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How much does the private sector really borrow - a new database for total credit to the private non-financial sector

Author

Listed:
  • Christian Dembiermont
  • Mathias Drehmann
  • Siriporn Muksakunratana

Abstract

Despite their importance, data capturing total credit to the private non-financial sector are scarce. This article introduces a new BIS database that provides this information for 40 economies with, on average, more than 45 years of quarterly data, reaching back to the 1940s and 1950s in some cases. It explains the key concepts underlying the compilation of the new series, including a description of the high-level statistical criteria applied, the characteristics of the underlying series used and the statistical techniques employed. For illustration purposes, some facets of the historical evolution of total credit are explored, revealing interesting similarities and differences across countries.

Suggested Citation

  • Christian Dembiermont & Mathias Drehmann & Siriporn Muksakunratana, 2013. "How much does the private sector really borrow - a new database for total credit to the private non-financial sector," BIS Quarterly Review, Bank for International Settlements, March.
  • Handle: RePEc:bis:bisqtr:1303h
    as

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    References listed on IDEAS

    as
    1. Stefan Avdjiev & Robert McCauley & Patrick McGuire, 2012. "Rapid credit growth and international credit: Challenges for Asia," BIS Working Papers 377, Bank for International Settlements.
    2. Levine, Ross & Zervos, Sara, 1998. "Stock Markets, Banks, and Economic Growth," American Economic Review, American Economic Association, pages 537-558.
    3. Robert B. Litterman, 1983. "A random walk, Markov model for the distribution of time series," Staff Report 84, Federal Reserve Bank of Minneapolis.
    4. Rajan, Raghuram G & Zingales, Luigi, 1998. "Financial Dependence and Growth," American Economic Review, American Economic Association, pages 559-586.
    5. Patrick McGuire & Philip Wooldridge, 2005. "The BIS consolidated banking statistics: structure, uses and recent enhancements," BIS Quarterly Review, Bank for International Settlements, September.
    6. Rajan, Raghuram G & Zingales, Luigi, 1998. "Financial Dependence and Growth," American Economic Review, American Economic Association, pages 559-586.
    7. Victor Pontines & Reza Siregar, 2012. "Exchange Rate Appreciation, Capital Flows and Excess Liquidity: Adjustment and Effectiveness of Policy Responses," Research Studies, South East Asian Central Banks (SEACEN) Research and Training Centre, number rp87, April.
    8. Cussen, Mary & Phelan, Gillian, 2010. "Irish Households: Assessing the Impact of the Economic Crisis," Quarterly Bulletin Articles, Central Bank of Ireland, pages 62-76, October.
    9. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, pages 372-375.
    10. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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