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Effective exchange rates

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.

Bilateral exchange rates

Creators: BIS statistics
Publication Date: 2025-04-03
Creators: BIS statistics

The bilateral exchange rate data set contains long time series on US dollar nominal exchange rates. They record the nominal value of one US dollar (USD) relative to a given currency. A decrease (increase) indicates an appreciation (depreciation) of the currency against the USD.

The data set features daily series for around 80 economies. Most daily series start around 1970, while 14 currencies have data going back to 1950. The data set also includes monthly, quarterly and annual series which cover approximately 190 economies. These series typically feature longer time spans than the daily series and start around 1957.

The time series are calculated as end-of-period or averages over daily data. The data set also includes long historical series, which are backdated with comparable low-frequency historical data.

The exchange rates series are compiled combining several sources, ensuring the highest possible level of consistency. The European Central Bank (ECB) is the primary source of daily data for the most recent periods, complemented by data from the US Federal Reserve. Data are also sourced from other BIS member central banks for periods not covered by the ECB or the Federal Reserve. The Deutsche Bundesbank and the International Monetary Fund (International Financial Statistics) are the main sources of historical data.

This data set serves as the input for calculating the BIS effective exchange rates and is also used for foreign exchange conversion into US dollars in other BIS data sets.

Central bank policy rates

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

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.

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

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.

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