Monetary, Macroprudential Policies and Housing Cycles: Exploring the Nexus in Turkey

Abstract

Given the pro-cyclicality of the financial cycles on the business cycles, it is of importance to analyze whether the use of the traditional monetary policy instruments along with the prudential responsibilities result in the prevention of unsustainable financial cycles e.g., housing cycles. Still, there is not enough empirical evidence regarding the exploration of the nexus between housing variables and monetarymacroprudential policy rules. Observing the developments in housing market in Turkey, that is, the simultaneous increase in both house prices and residential investments in the last decade, the nexus between housing market and macro economy deserves a further investigation. Accordingly, a new Keynesian DSGE model is estimated with Turkish data for a period 2010-2014 using Bayesian techniques in this thesis. Results reveal that arguments for a monetary policy regime that produces aggregate price stability will, as a byproduct, tend to promote stability of housing markets don't fully hold in the estimation. It can also be stated that the monetary policy rules with existing prudential policy instruments may not result in prevention of further housing "bubbles". The Variance-shock decomposition analyses show that demand and supply shocks dramatically determine the cycles of the real housing prices and residential investment whereas the monetary policy shocks and shocks in central bank's inflation target do not explain the volatility of the housing variables. iii GENEL BİLGİLER

Turkish Housing Market Dynamics: An Estimated DSGE Model

“…The discount factor for impatient households, β ' , is set considerably below β , as the collateral constraint is constantly binding. In line with many studies on Turkey (Alp & Elekdağ, 2011; Doğruel & Polat, 2015; Yüksel, 2013), the markup on price and wages are set at X = X wc = X wh = 1.15, which implies a 15 per cent markup in the steady state. The weight on housing in the utility function is set at j = 0.12.…”

“…Their findings show that housing market shocks such as the LTV ratio and housing demand drive the business cycle in China. Similarly, Wen and He (2015) and Ng (2015) show that housing demand substantially explains fluctuation in house prices in China. Ng (2015) also reveals that monetary policy shocks drive movements in residential investments by 32 per cent.…”

“…Similarly, Wen and He (2015) and Ng (2015) show that housing demand substantially explains fluctuation in house prices in China. Ng (2015) also reveals that monetary policy shocks drive movements in residential investments by 32 per cent. Lee and Song (2015) investigate the importance of the housing sector on business cycles in Korea and finds that housing demand shocks explain a majority of fluctuations, mainly of aggregate consumption, through the collateral constraint mechanism.…”

“…Table 1 lists the calibrated parameters. Some of these rely mainly on Iacoviello and Neri (2010) and Hloušek (2016) and other studies on the Turkish economy (Alp & Elekdağ, 2011; Bari & Şıklar, 2016; Çebi, 2012; Doğruel & Polat, 2015; Sekmen & Şıklar, 2016; Yüksel, 2013). The subjective discount rate for patient households ( β ) is set to 0.9950, which shows that the average annual real interest rate over the sample is at a steady state.…”

“…Table 2 reports the mean and distribution of the prior and posterior for all estimated parameters. For most priors, we follow similar studies (Doğruel & Polat, 2015; Hloušek, 2016; Iacoviello & Neri, 2010; Ng, 2015). The prior distribution of patient households’ income share parameter α is set at 0.65 with a standard deviation of 0.05, following a beta distribution.…”