A Global Database of Inflation
The World Bank’s Prospects Group has constructed a global database of inflation. The database covers up to 196 countries over the period 1970-2021, and includes six measures of inflation in three frequencies (annual, quarterly, and monthly):
- Headline consumer price index (CPI) inflation
- Food CPI inflation
- Energy CPI inflation
- Core CPI inflation
- Producer price index inflation
- Gross domestic product deflator
The database also provides aggregate inflation for global, advanced-economy, and emerging market and developing economies as well as measures of global commodity prices.
Jordà-Schularick-Taylor Macrohistory Database
With the latest release (R.5), the data now covers 18 advanced economies since 1870 on an annual basis. We have been able to add Ireland thanks to the work of Ronan Lyons and his team at Trinity College Dublin. Recent additions include long-run bank capital ratios and loan-to-deposit ratios. The database now comprises 48 real and nominal variables. Among these, there are many time series that had been hitherto unavailable to researchers, among them financial variables such as bank credit to the non-financial private sector, mortgage lending and long-term returns on housing, equities, bonds and bills. The database captures the near-universe of advanced-country macroeconomic and asset price dynamics, covering on average over 90 percent of advanced-economy output and over 50 percent of world output.
Nominal GDP (local currency), Real GDP per capita (PPP), Real GDP per capita (index, 2005=100), Real Consumption per capita (index, 2006=100), Investment-to-GDP Ratio, Population
Current Account (nominal, local currency), Imports (nominal, local currency), Exports (nominal, local currency), USD Exchange Rate (local currency/USD)
Government Revenue (nominal, local currency), Government Expenditure (nominal, local currency), Public Debt-to-GDP Ratio
Money, Prices & Interest Rates
Narrow Money (nominal, local currency), Broad Money (nominal, local currency), Short-term Interest Rate (nominal, percent per year), Long-term Interest Rates (nominal, percent per year), Consumer Prices (index, 1990=100)
Total Loans to Non-financial Private Sector (nominal, local currency), Mortgage Loans to Non-financial Private Sector (nominal, local currency), Total Loans to Households (nominal, local currency), Total Loans to Business (nominal, local currency)
House Prices (index, 1990=100)
Systemic Financial Crisis (0-1 dummy)
Rates of Return
Equity Total Return, Capital Gain and Dividend Yield; Housing Total Return, Capital Gain and Rental Yield; Government Bond Total Return, Government Bill Rate; Total Rates of Return on Risky and Safe Assets, and on Overall Wealth. All data are nominal, local currency
Peg (0-1 dummy), Strict Peg (0-1 dummy), Peg Type (Base, Peg, Float), Peg Base
Bank Balance Sheet Ratios
Capital Ratio, Loan-to-Deposit Ratio, Non-core Funding Ratio
International Monetary Fund – Guide
The last decade or so has seen a mushrooming of new sovereign debt databases covering long time spans for several countries. This represents an important breakthrough for economists who have long sought to, but been unable to tackle, first-order questions such as why countries have differential debt tolerance, and how debt levels affect the scope for countercyclical policy in recessions and financial crises. This paper backdrops these recent data efforts, identifying both the key innovations, and cautions that users should be aware of. A Directory of existing publicly available sovereign debt databases, featuring compilations by institutions and individual researchers, is also included.
Organisation for economic co-operation and development – OECD.Stat
The Financial Statistics dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and some selected other countries.
The dataset itself contains financial statistics on 4 separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial statistics for which comparable data across countries is available. In all cases, a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. All data are available monthly, and are presented as either an index (where the year 2010 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context.
Bilateral exchange rates vis-à-vis the US dollar are available here: https://data.oecd.org/conversion/exchange-rates.htm
PPP conversion rates vis-à-vis the US dollar are available here: https://data.oecd.org/conversion/purchasing-power-parities-ppp.htm
The database can be completely downloaded in a CSV file. After the importation of the file in Excel, you may have to use the Excel N function and the VALUE function (CNUM in French) to transform the data in numerical value.
The computation methodology for the PPP is described here: https://www.oecd-ilibrary.org/economics/eurostat-oecd-methodological-manual-on-purchasing-power-parities_9789264189232-en
Monthly exchange rates can be found here: https://stats.oecd.org/
University of Groningen – Penn World Table
PWT version 10.0 is a database with information on relative levels of income, output, input and productivity, covering 183 countries between 1950 and 2019.
