262 Resources

Open Dataset

Showing 89-96 of 262 results
Effective exchange rates

Effective exchange rates

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-04-03
Creators: BIS statistics

The BIS effective exchange rates data set covers long time series on nominal and real effective exchange rates. They can serve as a measure of international competitiveness, components of financial conditions indices or as a gauge of the transmission of external shocks.

The broad effective exchange rate indices cover 64 economies. Narrow indices include 26 and 27 economies for the nominal and real indices, respectively. Nominal effective exchange rates (NEER) are calculated as geometric trade-weighted averages of bilateral exchange rates. Real effective exchange rates (REER) are derived by adjusting the NEER by relative consumer prices.

Specifically, changes in the REER take into account both nominal exchange rate developments and the inflation differential against a basket of trading partners. An increase in NEER indicates an appreciation in nominal terms, whereas an increase in REER corresponds to an appreciation in real terms.

The weights used in the calculations of the effective exchange rates are derived from manufacturing trade flows. They capture both direct bilateral trade and third-market competition by double-weighting. To account for changes in trade over time, the weighting pattern is time-varying on a three-year basis. For instance, the effective exchange rates index for 2009 is calculated using the weights which refer to the period from 2008 to 2010. The weights of 1990-92 are applied to data prior to 1990, while the most recent set of weights is also used to calculate effective exchange rates for the latest period. Whenever possible, the BIS uses published US dollar exchange rates and consumer prices as inputs for the effective exchange rates.

Central bank total assets

Central bank total assets

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-02-27
Creators: BIS statistics

The BIS central bank total assets data set tracks the evolution of the size of central banks’ balance sheets across the world. It covers more than 50 advanced and emerging market economies.

This data set contains long annual, quarterly and monthly series. The annual series feature an average length of around a century and, for most of the countries, show data since the establishment of the central bank. The median start year is 1942, and several series go back to the 19th century or earlier. Data with higher frequency often start later than annual series due to the limited availability of historical data.

Data on central banks’ balance sheets originate from multiple sources. Financial statements or accounting balance sheets are typically the main source and are compiled in accordance with national accounting standards. Other sources include the monetary presentation or statistical balance sheets.

Central bank policy rates

Central bank policy rates

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-04-03
Creators: BIS statistics

The BIS central bank policy rates data set tracks the evolution of policy rates across the world. The policy rate is an important instrument used by central banks to implement their monetary policy.

The central bank policy rates data set features long time series for more than 40 advanced and emerging market economies, on a daily and monthly frequency.

This data set is unique in three respects. First, the BIS has closely collaborated with national central banks in the selection of the policy rate(s). Depending on the country, the policy rate may correspond to the target, repo or discounting rate. For periods when monetary policy was not conducted with an interest rate instrument, eg under monetary base targeting, the most widely referenced money market or central bank interest rate is taken.

Second, the data set also contains historical data to construct long, spliced series. Most daily series start after 1980, with data going back to 1946 for several economies. From January 2024, the BIS disseminates historical policy rates for selected euro area countries. Third, the series are published along extensive metadata, which detail, for example, the underlying series spliced into the main policy rate or the time lag between the announcement of the policy rate change and the day it becomes effective.

Retail payments, currency and related indicators

Retail payments, currency and related indicators

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-03-25
Creators: BIS statistics

The BIS statistics on the supply and use of retail payments are part of the Red Book statistics of the 27 member jurisdictions of the Committee on Payments and Market Infrastructures (CPMI) and are published annually.

The statistics contain two distinct sections. The first section includes general macroeconomic statistics, which can be used to relate the size of a country’s payment industry to the size of its economic activity. This section also includes figures on banknotes and coins in circulation and on the narrow money supply. The second section details institutions offering payment services to end users, supply of cards and terminals, use of cashless payments, cash withdrawals and deposits. The data set also presents qualitative information on card schemes.

The country tables present developments for individual CPMI jurisdictions over time. The comparative tables combine key data from the country tables from all CPMI jurisdictions. The comparative tables also contain qualitative information on credit and debit card schemes.

Financial market infrastructures and critical service providers

Financial market infrastructures and critical service providers

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-03-25
Creators: BIS statistics

The BIS statistics on financial market infrastructures and their critical services are part of the Red Book statistics of the 27 member jurisdictions of the Committee on Payments and Market Infrastructures (CPMI) and are published annually.

The statistics detail quantitative and qualitative information on participation and activities in payment systems, central securities depositories and central counterparties, such as the number of members and their overall settlement/clearing activity. This section also provides information on the flows of SWIFT messages.

