Federal Reserve Economic Data

OECD Data Filters: REF_AREA: USA MEASURE: SHARE UNIT_MEASURE: GR ACTIVITY: _Z ADJUSTMENT: _Z 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: AUS MEASURE: IRLT 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: IR3TTS01 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, Chicago Board Options Exchange, Inc. Reprinted with permission.

The Chicago Fed’s National Financial Conditions Index (NFCI) provides a comprehensive weekly update on U.S. financial conditions in money markets, debt and equity markets, and the traditional and “shadow” banking systems. Source: http://www.chicagofed.org/webpages/publications/nfci/index.cfm. "Positive values of the NFCI indicate financial conditions that are tighter than average, while negative values indicate financial conditions that are looser than average." "The three subindexes of the NFCI (risk, credit and leverage) allow for a more detailed examination of the movements in the NFCI. Like the NFCI, each is constructed to have an average value of zero and a standard deviation of one over a sample period extending back to 1971. The risk subindex captures volatility and funding risk in the financial sector; the credit subindex is composed of measures of credit conditions; and the leverage subindex consists of debt and equity measures. Increasing risk, tighter credit conditions and declining leverage are consistent with tightening financial conditions. Thus, a positive value for an individual subindex indicates that the corresponding aspect of financial conditions is tighter than on average, while negative values indicate the opposite. The nonfinancial leverage subindex of the NFCI best exemplifies how leverage can serve as an early warning signal for financial stress and its potential impact on economic growth. The positive weight assigned to both the household and nonfinancial business leverage measures in this NFCI subindex make it characteristic of the feedback process between the financial and nonfinancial sectors of the economy often referred to as the “financial accelerator." Increasingly tighter financial conditions are associated with rising risk premiums and declining asset values. The net worth of households and nonfinancial firms is, thus, reduced at the same time that credit tightens. This leads to a period of deleveraging (i.e., debt reduction) across the financial and nonfinancial sectors of the economy and ultimately to lower economic activity." Source: http://www.chicagofed.org/webpages/research/data/nfci/background.cfm. For further information, please visit the Federal Reserve Bank of Chicago's NFCI website at http://www.chicagofed.org/webpages/publications/nfci/index.cfm.

OECD Descriptor ID: CPALCY01 OECD unit ID: IDX 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

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: MANMM101 OECD unit ID: EUR 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

OECD Data Filters: REF_AREA: CAN 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)).

Source Code: Q:PT:R:368 Coverage includes all types of new and existing dwellings in the whole country. 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: PRCNTO01 OECD unit ID: M2 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

OECD Data Filters: REF_AREA: CAN MEASURE: WAP UNIT_MEASURE: PS 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.

This data represents the semi-annual yield to worst of the ICE BofA US High Yield Index, which tracks the performance of US dollar denominated below investment grade rated corporate debt publicly issued in the US domestic market. To qualify for inclusion in the index, securities must have a below investment grade rating (based on an average of Moody's, S&P, and Fitch) and an investment grade rated country of risk (based on an average of Moody's, S&P, and Fitch foreign currency long term sovereign debt ratings). Each security must have greater than 1 year of remaining maturity, a fixed coupon schedule, and a minimum amount outstanding of $100 million. Original issue zero coupon bonds, "global" securities (debt issued simultaneously in the eurobond and US domestic bond markets), 144a securities and pay-in-kind securities, including toggle notes, qualify for inclusion in the Index. Callable perpetual securities qualify provided they are at least one year from the first call date. Fixed-to-floating rate securities also qualify provided they are callable within the fixed rate period and are at least one year from the last call prior to the date the bond transitions from a fixed to a floating rate security. DRD-eligible and defaulted securities are excluded from the Index. ICE BofA Explains the Construction Methodology of this series as: Index constituents are capitalization-weighted based on their current amount outstanding. With the exception of U.S. mortgage pass-throughs and U.S. structured products (ABS, CMBS and CMOs), accrued interest is calculated assuming next-day settlement. Accrued interest for U.S. mortgage pass-through and U.S. structured products is calculated assuming same-day settlement. Cash flows from bond payments that are received during the month are retained in the index until the end of the month and then are removed as part of the rebalancing. Cash does not earn any reinvestment income while it is held in the Index. The Index is rebalanced on the last calendar day of the month, based on information available up to and including the third business day before the last business day of the month. Issues that meet the qualifying criteria are included in the Index for the following month. Issues that no longer meet the criteria during the course of the month remain in the Index until the next month-end rebalancing at which point they are removed from the Index. Yield to worst is the lowest potential yield that a bond can generate without the issuer defaulting. The standard US convention for this series is to use semi-annual coupon payments, whereas the standard in the foreign markets is to use coupon payment frequencies of annual, semi-annual, quarterly, and monthly. 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 Descriptor ID: IR3TCD01 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

