Federal Reserve Economic Data

Eurostat unit ID: CLV10_MNAC Eurostat item ID: B1GQ Eurostat country ID: HU 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 data represents the semi-annual yield to worst of the ICE BofA US Corporate B Index, a subset of the ICE BofA US High Yield Master II Index tracking the performance of US dollar denominated below investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating B. 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. 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 payments with frequencies of annual, semi-annual, quarterly, and monthly. 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.

M1 comprises currency in circulation plus demand deposits in national currency of resident non-bank non-government sectors with the PBC and banking institutions. Currency in circulation refers to notes and coins by the PBC less the amount held by banking institutions. 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, Chicago Board Options Exchange, Inc. Reprinted with permission.

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for Dallas, Texas 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' user of Home Price Index for Dallas, Texas. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for San Diego, California 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' user of Home Price Index for San Diego, California. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

Series Is Presented Here As Two Variables--(1)--Original Data, 1871-1938 (2)--Original Data, 1926-1969. The Index For 1926-February 1957 Is Based On Daily Quotations For Ninety Stocks; The Index For March 1957-1969 Is Based On Daily Quotations For Five Hundred Stocks. Source: Standard And Poor'S, Data For 1926-1963: Trade And Security Statistics: Security Price Index Record, 1964 Edition. Data For 1964-1969: Current Statistics, Monthly Issues. This NBER data series m13046b appears on the NBER website in Chapter 13 at http://www.nber.org/databases/macrohistory/contents/chapter13.html. NBER Indicator: m13046b

The AD&Co US Mortgage High Yield Index crOAS, credit-and-option-adjusted spread, is an extension of the traditional OAS measure. On a set of 20 standardized, probabilistically weighted, market-and-model stress scenarios, AD&Co computes a discount rate that equates expected present value of tranche's cash flows to the observed market price; the cash flows are loss-adjusted using AD&Co's LoanDynamics Model (LDM). Investors and fund managers can use the index to assess the broad market returns, risks and opportunities available through investing in a market-weighted, passive portfolio of US mortgage credit risk transfer instruments. The Index also provides a means of comparing the returns of an actively managed portfolio against a passive, naive market portfolio as approximated by the Index. The Mid-Tier and its sub-indices allow for approximations of performance comparisons by vintage or age, across the capital stack, and by initial credit risk level and/or vintage as indicated by original attachment point. <b>Disclaimer:</b> The AD&Co U.S. Mortgage High-Yield Index serves as an informational index and is not for commercial-use purposes. The Index's accuracy, completeness, timeliness and suitability for any purpose are not guaranteed. The Index does not constitute (1) investment, legal, accounting, tax, or other professional advice or (2) any recommendation or solicitation to purchase, hold, sell, or otherwise deal in any investment. This Index has been prepared for general informational purposes, without consideration of the circumstances or objectives of any particular investor. Any reliance on the Index is at the reader's sole risk. All investment is subject to numerous risks, known and unknown. Past performance is no guarantee of future results. For investment advice, seek a qualified investment professional. Not for redistribution without permission. Note: An affiliate of Andrew Davidson & Co., Inc. engages in trading activities in investments that may be the same or similar to those featured in the Index. <b>Index Inclusion Rules</b> Only cash CAS and STACR bonds offered to the public, whether they are exchangeable or not, that have or have had IDC prices. Bond factor > = .25 Floating rate bonds only. Collateral Types 30 Year Residential. Fixed Rate: STACR-DN, DNA, HQ, HQA, HRP, CAS – C0 Tranche names – B, B1, B2, M3, M2, M1 Normally listed on GSE websites: <a href='https://crt.freddiemac.com/offerings/stacr.aspx#issuance-details'>Freddie Mac</a>, <a href='http://www.fanniemae.com/portal/funding-the-market/credit-risk/transactions.html'>Fannie Mae</a> No private placements No Child Classes (Exchangeable into) or Retained Classes (H bonds) No CIRT, ACIS, SPI Original attachment points and CAS STACR <table style='width:50%'><tr><th>Tier</th><th>Attachment Points</th><th>CAS STACR Class</th></tr><tr><td>0</td><td>> = 0.00 < .25</td><td>STACR Class B, B2; CAS Class B</td></tr><tr><td>1</td><td>> = 0.25 < .95</td><td>STACR Class B1, Old M3; CAS Class B1</td></tr><tr><td>2</td><td>> = 0.95 < 1.75</td><td>STACR Class M3, M2; CAS Class M2</td></tr><tr><td>3</td><td>> = 1.75 < 3.75</td><td>STACR Class M2, M1; CAS Class M1</td></tr><tr><td>Mid</td><td>> = 0.25 < 3.75</td><td>STACR Class Mixed; CAS Class Mixed</td></tr></table> Input data provided by Intex and ICE Data Services. © Andrew Davidson & Co., Inc. All rights reserved.

