Fixed- and Variable-Rate Mortgages, Business Cycles, and Monetary Policy

Rubio, Margarita

doi:10.1111/j.1538-4616.2011.00391.x

Cited by 98 publications

(54 citation statements)

References 29 publications

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“…Most existing business cycle models with housing assume one‐period loans. The interest rate applied to the loan is either the current short‐term interest rate (e.g., Iacoviello, , and many others), a weighted average of the current and past interest rates (Rubio, ), or evolving in a sticky Calvo‐style fashion (Graham and Wright, ). The loan in Iacoviello () is equivalent to

δ_{D t} = 1

for all t , whereas the loans in Rubio () and Graham and Wright () are equivalent to

δ_{D t} = 1

for all t in Equation , but not in Equation .…”

mentioning

confidence: 99%

Housing Dynamics Over the Business Cycle

Kydland

Rupert

Šustek

2016

Int Economic Review

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Housing construction, measured by housing starts, leads GDP in a number of countries.Measured as residential investment, the lead is observed only in the US and Canada; elsewhere, residential investment is coincident. Variants of existing theory, however, predict housing construction lagging GDP. In all countries in the sample, nominal interest rates are low ahead of GDP peaks. Introducing fully-amortizing mortgages and an estimated process for nominal interest rates into a standard model aligns the theory with the observations on starts; one-period loans are insufficient to generate the lead. Longer time to build then makes residential investment cyclically coincident. JEL Classification Codes: E22, E32, R21, R31.

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δ_{D t} = 1

for all t , whereas the loans in Rubio () and Graham and Wright () are equivalent to

δ_{D t} = 1

for all t in Equation , but not in Equation .…”

mentioning

confidence: 99%

Housing Dynamics Over the Business Cycle

Kydland

Rupert

Šustek

2016

Int Economic Review

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“…This is clearly the case with housing demand and LTV shocks, but not, for instance, with total factor productivity (TFP) shocks, which leads us to exclude the latter from our experiments. Importantly and different from previous studies (see, e.g., Rubio ) we do not consider cost‐push shocks either. The latter are known to be a source of policy trade‐off in a standard New Keynesian model.…”

mentioning

confidence: 88%

“…The welfare measure is computed by augmenting the model structure with the following equations:

\begin{matrix} true \\ right {scriptW}_{t}^{j} & \equiv & left E_{0} \sum_{t = 0}^{\infty} {(β^{j})}^{t} {\frac{1}{1 - σ} {(X_{t}^{j})}^{1 - σ} - \frac{1}{1 + ϕ_{C}} {(N_{C, t}^{j})}^{1 + ϕ_{C}} \\ right & left - \frac{1}{1 + ϕ_{H}} {(N_{H, t}^{j})}^{1 + ϕ_{H}}} \end{matrix}

for

j = s, b

, which in recursive form read:

{scriptW}_{t}^{j} = U (X_{t}^{j}, N_{C, t}^{j}, N_{H, t}^{j}) + β^{j} E_{t} {scriptW}_{t + 1}^{j} .

Because of agents' heterogeneity, individual welfare functions must be aggregated into a social welfare function. We follow Lambertini, Mendicino, and Punzi (), Mendicino and Pescatori (), and Rubio () and define the social welfare function as a weighted average of individual welfare as follows:

{scriptW}_{t} \equiv φ^{s} {scriptW}_{t}^{s} + φ^{b} {scriptW}_{t}^{b},

where

φ^{s} = (1 - ω) (1 - β^{s})

and

φ^{b} = ω (1 - β^{b})

, so that given a constant stream of final consumption X , the two agents receive the same level of utility. In the following, we fo...…”

Section: Welfare Evaluationmentioning

confidence: 99%

“…They show that although rental prices are sticky and should therefore be stabilized under the optimal monetary policy rule, asymmetries in factor intensities across sectors imply that the optimal response to rental inflation is actually smaller than what theory would predict in the case of symmetric sectors . More closely related to our study are Mendicino and Pescatori () and Rubio (), who analyze welfare‐maximizing monetary rules in the presence of housing and borrowing constraints. The latter focuses in particular on the role of fixed and variable rate mortgages.…”

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confidence: 95%

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

Notarpietro¹,

Siviero²

2015

J of Money Credit Banking

159

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We probe the scope for reacting to house prices in simple and implementable monetary policy rules, using a New Keynesian model with a housing sector and financial frictions on the household side. We show that the socialwelfare-maximizing monetary policy rule features a reaction to house price variations, when the latter are generated by housing demand or financial shocks. The sign and size of the reaction crucially depend on the degree of financial frictions in the economy. When the share of constrained agents is relatively small, the optimal reaction is negative, implying that the central bank must move the policy rate in the opposite direction with respect to house prices. However, when the economy is characterized by a sufficiently high average loan-to-value ratio, then it becomes optimal to counter house price increases by raising the policy rate.JEL codes: E20, E44, E52

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“…26 We set = 2, implying a value of the labor supply elasticity of 1: 27 Following Horvath (2000) and Iacoviello and Neri (2010), we set the inverse elasticity of substitution across hours in the two sectors to one:For the loan-to-value ratio we consider a steady-state value of 0.67 and 0.80, for the Euro area and Spain, respectively, taking the average LTV ratio observed in the data. 28 The labor-income share of unconstrained consumers, , is set to 0:7. 29 We pick a value of 6…”

Section: Parameter Valuesmentioning

confidence: 99%

Spain and the Crisis: Housing Prices, Credit and Macroprudential Policies

Rubio

Carrasco-Gallego

2017

Singapore Econ. Rev.

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In this paper, we propose a two-country, two sector monetary union DSGE model with housing.One of the countries is calibrated to represent the Spanish economy while the other one is the rest of the European monetary union. First, we illustrate how looser credit conditions coming from the Euro area, together with increases in housing demand, lead to an increase in house prices and credit in Spain. Then, we analyze to what extent, macroprudential policies could have avoided the excess in credit that triggered the …nancial crisis in Spain. We …nd that a countercyclical loan-to-value rule that mainly responds to house prices would have mitigated the credit boom in Spain. These results can also be applied to other countries facing similar problems in the housing sector and thinking about implementing macroprudential policies.

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Fixed- and Variable-Rate Mortgages, Business Cycles, and Monetary Policy

Cited by 98 publications

References 29 publications

Housing Dynamics Over the Business Cycle

Housing Dynamics Over the Business Cycle

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

Spain and the Crisis: Housing Prices, Credit and Macroprudential Policies

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