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This paper explores the monetary explanation of the business cycle and the extent to which liquidity management by the banking sector affects it. It estimates a new Keynesian model with a non-trivial role for liquidity, focusing on the transmission mechanism and implications for interest rates, public debt, and real allocations. The findings suggest that shocks to the cost of financial intermediation are relevant for deposit and lending rates, and that public sector bonds provide liquidity services. Further analysis and discussion are needed to explore the role of liquidity in explaining variances in real variables.
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An estimated Euro area model with financial intermediation and central bank liquidity operations Discussion by Massimiliano Pisani Bank of Italy CBMMW 2013 Central Bank of the Republic of Turkey Istanbul, 7-8 November 2013 USUAL DISCLAIMERS HOLD
What’s the paper about • Monetary explanation of the business cycle • To which extent liquidity management by the banking sector matter for business cycle? • Estimation of an (otherwise standard) new Keynesian model featuring a non-trivial role for liquidity
The transmission mechanism • Banks finance loans to firms with households’ deposits and liquidity reserves provided by the central bank • Banks need eligible: public sector bond is collateral in open market operations for getting reserves • Stylized banking costs (increasing in the amount of loans/decreasing in the amount of reserves)
The transmission mechanism • The interest on loans depends on • monetary policy rate • banking costs • value of public sector bonds, which are the collateral in the liquidity constraint of the banking sector
The transmission mechanism: implications • Pass-through from the policy rate into the rate on loans is not full (rate on loans different from Taylor rule based policy rate) • Banking costs do matter for rate on loans • Public debt provides liquidity services (Ricardian equivalence does not hold, because public debt is a collateral and hence distortionary) • Central Bank can affect real allocations not only through the policy rate (Taylor rule), but also through banking sector reserves
Comment: banks’ collateral constraint • Key equation: amount of liquidity the banking sector gets from the central bank depends on the value of collateral, the government bond It = ktpBtBt-1/Rmt • Above mechanism is theoretically parsimonious and powerful (public debt becomes a relevant variable for liquidity, the constraint amplifies shocks)
Comment: banks’ collateral constraint • For the estimation, a shock ηomo,t is included: It =ηomo,t ktpBtBt-1/Rmt • According to the results, ηomo,t is a relevant determinant of reserves and lending rate (forecast error variance decomposition)
Comment: banks’ collateral constraint • Comment: shock in the constraint should be further discussed • Motivation for ηomo,t: according to the authors, in the data only 1/3 of collateral is government bonds; is this a relevant source of misspecification? • Moreover, ηomo,t could also capture the constraint slackness (is the constraint always binding in the data? • No easy theoretical solution (adding bonds other than those issued by public sector in the constraint is not trivial) • Comment: Why k is set to one (money injections vary with price of collateral)? Is it consistent with policy practices in the estimation period?
Comment: Cost of financial intermediation • Results suggest shocks to cost of financial intermediation is relevant for deposit and lending rates Other existing (micro) evidence on its properties: • relevant determinant of the pass-through of policy rate into interest rates on loans and deposits? • Functional form and calibration?
Comment: public finances • Public sector bonds provide liquidity services • Interaction between public finance and monetary policy rules (on money injections and policy rate) can affect (1) price stability, (2) equilibrium determinacy and, hence, (3) estimation • More discussion is needed
Comment: variance decomposition results • Looking at charts and tables, there is a “disconnect” between liquidity sector and real variables • New banking sector-specific shocks do not greatly contribute to explain the variance of real variables • New banking sector-specific shocks explain mainly banking sector variables • Is this result model-specific? Or is it common to other models featuring financial imperfections?
Suggestion: Stylized facts, moment matching, sensitivity • Report stylized facts/puzzles of the market for liquidity (loans, deposits,..) • Report moment analysis (variance, persistence, cross-correlations) • Report sensitivity analysis
To conclude • The paper is an attempt to take interesting theoretical features of monetary policy business cycle to the data • I enjoyed thinking about this paper
To conclude • While the theoretical model seems fine, authors should better think about the estimation/quantitative side (the current draft is preliminary, of course) • Quantitative results built on (1) sound calibration, (2) analysis of the interaction of monetary/public finance policies would be equally interesting • Looking forward for the follow up