The database is accessible in Excel, Stata and online here: https://www.rug.nl/ggdc/productivity/pwt/
The documentation about various vintages of the PWT is available here: https://www.rug.nl/ggdc/productivity/pwt/pwt-documentation
The data for the bilateral exchange rates against the US dollar are available in the PWT and the PPP conversion rates are provided by the World Bank’s International Comparison Program (ICP). The PPP rates can be found here: https://www.worldbank.org/en/programs/icp
The PPP’s calculations and results are described in the following report: https://openknowledge.worldbank.org
CEPII – EQCHANGE: A World Database on Actual and Equilibrium Effective Exchange Rates
EQCHANGE is a global database of annual indicators on effective exchange rates. It includes two sub-databases containing data on (i) nominal and real effective exchange rates, and (ii) equilibrium real effective exchange rates and corresponding currency misalignments for advanced, emerging and developing countries. More specifically, the first sub-database delivers effective exchange rates for 187 countries that are computed under three different weighting schemes and two panels of trading partners (186 and top 30) over the 1973-2016 period. The second sub-database provides behavioral equilibrium exchange rate (BEER) estimates and corresponding currency misalignments for 182 economies over the 1973-2016 period.
Click here for a tutorial on how to use EQCHANGE
Bibliographic reference: Cécile Couharde, Anne-Laure Delatte, Carl Grekou, Valérie Mignon and Florian Morvillier (2017), “EQCHANGE: A World Database on Actual and Equilibrium Effective Exchange Rates”, Working Paper CEPII 2017-14.
Database available after inscription here.
BIS – The new BIS effective exchange rate indices
The BIS effective exchange rate (EER) indices have been expanded and updated. The new indices cover 52 economies based on a consistent methodology, and reflect recent developments in global trade by using time-varying weighting patterns. Newly calculated indices have been made available to the public on the BIS website. The BIS effective exchange rate (EER) indices cover 61 economies, including individual euro area countries and, separately, the euro area as an entity. The most recent weights are based on trade in the 2011-13 period, with 2010 as the indices’ base year. Nominal EERs are calculated as geometric weighted averages of bilateral exchange rates. Real EERs are the same weighted averages of bilateral exchange rates adjusted by relative consumer prices. The weighting pattern is time-varying (see broad and narrow weights). The EER indices are available as monthly averages. An increase in the index indicates an appreciation. Broad indices comprise 61 economies. Narrow indices comprise 26 and 27 economies for the nominal and real indices, respectively.
BRUEGEL – Real effective exchange rates for 178 countries: a new database
The real effective exchange rate (REER), which measures the development of the real value of a country’s currency against the basket of the trading partners of the country, is a frequently used variable in both theoretical and applied economic research and policy analysis. It is used for a wide variety of purposes, such as assessing the equilibrium value of a currency, the change in price or cost competitiveness, the drivers of trade flows, or incentives for reallocation of production between the tradable and the non-tradable sectors. Due to the importance of the REER in economic research and policy analysis, several institutions, such as the World Bank, the Eurostat, the BIS, the OECD, just to name a few, publish various REER indicators which are freely downloadable. Altogether, these institutions publish data for 113 countries. The countries for which data are available include several advanced and several emerging and developing countries. However, different databases may have different methodologies and even the 109 countries included in the World Bank database miss several dozen countries of the world.
USDA – Agricultural Exchange Rate Data Set
This data set contains annual and monthly data for exchange rates important to U.S. agriculture. It includes both nominal and real exchange rates for 79 countries, plus the European Union (EU), as well as real trade-weighted exchange rate indexes for many commodities and aggregations. All series are updated quarterly. Data series start at the beginning of 1970 and run to the last available data point. The data described above allow us to report a complete monthly series of nominal, real, and trade-weighted exchange rates for 79 countries from January 1970 to the present month. Several criteria are used in selecting countries included in the data set. First, the countries included must reflect the bulk of U.S. agricultural exports for each covered commodity. In all cases, more than 90 percent of U.S. exports are represented by the countries chosen. A second objective is to have representative coverage of regions around the world. For example, African countries were selected based on their overall economic importance. Lastly, data availability is a constraint on country selection. Only countries with available data on nominal exchange rates and CPIs sufficient to derive a relatively reliable and complete data series were considered.