Federal Reserve Economic Data

Real Manufacturing and Trade Inventories (INVCMRMTSPL) was first constructed by the Federal Reserve Bank of St. Louis in June 2013. It is calculated using Real Manufacturing and Trade Inventories (INVHMRMT) (https://fred.stlouisfed.org/series/INVHMRMT) and Real Manufacturing and Trade Inventories (INVCMRMT) (https://fred.stlouisfed.org/series/INVCMRMT). Before January 1997 lag1(INVHMRMT) = one observation earlier than current time period observation INVHMRMT _PC = the growth rate of INVHMRMT lead1(INVCMRMTSPL) = one observation later than current time period observation INVHMRMT _PC = [INVHMRMT /lag1(INVHMRMT) –1] INVCMRMTSPL= lead1(INVCMRMTSPL)/(1+ INVHMRMT _PC) After December 1996 INVCMRMTSPL= INVCMRMT

OECD Descriptor ID: CPGREN01 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

Overview of the Index The Index is a quarterly comprehensive picture of the average American household’s financial condition. Built by assessing the key elements of financial health and distress, it converts a complex set of factors into a single, easy to understand number. Scope and History The index measures the U.S., all 50 states and more than 70 MSAs. The national and state versions date back to 1980 and the MSA versions date back to 1990. Public Data and Proprietary Methodology We use more than 65 data points from government, public and private data and a proprietary methodology for compiling, combining and evaluating data. With nearly 50 years of experience and insight into helping consumers in financial distress, we know the biggest causes of distress, how people react to financial challenges and proven strategies for regaining control. (Note: Our client data is not a data source for the Index) Measured on a 100 Point Scale Financial distress is measured on a 100 point scale and a score under 70 indicates financial distress. The lower the score equals more distress, a weaker financial position, more urgency to act, takes longer and is harder to resolve, and increases the probability of needing a third party help to resolve. The Index score is tied to one of 5 general rating categories, which reflect the strength and stability of the consumer’s position. Less than 60 Emergency / Crisis 60 – 69 Distressed / Unstable 70 – 79 Weakening / At-Risk 80 – 89 Good / Stable 90 and Above Excellent / Secure What Does the Index Measure? We measure the 5 categories of personal finance that reflect or lead to a secure, stable financial life—Employment, Housing, Credit, Household Budget and Net Worth. All are equally important, so have given each category equal weighting. Employment. Stable income is the foundation of any family’s finances. This category measures the impact of unemployment and underemployment on financial health. Key Measures: Unemployment, Underemployment Sample Data Source: Department of Labor, Bureau of Labor Statistics Housing. Safe, affordable housing is a priority for all families. This category measures how consumers are paying their mortgage/rent and the impact of housing costs on their finances. Key Measures: Mortgage and Rental Delinquencies, Housing as Percent of Budget Sample Data Source: National Delinquency Survey Credit. Responsible use of credit creates more borrowing options and lower costs. This category assesses the strength of credit scores and how well families manage their credit. Key Measures: Credit Scores, Trade Line Utilization, Credit Delinquencies, Per Capita Bankruptcies Sample Data Source: National Credit Bureau Household Budget. Spending less than you make is the daily choice that leads to long-term success. This category measures families’ spending patterns and saving for emergencies. Key Measures: Disposable Income, Savings, Consumer Confidence Sample Data Source: Department of Commerce, Bureau of Economic Analysis Net Worth. Strong, positive net worth creates options and independence. This category measures how well consumers are strengthening their personal balance sheets. Key Measures: Household Net Worth, Net Worth versus Funds Required for Long-Term Needs (e.g. retirement) Sample Data Source: Federal Reserve Flow of Funds, Survey of Consumer Finances

OECD Data Filters: REF_AREA: AUS 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)).

Copyright, 2016, OECD. Reprinted with permission. All OECD data should be cited as follows: OECD (2010), OECD National Accounts Statistics, http://dx.doi.org/10.1787/na-data-en, (accessed on date)

Copyright, 2016, OECD. Reprinted with permission. All OECD data should be cited as follows: OECD (2010), OECD National Accounts Statistics, http://dx.doi.org/10.1787/na-data-en, (accessed on date)

Source Code: Q:IN:N:368 Coverage includes all types of new and existing dwellings in big cities. 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.

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).

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

Source Code: Q:CZ:R:368 Coverage includes all types of owner occupied 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.

Data is 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.

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 Data Filters: REF_AREA: GBR MEASURE: CPI UNIT_MEASURE: PA METHODOLOGY: N EXPENDITURE: CP045_0722 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)).

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, 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, 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/).

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 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 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/).

