OECD descriptor ID: CPRPTT02 OECD unit ID: IXOB OECD country ID: GBR All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database),http://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission.

Calendar year average. This series was constructed by the Bank of England as part of the Three Centuries of Macroeconomic Data project by combining data from a number of academic and official sources. For more information, please refer to the Three Centuries spreadsheet at https://www.bankofengland.co.uk/statistics/research-datasets. Users are advised to check the underlying assumptions behind this series in the relevant worksheets of the spreadsheet. In many cases alternative assumptions might be appropriate. Users are permitted to reproduce this series in their own work as it represents Bank calculations and manipulations of underlying series that are the copyright of the Bank of England provided that underlying sources are cited appropriately. For appropriate citation please see the Three Centuries spreadsheet for guidance and a list of the underlying sources.

OECD Descriptor ID: IRLOHO02 OECD unit ID: PC OECD country ID: LUX All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

For Further Information See Source. Source: Manuel Gottlieb, "Long Swings In Urban Development, " Table E-9 This NBER data series a02291 appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: a02291

Percentage points contribution to GDP calculated within the historical chains of data. This series was constructed by the Bank of England as part of the Three Centuries of Macroeconomic Data project by combining data from a number of academic and official sources. For more information, please refer to the Three Centuries spreadsheet at https://www.bankofengland.co.uk/statistics/research-datasets. Users are advised to check the underlying assumptions behind this series in the relevant worksheets of the spreadsheet. In many cases alternative assumptions might be appropriate. Users are permitted to reproduce this series in their own work as it represents Bank calculations and manipulations of underlying series that are the copyright of the Bank of England provided that underlying sources are cited appropriately. For appropriate citation please see the Three Centuries spreadsheet for guidance and a list of the underlying sources.

In May of 2016, the source discovered errors in the calculation of the CFSI and began a detailed review of the index and its underlying model. Following that review, the source decided to discontinue the CFSI. https://www.clevelandfed.org/en/our-research/indicators-and-data/cleveland-financial-stress-index.aspx The source has posted to their website a message regarding this release: Cleveland Financial Stress Index under review and a revised index expected in the fourth quarter of 2016. A thorough review of the index is being conducted to both simplify the index and enhance its robustness, while also taking into consideration changes in financial markets and institutions. This review and the revisions to the CFSI are expected to be completed sometime during the fourth quarter of this year, and additional details will be made available at that time. Thank you for your patience while we improve the CFSI. This chart shows the contribution of the securitization of the residential mortgage-backed security spread to the CFSI. This spread is measured as the difference between the yield on residential mortgage-backed securities and 30-Year Treasury. It captures the ability of originators to raise capital and the relative riskiness of the securitized asset.

This series is constructed as the aggregated daily amount value of the RRP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A reverse repurchase agreement (known as reverse repo or RRP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Market Committee sells a security to an eligible counterparty with an agreement to repurchase that same security at a specified price at a specific time in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies. For more information, see https://www.newyorkfed.org/markets/rrp_faq.html

This series is constructed as the aggregated daily amount value of the RRP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A reverse repurchase agreement (known as reverse repo or RRP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Market Committee sells a security to an eligible counterparty with an agreement to repurchase that same security at a specified price at a specific time in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies. For more information, see https://www.newyorkfed.org/markets/rrp_faq.html

This series is constructed as the aggregated daily amount value of the RRP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A reverse repurchase agreement (known as reverse repo or RRP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Market Committee sells a security to an eligible counterparty with an agreement to repurchase that same security at a specified price at a specific time in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies. For more information, see https://www.newyorkfed.org/markets/rrp_faq.html

This series is constructed as the aggregated daily amount value of the RP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A repurchase agreement (known as repo or RP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Maker Committee buys a security from an eligible counterparty under an agreement to resell that security in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies.

In May of 2016, the source discovered errors in the calculation of the CFSI and began a detailed review of the index and its underlying model. Following that review, the source decided to discontinue the CFSI. https://www.clevelandfed.org/en/our-research/indicators-and-data/cleveland-financial-stress-index.aspx The source has posted to their website a message regarding this release: Cleveland Financial Stress Index under review and a revised index expected in the fourth quarter of 2016. A thorough review of the index is being conducted to both simplify the index and enhance its robustness, while also taking into consideration changes in financial markets and institutions. This review and the revisions to the CFSI are expected to be completed sometime during the fourth quarter of this year, and additional details will be made available at that time. Thank you for your patience while we improve the CFSI. This chart shows the contribution of the commercial mortgage-backed security spread to CFSI. This spread is measured as the difference between the yield on commercial mortgage-backed securities and 5-Year Treasury. It captures the ability of originators to raise capital and the relative riskiness of the securitized asset

This index includes rate locks from U.S. Department of Agriculture loans. Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

This index includes rate locks from U.S. Department of Veterans Affairs loans. Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

This index includes rate locks from Federal Housing Authority loans. Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

Optimal Blue Mortgage Market Indices (https://www2.optimalblue.com/obmmi/)™ (OBMMI™) is calculated from actual locked rates with consumers across over one-third of all mortgage transactions nationwide. OBMMI includes multiple mortgage pricing indices developed around the most popular products and specific borrower and loan level attributes. Each index is calculated as the average of all appropriate rate locks locked through the Optimal Blue product eligibility and pricing engine on a given day. More details about methodology and definitions are available here (https://www2.optimalblue.com/obmmi/).

