Eurostat unit ID: CP_MNAC Eurostat item ID: B1GQ Eurostat country ID: EU28 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).
This time series is an interpretation of Organisation of Economic Development (OECD) Composite Leading Indicators: Reference Turning Points and Component Series data, which can be found at http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm. The OECD identifies months of turning points without designating a date within the month that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the month. The arbitrary convention does not reflect any judgment on this issue by the OECD. Our time series is composed of dummy variables that represent periods of expansion and recession. A value of 1 is a recessionary period, while a value of 0 is an expansionary period. For this time series, the recession begins the first day of the period following a peak and ends on the last day of the period of the trough. For more options on recession shading, see the notes and links below. The recession shading data that we provide initially comes from the source as a list of dates that are either an economic peak or trough. We interpret dates into recession shading data using one of three arbitrary methods. All of our recession shading data is available using all three interpretations. The period between a peak and trough is always shaded as a recession. The peak and trough are collectively extrema. Depending on the application, the extrema, both individually and collectively, may be included in the recession period in whole or in part. In situations where a portion of a period is included in the recession, the whole period is deemed to be included in the recession period. The first interpretation, known as the midpoint method, is to show a recession from the midpoint of the peak through the midpoint of the trough for monthly and quarterly data. For daily data, the recession begins on the 15th of the month of the peak and ends on the 15th of the month of the trough. Daily data is a disaggregation of monthly data. For monthly and quarterly data, the entire peak and trough periods are included in the recession shading. This method shows the maximum number of periods as a recession for monthly and quarterly data. The Federal Reserve Bank of St. Louis uses this method in its own publications. A version of this time series represented using the midpoint method can be found at: https://fred.stlouisfed.org/series/INDRECDM The second interpretation, known as the trough method, is to show a recession from the period following the peak through the trough (i.e. the peak is not included in the recession shading, but the trough is). For daily data, the recession begins on the first day of the first month following the peak and ends on the last day of the month of the trough. Daily data is a disaggregation of monthly data. The trough method is used when displaying data on FRED graphs. The trough method is used for this series. The third interpretation, known as the peak method, is to show a recession from the period of the peak to the trough (i.e. the peak is included in the recession shading, but the trough is not). For daily data, the recession begins on the first day of the month of the peak and ends on the last day of the month preceding the trough. Daily data is a disaggregation of monthly data. A version of this time series represented using the peak method can be found at: https://fred.stlouisfed.org/series/INDRECDP The OECD CLI system is based on the "growth cycle" approach, where business cycles and turning points are measured and identified in the deviation-from-trend series. The main reference series used in the OECD CLI system for the majority of countries is industrial production (IIP) covering all industry sectors excluding construction. This series is used because of its cyclical sensitivity and monthly availability, while the broad based Gross Domestic Product (GDP) is used to supplement the IIP series for identification of the final reference turning points in the growth cycle. Zones aggregates of the CLIs and the reference series are calculated as weighted averages of the corresponding zone member series (i.e. CLIs and IIPs). Up to December 2008 the turning points chronologies shown for regional/zone area aggregates or individual countries are determined by the rules established by the National Bureau of Economic Research (NBER) in the United States, which have been formalized and incorporated in a computer routine (Bry and Boschan) and included in the Phase-Average Trend (PAT) de-trending procedure. Starting from December 2008 the turning point detection algorithm is decoupled from the de-trending procedure, and is a simplified version of the original Bry and Boschan routine. (The routine parses local minima and maxima in the cycle series and applies censor rules to guarantee alternating peaks and troughs, as well as phase and cycle length constraints.) The components of the CLI are time series which exhibit leading relationship with the reference series (IIP) at turning points. Country CLIs are compiled by combining de-trended smoothed and normalized components. The component series for each country are selected based on various criteria such as economic significance; cyclical behavior; data quality; timeliness and availability. OECD data should be cited as follows: OECD Composite Leading Indicators, "Composite Leading Indicators: Reference Turning Points and Component Series", http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm (Accessed on date)
Beginning of Period Seasonal credit is available to help relatively small depository institutions meet regular seasonal needs for funds that arise from a clear pattern of intrayearly movements in their deposits and loans and that cannot be met through special industry lenders. The discount rate on seasonal credit takes into account rates charged by market sources of funds and ordinarily is re-established on the first business day of each two-week reserve maintenance period.
