scholarly journals Has the Fed Responded to House and Stock Prices? A Time-Varying Analysis

2021 ◽  
pp. 1-28
Author(s):  
Knut Are Aastveit ◽  
Francesco Furlanetto ◽  
Francesca Loria
Keyword(s):  
Monetary Policy ◽  
Stock Prices ◽  
Stock Price ◽  
House Prices ◽  
House Price ◽  
Structural Var ◽  
Time Varying ◽  
Systematic Component ◽  
Price Growth ◽  
The Interest Rate

Abstract We investigate whether the Federal Reserve has responded systematically to house and stock prices and whether this response has changed over time using a Bayesian structural VAR model with time-varying parameters and stochastic volatility. To recover the systematic component of monetary policy, we interpret the interest rate equation in the VAR as an extended monetary policy rule responding to ination, the output gap, house prices and stock prices. Our results indicate that the systematic component of monetary policy in the U.S. responded to real stock price growth significantly but episodically, mainly around recessions and periods of financial instability, and took real house price growth into account only in the years preceding the Great Recession. Around half of the estimated response captures the predictor role of asset prices for future ination and real economic activity, while the remaining component reects a direct response to stock prices and house prices.

scholarly journals The Time-Varying Effects of Monetary Policy on House Prices in China: An Application of TVP-VAR Model with Stochastic Volatility

2018 ◽  
Vol 13 (4) ◽  
pp. 149 ◽  
Author(s):  
Weina Cai ◽  
Sen Wang
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
House Prices ◽  
Var Model ◽  
Time Varying ◽  
Credit Channel ◽  
Monetary Policy Shocks ◽  
Time Varying Parameter ◽  
Policy Shocks ◽  
Interest Rate Channel

The boom of housing market in China in recent years has attracted great concerns from all over the world. How monetary policy affects house prices in China becomes an essential topic. This paper studies the time-varying effects of monetary policy on house prices in China during 2005.7-2017.10, by using a time-varying parameter VAR model. This paper obtains three interesting results. First, there are time-varying features of the responses of house prices to monetary policy shocks half-year and 1-year ahead, no matter through interest rate channel or through credit channel. Second, interest rate channel and credit channel have been enhanced since financial crisis in 2008. Third, the responses of nominal house prices to monetary policy in China are mainly driven by the responses of real house prices, instead of inflation. Finally, this paper gives proper suggestions for each finding respectively to central bank in China.

International Real Estate Review

2009 ◽  
Vol 12 (3) ◽  
pp. 193-220
Author(s):  
Karol Jan Borowiecki ◽  
Keyword(s):  
Real Estate ◽  
Positive Impact ◽  
House Prices ◽  
House Price ◽  
Housing Price ◽  
Quality Improvements ◽  
Vector Autoregressive ◽  
Price Growth ◽  
Price Determinants ◽  
A Minor

This paper studies the Swiss housing price determinants. The Swiss housing economy is reproduced by employing a macro- series from the last seventeen years and constructing a vector-autoregressive model. Conditional on a comparatively broad set of fundamental determinants considered, i.e. wealth, banking, demographic and real estate specific variables, the following findings are made: 1) real house price growth and construction activity dynamics are most sensitive to changes in population and construction prices, whereas real GDP, in contrary to common empirical findings in other countries, turns out to have only a minor impact in the short-term, 2) exogenous house price shocks have no long-term impacts on housing supply and vice versa, and 3) despite the recent substantial price increases, worries of overvaluation are unfounded. Furthermore, based on a self-constructed quality index, evidence is provided for a positive impact of quality improvements in supplied dwellings on house prices.

scholarly journals The Time-Varying Effect of Monetary Policy on Asset Prices

2020 ◽  
Vol 102 (4) ◽  
pp. 690-704 ◽  
Author(s):  
Pascal Paul
Keyword(s):  
Monetary Policy ◽  
Asset Prices ◽  
House Prices ◽  
The United States ◽  
Model Parameters ◽  
Time Varying ◽  
Real Economy ◽  
Monetary Policy Shocks ◽  
Vector Autoregressive ◽  
Policy Shocks

This paper studies how monetary policy jointly affects asset prices and the real economy in the United States. I develop an estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks. This is achieved by integrating the surprises into a vector autoregressive model as an exogenous variable. I use current short-term rate surprises because these are least affected by an information effect. When allowing for time-varying model parameters, I find that compared to the response of output, the reaction of stock and house prices to monetary policy shocks was particularly low before the 2007–2009 financial crisis.

scholarly journals Identifying conventional and unconventional monetary policy shocks: a latent threshold approach

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Takeshi Kimura ◽  
Jouchi Nakajima
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Regime Switching ◽  
Structural Var ◽  
Var Model ◽  
Recursive Identification ◽  
Time Varying ◽  
Unconventional Monetary Policy ◽  
Monetary Policy Shocks ◽  
Policy Shocks

