媒体情绪与房价波动*

本文使用2000—2015年中国112个大中城市媒体报道和房价月度指数研究了媒体异质性对房价波动的影响。研究发现，纸媒情绪对房价波动的影响大于网媒情绪，中央媒体情绪对房价波动的影响大于地方媒体情绪，明星微博情绪对房价波动的影响大于普通微博情绪，媒体语气确定性和报道篇幅对房价波动有正影响，明星城市媒体情绪较非明星城市更易引起房价波动。据此，为防范非理性房价波动，应加强对不同媒体报道的监管。     

媒体情绪与房价波动*

本文使用2000—2015年中国112个大中城市媒体报道和房价月度指数研究了媒体异质性对房价波动的影响。研究发现，纸媒情绪对房价波动的影响大于网媒情绪，中央媒体情绪对房价波动的影响大于地方媒体情绪，明星微博情绪对房价波动的影响大于普通微博情绪，媒体语气确定性和报道篇幅对房价波动有正影响，明星城市媒体情绪较非明星城市更易引起房价波动。据此，为防范非理性房价波动，应加强对不同媒体报道的监管。     

What are the effects of fiscal policy on asset markets?

We investigate the link between fiscal policy shocks and asset markets. Our results show that spending shocks have: a positive and persistent effect on GDP in the U.S. and in the U.K., while for Germany and Italy, such impact is temporary; a positive and persistent effect on housing prices; a negative effect on stock prices; and mixed effects on the price level. A VAR counter-factual exercise suggests that fiscal shocks play a minor role in the asset markets of the U.S. and Germany, and substantially increase the variability of housing and stock prices in the U.K., while government revenue shocks have increased volatility in Italy.     

Forecasting UK house prices: A time varying coefficient approach

Previous studies of UK house prices, developed from the demand and supply ofhousing or from the asset market approach have been poor in terms of robustness and ex-post forecasting ability. The UK housing market has suffered a number of structural changes, particularly since the early 1980s with substantial house price increases, financial market deregulation and the removal of mortgage market constraints through competition. Consequently, models which assume that the underlying data-generating process is stable and apply constant parameter techniques tend to suffer in terms of parameter instability. This article uses the Time Varying Coefficient (TVC) methodology where the underlying data-generating process in the UK housing market is treated as unstable. The estimation results of the TVC regression of UK house prices is compared with those obtained from three alternative constant parameter regressions. Comparisons of forecasting performance suggest the TVC regression out-performs forecasts from an Error Correction Mechanism (ECM), Vector Autoregressive (VAR) and an Autoregressive Time Series regression.     

房地产价格波动与区域经济间的关系——以山西省为例

采用VAR模型,对1990—2009年山西省房地产价格波动与区域经济基本面变量的关系进行了定量分析,并对影响房价波动的关键因素进行了识别。研究表明:山西省的地区生产总值、城镇居民可支配收入、房地产投资额、城镇化水平与商品房价格存在协整关系,且前者均是商品房价格的Granger原因;市场主体预期对房地产价格的影响要大于宏观经济基本面因素。最后提出促进房地产业健康发展的相关建议。     

Measuring asymmetry and persistence in conditional volatility in real output: evidence from three East Asian tigers using a multivariate GARCH approach

We search for evidence of conditional volatility in the quarterly real Gross Domestic Product (GDP) growth rates of three East Asian tigers: Singapore, Hong Kong and Taiwan. The widely accepted Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH)-type model is used to capture the existence of asymmetric volatility and the potential structural break points in the volatility. We find evidence of asymmetry and persistence in the volatility of GDP growth rates. It is noted that the structural breakpoints of volatility correspond reasonably well to the historical economic and political events in these economies. Policy implications from our findings are discussed.     

Exchange rate volatility and export performance: a cointegrated VAR approach

During the last decades Norwegian exporters have–despite various forms of exchange rate targeting–faced a rather volatile exchange rate which may have influenced their behaviour. Recently, the shift to inflation targeting and a freely floating exchange rate has brought about an even more volatile exchange rate. We examine the causal link between export performance and exchange rate volatility across different monetary policy regimes within the cointegrated Vector Autoregression (VAR) framework using the implied conditional variance from a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model as a measure of volatility. Although treating the volatility measure as either a stationary or a nonstationary variable in the VAR, we are not able to find any evidence suggesting that export performance has been significantly affected by exchange rate uncertainty. We find, however, that volatility changes proxied by blip dummies related to the monetary policy change from a fixed to a managed floating exchange rate and the Asian financial crises during the 1990s enter significantly in a dynamic model for export growth–in which the level of relative prices and world market demand together with the level of exports constitute a significant cointegration relationship. A forecasting exercise on the dynamic model rejects the hypothesis that increased exchange rate volatility in the wake of inflation targeting in the monetary policy has had a significant impact on export performance.     

Seoul housing prices and the role of speculation

Between June 1998 and March 2006, the price index of apartment houses in Seoul, Korea, more than doubled, while fundamentals such as GDP, wage, and population increased by less than 35%. This study examines the role of a rational speculative bubble in this price surge. We find that unobservable information explains part of the price volatility; and that a rational bubble proxy is a significant driver of prices. However, neither latent information nor rational bubble is enough to explain the recent housing price appreciation, even in conjunction with observable fundamentals.     

HOUSING IN A NEOCLASSICAL GROWTH MODEL

We present evidence that in the USA, the relative price of housing exhibits secular growth and that its growth rate is a stationary series. The ratio of the value of house stock to either consumption or GDP is also stationary. We develop a two‐sector neoclassical growth model with housing that is consistent with these facts. Among the long‐run determinants of the growth of housing prices and housing stock per capita are factor intensities, rates of technological progress in both the housing and non‐housing sectors, and the excess of population growth over land growth. We also study the model's transitional dynamics.     