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: CCEUSP01 OECD unit ID: JPY OECD country ID: JPN 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/).
A zero value for the index indicates that the national economy is expanding at its historical trend rate of growth; negative values indicate below-average growth; and positive values indicate above-average growth. For further information, please visit the Federal Reserve Bank of Chicago's web site: http://www.chicagofed.org/webpages/research/data/cfnai/current_data.cfm
OECD Data Filters: REF_AREA: IDN MEASURE: PRVM UNIT_MEASURE: GR ACTIVITY: C ADJUSTMENT: Y 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)).
Yield to maturity on accrued principal. Treasury Inflation-Protected Securities, or TIPS, are securities whose principal is tied to the Consumer Price Index (CPI). The principal increases with inflation and decreases with deflation. When the security matures, the U.S. Treasury pays the original or adjusted principal, whichever is greater. Copyright, 2016, Haver Analytics. Reprinted with permission.
OECD Descriptor ID: CCUSSP02 OECD unit ID: RUB OECD country ID: RUS 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: DEU MEASURE: TOVM UNIT_MEASURE: IX ACTIVITY: G47 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: IRLTLT01 OECD unit ID: PC OECD country ID: RUS 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: HUN 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)).
OECD Descriptor ID: CPGRLE01 OECD unit ID: PC OECD country ID: DEU 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: DNK 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)).
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.
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: LCEAPR01 OECD unit ID: IDX OECD country ID: EA19 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 total of both active listings and pending 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/).
OECD Data Filters: REF_AREA: FIN MEASURE: UNE_LF_M UNIT_MEASURE: PT_LF_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: _T AGE: Y_GE15 ACTIVITY: _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)).
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/).
OECD Descriptor ID: XTEXVA01 OECD unit ID: PC OECD country ID: CHN 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, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available at http://www.imf.org/external/terms.htm.
This series is calculated by the authors starting on June 13, 1945. It last appears on the original press release on June 6, 1945. Data before Wednesday, April 27, 1921 represent weekly values as of Friday. Authors: Cecilia Bao, Justin Chen, Nicholas Fries, Andrew Gibson, Emma Paine, and Kurt Schuler Studies in Applied Economics no. 115, Johns Hopkins University Institute for Applied Economics, Global Health, and the Study of Business Enterprise, July 2018; co-published with the Center for Financial Stability
This series covers commercial real estate price indices. Currently, there is limited international experience in constructing representative real estate price indices as real estate markets are heterogeneous, both within and across countries, and illiquid. A rapid increase in real estate prices, followed by a sharp economic downturn, can have a detrimental effect on financial sector soundness by affecting credit quality and the value of collateral. 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.
Copyright, 2016, Swiss National Bank. (+) numbers mean purchases of USD, (-) numbers mean sales of USD. Unpublished 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.
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/).
OECD Data Filters: REF_AREA: BRA 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: DNK 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: MABMM301 OECD unit ID: RUB OECD country ID: RUS 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: CHE 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 Data Filters: REF_AREA: IDN MEASURE: UNE_LF UNIT_MEASURE: PT_LF_SUB TRANSFORMATION: _Z ADJUSTMENT: N SEX: _T AGE: Y_GE15 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)).
OECD Data Filters: REF_AREA: CAN 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)).
