Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
Conceptual Changes Adopted In The 1953 Revision Were Not Made For 1929-1939 Data, But The Major Components Of The Old Series Were Linked To The Revised Series On The Basis Of The Relationship Between The Old And New Estimates At The End Of 1939. The Amounts Involved In These Adjustments Were Relatively Small. Data For 1956-May 1960 Have Been Slightly Revised. Major Revisions Begin In June 1960. Data For Alaska Included From January 1959; Data For Hawaii From August 1959. Source: Federal Reserve Board, Data For 1929-1939: Bulletin, April 1953, P. 354; Data For 1940-1947: Same Issue, Pp. 346-347; Data For 1948-1954: Bulletin Of October 1956; Data For 1955: Supplement To Banking And Money Statistics, Section 16 (New), 1965 Edition; For 1956-October 1968 Data: Bulletin Of December 1968; Data For November 1968: Statistical Release, G-19, "Consumer Credit" This NBER data series m10044 appears on the NBER website in Chapter 10 at http://www.nber.org/databases/macrohistory/contents/chapter10.html. NBER Indicator: m10044
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
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 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/).
Real effective exchange rates are calculated as weighted averages of bilateral exchange rates adjusted by relative consumer prices. Copyright, 2016, Bank for International Settlements (BIS). Terms and conditions of use are available at http://www.bis.org/terms_conditions.htm#Copyright_and_Permissions.
Real effective exchange rates are calculated as weighted averages of bilateral exchange rates adjusted by relative consumer prices. Copyright, 2016, Bank for International Settlements (BIS). Terms and conditions of use are available at http://www.bis.org/terms_conditions.htm#Copyright_and_Permissions.
Notes regarding this series can be found in International Financial Statistics Yearbooks produced by the International Monetary Fund (IMF). We have requested these publications from the IMF. Notes on this series will populate once they become available. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
Notes regarding this series can be found in International Financial Statistics Yearbooks produced by the International Monetary Fund (IMF). We have requested these publications from the IMF. Notes on this series will populate once they become available. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
Gross debt consists of all liabilities that require payment or payments of interest and/or principal by the debtor to the creditor at a date or dates in the future. This includes debt liabilities in the form of Special Drawing Rights (SDRs), currency and deposits, debt securities, loans, insurance, pensions and standardized guarantee schemes, and other accounts payable. Thus, all liabilities in the Government Finance Statistics Manual 2001 (GFSM 2001) system are debt, except for equity and investment fund shares and financial derivatives and employee stock options. Debt can be valued at current market, nominal, or face values (GFSM 2001, paragraph 7.110). A projection of this data can be found at https://fred.stlouisfed.org/series/GGGDTPAUA188N. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).
OECD Descriptor ID: CPALTT01 OECD unit ID: PC OECD country ID: SWE 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: NAEXCP03 OECD unit ID: EUR OECD country ID: GRC 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
Series Is Presented Here As Two Variables--(1)-- Original Data, 1935-1949 (2)--Original Data, 1946-1968. Through 1949 The Data Repesent Averages Of 4 Or 5 Quotations A Month; Thereafter, They Are Daily Quotations. For 1946-1947 The Averages Have Been Derived From The Source (See Above) With Indexes Having Only 1 Decimal; All Published Averages, However, Are Based On Indexes Carried To Two Decimal Places. Source: Bls Table (Unpublished): Daily Spot Market Price Index, Raw Industrials: 1956 And Earlier, " (December, 1962), And Similar Table Dated October, 1962 For 1957-September, 1962. Thereafter: "Daily Spot Market Price Indexes And Prices, " Weekly Bls Release. Averages Also In Survey Of Current Business. This NBER data series m04201b appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04201b
OECD Descriptor ID: NAEXCP03 OECD unit ID: EUR OECD country ID: ITA 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: NAEXCP03 OECD unit ID: EUR OECD country ID: FRA 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
Copyright, 2016, OECD. Reprinted with permission. All OECD data should be cited as follows: OECD (2010), OECD National Accounts Statistics, http://dx.doi.org/10.1787/na-data-en, (accessed on date)
OECD Descriptor ID: NAEXCP06 OECD unit ID: GBP OECD country ID: GBR 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
