Monetary Policy and Housing Sector Dynamics in a Large-Scale Bayesian Vector Autoregressive Model / Pinigų Politika Ir Būsto Sektoriaus Dinamika Taikant Plataus Masto Bajeso Vektorinį Autoregresinį Modelį

Abstract

<jats:p>Our paper considers the channel whereby monetary policy, a federal funds rate shock, affects the dynamics of the US housing sector. The analysis uses impulse response functions obtained from a large-scale Bayesian vector autoregressive model that incorporates 143 monthly macroeconomic variables over the period of 1986:01 to 2003:12, including 21 variables relating to the housing sector at the national and four Census regions. We find at the national level that housing starts, housing permits, and housing sales fall in response to the tightening of monetary policy. Housing sales react more quickly and sharply than starts and permits and exhibit more duration. Housing prices show the weakest response to the monetary policy shock. At the regional level, we conclude that the housing sector in the south drives the national findings in the sense that the response patterns in the South most closely match the response patterns in the nation as a whole. The West's responses differs the most from the other regions, especially for the impulse responses of housing starts and permits. Santrauka Straipsnyje nagrinėjama, kokiais kanalais pinigų politika (sukrėtimai dėl federalinių fondų palūkanų normos) veikia JAV būsto sektoriaus dinamiką. Analizei naudojamos reakcijos į impulsus funkcijos, gautos iš plataus masto Bajeso vektorinio autoregresinio modelio, kuris apima laikotarpį nuo 1986 m. sausio mėn. iki 2003 m. gruodžio mėn. ir 143 mėnesinius makroekonominius kintamuosius, įskaitant 21 su būsto sektoriumi susijusį kintamąjį nacionaliniu mastu pagal keturis statistinius regionus (angl. Census regions). Nustatyta, kad, nacionaliniu lygmeniu griežtėjat pinigų politikai, statoma mažiau naujų būstų, išduodama mažiau leidimų gyvenamajai statybai ir parduodama mažiau būstų. Prekybos būstais sektorius reaguoja sparčiau ir aštriau nei naujų statybų ir leidimų sektorius, o reakcija trunka ilgiau. Nustatyta, kad būstų kainos į pinigų politikos sukrėtimus reaguoja menkiausiai. Daroma išvada, kad regioniniu lygmeniu Pietų regiono būstų sektorius labiausiai prisideda prie nacionalinių išvadų tuo požiūriu, jog reakcijos pobūdis Pietuose panašiausias į bendrą nacionalinį reakcijos pobūdį. Vakarų reakcija nuo kitų regionų skiriasi labiausiai, ypač kalbant apie reakcijas į impulsus, susijusias su statomais būstais ir statybų leidimais.</jats:p>

Time-varying impact of uncertainty shocks on the US housing market

“…dynamic conditional correlation or rolling estimations, the models in general were restricted to only few macroeconomic variables. Given the well-known fact that the US real estate market is affected by large number of variables (see, Gupta et al, (2011), Gupta et al, (2012a, and Akinsomi et al, 2016 for detailed discussions in this regard), we use an extended factor augmented vector autoregressive (FAVAR) model (as proposed by Mumtaz and Theodoridis (2018)), based on a dataset of 45 variables for the US, that allows the estimation of a measure of macroeconomic uncertainty which encompasses volatility of the real and financial sectors. In addition, we allow for time-varying parameters (TVP) in the proposed FAVAR model (TVP-FAVAR), which in turn allows us to estimate time-varying response of not only house prices, but home sales, permits and starts, as well as sentiment associated with the housing market to uncertainty shocks, thus allowing the investigation of temporal shifts in the overall housing market in a coherent manner.…”

Macroeconomic Shocks and Changing Dynamics of the U.S. REITs Sector

“…Against this backdrop, realizing that housing markets are regional in nature, with tremendous heterogeneity in terms of their response to (monetary) policy shocks [12][13][14], we analyze the role of various macroeconomic shocks in driving the Real Estate Investment Trusts (REITs) prices of the US, which tends to be homogenous across the country, being based on a broad single index. For our purpose, unlike Plakandaras et al [11], we use higher-frequency (monthly) data covering the more recent period 1972:12 of 2016:12.…”

Fiscal Policy Shocks and the Dynamics of Asset Prices: The South African Experience

“…Research on the linkages between economic policy and asset markets typically focuses on monetary policy (Bjørnland and Leitemo 2009;Sousa 2010a, forthcoming a, forthcoming b; Iglesias and Haughton 2011;Castro and Sousa 2012;Gupta et al 2012aGupta et al , 2012b and Jacobsen forthcoming). Whilst monetary policy dominates the field of academic and policy discussions on controlling elements of the business cycle, fiscal policy becomes key when monetary policy reaches the zero interest rate lower bound such as during the Great Recession (Feldstein 2009).…”