AbstractThis paper proposes a new estimation framework for identifying monetary policy shocks in both conventional and unconventional policy regimes using a structural VAR model. Exploiting a latent threshold modeling strategy that induces time-varying shrinkage of the parameters, we explore a recursive identification switching with a time-varying overidentification for the interest rate zero lower bound. We empirically analyze Japan’s monetary policy to illustrate the proposed approach for modeling regime-switching between conventional and unconventional monetary policy periods, and find that the proposed model is preferred over a nested standard time-varying parameter VAR model. The estimation results show that increasing bank reserves lowers long-term interest rates in the unconventional policy periods, and that the impulse responses of inflation and the output gap to a bank reserve shock appear to be positive but highly uncertain.

scholarly journals Club convergence of house prices: Evidence from China’s ten key cities

2015 ◽  
Vol 29 (24) ◽  
pp. 1550181 ◽  
Author(s):  
Hao Meng ◽  
Wen-Jie Xie ◽  
Wei-Xing Zhou
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Economic Recession ◽  
Housing Markets ◽  
Extensive Study ◽  
Ripple Effect ◽  
Chinese Stock Market ◽  
Price Growth ◽  
Chinese Housing Market

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China’s economy has also slowed down by about 2%–3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.

scholarly journals Time-Varying Impacts of Carbon Price Drivers in the EU ETS: A TVP-VAR Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Peng Li ◽  
Hao Zhang ◽  
Yongna Yuan ◽  
Aimin Hao
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Carbon Price ◽  
Paris Agreement ◽  
Fine Tuning ◽  
Time Varying ◽  
Eu Ets ◽  
The European Union ◽  
Oil Gas ◽  
The Eu

This study analyzes the impacts of different drivers on the pricing of EU carbon futures in various periods by using the time-varying parameter vector autoregressive (TVP-VAR) model. The results indicate that: (1) The relationships between oil, gas, electricity, stock prices and carbon price have significant time-varying characteristics and those relationships have experienced an inversion in 2016. This might be due to the pressure of achieving the “EU 20-20-20” targets and the signing of the Paris Agreement as well as the fine-tuning of the European Union Emissions Trading Scheme (EU ETS). (2) The impacts of different drivers on carbon price are various. The carbon price is more sensitive to oil, gas, electricity prices as well as the stock price before the inversion in the short-term, while its response to changes in the stock price after the inversion is more obvious in the mid-long term. (3) After the signing of the Paris Agreement in the second quarter of 2016, the carbon price has a greater response to changes in its drivers. The oil price’s impact on carbon price became the most significant one among them.

scholarly journals Pengaruh Suku Bunga, PER, dan PBV Terhadap Harga Saham Perusahaan Sub Sektor Konstruksi Bangunan

2021 ◽  
Vol 4 (2) ◽  
pp. 706-711
Author(s):  
Rosa Arbaningrum ◽  
Asep Muslihat
Keyword(s):  
Interest Rate ◽  
Stock Prices ◽  
Stock Price ◽  
Descriptive Analysis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Share Price ◽  
Result Show ◽  
The Interest Rate ◽  
Test Result

The study aims to determine how much influence of interest rate, PER, and PBV have on stock prices. The method used is descriptive verification with a quantitative approaches. Data were analyzed using multiple linear regression analysis. Based on the results of a descriptive analysis of the highest interest rate occurred in 2014-2015 while the lowest interest rate in the 2017. There are 5 building construction sub-sector companies that have PER industry average, while 4 other companies have PER above industry average. Furthermore, there are 4 companies that have the value of PBV below the industry average and 5 companies have PBV above the industry average. Then, there are 5 companies that have a share price above the industry average and 4 companies have the stock price below the industry average. Based on the result of verificative analysis that interest rate variable has no signification effect on stock price, while PER variable has no signification effect on stock price and PBV variable has signification effect on stock price. R square test result show that the interest rate, PER, and PBV has effect of 29,3% against the stock price so that remaining 71,7% is affected by other variables that are not researched. Keywords: Interest Rate; PER; PBV; Stock Price.  

scholarly journals Monetary Policy and Intangible Investment

2020 ◽  
Vol 20 (160) ◽  
Author(s):  
Robin Döttling ◽  
Lev Ratnovski
Keyword(s):  
Monetary Policy ◽  
Stock Prices ◽  
Stock Price ◽  
Intangible Assets ◽  
User Cost ◽  
Monetary Policy Shocks ◽  
Policy Shocks ◽  
Total Investment ◽  
Intangible Investment ◽  
Local Projections

We contrast how monetary policy affects intangible relative to tangible investment. We document that the stock prices of firms with more intangible assets react less to monetary policy shocks, as identified from Fed Funds futures movements around FOMC announcements. Consistent with the stock price results, instrumental variable local projections confirm that the total investment in firms with more intangible assets responds less to monetary policy, and that intangible investment responds less to monetary policy compared to tangible investment. We identify two mechanisms behind these results. First, firms with intangible assets use less collateral, and therefore respond less to the credit channel of monetary policy. Second, intangible assets have higher depreciation rates, so interest rate changes affect their user cost of capital relatively less.

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