OECD Data Filters: REF_AREA: CHL 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)).

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/).

Prior to 1982 equals the posted price. On August 5, 2013, the Wall Street Journal discontinued publication of some of its commodity energy prices. As a current substitute, see the monthly oil spot prices reported by the U.S. Department of Energy, Energy Information Administration at https://fred.stlouisfed.org/series/MCOILWTICO Copyright, 2016, Dow Jones & Company

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 Zillow Home Value Index or ZHVI is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. Home types captured in ZHVI include single-family residences, condos, and co-ops. A single-family home is a standalone, detached house used as a single dwelling unit, meaning a residence for one family, person or household. It has its own private entrance and direct street access, and is built on its own land, usually with additional yard space. An owner-occupied apartment is generally referred to as a condominium or condo. The public common areas are jointly-owned and usually managed by a homeowners association (HOA). A cooperative, or co-op, is a type of housing that is actually a corporation. A co-op resembles a condominium but the unit owners do not own their unit outright. Each resident owns a share in a corporation that entitles them to live in one of the units under a lease agreement. For more information on types of houses, check out Zillow's types of houses article (https://www.zillow.com/resources/stay-informed/types-of-houses/). For information about ZHVI, check out their user guide (https://www.zillow.com/research/zhvi-user-guide/). For more information about methodology check out this overview of ZHVI (https://www.zillow.com/research/zhvi-methodology-2019-highlights-26221/) and a deep-dive into its methodology (https://www.zillow.com/research/zhvi-methodology-2019-deep-26226/).

Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).

Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).

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

OECD descriptor ID: CPALTT01 OECD unit ID: GY OECD country ID: EU28 All OECD data should be cited as follows: OECD,"Main Economic Indicators - complete database"Main Economic Indicators(database)http://dx.doi.org/10.1787/data-00052-en(Accessed on date)Copyright, 2016, OECD. Reprinted with permission.

OECD Descriptor ID: CPGRLE01 OECD unit ID: PC OECD country ID: USA 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

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.

OECD Descriptor ID: LCWRIN01 OECD unit ID: IDX OECD country ID: ITA All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

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 on the 15th day of the month of the peak and ends on the 15th day of the month of the trough. This time series is a disaggregation of the monthly series. For more options on recession shading, see the note 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. The midpoint method is used for this series. 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/CANRECD 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/CANRECDP 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)

Quarterly 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.

Source Code: Q:ID:R:368 Coverage includes new houses in big cities. 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 Data Filters: REF_AREA: OECD 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)).

OECD Data Filters: REF_AREA: KOR 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)).

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for Phoenix, Arizona 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' user of Home Price Index for Phoenix, Arizona. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

OECD Descriptor ID: MANMM101 OECD unit ID: CNY 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

Components Of This Index And Their Respective Weights Are: Industrial Prices, Non-Agricultural, Wholesale (10); Farm Prices At The Farm (10); Retail Food Prices In 51 Cities (10); Rents, In 32 Cities (5); Clothing, Fuel, Furnishings, Etc., Retail (10); Freight And Transportation Costs (5); Realty Value, Urban And Farm (10); Securities, Bonds, And Stocks (10); Equipment And Machinery (10); Hardware Prices (3); Automobile Prices (2); Wages, Federal Reserve Board, New York Composite (15). "Data For 1934-November, 1939, Are Correct As Given In The"Monthly Review"; They Are Discontinued After November, 1939." Telephone Conversation Of 5/24/41 With Reports Division Of The Federal Reserve Board Of New York. Source: Federal Reserve Bank Of New York City, Letter From Reports Department For 1860-1933. For 1934-1939, Data Are From "Monthly Review Of Credit And Business Conditions." This NBER data series m04051 appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04051

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

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

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

Source Code: Q:BR:N:368 Coverage includes all types of new and existing dwellings in metropolitan area. 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.

All data is as of 5 PM PST. Given the volatility in the cryptocurrency markets, users may wish to view the large variation in values in a log scale. Changes in the data can be analyzed by turning on a log scale functionality that can be applied in the Format tab under Edit Graph button. For more information to the Coinbase index, see https://am.coinbase.com/index Copyright, 2018, Coinbase. Reproduction of Coinbase data in any form is prohibited except with the prior written permission of Coinbase.