The financial market infrastructures covered in the statistics are:

  • Payment systems: Payment systems (PS). A distinction is made between:
    • Large-value Payment Systems (LVPS)
    • Retail payment systems (RPS)
    • Fast payment systems (FPS)
  • Central counterparties (CCP) or clearing houses (CH)
  • Central securities depositories (CSD)
  • Trade repositories (TR)

The country tables present developments for individual CPMI jurisdictions over time. The comparative tables combine key data from the country tables from all CPMI jurisdictions. The comparative tables also contain qualitative information on the payment systems, central securities depositories, central counterparties and trade repositories in the CPMI jurisdictions.

Locational banking statistics

Locational banking statistics

carol.reyes.dulong
Open Dataset
Creators: BIS statistics
Publication Date: 2025-03-11
Creators: BIS statistics

The locational banking statistics (LBS) measure international banking activity from a residence perspective, focusing on the location of the banking office.

They are compiled following principles that are consistent with balance of payments statistics. The LBS capture the outstanding claims (financial assets) and liabilities of internationally active banks located in reporting countries on counterparties residing in more than 200 countries. Banks record their positions on an unconsolidated basis, including intragroup positions between offices of the same banking group. The LBS capture around 95% of all cross-border banking activity. The availability of a currency breakdown in the LBS, coupled with the reporting of breaks arising from changes in methodology, reporting practices or reporting population, enables the BIS to calculate break- and exchange rate-adjusted changes in amounts outstanding. Such adjusted changes approximate underlying flows during a quarter.

Artstor Museum Image Data

Artstor Museum Image Data

Stefan
Open Dataset
Creators: ARTSTOR
Publication Date: 2025
Creators: ARTSTOR

Explore Artstor’s collections of high-quality images, curated from leading museums and archives around the world. Artstor’s diverse collections are rights-cleared for education and research, and include Open Access content as well as rare materials not available elsewhere. Artstor gives access to 865.914 items in 308 collections.

Social Network Data of Student Relationships

Social Network Data of Student Relationships

Stefan
Open Dataset
Creators: Rebecca Mauldin
Publication Date: 2024
Creators: Rebecca Mauldin

This dataset is from longitudinal social network analysis research that collected survey data from one class of graduate students (N=142) in a Master of Social Work (MSW) program in a large U.S. public university. The program used cohort-based learning in the first semester after which students were integrated into the student body as a whole. The dataset contains network data about friendships, academic discussion ties, and professional influence among classmates. Student attribute data include archival data from the school (e.g., student demographics, incoming GPA, GRE scores) and survey items (e.g., sense of belonging scale, multicultural perspective, perceived stress).

DATA-SPECIFIC INFORMATION

Participation Status across all Four Waves Overview:
File name: ParticipationAcrossWaves.csv
Number of variables: 6
Number of cases/rows: 145

Wave 1 Characteristics Overview:
File name: w1_Characteristics.csv
Number of variables: 39
Number of cases/rows: 145

Wave 3 Characteristics Overview:
File name: w3_Characteristics.csv
Number of variables: 40
Number of cases/rows: 145

Wave 4 Characteristics Overview:
File name: w4_Characteristics.csv
Number of variables: 49
Number of cases/rows: 145

Wave 1 Know-of Ties:
File name: w1_KnowofEdgelist.csv
Number of variables: 2
Number of cases/rows: 169

 

Academic Ties Overview:
File name (wave 2): w2_AcademicEdgelist.csv
Number of variables: 2
Number of cases/rows: 1464

File name (wave 3): w3_AcademicEdgelist.csv
Number of variables: 2
Number of cases/rows: 1642

File name (wave 4): w4_AcademicEdgelist.csv
Number of variables: 2
Number of cases/rows: 2260

Friendship Ties Overview:
File name (wave 2): w2_FriendshipEdgelist.csv
Number of variables: 2
Number of cases/rows: 684

File name (wave 3): w3_FriendshipEdgelist.csv
Number of variables: 2
Number of cases/rows: 752

File name (wave 4): w4_FriendshipEdgelist.csv
Number of variables: 2
Number of cases/rows: 964

Professional Influence Ties Overview:
File name (wave 2): w2_ProfessionalEdgelist.csv
Number of variables: 2
Number of cases/rows: 567

File name (wave 3): w3_ProfessionalEdgelist.csv;
Number of variables: 2
Number of cases/rows: 809

File name (wave 4): w4_ProfessionalEdgelist.csv
Number of variables: 2
Number of cases/rows: 981

Shared Courses Edgelist Overview:
File name: SharedCourseValuedEdgelist.csv
Number of variables: 3
Number of cases/rows: 14,714

Shared Course Affiliation Matrix Overview:
File name: SharedCourseAffiliationMatrix.csv
Number of matrix rows: 145
Number of matrix columns: 145

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