Identification of credit supply shocks in a Bayesian SVAR model of the Hungarian economy
AbstractUsing Hungarian macroeconomic and financial data, we estimate a Bayesian structural VAR model suitable for macroprudential simulations. We identify standard macroeconomic and credit supply shocks by sign and zero restrictions. In contrast to the previous literature, different types of credit shocks are distinguished in our paper: a risk assessment and a policy shock. Our main findings are the following. First, we demonstrate that both credit supply and macroeconomic shocks explain the variance of endogenous variables at roughly similar order of magnitude. Second, it is shown that credit supply shocks do not have a dominant role in the decline of the Hungarian economy over the crisis period that started in 2008, although their contribution was non-negligible. Third, the importance of unidentified shocks increased in the crisis period.
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Bibliographic InfoPaper provided by Magyar Nemzeti Bank (the central bank of Hungary) in its series MNB Working Papers with number 2011/7.
Length: 26 pages
Date of creation: 2011
Date of revision:
Bayesian SVAR; zero and sign restrictions; credit supply shocks;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-15 (All new papers)
- NEP-BAN-2011-08-15 (Banking)
- NEP-CBA-2011-08-15 (Central Banking)
- NEP-TRA-2011-08-15 (Transition Economics)
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