Series is calculated as the spread between 3-Month Treasury Constant Maturity (BC_3MONTH) and Effective Federal Funds Rate (https://fred.stlouisfed.org/series/EFFR). Starting with the update on June 21, 2019, the Treasury bond data used in calculating interest rate spreads is obtained directly from the U.S. Treasury Department (https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield).

OECD Data Filters: REF_AREA: JPN 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)).

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.

For A Description Of The Index See Special Memorandum No. 28. Source: London And Cambridge Economic Service, Bulletin Of July 1929, P. 203, And Following Issues. Data For 1936-1939 Are All In Bulletin Of August 23, 1939, P. 379. This NBER data series m08048b appears on the NBER website in Chapter 8 at http://www.nber.org/databases/macrohistory/contents/chapter08.html. NBER Indicator: m08048b

The median number of days property listings spend on the market 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 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: CHN MEASURE: LI UNIT_MEASURE: IX ACTIVITY: _Z ADJUSTMENT: NOR 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)).

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.

Copyright, 2016, National Association of Realtors. Reprinted with permission. Per the agreement with the source, data in FRED are available for the prior 13 months. Measures the degree to which a typical family can afford the monthly mortgage payments on a typical home. Value of 100 means that a family with the median income has exactly enough income to qualify for a mortgage on a median-priced home. An index above 100 signifies that family earning the median income has more than enough income to qualify for a mortgage loan on a median-priced home, assuming a 20 percent down payment. For example, a composite housing affordability index (COMPHAI) of 120.0 means a family earning the median family income has 120% of the income necessary to qualify for a conventional loan covering 80 percent of a median-priced existing single-family home. An increase in the COMPHAI then shows that this family is more able to afford the median priced home. This index is calculated as composite of the fixed and adjustable rate mortgages.

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.

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).

On November 17, 2022, Freddie Mac changed the methodology of the Primary Mortgage Market Survey® (PMMS®). The weekly mortgage rate is no longer based on a survey of lenders. For more information regarding Freddie Mac’s enhancement, see their research note (https://www.freddiemac.com/research/insight/20221103-freddie-macs-newly-enhanced-mortgage-rate-survey). Data are provided “as is” by Freddie Mac®, with no warranties of any kind, express or implied, including but not limited to warranties of accuracy or implied warranties of merchantability or fitness for a particular purpose. Use of the data is at the user’s sole risk. In no event will Freddie Mac be liable for any damages arising out of or related to the data, including but not limited to direct, indirect, incidental, special, consequential, or punitive damages, whether under a contract, tort, or any other theory of liability, even if Freddie Mac is aware of the possibility of such damages. Copyright, 2016, Freddie Mac. Reprinted with permission.

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).

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.

Value represents the benchmark prices which are representative of the global market. They are determined by the largest exporter of a given commodity. Prices are period averages in nominal U.S. dollars. 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 data represents the effective yield of the ICE BofA US Corporate 15+ Year Index, 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 15 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.

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: GBR 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)).

Source Code: Q:ZA:R:368 Coverage includes all middle segments new and existing dwellings in the whole country. 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.

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 Nowcast for Real Personal Consumption Expenditures uses a nowcasting model to synthesize the bridge equation approach relating GDP subcomponents to monthly source data with factor model and Bayesian vector autoregression approaches. The Federal Reserve Bank of Atlanta’s GDPNow release complements the quarterly GDP release from the Bureau of Economic Analysis (BEA). The Atlanta Fed recalculates and updates their GDPNow forecasts (called “nowcasts”) throughout the quarter as new data are released, up until the BEA releases its “advance estimate” of GDP for that quarter. The St. Louis Fed constructs a quarterly time series for this dataset, in which both historical and current observations values are combined. In general, the most-current observation is revised multiple times throughout the quarter. The final forecasted value (before the BEA’s release of the advance estimate of GDP) is the static, historical value for that quarter. For futher information visit the source at https://www.frbatlanta.org/cqer/research/gdpnow.aspx?panel=1.

