Optimal Monetary Policy Rules and House Prices: The Role of Financial Frictions

Notarpietro, Alessandro; Siviero, Stefano

doi:10.1111/jmcb.12208

Cited by 159 publications

(6 citation statements)

References 37 publications

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“…In literature, there is no consensus on whether central banks should respond to housing prices or not. However, in recent years, there have been several studies that analyse the extended Taylor rule by incorporating asset and house prices in the central bank’s response function (Aspachs-Bracons & Rabanal, 2011; Finocchiaro & Heideken, 2013; Fuhrer & Tootell, 2008; Gupta & Sun, 2020; Kannan et al, 2012; Notarpietro & Siviero, 2015; Sun & Tsang, 2014). However, so far, there has been no study which takes into account house prices in Turkey.…”

Section: Quantitative Resultsmentioning

confidence: 99%

Turkish Housing Market Dynamics: An Estimated DSGE Model

Yıldırım

İvrendi

2021

Margin: The Journal of Applied Economic Research

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In this article, we investigate the underlying driving dynamics behind house price variations in Turkey by estimating a dynamic stochastic general equilibrium (DSGE) model in which the housing market and collateral constraints are included. The model also analyses the interaction between macroeconomic variables and the housing market by making policy simulations under different loan-to-value (LTV) ratios, which are used as a housing market-specific economic policy tool. The model is extended by including the traditional Taylor rule with house prices for representing monetary policy. Our findings show that house prices in Turkey are largely explained by housing preference shocks. Besides, we find that monetary policy shock plays a small role in determining the variables of the housing market in the short-term period. However, the magnitude of the impact of housing market shocks on the rest of the economy depends on the LTV ratios. The higher the LTV ratio, the higher are the effects of the government’s housing policy instrument for stabilising the housing market on real macroeconomic variables such as consumption and output in Turkey. Finally, our findings show that the fluctuations in house prices have not played a substantial role in the monetary policy reaction function of Turkey. JEL Codes: E32, E52, E44, E51, R31

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Section: Quantitative Resultsmentioning

confidence: 99%

Turkish Housing Market Dynamics: An Estimated DSGE Model

Yıldırım

İvrendi

2021

Margin: The Journal of Applied Economic Research

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“…2009; Christoffel and Schabert 2015). For the housing preference parameter,

η_{H}

, we use the same value 0.1 as in Notarpietro and Siviero (2015). The share parameter in the index of money holdings,

ν

, which corresponds to the relative share of cash in narrow money, is set at 0.2 to capture the predominant use of deposits in transactions in both regions.…”

Section: Parametrizationmentioning

confidence: 99%

“…The parameter for composite monetary assets, 𝜂 x , is set at a low value, 0.01, to capture the common assumption in the literature that the direct utility value of money is fairly small (see, for instance, Coenen et al 2009;Christoffel and Schabert 2015). For the housing preference parameter, 𝜂 H , we use the same value 0.1 as in Notarpietro and Siviero (2015). The share parameter in the index of money holdings, 𝜈, which corresponds to the relative share of cash in narrow money, is set at 0.2 to capture the predominant use of deposits in transactions in both regions.…”

Section: Parametrizationmentioning

confidence: 99%

Global banking, financial spillovers and macroprudential policy coordination

2023

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The transmission of financial shocks and the gains from international macroprudential policy coordination are studied in a two‐region, core–periphery model with a global bank, a two‐level financial structure and imperfect financial integration. The model replicates the stylized facts associated with global banking shocks, with respect to output, credit, house prices and real exchange rate fluctuations in recipient countries, as documented empirically. Numerical experiments, based on a parametrized version of the model, show that the gains from coordination increase with the degree of financial integration, which raises the scope for spillback effects from the periphery to the core, through trade and private capital flows. However, even when coordination is Pareto‐improving, the resulting gains may be highly asymmetric across regions.

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“…Mishkin (2007) reviews the main housing‐related channels of the monetary transmission mechanism and discusses how the housing sector might be a source of financial instability, and whether such instability could affect the ability of a central bank to stabilize the overall economy. Notarpietro and Siviero (2015) probe the scope for reacting to house prices in implementable and straightforward monetary policy rules, using a New Keynesian model with a housing sector and financial frictions on the household side. Nutahara (2017) finds that if housing prices are a target of a central bank, the monetary policy response to asset prices is helpful for equilibrium determinacy.…”

Section: Monetary Policy House and Stock Prices In The Eamentioning

confidence: 99%

“…Although housing has a dual role as a store of wealth and as durable consumption good (Case, Quigley, & Shiller, 2005; Corradin, Fillat, & Vergara‐Alert, 2014; Corradin & Fontana, 2013), its market is prone to boom and bust episodes (Beltratti & Morana, 2010; Reinhart & Rogoff, 2009). This variation leads to financial instability and as such the literature has debated whether this is a suitable guide or predictor for central banks' policymakers to achieve better equilibrium (Mishkin, 2007; Notarpietro & Siviero, 2015; Nutahara, 2017).…”

Section: Introductionmentioning

confidence: 99%

Incorporating asset price stability in the European Central Bank's inflation targeting framework

Shah

Sosvilla‐Rivero

2020

Int. J Fin Econ

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We propose a new flexible inflation targeting index, the economic stability index (ESI), that could enable the European Central Bank (ECB) to implement more effective monetary policy for the euro area (EA). This index incorporates separately weighed house prices and stock prices. Furthermore, by weighting the housing sector in both normal and bubble events, it enhances the forecasting ability and accuracy of this new index. We demonstrate the resilience of this index using a range of robustness checks with multiple empirical methods. Our index that is equipped with these forward‐looking variables enhances the ability to sense potential economic risks, whilst improving price stability and minimizing the output gap variance. This broader index may assist the ECB in addressing the challenges of the long‐term decline of neutral interest rates in many EA economies and the weakening of the inflation/unemployment relationship under the Philips curve. The complexity of the ECB relationship with different fiscal authorities prevents any changes without significant structural variance. The ECB, however, can use a stabilization tool with enhanced foreseeability such as this ESI to improve stability without making significant structural changes.

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Optimal Monetary Policy Rules and House Prices: The Role of Financial Frictions

Cited by 159 publications

References 37 publications

Turkish Housing Market Dynamics: An Estimated DSGE Model

Turkish Housing Market Dynamics: An Estimated DSGE Model

Global banking, financial spillovers and macroprudential policy coordination

Incorporating asset price stability in the European Central Bank's inflation targeting framework

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