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

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

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/CHNRECD 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/CHNRECDP 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)

OECD Descriptor ID: NAEXCP01 OECD unit ID: EUR OECD country ID: DEU All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

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 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.

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 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/).

This series measures the probability that the expected personal consumption expenditures price index (PCEPI) inflation rate (12-month percent changes) over the next 12 months will range between 0 and 1.5 percent. For additional information on the Price Pressures Measure and its construction, see Introducing the St. Louis Fed Price Pressures Measure (https://research.stlouisfed.org/publications/economic-synopses/2015/11/06/introducing-the-st-louis-fed-price-pressures-measure/). As of April 5, 2023, the MZM Money Stock measure, in SA billions of dollars, has been replaced with the series Revolving Consumer Credit Outstanding (break-adjusted), in SA billions of dollars, from the Federal Reserve’s monthly G.19 release. This change was made because the MZM series was discontinued. As of February 3, 2020, the Emerging and Developing Asia and Western Hemisphere Consumer Prices Indexes have been replaced with Asia/Pacific Rim and Latin America Consumer Price Indexes respectively. These changes were made to facilitate a more timely updating of the PPM. Switching the Consumer Prices Indexes produced no meaningful change in the PPM series. As of January 29, 2021, the Adjusted Monetary Base (including Deposits to Satisfy Clearing Balance Contracts) Seasonally Adjusted, in billions of dollars has been replaced with the series, Monetary Base, NSA, in billions of dollars.

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/).

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: TUR MEASURE: IRSTCI UNIT_MEASURE: PA ACTIVITY: _Z ADJUSTMENT: _Z TRANSFORMATION: _Z FREQ: M All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).

OECD Data Filters: REF_AREA: AUT 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: CPGREN01 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.

This time series is an interpretation of Organisation of Economic Development (OECD) Composite Leading Indicators: Reference Turning Points and Component Series data, which can be found at http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm. The OECD identifies months of turning points without designating a date within the month that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the month. The arbitrary convention does not reflect any judgment on this issue by the OECD. Our time series is composed of dummy variables that represent periods of expansion and recession. A value of 1 is a recessionary period, while a value of 0 is an expansionary period. For this time series, the recession begins the first day of the period following a peak and ends on the last day of the period of the trough. For more options on recession shading, see the notes and links below. The recession shading data that we provide initially comes from the source as a list of dates that are either an economic peak or trough. We interpret dates into recession shading data using one of three arbitrary methods. All of our recession shading data is available using all three interpretations. The period between a peak and trough is always shaded as a recession. The peak and trough are collectively extrema. Depending on the application, the extrema, both individually and collectively, may be included in the recession period in whole or in part. In situations where a portion of a period is included in the recession, the whole period is deemed to be included in the recession period. The first interpretation, known as the midpoint method, is to show a recession from the midpoint of the peak through the midpoint of the trough for monthly and quarterly data. For daily data, the recession begins on the 15th of the month of the peak and ends on the 15th of the month of the trough. Daily data is a disaggregation of monthly data. For monthly and quarterly data, the entire peak and trough periods are included in the recession shading. This method shows the maximum number of periods as a recession for monthly and quarterly data. The Federal Reserve Bank of St. Louis uses this method in its own publications. A version of this time series represented using the midpoint method can be found at: https://fred.stlouisfed.org/series/DEURECDM The second interpretation, known as the trough method, is to show a recession from the period following the peak through the trough (i.e. the peak is not included in the recession shading, but the trough is). For daily data, the recession begins on the first day of the first month following the peak and ends on the last day of the month of the trough. Daily data is a disaggregation of monthly data. The trough method is used when displaying data on FRED graphs. The trough method is used for this series. The third interpretation, known as the peak method, is to show a recession from the period of the peak to the trough (i.e. the peak is included in the recession shading, but the trough is not). For daily data, the recession begins on the first day of the month of the peak and ends on the last day of the month preceding the trough. Daily data is a disaggregation of monthly data. A version of this time series represented using the peak method can be found at: https://fred.stlouisfed.org/series/DEURECDP 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)

This data represents the Option-Adjusted Spread (OAS) for the ICE BofA High Yield US Emerging Markets Liquid Corporate Plus Index is a subset of the ICE BofA Emerging Markets Liquid Corporate Plus Index, which includes only securities rated BB1 or lower. The same inclusion rules apply for this series as those that apply for ICE BofA Emerging Markets Liquid Corporate Plus Index (https://fred.stlouisfed.org/series/BAMLEMCLLCRPIUSTRIV?cid=32413). The ICE BofA OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond's OAS, weighted by market capitalization. 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 ICE BofA Option-Adjusted Spreads (OASs) are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond's OAS, weighted by market capitalization. The US Corporate 10-15 Year OAS is a subset of the ICE BofA US Corporate Master OAS, BAMLC0A0CM. This subset includes all securities with a remaining term to maturity of greater than or equal to 10 years and less than 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.