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. The CFSI is designed to track distress in the US financial system on a continuous basis giving the financial-system supervisors the ability to monitor stressful episodes as they are building in the economy. Such early detection is important because financial stress can quickly be amplified when stress is occurring in more than one market. The CFSI tracks stress in six types of markets: credit markets, equity markets, foreign exchange markets, funding markets (interbank markets), real estate markets, and securitization markets. The CFSI is a coincident indicator of systemic stress, where a high value of CFSI indicates high systemic financial stress. Units of CFSI are expressed as standardized differences from the mean (z-scores). The CFSI data for weekends and holidays is extrapolated. To interpret the stress continuum, CFSI is first divided it into four levels or grades. The grade thresholds are dynamic and move slowly over time. The four grades are: Grade Description Range Grade 1 Low stress period CFSI < -0.733 Grade 2 Normal stress period -0.733 ≥ CFSI < 0.544 Grade 3 Moderate stress period 0.544 ≥ CFSI < 1.82 Grade 4 Significant stress period CFSI ≥ 1.82
Series Is Presented Here As Four Variables--(1)--Original Data, 1873-1890 (2)--Original Data, 1890-1892; (3)--Original Data, 1889-1894 (7)--Original Data, 1894-1958. Data Are Averages Of Weekly Quotations. Discrepancies Between Bls Figures And Those Reported In Iron Age Were Checked By Averaging Weekly Figures In Iron Age. In Most Cases The Iron Age Monthly Figures Were Incorrectly Computed. March, 1951-May, 1952 And August, 1952-January, 1953 Prices Reflect The Ops Basing Point Price Ceiling. The Figure For April, 1958, Is For Three Weeks Only Source: Iron Age, Weekly Issues, For Data From 1894-1900. For The Years 1901-1912, Data Were Taken From Iron Age, January 2, 1902, P.10, January 1, 1903, P.48, And January 7, 1915, P.15. 1913-1939 Data Are From Bls Bulletins And "Wholesale Prices" And Iron Age, January 4, 1923, P.74, January 4, 1940, And Following Issues. This NBER data series m04142d appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04142d
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 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 active single-family and condo/townhome listings for a given market during the specified month (excludes pending listings). 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/).
Series Is Presented Here As Three Variables--(1)--Original Data, 1914-1918 (2)--Original Data, 1914-1920 (3)--Original Data, 1914-1935 Data Cover The Territory Of Pre-War Germany. Coverage Includes Ingots And Castings; Welded Steel (Schweiss Stahl) Is Excluded. Source: Wirtschaftsgruppe Eisen Schaffende Industrie (Formerly Verein Deutscher Eisen Und Stahl Industrieller), "Die Rohstahl - Gerwinnung Im Deutscher Zollgebiet, 1910 Bis 1924", February 1925, Pp. 9-12. This NBER data series m01137a appears on the NBER website in Chapter 1 at http://www.nber.org/databases/macrohistory/contents/chapter01.html. NBER Indicator: m01137a
Indeed calculates the index change in seasonally-adjusted job postings since February 1, 2020, the pre-pandemic baseline. Indeed seasonally adjusts each series based on historical patterns in 2017, 2018, and 2019. Each series, including the national trend, occupational sectors, and sub-national geographies, is seasonally adjusted separately. Indeed switched to this new methodology in December 2022 and now reports all historical data using this new methodology. Historical numbers have been revised and may differ significantly from originally reported values. The new methodology applies a detrended seasonal adjustment factor to the index change in job postings. For more information, see Frequently Asked Questions (https://www.hiringlab.org/indeed-data-faq/) regarding Indeed Data. Copyrighted: Pre-approval required. Contact Indeed to request permission to use the data at their contact information provided here (https://github.com/hiring-lab/data#readme). End Users are excluded of any warranty and liability on the part of Indeed for the accuracy of the Indeed Data. End Users will refrain from any external distribution of Indeed Data except in oral or written presentations, provided that such portions or derivations are incidental to and supportive of such presentations and, provided further that the End Users shall not distribute or disseminate in such presentations any amount of Indeed Data which could cause such presentations to be susceptible to use substantially as a source of, or substitute for Indeed Data. End Users agree to credit Indeed as the source and owner of the Indeed Data when making it available to third parties in any permissible manner as well as in internal use. End Users agree to not sell or otherwise provide the Indeed Data obtained from Licensee to third parties.
