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Banking Crisis Impact on Sectoral Exports

Finance & Banking Analytics

Tags and Keywords

Exports

Banking

Crisis

Finance

Economics

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Banking Crisis Impact on Sectoral Exports Dataset on Opendatabay data marketplace

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About

This file examines the impact of banking crises on the export growth of various industrial sectors. It analyses how sectors with high reliance on external finance, like electric machinery, experience reduced export growth compared to sectors with lower dependence, such as footwear. The data also explores the role of tangible assets as collateral, showing that industries with more tangible assets see relatively faster export growth during a crisis. Additionally, it investigates the effect of inter-firm finance, suggesting that sectors reliant on trade credit are not disproportionately affected by a banking crisis, potentially because importers may extend credit to their suppliers.

Columns

  • exporter: Country code of the exporting nation.
  • year: The year of the data record.
  • product: Code representing the product category.
  • tradevalue: The monetary value of the trade.
  • tradeshare: The percentage share of the trade.
  • expgrowth: The growth rate of exports.
  • expgrowthTRIM: The quarterly growth rate of exports.
  • BANK: A variable related to banking.
  • BANK_W3: A variable related to banking.
  • TWIN: A variable labelled 'Twin'.
  • RZ: A variable labelled 'RZ'.
  • FL: A variable labelled 'Fl'.
  • TANG: A variable related to tangible assets.
  • ofagdp: A variable related to GDP.
  • pcrdbofgdp: A variable related to GDP.
  • stmktcap: A variable labelled 'CAP'.
  • RecessionAbroad: A variable indicating recession in other countries.
  • GDPgrAbroad: GDP growth in other countries.
  • durables: A variable indicating durable goods.
  • loss: A variable labelled 'Loss'.
  • loss2: A variable labelled 'Loss2'.
  • GDPcap: A variable for GDP Cap.
  • developed: A dummy variable for developed countries.
  • developing: A dummy variable for developing countries.
  • blanguar: A dummy variable.
  • liqsup: A variable labelled 'Liqsup'.
  • forba: A variable labelled 'forba'.
  • forbb: A variable labelled 'forbb'.
  • recaps: A variable labelled 'recaps'.
  • debtrelief: A variable related to debt relief.
  • policytot: A variable for policy.
  • recession: A dummy variable for recession.
  • GDPgr: GDP growth.
  • INVSA: A variable labelled 'Inv'.
  • CCC: A variable labelled 'CCC'.
  • RZyoung: A variable labelled 'reason'.
  • rznoncrisis: A variable labelled 'reason'.
  • caplab: A variable labelled 'lab'.
  • rd: A variable labelled 'rd'.
  • homogeneity: A dummy variable for homogeneity.
  • n: A variable labelled 'n'.
  • herf: A variable labelled 'herf'.
  • intout: A variable labelled 'intout'.
  • contcrisis: A dummy variable for continuous crisis.

Distribution

The data is provided in a single CSV file named finaldataset_1.csv with a size of 17.64 MB. It is structured in a tabular format with 44 columns and approximately 39,600 rows. The dataset is not expected to be updated.

Usage

This dataset is ideal for economic research and financial analysis. It can be used to model the differential effects of financial crises on international trade across various industries. Economists can test hypotheses related to credit constraints, collateral, and trade finance. Financial analysts can use it to assess sector-specific risks associated with banking system instability in different countries.

Coverage

The dataset covers a time range from 1980 to 2006. Geographically, it includes data from 22 unique exporting countries, with Italy and Portugal being the most common. The data spans multiple industrial product sectors. Note that some variables, such as 'ofagdp', 'blanguar', 'liqsup', and 'policytot', have a significant number of missing values.

License

CC0: Public Domain

Who Can Use It

  • Academic Researchers: For empirical studies on the relationship between finance and international trade.
  • Economists at Financial Institutions: To analyse macroeconomic risks and their impact on different export-oriented sectors.
  • Policy Makers: To understand how banking crises affect a country's export economy and to inform policy responses.
  • Data Scientists: For building predictive models on export performance based on financial indicators.

Dataset Name Suggestions

  • Banking Crisis Impact on Sectoral Exports
  • Global Exports and Financial Crises Analysis
  • International Trade Finance during Banking Crises
  • Sectoral Export Performance and Credit Constraints
  • Finance and International Trade Data (1980-2006)

Attributes

Listing Stats

VIEWS

1

DOWNLOADS

1

LISTED

28/09/2025

REGION

GLOBAL

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

VERSION

1.0

Free

Download Dataset in CSV Format