Figures For 1860-1870 Are For No. 2 Mixed Corn, Weekly And Semi-Monthly Averages; Figures For 1871-1873 Include No. 2 Contract Corn, Average Of Semi-Monthly High And Low Quotations; Figures For 1874-1940 Include No. 2 Contract Corn, Average Of Monthly High And Low Quotations. Figures For September-December, 1943, Are Derived From A Straight Line Interpolation Between August, 1943 And January, 1944. The Figure For June, 1946 Was Derived From A Straight Line Interpolation Between May And July, 1946. Figures For January-April And June-October, 1944, January- February And November, 1945, And January-April, 1946, Were Interpolated By Use Of Ratio To Trend Line Deviations Method. The Interpolating Figures Were Taken From The Series "Corn No. 2, Yellow, Chicago, Weighted" Source: H.A. Wallace And E.N. Bressman, Corn And Corn Growing, Pp.341- 343, 3Rd Edition, 1928, For 1860-1870 Data; Chicago Board Of Trade, Annual Report. United States Department Of Agriculture, Bureau Of Agricultural Economics, "Feed Statistics." This NBER data series m04005 appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04005
OECD Data Filters: REF_AREA: CHN MEASURE: RS UNIT_MEASURE: IX ACTIVITY: _Z ADJUSTMENT: RT TRANSFORMATION: IX TIME_HORIZ: _Z METHODOLOGY: H 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)).
Data For 1925 Are For Forty-Seven States Plus Estimates For The Other Three States (Which Account For Only 2% Of The Total Registration). Data For 1926 Only Exclude Mississippi; Data For 1927 On Include All States. Data For 1941-1945 Exclude Deliveries To The Federal Government. Data For January 1959 On Include Alaska; Hawaii Included From January 1960 On. Source: Data For 1925-1950: U.S. Department Of Commerce, Survey Of Current Business, August 1933, P. 19 And Successive Issues. Data For 1951-1966: Automobile Manufacturers Association, Automobile Facts And Figures, 1951-1967 Issues. This NBER data series m01109 appears on the NBER website in Chapter 1 at http://www.nber.org/databases/macrohistory/contents/chapter01.html. NBER Indicator: m01109
OECD Descriptor ID: LORSGPNO OECD unit ID: IDX 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
The Published Wholesale Price For Portland Cement Represents The Simple Average F.O.B. Plant Prices In 6 Important Production Centers Regionally Scattered Throughout The Country. The Production Centers Are Among The More Important Basing Points For The Industry. The Prices Are Furnished By Manufacturers Of Cement And Represent F.O.B. Plant Net Cash Prices. That Is, The Quoted Price Less Trade Discounts, Cash Discounts, And Allowance For Return Of Bags. Quoted By NBER From Letter From Lubin, 02/09/37. From 1929 On, The Series Is Called Composite Price, Plants. No Prices Were Quoted After December, 1938. Source: Bls Bulletins, Nos. 335, 367, 415, 440, 473, 493, 521, 543, And 572 And Monthly "Wholesale Prices." This NBER data series m04099a appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04099a
Series Is Presented Here As Two Variables --(1)-- Original Data, 1890-1928 (2)--Original Data, 1923-1941" Spot Price Quoted For 8 Cities For 1923-1928; For 1929, Data Refers To Anthracite Chestnut Composite. Thereafter, Anthracite, Chestnut On Tracks, Destination, Composite Are Quoted. Owing To The Situation Brought About By The Strike No Satisfactory Information Is Available From October-December, 1925. From 1923 On, Monthly Averages For Chestnut Coal As Reported By 15 Firms, F.O.B. City (Survey Of Current, 1932 Annual Supplement) Are Quoted. October-December, 1931 And October, 1932, Original Figures Give Price Per Short Ton; Price Per Long Ton Computed By NBER. Given Short Ton Price Multiplied By 1.12 Equals Long Ton Price. Source: Bls Bulletin No. 390 And Following Wholesale Price Bulletins. This NBER data series m04044b appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04044b
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/).
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/).
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.