This series is constructed as the aggregated daily amount value of the RP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A repurchase agreement (known as repo or RP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Maker Committee buys a security from an eligible counterparty under an agreement to resell that security in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies.

This series is constructed as the aggregated daily amount value of the RP transactions reported by the New York Fed as part of the Temporary Open Market Operations. Temporary open market operations involve short-term repurchase and reverse repurchase agreements that are designed to temporarily add or drain reserves available to the banking system and influence day-to-day trading in the federal funds market. A repurchase agreement (known as repo or RP) is a transaction in which the New York Fed under the authorization and direction of the Federal Open Maker Committee buys a security from an eligible counterparty under an agreement to resell that security in the future. For these transactions, eligible securities are U.S. Treasury instruments, federal agency debt and the mortgage-backed securities issued or fully guaranteed by federal agencies.

The count of listings which have had their price increased in a given market during the month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

Source: Life Insurance Association Of America, Data For 1952-1960 Are From Association Files; Data For 1961-1967 Are From The Monthly Release, "Forward Investment Of Commitments Of Life Insurance Companies" This NBER data series m10127 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10127

Source: Life Insurance Association Of America, Data For 1952-1960 Are From Association Files; Data For 1961-1967 Are From The Monthly Release, "Forward Investment Of Commitments Of Life Insurance Companies" This NBER data series m10128 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10128

Source: Life Insurance Association Of America, Data For 1952-1960 Are From Association Files; Data For 1961-1967 Are From The Monthly Release, "Forward Investment Of Commitments Of Life Insurance Companies" This NBER data series m10129 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10129

Data Are At Annual Rate. Source: Data Derived By NBER From Series 10111-115 (Mortgage Debt Held By Financial Institutions And Life Insurance Companies) This NBER data series m10131 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10131

Source: Life Insurance Association Of America, Data For 1952-1963: Mimeographed Summary Table On "New Commitments Of Reporting Life Insurance Companies"; Data For 1964-1965: Monthly Tabulation Of "Forward Investment Commitments Of Life Insurance Companies" This NBER data series m10169 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10169

Source: Life Insurance Association Of America, Data For 1952-1963: Mimeographed Summary Table On "New Commitments Of Reporting Life Insurance Companies"; Data For 1964-1965: Monthly Tabulation Of "Forward Investment Commitments Of Life Insurance Companies" This NBER data series m10170 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10170

Source: Life Insurance Association Of America, Data For 1952-1963: Mimeographed Summary Table On "New Commitments Of Reporting Life Insurance Companies"; Data For 1964-1965: Monthly Tabulation Of "Forward Investment Commitments Of Life Insurance Companies" This NBER data series m10171 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10171

Series Is Presented Here As Three Variables--(1)--Original Data, 1955-1959 (2)--Original Data, 1959-1966 (3)--Original Data, 1965-1968. Bank Holdings Are Here Represented By Those Of The Weekly Reporting Member Banks (Between 80% And 90% Of Commercial Banks) And They Refer To The Last Wednesday Of Each Month. The Member Bank Statement Was Revised In July 1959; There Was Only Little Effect On Real Estate Loans Except That Of Increase In Coverage (See The Variables Covering 1959-1966. Source: Data Derived By NBER From The Following Sources: Federal Reserve Bulletins; Fhlb"Selected Balance Sheet Data, All Operating Savings And Loan Associations"; Savings Bank Journal; Statistical Bulletin, National Association Of Mutual Savings Banks;"Trends In Savings And Lending At Savings And Load Associations";"The Life Insurance Tally" This NBER data series m10130a appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10130a

Series Is Presented Here As Three Variables--(1)--Original Data, 1955-1959 (2)--Original Data, 1959-1966 (3)--Original Data, 1965-1968. The Figures For January-June, 1959 Include Member Bank Holdings Adjusted To Reflect New Coverage; From July 1959 On, Member Bank Holdings Represent Revised Figures. Source: Data Derived By NBER From The Following Sources: Federal Reserve Bulletins; Fhlb"Selected Balance Sheet Data, All Operating Savings And Loan Associations"; Savings Bank Journal; Statistical Bulletin, National Association Of Mutual Savings Banks;"Trends In Savings And Lending At Savings And Load Associations";"The Life Insurance Tally" This NBER data series m10130b appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10130b

Series Is Presented Here As Three Variables--(1)--Original Data, 1955-1959 (2)--Original Data, 1959-1966 (3)--Original Data, 1965-1968. The Figures For January Of Both 1966 And 1967 Reflect Changes In Coverage For Savings And Loan Associations. Month To Month Changes Are Derived From The First January Figure For December-January; From The Second January Figure For January-February. Source: Data Derived By NBER From The Following Sources: Federal Reserve Bulletins; Fhlb"Selected Balance Sheet Data, All Operating Savings And Loan Associations"; Savings Bank Journal; Statistical Bulletin, National Association Of Mutual Savings Banks;"Trends In Savings And Lending At Savings And Load Associations";"The Life Insurance Tally" This NBER data series m10130c appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10130c

