proxied by the real interest rate) and
population growth.
In the literature, the impact of demographic developments on the housing market is usually discussed in the context of house prices.1 Several studies include demographic variables in their estimated house price equations (e.g. Meen 2002, Ahearne et al. 2005) , but they are omitted in recent VAR-studies (Sutton 2002, Tsatsaronis and Zhu 2004). Girouard and Blöndal (2001) discuss the influence of house prices on residential investment through the price-cost ratio, but do not discuss other determinants of residential investment.
Residential investment is typically a relatively volatile demand component, characterized by pronounced swings in growth rates from year to year and subject to strong cyclical fluctuations.
It is evident that, notwithstanding a large amount of heterogeneity, national
series tended to move in similar directions. This is especially true for recessionary phases (in terms of aggregate output), such as the mid 1970s, the early 1980s and early 1990s, although the timing of the peaks and bottoms varies slightly from one country to another.
In the most recent phase of weak production growth between 2001 and 2004, there is also some similarity in that most national series show at least some deceleration of growth. However, the strong deceleration of residential investment growth registered for the euro area as a whole is to a large extent due to a prolonged and pronounced decline in residential investment in Germany; housing investment in other large euro area economies such as France, Italy and Spain by contrast remained relatively strong.
While in Germany investment stagnated in the second half of the 1990 and has been falling since 2000, Spain, the Netherlands and France saw a rapid expansion of investment; in Italy investment declined in the second half of the 1990s but picked up after the start of EMU.
The standard deviation of growth rates of residential investment in the euro area is much larger than the standard deviation of aggregate output growth, reflecting the relatively pronounced volatility of this demand component. Although there is no clear trend discernible in the standard deviation over the past 40 years, it is interesting to note that differences in growth rates have been relatively small in the most recent years, while the divergence of economic growth in general and residential construction activity in particular in the years following the German unification is clearly visible.
The post-unification boom in residential investment in Germany has been associated with a sharp acceleration of population growth stemming mainly from immigration from Central and Eastern Europe and refugees from the Balkans.3 Conversely, when residential investment decelerated in the midnineties and started to decline towards the end of the century, population growth slowed to a crawl. Inspection of the relationship between population growth and residential investment growth (smoothed using centered 5-yearaverages) over a longer period of time and across other euero area countries shows, however, that such a close co-movement of these variables is not the rule.
In 1990-91, German unification led to a de-synchronization of cyclical developments, triggering a boom in Germany when most other industrial countries experienced deceleration of growth or even recession. Although some of the demand generated in Germany spilled over into neighbor countries, economic growth in the rest of (what is today) the euro area slowed down when German growth accelerated. Following a brief period of almost synchronized growth in 1993 (recession) and 1994 (recovery), from the mid-1990s onwards the German economy consistently grew less rapidly than the rest of the euro area.
Klaus - Jürgen Gern and Carsten - Patrick Meier
IfW, Kiel Institute for the World Economy
In our econometric analysis of housing investment in the euro area we, as a first step, distinguish between Germany and the rest of the euro area. This distinction is motivated by the fact that German developments have been special in several respects over the past 20 years and, given the large size of the Germany as a proportion of the euro area economy, influence the developments on an aggregate euro area level significantly (as opposed to, e.g., Austria where housing investment—and population growth—was rather similar to German patterns).
Since swings in housing investment in Germany over the recent two decades have been associated with pronounced changes in population growth, special emphasis is given to the importance of demographic developments in explaining diverging trends in housing investment. Population growth and demographic developments that affect the number of households, such as shifts in the share of population in household formation age and falls in the average size of households, all have potentially important implications for housing demand.
We estimate functions for Germany and the rest of the euro
area where residential investment depends on the existing level of housing
stock, real income, the user cost of capital (proxied by the real interest rate) and
population growth.
In the literature, the impact of demographic developments on the housing market is usually discussed in the context of house prices.1 Several studies include demographic variables in their estimated house price equations (e.g. Meen 2002, Ahearne et al. 2005) , but they are omitted in recent VAR-studies (Sutton 2002, Tsatsaronis and Zhu 2004). Girouard and Blöndal (2001) discuss the influence of house prices on residential investment through the price-cost ratio, but do not discuss other determinants of residential investment.
Residential investment is typically a relatively volatile demand component, characterized by pronounced swings in growth rates from year to year and subject to strong cyclical fluctuations.
It is evident that, notwithstanding a large amount of heterogeneity, national
series tended to move in similar directions. This is especially true for recessionary phases (in terms of aggregate output), such as the mid 1970s, the early 1980s and early 1990s, although the timing of the peaks and bottoms varies slightly from one country to another.
