Turkish Housing Market Dynamics: An Estimated DSGE Model

2021 ◽  
Vol 15 (2) ◽  
pp. 238-267
Author(s):  
Mustafa Ozan Yıldırım ◽  
Mehmet İvrendi
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Policy Instrument ◽  
Dsge Model ◽  
Macroeconomic Variables ◽  
Dynamic Stochastic ◽  
Monetary Policy Reaction Function ◽  
The Impact

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

scholarly journals Liquidity, interest rates and house prices in the euro area: a DSGE analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 4-25 ◽  
Author(s):  
Margarita Rubio ◽  
José A. Carrasco-Gallego
Keyword(s):  
Interest Rates ◽  
Monetary Union ◽  
Euro Area ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Dsge Model ◽  
Content Type ◽  
The Core ◽  
Dynamic Stochastic

Purpose This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery. Design/methodology/approach In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies. Findings The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies. Originality/value This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

scholarly journals House prices and neighbourhood amenities: beyond the norm?

2018 ◽  
Vol 11 (2) ◽  
pp. 263-289 ◽  
Author(s):  
Michael James McCord ◽  
Peadar Thomas Davis ◽  
Paul Bidanset ◽  
William McCluskey ◽  
John McCord ◽  
...  
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Ordinary Least Squares ◽  
Content Type ◽  
Conditional Quantiles ◽  
Price Distribution ◽  
Regression Techniques ◽  
High Level ◽  
The Impact

Purpose Understanding the key locational and neighbourhood determinants and their accessibility is a topic of great interest to policymakers, planners and property valuers. In Northern Ireland, the high level of market segregation means that it is problematic to understand the nature of the relationship between house prices and the accessibility to services and prominent neighbourhood landmarks and amenities. Therefore, this paper aims to quantify and measure the (dis)amenity effects on house pricing levels within particular geographic housing sub-markets. Design/methodology/approach Most hedonic models are estimated using regression techniques which produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price. This paper uses a quantile regression (QR) approach that provides a “more complete” depiction of the marginal impacts for different quantiles of the price distribution using sales data obtained from 3,780 house sales transactions within the Belfast Housing market over 2014. Findings The findings emerging from this research demonstrate that housing and market characteristics are valued differently across the quantile values and that conditional quantiles are asymmetrical. Pertinently, the findings demonstrate that ordinary least squares (OLS) coefficient estimates have a tendency to over or under specify the marginal mean conditional pricing effects because of their inability to adequately capture and comprehend the complex spatial relationships which exist across the pricing distribution. Originality value Numerous studies have used OLS regression to measure the impact of key housing market externalities on house prices, providing a single estimate. This paper uses a QR approach to examine the impact of local amenities on house prices across the house price distribution.

scholarly journals Regional house price cycles in the UK, 1978-2012: a Markov switching VAR

2014 ◽  
Vol 7 (3) ◽  
pp. 345-366 ◽  
Author(s):  
Rosen Azad Chowdhury ◽  
Duncan Maclennan
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Housing Policy ◽  
Markov Switching ◽  
House Price ◽  
Empirical Work ◽  
Extensive Literature ◽  
Content Type ◽  
The Impact ◽  
The Way

Purpose – This paper aims to use Markov switching vector auto regression (MSVAR) methods to examine UK house price cycles in UK regions at NUTS1 level. There is extensive literature on UK regional house price dynamics, yet empirical work focusing on the duration and magnitude of regional housing cycles has received little attention. The research findings indicate that the regional structure of UK exhibits that UK house price changes are best described as two large groups of regions with marked differences in the amplitude and duration of the cyclical regimes between the two groups. Design/methodology/approach – MSVAR principal component analysis NUTS1 data are used. Findings – The housing cycles can be divided into two super regions based on magnitude, duration and the way they behave during recession, boom and sluggish periods. A north-south divide, a uniform housing policy and a monetary policy increase the diversion among the regions. Research limitations/implications – Markov switching needs high-frequency data and long time spans. Practical implications – Questions a uniform housing policy in a heterogeneous housing market. Questions the impact of monetary policy on a heterogeneous housing market. The way the recovery of the housing market varies among regions depends on regional economic performance, housing market structure and the labour market. House price convergence, beta-convergence. Originality/value – No such work has been done looking at duration and magnitude of regional housing cycles. A new econometric method was used.

scholarly journals The sources of house price change: identifying liquidity shocks to the housing market