OECD Data Filters: REF_AREA: SWE MEASURE: CPI UNIT_MEASURE: PD METHODOLOGY: N EXPENDITURE: _T ADJUSTMENT: N TRANSFORMATION: GOY 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: DEU 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)).

OECD Data Filters: REF_AREA: ITA 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)).

OECD Data Filters: REF_AREA: MEX MEASURE: EAR UNIT_MEASURE: IX ADJUSTMENT: Y ACTIVITY: C SECTOR: S1 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: MANMM101 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:MX:R:368 Coverage includes all types of new and existing dwellings in the whole country. 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.

View a monthly index that tracks changes in the price of residential real estate in 20 major metropolitan regions in the U.S.

OECD Data Filters: REF_AREA: IDN 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)).

This time series is an interpretation of US Business Cycle Expansions and Contractions data provided by The National Bureau of Economic Research (NBER) at http://www.nber.org/cycles/cyclesmain.html. Our time series is composed of dummy variables that represent periods of expansion and recession. The NBER identifies months and quarters of turning points without designating a date within the period that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the period. The arbitrary convention does not reflect any judgment on this issue by the NBER's Business Cycle Dating Committee. 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 of the peak and ends on the last day of the period before 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/USRECDM 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. A version of this time series represented using the trough method can be found at: https://fred.stlouisfed.org/series/USRECD 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. The peak method is used for this series.

OECD Data Filters: REF_AREA: CHE MEASURE: CPI UNIT_MEASURE: PD METHODOLOGY: N EXPENDITURE: _T ADJUSTMENT: N TRANSFORMATION: GOY 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 Were Computed From Wartime Current Prices Divided By Money Which Had Been Centered To June 30 For Each Year. Source: Simon Kuznets, NBER This NBER data series a14187 appears on the NBER website in Chapter 14 at http://www.nber.org/databases/macrohistory/contents/chapter14.html. NBER Indicator: a14187

The median number of days property listings spend on the market 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 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/).

M2 comprises M1 and other deposits in national currency of other financial corporations, state and local governments, public nonfinancial corporations, and private sector with commercial banks. Beginning December 2005, comprises M1 and other deposits in national and foreign currency with other depository corporations. 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 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/).

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.

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.

Copyright, European Union, 1995-2016, http://ec.europa.eu/geninfo/legal_notices_en.htm#copyright.

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.

This series is in the H.4.1 Factors Affecting Reserve Balances statistical press release and is available in FRED as WALCL (https://fred.stlouisfed.org/series/WALCL). 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

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: GBR MEASURE: UNE_LF UNIT_MEASURE: PT_LF_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)).

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:CN: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. For information specifying what comprises G20, Advanced Economies, Emerging Market Economies, and All Reporting Economies, visit https://www.bis.org/statistics/totcredit/tables_f.pdf

The observations for the Dow Jones Transportation Average represent the daily index value at market close. The market typically closes at 4 PM ET, except for holidays when it sometimes closes early. Originally made up of only railroad stocks, the Dow Jones Transportation Average now provides a view of the 20 transportation companies in US stock market. For more information, please visit Dow Jones Transportation Average (http://us.spindices.com/indices/equity/dow-jones-transportation-average). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Dow Jones Transportation Average in any form is prohibited except with the prior written permission of S&P Dow Jones Indices LLC (S&P). S&P does not guarantee the accuracy, adequacy, completeness or availability of any information and is not responsible for any errors or omissions, regardless of the cause or for the results obtained from the use of such information. S&P DISCLAIMS ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE OR USE. In no event shall S&P be liable for any direct, indirect, special or consequential damages, costs, expenses, legal fees, or losses (including lost income or lost profit and opportunity costs) in connection with subscriber's or others' use of Dow Jones Transportation Average. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available here (http://us.spindices.com/contact-us), including phone numbers for all regional offices.

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.