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: MABMM301 OECD unit ID: AUD OECD country ID: AUS All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for New York, New York 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' user of Home Price Index for New York, New York. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for Miami, Florida 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' user of Home Price Index for Miami, Florida. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). Copyright © 2016, S&P Dow Jones Indices LLC. All rights reserved. Reproduction of Home Price Index for Denver, Colorado 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' user of Home Price Index for Denver, Colorado. Permission to reproduce this series can be requested from index_services@spdji.com. More contact details are available from http://us.spindices.com/contact-us/, including phone numbers for all of its regional offices.

OECD Data Filters: REF_AREA: ZAF 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)).

Series Is Presented Here As Two Variables--(1)--Original Data, 1917-1948 (2)--Original Data, 1948-1955. Data Are For Amount Of Crude Oil Run To Stills At Refineries, Including Foreign As Well As Domestic Petroleum. Beginning In 1949 A New Method Of Reporting Crude Oil In California Was Instituted, Shifting A Considerable Proportion Crude Oil Formerly Reported As Residual Fuel Oil To Oil Reported To Runs To Stills. Source: U.S. Bureau Of Mines; Mineral Industry Surveys, Monthly And Annual Petroleum Statement. This NBER data series m01125ab appears on the NBER website in Chapter 1 at http://www.nber.org/databases/macrohistory/contents/chapter01.html. NBER Indicator: m01125ab

1936-1940 Data Were Computed By NBER From Data In Statistics Of Income (See Notes). The 1938 Data Were Adjusted By NBER To Conform To 1937 Industrial Classification (See Notes). The Data For 1939-1940 Are Based On 1938 Standard Industrial Classification. Source: Bureau Of Internal Revenue: Statistics Of Income, 1916 And Successive Years. This NBER data series a09021 appears on the NBER website in Chapter 9 at http://www.nber.org/databases/macrohistory/contents/chapter09.html. NBER Indicator: a09021

Data Show Changes In Freight Car Rates Of Fifty Representative Agricultural Products. Source: U.S. Department Of Agriculture, Division Of Statistical And Historical Research, Yearbook, 1923, P. 1177; 1926, P. 1248. This NBER data series m03013 appears on the NBER website in Chapter 3 at http://www.nber.org/databases/macrohistory/contents/chapter03.html. NBER Indicator: m03013

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.

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).

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.

Eurostat unit ID: CLV10_MNAC Eurostat item ID: B1GQ Eurostat country ID: EU27_2020 European Union (27 countries from 2020) represents the 2020 reduction in the European Union countries due to the departure of the United Kindom. European Union (27 countries): Belgium, Denmark, Germany, Ireland, Greece, Spain, France, Italy, Luxembourg, the Netherlands, Portugal, Austria, Finland, Sweden, Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovenia, Slovakia, Bulgaria, Romania, and Croatia. 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).

Source Code: Q:PH:R:368 Coverage includes flats and commercial properties in Makati (part of metropolitan Manila). 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 Data Filters: REF_AREA: USA MEASURE: IRSTCI UNIT_MEASURE: PA ACTIVITY: _Z ADJUSTMENT: _Z TRANSFORMATION: _Z FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).

OECD Descriptor ID: NAEXKP01 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

The January 2023 report presents the scheduled annual revision of the ADP National Employment Report (NER), which updates the data series to be consistent with the annual Quarterly Census of Employment and Wages (QCEW) benchmark data through March 2022. This is a recurring process that happens every year, and is a common practice for reports of this nature. In addition to this regular, annual update, the NER weighting methodology was revised to facilitate an easier comparison of total employment estimates between the NER and QCEW; monthly aggregates now leverage weekly seasonal adjustments rather than a separate monthly seasonal adjustment; and the national aggregate is now constructed from industry aggregates. There was also a refinement in the labeling methodology which is used to determine how various employment sources fall into a particular industry and geography definitions. These changes were applied retroactively to the 13-year history of the NER.

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 Data Filters: REF_AREA: JPN COUNTERPART_AREA: W UNIT_MEASURE: XDC TRADE_FLOW: X PRODUCT_TYPE: C ADJUSTMENT: Y TRANSFORMATION: N FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).

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/).

This data represents the ICE BofA AAA 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 given investment grade rating AAA. 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: IR3TTS01 OECD unit ID: ST OECD country ID: GBR All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database),http://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission.

For more information regarding the index, please visit Standard & Poor's (https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-corelogic-cs-home-price-indices.pdf). There is more information about home price sales pairs in the Methodology section. Copyright, 2016, Standard & Poor's Financial Services LLC. Reprinted with permission.

Indeed calculates the index change in seasonally-adjusted job postings since February 1, 2020, using a 7-day trailing average. February 1, 2020, is 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 January 2021 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.

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/).

Copyright, 2016, Chicago Board Options Exchange, Inc. Reprinted with permission.