2016 ◽  
Vol 9 (1) ◽  
pp. 98-120 ◽  
Author(s):  
Paloma Taltavull de La Paz ◽  
Michael White
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Error Correction ◽  
House Prices ◽  
Price Change ◽  
Housing Prices ◽  
House Price ◽  
Content Type ◽  
The Uk

Purpose The purpose of this paper is to examine the role of monetary liquidity in house price evolution through examining the Asset (housing) Inflation channel. It identifies the main channels of transmission affecting house prices from monetary supply channels to house price change, examining how the Asset Price channel transmits changes in M1 to housing prices in Spain and the UK. Design/methodology/approach The paper uses Vector Auto Regression (VAR) and Error Correction models to test the Asset Inflation channel in the UK and Spain from 1991 to 2013 in two steps. In the first step, the supply elasticity is estimated through the long-term relationship between house prices and stock supply. The second step estimates a Vector Error Correction (VEC) to explain house price dynamics conditioned on supply reactions. The latter is defined as a long-term inverse demand model where housing prices are controlled by fundamentals in each market. Models allow forecast testing using Choleski impulse responses methodology. Findings Several results are found. In the supply model, both countries show rapid convergence to equilibrium with a larger elasticity of supply in Spain than in the UK but with a short run effect of new supply on prices in the UK. Regarding the Asset Inflation Channel model, the paper finds evidence of the existence of a housing accelerator effect in Spain, but not in the UK where changes in liquidity fully impact house prices in one direction. Research limitations/implications Implications of findings are mainly to forecast the effects of Monetary Policy measures in different economies. Practical implications The model supports the evaluation of different impacts of monetary policy in territories. It shows that the same policy will have different impacts in different housing markets and therefore highlights the importance of examining each market separately to identify the appropriate policy interventions. Originality/value This is the first paper that estimates the impact of the Asset Inflation Channel on house prices that endogenises housing market conditions and compares effects and interrelationships in two different economies.

scholarly journals Housing prices in peninsular Malaysia: supported by income, foreign inflow or speculation?

2019 ◽  
Vol 12 (3) ◽  
pp. 424-441 ◽  
Author(s):  
Wang Li Wong ◽  
Chin Lee ◽  
Seow Shin Koong
Keyword(s):  
Housing Market ◽  
Low Income ◽  
House Prices ◽  
Correction Term ◽  
Housing Prices ◽  
House Price ◽  
Peninsular Malaysia ◽  
Financial Asset ◽  
Content Type ◽  
The Impact

Purpose This paper is motivated by a concern about the ability of the average Malaysian income to catch up with the rapidly increasing house prices in Peninsular Malaysia. Financial innovation in financial system now regards houses as a financial asset and speculation vehicle. Therefore, a house purchase is made to acquire not merely a necessity but also a financial asset which can generate future returns. Given the problems in the housing market, this paper aims to examine the determinants of house prices in Malaysia, including those such as income, population, foreign inflow and speculation. Design/methodology/approach This study adopts panel data analyses, namely, the fixed effect model (FEM) and the pooled mean group (PMG), and uses data at state level in quarterly frequency, spanning from 2005Q1 to 2013Q4. Findings Based on the results of FEM, these determinants influence house prices significantly. Moreover, the PMG results suggest that there is convergence in the model, which are indicated by the significant and negative sign of the error correction term. In conclusion, the rapidly increasing house price is not caused by speculation activities in the housing market. More precisely, Malaysian income is capable of catching up with the increasing house prices. Practical implications As income remains to be one of the major drivers in influencing Malaysian house price, Malaysian Government shall continue the policies of supply low cost houses to the low-income groups and My First Home Scheme (SRP) by offering less stringent rules in applying house loan for the first-time house buyers. Originality/value This study used the actual data of foreign housing purchase obtained from Malaysia Valuation and Property Services Department to represent foreign inflow; therefore, the results will reflect the impact of foreign inflow in a better manner.

scholarly journals The role and significance of planning in the determination of house prices in Australia: Recent policy debates

2021 ◽  
pp. 0308518X2198894
Author(s):  
Peter Phibbs ◽  
Nicole Gurran
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Land Use Planning ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Evidence Base ◽  
Urban Housing ◽  
Price Inflation ◽  
Depth Analysis

On the world stage, Australian cities have been punching above their weight in global indexes of housing prices, sparking heated debates about the causes of and remedies for, sustained house price inflation. This paper examines the evidence base underpinning such debates, and the policy claims made by key commentators and stakeholders. With reference to the wider context of Australia’s housing market over a 20 year period, as well as an in depth analysis of a research paper by Australia’s central Reserve Bank, we show how economic theories commonly position land use planning as a primary driver of new supply constraints but overlook other explanations for housing market behavior. In doing so, we offer an alternative understanding of urban housing markets and land use planning interventions as a basis for more effective policy intervention in Australian and other world cities.