Source: Federal Home Loan Bank Board, Supplements To"Survey Of Current Business, " 1939-June 1954, Except 1944-46, "Survey Of Current Business, May 1950;"Mortgage Recording Letter" Thereafter This NBER data series m02173 appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: m02173

Series Is Presented Here As 2 Variables: (1) Original Data, 1938-40; (2) Original Data, 1945-56. Source: Federal Housing Administration, "Monthly Report Of Fha Insuring Operations" This NBER data series m02163a appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: m02163a

Series Is Presented Here As 2 Variables: (1) Original Data, 1938-40; (2) Original Data, 1945-56. Source: Federal Housing Administration, "Monthly Report Of Fha Insuring Operations" This NBER data series m02163b appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: m02163b

Series Is Presented Here As 2 Variables: (1) Original Data, 1938-41; (2) Original Data, 1947-56. Figures For 11/1946-3/1948, And 5/1950 Adjusted Downward By Source To "Eliminate Effects Of Amendments To The National Housing Act Or Of Administrative Changes Affecting The Magnitude Of These Data Series." - Letter Of 6/6/1956 To NBER By A. F. Thornton, Director, Div. Of Res. & Statistics, F.H.A. Source: Federal Housing Administration, Division Of Research And Statistics This NBER data series m02164a appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: m02164a

Series Is Presented Here As 2 Variables: (1) Original Data, 1938-41; (2) Original Data, 1947-56. Figures For 11/1946-3/1948, And 5/1950 Adjusted Downward By Source To "Eliminate Effects Of Amendments To The National Housing Act Or Of Administrative Changes Affecting The Magnitude Of These Data Series." - Letter Of 6/6/1956 To NBER By A. F. Thornton, Director, Div. Of Res. & Statistics, F.H.A. Source: Federal Housing Administration, Division Of Research And Statistics This NBER data series m02164b appears on the NBER website in Chapter 2 at http://www.nber.org/databases/macrohistory/contents/chapter02.html. NBER Indicator: m02164b

Series Is Presented Here As Two Variables--(1)--Original Data, 1913-1937 (2)--Original Data, 1933-1944. Monthly Data Were Available Beginning In 1933. Annual Averages Date To 1913. The 1937 Annual Figure For The Two Variables Has A Ratio Of 1.063 (1937 2Nd Segment Divided By The 1St Segment Yields 877.43/825.31=1.063. Source: Bls Letters For 1933, 1934, 1936, 1937; Bls "Wholesale Prices, " January, 1936, P.17, For 1935; Current Bulletins For 1938 And Succeeding Years. This NBER data series m04137b appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04137b

OECD descriptor ID: CPRPTT02 OECD unit ID: IXOB OECD country ID: GBR All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database),http://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission.

This series was constructed by the Bank of England as part of the Three Centuries of Macroeconomic Data project by combining data from a number of academic and official sources. For more information, please refer to the Three Centuries spreadsheet at https://www.bankofengland.co.uk/statistics/research-datasets. Users are advised to check the underlying assumptions behind this series in the relevant worksheets of the spreadsheet. In many cases alternative assumptions might be appropriate. Users are permitted to reproduce this series in their own work as it represents Bank calculations and manipulations of underlying series that are the copyright of the Bank of England provided that underlying sources are cited appropriately. For appropriate citation please see the Three Centuries spreadsheet for guidance and a list of the underlying sources.

OECD Descriptor ID: IRLOHO02 OECD unit ID: PC OECD country ID: LUX All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

OECD descriptor ID: SWE.CP100000.CTGY.M OECD unit ID: OECD country ID: CP100000 All OECD data should be cited as follows: OECD,"Main Economic Indicators - complete database"Main Economic Indicators(database)http://dx.doi.org/10.1787/data-00052-en(Accessed on date)Copyright, 2016, OECD. Reprinted with permission.

Data Through June 1961 Are Based On 25 Year Mortgages Prepaid In 12 Years; Data For July 1961-1965 Are Based On 30 Year Mortgages Prepaid In 15 Years. Source: U.S. Department Of Commerce, Business Condition Digest. This NBER data series m13045 appears on the NBER website in Chapter 13 at http://www.nber.org/databases/macrohistory/contents/chapter13.html. NBER Indicator: m13045

The count of listings which have had their price increased in a given market during the month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The median listing price per square foot in a given market during the specified month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The median listing price per square foot in a given market during the specified month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The count of new listings added to the market in a given geography during the month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The percent change in days in the median number of days on market for listings in a given geography from the previous month. With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The median number of days on market of listings in a given geography during the specified month (calculated from list date to closing, pending, or off-market date depending on data availability). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

Market size rank based on total number of households With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

The median home size in square feet for listings in a given market during the specified month. With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/). With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).