Showing 9-16 of 43 results
Industry-Level Policy and Economic Indicators for Indian Sectors

Industry-Level Policy and Economic Indicators for Indian Sectors

carol.reyes.dulong
Open Dataset
Creators: Natalie Bau, Adrien Matray
Publication Date: 2023-01-01
Creators: Natalie Bau, Adrien Matray

This dataset collection compiles firm- and sector-level data to support the analysis of economic activity and policy conditions across Indian industries. It includes measures of foreign direct investment (FDI) restrictions at multiple NIC classification levels, tariff schedules, dereservation indicators, and state-level financial development variables. Additionally, it provides merged datasets linking financial indicators from the Reserve Bank of India (RBI) with NIC-based classifications. To ensure comparability over time, the collection contains crosswalks between NIC codes and a variety of deflators, covering output, input, capital, and GDP, along with currency conversion rates. These files enable real-term adjustments and longitudinal consistency in economic indicators, facilitating empirical research on industrial dynamics and regulatory environments.

Food Consumption, Prices, and Nutrient Characteristics

Food Consumption, Prices, and Nutrient Characteristics

carol.reyes.dulong
Open Dataset
Creators: Jean‐Jacques Forneron
Publication Date: 2023-05-01
Creators: Jean‐Jacques Forneron

This collection includes structured data on food item consumption quantities, associated prices, and nutritional content. Variables cover a wide range of food categories and nutrients, enabling analysis of consumption patterns, relative pricing, and dietary composition. Additional metadata clarifies food group classifications and measurement units to support consistent interpretation. The data structure allows for temporal and comparative analysis across items, suitable for applications in food economics, nutrition studies, and price analysis.

Macroeconomic Time Series for Policy Shock Analysis

Macroeconomic Time Series for Policy Shock Analysis

carol.reyes.dulong
Open Dataset
Creators: Alisdair McKay, Christian K. Wolf
Publication Date: 2023-09-01
Creators: Alisdair McKay, Christian K. Wolf

This dataset provides macroeconomic time-series variables prepared for structural vector autoregression (VAR) analysis. It includes indicators such as real output, inflation, interest rates, and monetary policy shocks. The variables are formatted to support empirical evaluation of policy scenarios through VAR-based counterfactual exercises. Metadata from the accompanying documentation clarifies variable transformations and modeling roles within the policy identification framework.

US State-Level Corporate Tax, Apportionment, and Control Variables with FIPS Crosswalk (1980–2014)

US State-Level Corporate Tax, Apportionment, and Control Variables with FIPS Crosswalk (1980–2014)

carol.reyes.dulong
Open Dataset
Creators: Suárez Serrato, Juan Carlos, and Owen Zidar
Publication Date: 2019-12-10
Creators: Suárez Serrato, Juan Carlos, and Owen Zidar

This dataset collection provides comprehensive, state-level information on corporate tax rates, apportionment factors, and tax base controls for the United States covering various periods from 1980 to 2014. It includes a crosswalk file linking state FIPS codes to different state names and abbreviations, detailed records of both state and federal corporate tax rates by state-year, and apportionment factors (payroll, sales, and property) sourced from the Book of the States by the Council of State Governments. Additionally, it offers a range of state tax base control variables for each state-year, which were used for analytical controls in related research. This collection is designed to support empirical analysis in public finance, taxation policy, and state-level economic research.

Consolidated banking statistics

Consolidated banking statistics

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

The consolidated banking statistics (CBS) measure international banking activity from a nationality perspective, focusing on the country where the banking group’s parent is headquartered.

While residence-based data such as the locational banking statistics indicate where positions are booked, they do not always identify where underlying decisions are made. This is because banking offices in one country may operate within a business model decided by the group’s controlling parent, which may be headquartered in another country. The CBS capture the worldwide claims of banking groups based in reporting countries and exclude intragroup positions, similar to the consolidation approach followed by banking supervisors. The CBS provide several different measures of banking groups’ country risk exposures, on either an immediate counterparty or a guarantor basis. The most appropriate exposure measure depends on the issue being analysed. The benchmark measure in the CBS is foreign claims, which capture credit to borrowers outside a banking group’s home country.

Debt securities statistics

Debt securities statistics

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

This data set covers borrowing and investment activities in debt capital markets, capturing debt instruments designed to be traded in financial markets such as treasury bills, commercial paper, negotiable certificates of deposit, bonds, debentures and asset-backed securities. These statistics are harmonised with the recommendations of the Handbook on securities statistics (HSS) and distinguish between debt securities issued and held in international and domestic markets.

The data set is available at quarterly frequency for over 50 economies starting as early as 1946. It benefited from close collaboration with national central banks and national authorities, also as part of the G20 Data Gaps Initiative.

Total debt securities are issued by residents in all markets. Domestic (international) debt securities are issued in (outside) the local market of the country where the borrower resides, regardless of the currency denomination of the security. As valuation methods differ across countries, some amounts are presented at market value and others at nominal or face value.

International debt securities (BIS-compiled)

International debt securities (BIS-compiled)

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

The international debt securities (IDS) statistics cover borrowing activity in debt capital markets. They are issued outside the local market of the country where the borrower resides. They capture debt instruments designed to be traded in financial markets, such as treasury bills, commercial paper, negotiable certificates of deposit, bonds, debentures and asset-backed securities (including issues conventionally known as eurobonds and foreign bonds but excluding negotiable loans). The IDS statistics are compiled from a security-by-security database built by the BIS using information from commercial data providers. Amounts are presented at face value.

The IDS statistics are presented by the issue’s currency, maturity and interest rate type, and the issuer’s nationality and residence. The residence of the issuer is the country where the issuer is incorporated, whereas the nationality of the issuer is the country where the issuer’s parent is headquartered.

Credit to the non-financial sector

Credit to the non-financial sector

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

The data set on credit to the non-financial sector captures borrowing activity by the government sector and the private non-financial sector in more than 40 economies.

Quarterly data on credit to the government sector cover on average 20 years, while those on credit to the private non-financial sector on average more than 45 years. The statistics follow the framework of the System of National Accounts.

On the lending side, two credit data series are provided. On the one hand, total credit comprises financing from all sources, including domestic banks, other domestic financial corporations, non-financial corporations and non-residents. On the other, bank credit includes credit extended by domestic banks to the private non-financial sector.

On the borrowing side, total credit to the non-financial sector is broken down into credit to the government sector and the private non-financial sector, and the latter is further split between non-financial corporations and households (including non-profit institutions serving households).

The financial instruments covered comprise currency and deposits (which are mostly zero in the case of credit to the private non-financial sector), loans and debt securities. The sum of these three instruments is defined here as “core debt”. For the government sector, core debt generally represents the bulk of total debt.

The statistics follow the framework of the System of National Accounts 2008, which stipulates that outstanding credit instruments should be valued at market values. For credit to the government, data are also provided in nominal (face) values, since these can be useful in some forms of debt sustainability analysis.

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