In the most recent phase of weak production growth between 2001 and 2004, there is also some similarity in that most national series show at least some deceleration of growth. However, the strong deceleration of residential investment growth registered for the euro area as a whole is to a large extent due to a prolonged and pronounced decline in residential investment in Germany; housing investment in other large euro area economies such as France, Italy and Spain by contrast remained relatively strong.
While in Germany investment stagnated in the second half of the 1990 and has been falling since 2000, Spain, the Netherlands and France saw a rapid expansion of investment; in Italy investment declined in the second half of the 1990s but picked up after the start of EMU.
The standard deviation of growth rates of residential investment in the euro area is much larger than the standard deviation of aggregate output growth, reflecting the relatively pronounced volatility of this demand component. Although there is no clear trend discernible in the standard deviation over the past 40 years, it is interesting to note that differences in growth rates have been relatively small in the most recent years, while the divergence of economic growth in general and residential construction activity in particular in the years following the German unification is clearly visible.
The post-unification boom in residential investment in Germany has been associated with a sharp acceleration of population growth stemming mainly from immigration from Central and Eastern Europe and refugees from the Balkans.3 Conversely, when residential investment decelerated in the midnineties and started to decline towards the end of the century, population growth slowed to a crawl. Inspection of the relationship between population growth and residential investment growth (smoothed using centered 5-yearaverages) over a longer period of time and across other euero area countries shows, however, that such a close co-movement of these variables is not the rule.
In 1990-91, German unification led to a de-synchronization of cyclical developments, triggering a boom in Germany when most other industrial countries experienced deceleration of growth or even recession. Although some of the demand generated in Germany spilled over into neighbor countries, economic growth in the rest of (what is today) the euro area slowed down when German growth accelerated. Following a brief period of almost synchronized growth in 1993 (recession) and 1994 (recovery), from the mid-1990s onwards the German economy consistently grew less rapidly than the rest of the euro area.
Monday, July 2, 2007
Migration and Trend Growth in the UK
The BoS group have this piece on UK migration.
Polish plumbers: mending your pipes and keeping your mortgage down
Migration is adding 180,000 to the UK population each year and has been boosted by workers from eight eastern European states (A8) which joined the EU in 2004. These recent migrants are young, often highly qualified and hard-working. But they are employed mainly in low skilled, low paid jobs that can be arduous and which many indigenous people will not do. Employers say they like recent migrants’ work ethic, contrasting this favourably with the soft skills such as motivation of some UK-born people. Migration raises the economy’s capacity to grow without stoking inflation, keeping interest rates lower than they would have been, saving an estimated £500 per year on the average mortgage. This yields an extra £16b of output over five years, enough to pay for the 2012 Olympics facilities five times.
and they link to: Trend growth: new evidence and prospects. UK Treasury.
There has also been significant new evidence published since Budget 2006 on migration flows and population trends. This evidence is strong enough to lead the Treasury to revise the current working-age population projection for the post-2006 period. Analysis of these new data support a higher contribution of net inward migration to growth in working age population post-2006, leading to an upward revision to working-age population growth post-2006 from 0.4 per cent to 0.6 per cent a year. This upward revision offsets the downward effect of post-war baby-boom women retiring that was previously driving the fall in the trend output growth assumption post-2006. Therefore, the upward revision to working-age population growth implies an increase in the post-2006 neutral estimate of trend output growth from 2| per cent to 2~ per cent a year.
Polish plumbers: mending your pipes and keeping your mortgage down
Migration is adding 180,000 to the UK population each year and has been boosted by workers from eight eastern European states (A8) which joined the EU in 2004. These recent migrants are young, often highly qualified and hard-working. But they are employed mainly in low skilled, low paid jobs that can be arduous and which many indigenous people will not do. Employers say they like recent migrants’ work ethic, contrasting this favourably with the soft skills such as motivation of some UK-born people. Migration raises the economy’s capacity to grow without stoking inflation, keeping interest rates lower than they would have been, saving an estimated £500 per year on the average mortgage. This yields an extra £16b of output over five years, enough to pay for the 2012 Olympics facilities five times.
and they link to: Trend growth: new evidence and prospects. UK Treasury.
There has also been significant new evidence published since Budget 2006 on migration flows and population trends. This evidence is strong enough to lead the Treasury to revise the current working-age population projection for the post-2006 period. Analysis of these new data support a higher contribution of net inward migration to growth in working age population post-2006, leading to an upward revision to working-age population growth post-2006 from 0.4 per cent to 0.6 per cent a year. This upward revision offsets the downward effect of post-war baby-boom women retiring that was previously driving the fall in the trend output growth assumption post-2006. Therefore, the upward revision to working-age population growth implies an increase in the post-2006 neutral estimate of trend output growth from 2| per cent to 2~ per cent a year.
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