Net lending (+)/ borrowing (-) is calculated as revenue minus total expenditure. This is a core Government Finance Statistics (GFS) balance that measures the extent to which general government is either putting financial resources at the disposal of other sectors in the economy and nonresidents (net lending), or utilizing the financial resources generated by other sectors and nonresidents (net borrowing). This balance may be viewed as an indicator of the financial impact of general government activity on the rest of the economy and nonresidents (Government Finance Statistics Manual 2001 (GFSM 2001), paragraph 4.17). Note: Net lending (+)/borrowing (-) is also equal to net acquisition of financial assets minus net incurrence of liabilities. A projection of this data can be found at https://fred.stlouisfed.org/series/GGNLBPGBA188N. 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: SLRTTO02 OECD unit ID: IDX OECD country ID: JPN 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 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/).
The CSBS Community Bank Sentiment, Business Conditions Index captures on a quarterly basis what community bankers nationwide think about future business conditions over the next 12 months. The Business Conditions Index is one of seven indicators used to create the Community Bank Sentiment Index. Survey responses are used to calculate an index for each indicator. Each index is calculated by subtracting the percentage of respondents reporting a decrease from the percentage reporting an increase and then adding 100. When the share of community banks reporting an increase exceeds the share of community banks reporting a decrease, the index will be greater than 100, suggesting expansion and positive sentiment. If the share of community banks reporting a decrease exceeds the share reporting an increase, the index will be below 100, suggesting contraction and negative sentiment. An index will be 100 when the number of community banks reporting an increase is equal to the number of community banks reporting a decrease. For further information regarding the CSBS Community Bank Sentiment Index, visit: The CSBS website (https://www.csbs.org/cbindex) <b>Copyrighted: Citation required</b> These series are under copyright; but, provided you have not engaged in any prohibited uses, you may use these data series with proper attribution of the source and acknowledgment that you obtained the data from FRED (example, “Source: CSBS via FRED”) when displaying or publishing it.
AMERIBOR® (American Interbank Offered Rate) is a benchmark interest rate based on overnight unsecured loans transacted on the American Financial Exchange (AFX). AMERIBOR® is calculated as the transaction volume weighted average interest rate of the daily transactions in the AMERIBOR® overnight unsecured loan market on the AFX. More details about AMERIBOR® methodology can be found on the source's website (https://ameribor.net), under the Resources section. AMERIBOR® and AMBOR90™ are registered trademarks of the American Financial Exchange (AFX). © Copyright, American Financial Exchange (AFX). All Rights Reserved.
This data represents the ICE BofA 5-7 Year US Corporate Index value, a subset of the ICE BofA US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a remaining term to maturity of greater than or equal to 5 years and less than 7 years. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments. Certain indices and index data included in FRED are the property of ICE Data Indices, LLC (“ICE DATA”) and used under license. ICE® IS A REGISTERED TRADEMARK OF ICE DATA OR ITS AFFILIATES AND BOFA® IS A REGISTERED TRADEMARK OF BANK OF AMERICA CORPORATION LICENSED BY BANK OF AMERICA CORPORATION AND ITS AFFILIATES (“BOFA”) AND MAY NOT BE USED WITHOUT BOFA’S PRIOR WRITTEN APPROVAL. ICE DATA, ITS AFFILIATES AND THEIR RESPECTIVE THIRD PARTY SUPPLIERS DISCLAIM ANY AND ALL WARRANTIES AND REPRESENTATIONS, EXPRESS AND/OR IMPLIED, INCLUDING ANY WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE OR USE, INCLUDING WITH REGARD TO THE INDICES, INDEX DATA AND ANY DATA INCLUDED IN, RELATED TO, OR DERIVED THEREFROM. NEITHER ICE DATA, NOR ITS AFFILIATES OR THEIR RESPECTIVE THIRD PARTY PROVIDERS SHALL BE SUBJECT TO ANY DAMAGES OR LIABILITY WITH RESPECT TO THE ADEQUACY, ACCURACY, TIMELINESS OR COMPLETENESS OF THE INDICES OR THE INDEX DATA OR ANY COMPONENT THEREOF. THE INDICES AND INDEX DATA AND ALL COMPONENTS THEREOF ARE PROVIDED ON AN “AS IS” BASIS AND YOUR