Source: Banco de Mexico: http://www.banxico.org.mx/ (+) numbers mean purchases of USD (Sell Peso), (-)numbers mean sales of USD (Buy Peso) 1. Banco de Mexico provides background information on its "Contingent dollar sales mechanism," which constitutes sterilized interventions (14 total) from February 1997-June 2001: "In February 1997, the Foreign Exchange Commission, composed of officials from the Ministry of Finance and Banco de México (and responsible for Mexico's foreign exchange policy) announced the establishment of an auction mechanism to sell US dollars. This mechanism was implemented in order to ease the volatility in the foreign exchange market without violating the principles inherent in the prevailing floating exchange rate regime (see the Exchange Commission Statement and Banco de México's Circular 10/97). Implementation of the mechanism was possible due to a significant accumulation of reserves, mainly achieved through the auction of foreign exchange options. Under this mechanism, Banco de México undertook daily sales of up to USD200 million, with a minimum price for the dollar set at 1.02 times the Mexican peso, as determined by the FIX on the preceding day. If any bids were allocated during the auction, the minimum price for the dollar on the following day was set at 1.02 times the weighted average peso exchange rate determined in the auction. The Contingent Dollar Sales Mechanism was effective until June 2001. It was triggered and implemented only fourteen days during the entire period, for a total amount of USD 1.950 billion sold. Furthermore, almost 60% of total dollar sales took place between August 1998 and January 1999, a period that was characterized by very high volatility in international financial markets." (http://www.banxico.org.mx/sistema-financiero/estadisticas/mercado-cambiario/operaciones-vigentes-del-banco-de-mexico-en-el-mer/mecanismos/february-1997---june-2001--co.html) 2. Banco de Mexico has two added notes about the history of the Contingent dollar sales mechanism: "1. Daily auction of dollars conducted as stipulated by the Foreign Exchange Commission in the press bulletin of February 19,1997 and circular 10/97 of Banco de México. 2. On September 10,1998 there was also a discretionary intervention for 278 million dollars.” 3. Banco de Mexico has added additional intervention data. For information on new mechanisms and data please visit: (http://www.banxico.org.mx/sistema-financiero/estadisticas/mercado-cambiario/banco-mexico-s-foreign-exchan.html)

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

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

Data Is Listed As "Summe Der Neuen Konkurse." Data For 1895 Were Computed By Adding "Eroffnung Der Konkursverfahrungs" And All Items Under "Wegen Nichtvorhandenseins" (See Source, 1896, I, P. 156). Only First Quarter Data Are Available For 1911 (See Source Footnote, 1913, Ii, P. 208). For 1913 Data See Source, 1913, Iii, P. 10. Beginning In The Fourth Quarter Of 1918 Alsaice-Lorraine Is Excluded; Beginning In The Fourth Quarter Of 1921 The Saar Is Also Excluded. Source: Statistisches Reichsamt, Vierteljahrshefte Zur Statistik; Monthly Figures For 1925-1932 Also From Konjunkturstatistisches Jahrbuch, 1933, P. 170. This NBER data series m09043 appears on the NBER website in Chapter 9 at http://www.nber.org/databases/macrohistory/contents/chapter09.html. NBER Indicator: m09043

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).

Exchange Traded Funds (ETFs) are shares of trusts that hold portfolios of stocks designed to closely track the price performance and yield of specific indices. Copyright, 2016, Chicago Board Options Exchange, Inc. Reprinted with permission.

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

OECD Data Filters: REF_AREA: CHN 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: IR3TCD01 OECD unit ID: PC OECD country ID: JPN All OECD data should be cited as follows: OECD, "Main Economic Indicators - complete database", Main Economic Indicators (database), https://dx.doi.org/10.1787/data-00052-en (Accessed on date) Copyright, 2016, OECD. Reprinted with permission

OECD Descriptor ID: BSCICP03 OECD unit ID: IDX 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

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

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/).

A zero value for the index indicates that the national economy is expanding at its historical trend rate of growth; negative values indicate below-average growth; and positive values indicate above-average growth. For further information, please visit the Federal Reserve Bank of Chicago's web site: http://www.chicagofed.org/webpages/research/data/cfnai/current_data.cfm

OECD Descriptor ID: IRSTFR01 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

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.

OECD Data Filters: REF_AREA: IRL 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)).

Source Code: Q:AT: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.

M2 comprises currency in circulation and demand, time, and savings deposits in national currency of other financial corporations, public nonfinancial corporations, private nonfinancial corporations, and households with the CBR and 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/).

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 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: HUN 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)).