The Impact of the Credit Channel on Macroeconomic Variables and Bank Characteristics in the Brazilian Economy from 2009 to 2018

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Mohammad Farajnezhad
Keyword(s):  
Monetary Policy ◽  
Fixed Effect Model ◽  
Credit Channel ◽  
Macroeconomic Variables ◽  
Brics Countries ◽  
Effect Model ◽  
Level Data ◽  
Monetary Policy Transmission Mechanism ◽  
The Interest Rate ◽  
The Impact

This article uses commercial bank-level data to examine a credit channel of the monetary policy transmission mechanism in the Brazilian economy from BRICS countries.  Static panel data with a fixed-effect model are used for data analysis. Using a sample of 212 commercial banks from 2009 to 2018. According to the findings of this study, there is a significant and positive relationship between macroeconomic variables that affect the interest rate and GDP with the loan amount, but not with the inflation rate. Also, it is reasonable to conclude that banks in Brazil react to monetary policy in a variety of ways.

ENERGY IN A MODEL OF FIRM ENTRY

2018 ◽  
Vol 24 (2) ◽  
pp. 231-254
Author(s):  
Soma Patra
Keyword(s):  
Negative Impact ◽  
The United States ◽  
Energy Price ◽  
Firm Entry ◽  
Energy Prices ◽  
Dsge Model ◽  
Price Shocks ◽  
Firm Level ◽  
Dynamic Stochastic ◽  
The Impact

Nine out of the last ten recessions in the United States have been preceded by an increase in the price of oil as noted by Hamilton [Palgrave Dictionary of Economics]. Given the small share of energy in gross domestic product this phenomenon is difficult to explain using standard models. In this paper, I show that firm entry can be an important transmission and amplifying channel for energy price shocks. The results from the baseline dynamic stochastic general equilibrium (DSGE) model predict a drop in output that is two times the impact in a model without entry. The model also predicts an increase in energy prices would lead to a decline in real wages, investment, consumption, and return on investment. Additionally, using US firm level data, I demonstrate that a rise in energy prices has a negative impact on firm entry as predicted by the DSGE model. This lends further support toward endogenizing firm entry when analyzing the effects of energy price shocks.

Rent or buy, what are the odds? Analysing the price-to-rent ratio for housing types within the Northern Ireland housing market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Lo ◽  
Michael James McCord ◽  
John McCord ◽  
Peadar Thomas Davis ◽  
Martin Haran
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Main Property ◽  
Property Market ◽  
Important Indicator ◽  
Content Type ◽  
Rental Market ◽  
Price Series ◽  
The Relationship

Purpose The price-to-rent ratio is often regarded as an important indicator for measuring housing market imbalance and inefficiency. A central question is the extent to which house prices and rents form part of the same market and thus whether they respond similarly to parallel stimulus. If they are close proxies dynamically, then this provides valuable market intelligence, particularly where causal relationships are evident. Therefore, this paper aims to examine the relationship between market and rental pricing to uncover the price switching dynamics of residential real estate property types and whether the deviation between market rents and prices are integrated over both the long- and short-term. Design/methodology/approach This paper uses cointegration, Wald exogeneity tests and Granger causality models to determine the existence, if any, of cointegration and lead-lag relationships between prices and rents within the Belfast property market, as well as the price-to-rent ratios amongst its five main property sub-markets over the time period M4, 2014 to M12 2018. Findings The findings provide some novel insights in relation to the pricing dynamics within Belfast. Housing and rental prices are cointegrated suggesting that they tend to move in tandem in the long run. It is further evident that in the short-run, the price series Granger-causes that of rents inferring that sales price information unidirectionally diffuse to the rental market. Further, the findings on price-to-rent ratios reveal that the detached sector appears to Granger-cause those of other property types except apartments in both the short- and long-term, suggesting possible spill-over of pricing signals from the top-end to the lower strata of the market. Originality/value The importance of understanding the relationship between house prices and rental market performance has gathered momentum. Although the house price-rent ratio is widely used as an indicator of over and undervaluation in the housing market, surprisingly little is known about the theoretical relationship between the price-rent ratio across property types and their respective inter-relationships.

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