OECD Data Filters: REF_AREA: POL MEASURE: CPI UNIT_MEASURE: IX METHODOLOGY: N EXPENDITURE: CP045_0722 ADJUSTMENT: N TRANSFORMATION: _Z FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Data Filters: REF_AREA: USA MEASURE: IN UNIT_MEASURE: PB ACTIVITY: _Z ADJUSTMENT: Y TRANSFORMATION: _Z TIME_HORIZ: FT METHODOLOGY: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
What is the Survey of Economic Conditions? Contacts located in the Seventh Federal Reserve District are asked to rate various aspects of economic conditions along a seven-point scale ranging from "large increase" to "large decrease." A series of diffusion indexes summarizing the distribution of responses is then calculated. How are the indexes constructed? Respondents' answers on the seven-point scale are assigned a numeric value ranging from +3 to –3. Each diffusion index is calculated as the difference between the number of respondents with answers above their respective average responses and the number of respondents with answers below their respective average responses, divided by the total number of respondents. The index is then multiplied by 100 so that it ranges from +100 to −100 and will be +100 if every respondent provides an above-average answer and –100 if every respondent provides a below-average answer. Respondents with no prior history of responses are excluded from the calculation. What do the numbers mean? Respondents' respective average answers to a question can be interpreted as representing their historical trends, or long-run averages. Thus, zero index values indicate, on balance, average growth (or a neutral outlook) for activity, hiring, capital spending, and cost pressures. Positive index values indicate above-average growth (or an optimistic outlook) on balance, and negative values indicate below-average growth (or a pessimistic outlook) on balance. Beginning with the May 12, 2020 release, the CFSEC moved to a monthly release schedule. This release, with data for April 2020, now contains estimated monthly historical values for the CFSEC indexes, as will all future releases. For additional information on how the survey and indexes changed, see the CFSEC FAQs available here (https://www.chicagofed.org/research/data/cfsec/current-data). Prior to April 2022, the Chicago Fed Survey of Economic Conditions was named the Chicago Fed Survey of Business Conditions (CFSBC). The name change was made to better represent the survey’s aim and base of respondents. The goal of the survey is to assess the state of the economy in the Seventh Federal Reserve District. Moreover, since the beginning of the survey, it was been filled out by both business and nonbusiness contacts.
OECD Descriptor ID: PRINTO01 OECD unit ID: CAD OECD country ID: CAN 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 Data Filters: REF_AREA: AUT COUNTERPART_AREA: W UNIT_MEASURE: XDC TRADE_FLOW: X PRODUCT_TYPE: C ADJUSTMENT: Y TRANSFORMATION: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Data Filters: REF_AREA: COL COUNTERPART_AREA: W UNIT_MEASURE: XDC TRADE_FLOW: X PRODUCT_TYPE: C ADJUSTMENT: Y TRANSFORMATION: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Data Filters: REF_AREA: FRA MEASURE: CPI UNIT_MEASURE: PA METHODOLOGY: N EXPENDITURE: _TXCP01_NRG ADJUSTMENT: N TRANSFORMATION: GY FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Data Filters: REF_AREA: AUS COUNTERPART_AREA: W UNIT_MEASURE: XDC TRADE_FLOW: X PRODUCT_TYPE: C ADJUSTMENT: Y TRANSFORMATION: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Descriptor ID: LRUNTTTT OECD unit ID: PC OECD country ID: KOR 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 more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). There is more information about home price sales pairs in the Methodology section. Copyright, 2016, Standard & Poor's Financial Services LLC. Reprinted with permission.
Monthly data is taken as the average of daily data. In order to fully understand the values in this series, it is necessary to consult the corresponding publication document provided at https://data.snb.ch/en/topics/texts#!/doc/explanations_snb
OECD Descriptor ID: PIEAMP02 OECD unit ID: PC OECD country ID: GBR 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
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/).