USE IS AT YOUR OWN RISK. ICE DATA, ITS AFFILIATES AND THEIR RESPECTIVE THIRD PARTY SUPPLIERS DO NOT SPONSOR, ENDORSE, OR RECOMMEND FRED, OR ANY OF ITS PRODUCTS OR SERVICES. Copyright, 2023, ICE Data Indices. Reproduction of this data in any form is prohibited except with the prior written permission of ICE Data Indices. The end of day Index values, Index returns, and Index statistics (“Top Level Data”) are being provided for your internal use only and you are not authorized or permitted to publish, distribute or otherwise furnish Top Level Data to any third-party without prior written approval of ICE Data. Neither ICE Data, its affiliates nor any of its third party suppliers shall have any liability for the accuracy or completeness of the Top Level Data furnished through FRED, or for delays, interruptions or omissions therein nor for any lost profits, direct, indirect, special or consequential damages. The Top Level Data is not investment advice and a reference to a particular investment or security, a credit rating or any observation concerning a security or investment provided in the Top Level Data is not a recommendation to buy, sell or hold such investment or security or make any other investment decisions. You shall not use any Indices as a reference index for the purpose of creating financial products (including but not limited to any exchange-traded fund or other passive index-tracking fund, or any other financial instrument whose objective or return is linked in any way to any Index) without prior written approval of ICE Data. ICE Data, their affiliates or their third party suppliers have exclusive proprietary rights in the Top Level Data and any information and software received in connection therewith. You shall not use or permit anyone to use the Top Level Data for any unlawful or unauthorized purpose. Access to the Top Level Data is subject to termination in the event that any agreement between FRED and ICE Data terminates for any reason. ICE Data may enforce its rights against you as the third-party beneficiary of the FRED Services Terms of Use, even though ICE Data is not a party to the FRED Services Terms of Use. The FRED Services Terms of Use, including but limited to the limitation of liability, indemnity and disclaimer provisions, shall extend to third party suppliers.
OECD Data Filters: REF_AREA: USA MEASURE: OLF_WAP UNIT_MEASURE: PT_WAP_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: _T AGE: Y15T64 ACTIVITY: _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)).
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.
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/).
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 Data Filters: REF_AREA: AUS MEASURE: UNE_LF UNIT_MEASURE: PT_LF_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: _T AGE: Y15T64 ACTIVITY: _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)).
Future Capital Expenditures reports the likely direction of capital expenditures for the manufacturing sector over the six months ahead for the state of Texas. Survey responses are used to calculate an index for each indicator. Each index is calculated by subtracting the percentage of respondents reporting a decrease from the percentage reporting an increase. When the share of firms reporting an increase exceeds the share of firms reporting a decrease, the index will be greater than zero, suggesting the indicator has increased over the prior month. If the share of firms reporting a decrease exceeds the share reporting an increase, the index will be below zero, suggesting the indicator has decreased over the prior month. An index will be zero when the number of firms reporting an increase is equal to the number of firms reporting a decrease. For further information regarding the Texas Manufacturing Outlook Survey release from the Federal Reserve Bank of Dallas visit: https://www.dallasfed.org/research/surveys/tmos.aspx#tab-reports.
OECD Data Filters: REF_AREA: ZAF MEASURE: PRVM UNIT_MEASURE: IX ACTIVITY: C 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 Data Filters: REF_AREA: LUX MEASURE: PRVM UNIT_MEASURE: GR ACTIVITY: BTE ADJUSTMENT: Y TRANSFORMATION: G1 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: MEX MEASURE: PRVM UNIT_MEASURE: GR ACTIVITY: C ADJUSTMENT: Y TRANSFORMATION: G1 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: SWE MEASURE: PRVM UNIT_MEASURE: GR ACTIVITY: BTE ADJUSTMENT: Y TRANSFORMATION: G1 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)).