OECD Data Filters: REF_AREA: GRC MEASURE: PRVM UNIT_MEASURE: IX ACTIVITY: BTE ADJUSTMENT: Y TRANSFORMATION: _Z TIME_HORIZ: _Z METHODOLOGY: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Descriptor ID: CPALTT01 OECD unit ID: PC OECD country ID: NOR 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: CPALTT01 OECD unit ID: PC OECD country ID: MEX 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
The data for household debt comprise debt incurred by resident households of the economy only. This FSI measures the overall level of household indebtedness (commonly related to consumer loans and mortgages) as a share of GDP. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
Credit is provided by domestic banks, all other sectors of the economy and non-residents. The "private non-financial sector" includes non-financial corporations (both private-owned and public-owned), households and non-profit institutions serving households as defined in the System of National Accounts 2008. The series have quarterly frequency and capture the outstanding amount of credit at the end of the reference quarter. In terms of financial instruments, credit covers loans and debt securities.(1) The combination of different sources and data from various methodological frameworks resulted in breaks in the series. The BIS is therefore, in addition, publishing a second set of series adjusted for breaks, which covers the same time span as the unadjusted series. The break-adjusted series are the result of the BIS's own calculations, and were obtained by adjusting levels through standard statistical techniques described in the special feature on the long credit series of the March 2013 issue of the BIS Quarterly Review at https://www.bis.org/publ/qtrpdf/r_qt1303h.htm. (1) Source Code: Q:JP:P:A:M:USD:A (1) Bank for International Settlements. "Long series on credit to private non-financial ://www.bis.org/statistics/credtopriv.htm Copyright, 2016, Bank for International Settlements (BIS). Terms and conditions of use are available at http://www.bis.org/terms_conditions.htm#Copyright_and_Permissions. Unless otherwise specified, series values are market values.
OECD Data Filters: REF_AREA: COL MEASURE: CPI UNIT_MEASURE: PA METHODOLOGY: N EXPENDITURE: _T ADJUSTMENT: N TRANSFORMATION: GY FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
Notes regarding this series can be found in International Financial Statistics Yearbooks produced by the International Monetary Fund (IMF). We have requested these publications from the IMF. Notes on this series will populate once they become available. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
OECD Descriptor ID: LRHUTTTT OECD unit ID: PC OECD country ID: ITA 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: NAEXCP01 OECD unit ID: CAD OECD country ID: CAN 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
Source Code: Q:5R:R:771 The series is deflated using CPI. For more information, please see https://www.bis.org/statistics/pp_detailed.htm. Any use of the series shall be cited as follows: "Sources: National sources, BIS Residential Property Price database, http://www.bis.org/statistics/pp.htm." Copyright, 2016, Bank for International Settlements (BIS). Terms and conditions of use are available at http://www.bis.org/terms_conditions.htm#Copyright_and_Permissions.
OECD Descriptor ID: IRSTCB01 OECD unit ID: PC OECD country ID: CZE 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 Data Filters: REF_AREA: CHL MEASURE: IRSTCI UNIT_MEASURE: PA ACTIVITY: _Z ADJUSTMENT: _Z TRANSFORMATION: _Z FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
OECD Descriptor ID: MABMM301 OECD unit ID: ZAR OECD country ID: ZAF 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 Data Filters: REF_AREA: COL MEASURE: IR3TIB UNIT_MEASURE: PA ACTIVITY: _Z ADJUSTMENT: _Z TRANSFORMATION: _Z FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
Eurostat unit ID: CP_MNAC Eurostat item ID: B1GQ Eurostat country ID: DK Copyright, European Union, http://ec.europa.eu, 1995-2016. Complete terms of use are available at https://ec.europa.eu/geninfo/legal_notices_en.htm (https://ec.europa.eu/geninfo/legal_notices_en.htm).
OECD Data Filters: REF_AREA: GBR MEASURE: LF_WAP UNIT_MEASURE: PT_WAP_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: _T AGE: Y15T64 ACTIVITY: _Z FREQ: Q All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).
Copyright, European Union, 1995-2016, http://ec.europa.eu/geninfo/legal_notices_en.htm#copyright.