价格粘性下人民币不同升值模式对中国经济的影响研究

文章以衰减函数的方式将新凯恩斯学派提出的价格粘性理论引入中国动态可计算一般均衡模型中,使模型更符合经济系统中价格调整规律,并利用模型模拟渐进式升值和快速升值两种不同的人民币升值模式对我国经济的影响。模拟结果表明,在价格粘性的作用下,人民币快速升值将在短期内对我国实体经济产生较大的负面冲击,GDP增速下降最高达1.6个百分点,失业率明显上升,而渐进式升值最高只有0.67个百分点;快速升值能有效抑制我国的通货膨胀和促使我国贸易再平衡,最多使我国CPI增速下降3.6个百分点和贸易顺差占GDP比重下降1.06个百分点,并且在长期内对实体经济的负面效应略小于渐进式升值。因此,在不同的经济形势下应采取不同的人民币升值模式。     

The effects of monetary policy in the Czech Republic: an empirical study

In this paper, we examine the effects of Czech monetary policy on the economy within the vector auto regression (VAR), structural VAR, Bayesian VAR with sign restrictions, and factor-augmented VAR, frameworks. We document a well-functioning transmission mechanism similar to the euro area countries, especially in terms of persistence of monetary policy shocks. Subject to various sensitivity tests, we find that a contractionary monetary policy shock has a negative effect on the degree of economic activity and the price level, both with a peak response after one year or so. Regarding prices at the sectoral level, tradables adjust faster than non-tradables, which is in line with microeconomic evidence on price stickiness. There is no price puzzle, as our data come from a single monetary policy regime. There is a rationale in using the real-time output gap instead of current GDP growth, as using the former results in much more precise estimates. The results indicate a rather persistent appreciation of the domestic currency after a monetary tightening, with a gradual depreciation afterwards.     

Fiscal policy and asset price volatility

This paper investigates the relationship between volatility of different asset prices and the volatility of various indicators of fiscal policy (primary balance, spending and revenue). We find evidence that asset price volatility affects the volatility of fiscal policy stance in a positive and significant way. The effect comes primarily through residential property and equity price volatility on government revenue and spending. Increased volatility in commercial property prices is associated with increased variability of government revenue. Output growth volatility is the dominant determinant of revenue and primary balance variability, whereas bad budgetary conditions and the size of the public sector are the most significant determinants of spending variability. Trade openness leads to greater variability of government spending, revenue and primary balance to GDP ratios.     

The long-run relationship between stock return dispersion and output

Based on the rational that some industry groups are more closely linked to the business cycle than others, we re-examined a previous analysis on the long-term relationship between stock return dispersion by industry and Gross Domestic Product (GDP), which evaluated data until 1987 by extending it to 2008. Using Mean Square Forecast Errors (MSFE) statistics, we find that incorporating the return dispersion in Vector Autoregressive (VAR) models enhances their forecasting power for output (GDP) in the long run. This article also determines that the relationship between stock return dispersion by industry and GDP is tenuous in the recent decade from 1999.     

The Impact of Monetary Policy and Housing-Purchase Restrictions on Housing Prices in China

This paper examines the level and volatility effect of monetary policy on housing prices in China utilizing a novel set of housing price indices constructed by (Fang, H., QuanlinGu, W. X., & Zhou, L.-A. (2015). Demystifying the Chinese housing boom. NBER Macroeconomics Annual 2015, Volume 30. University of Chicago Press.). We find that in the long-run, average housing prices react positively to inflation, money supply and bank lending growth, and negatively to the reserve requirement ratio and benchmark lending rate. Housing prices in Tier 1 cities respond more sensitively to monetary shocks relative to Tier 2 and 3 cities, possibly due to surging demand and limited supply under housing-purchase restrictions (HPR). We further study the volatility effect of monetary shocks using the GARCH model and find that the benchmark lending rate, reserve requirement ratio and money supply growth have strong negative impact on the volatility of housing price growth. Our benchmark results remain robust after incorporating the HPR policy variable in the estimation, with a significant negative effect of HPR on housing price growth in Tier 1 and Tier 2 cities. Lastly, we conclude with recommendations on future monetary policy design and implementation, with a specific focus on the heterogeneous characteristics of China’s housing market.     

Educational attainment,growth and poverty reduction within the MDG framework: simulations and costing for the Peruvian case

Using quarterly data, 1999:Q2–2009:Q3, we empirically examine the key macro determinants of housing prices for China’s residential market. Employing Granger causality and Vector Auto-Regression (VAR) models, we find that there exists strong bivariate causality between house price increases and its determinants. The variance decomposition suggests that speculative factors reflected by past increases in real house price contribute a relatively larger proportion to house price rises relative to fundamental factors.     

The impact of monetary policy on local housing markets: Do regulations matter?

This paper shows that monetary policy has uneven impacts on local housing markets, and that the magnitude of the impacts are correlated with housing supply regulations. We apply the linearized present value model, which allows the log rent–price ratio to be decomposed into the expected present values of all future real interests rates, real housing premia, and real rent growth, to the housing markets in 23 US metropolitan statistical areas. Based on the indirect inference bias-corrected VAR estimates, we find that MSAs that are more regulated have (i) a higher variance in the log rent–price ratio, (ii) a larger share of the variance explained by real interest rate, and (iii) a stronger impulse response of house price to the real interest rate shock.     

Expectation,volatility and liquidity in the housing market

Measuring housing price volatility is fundamental to understanding the dynamics of housing price risk. This article aims to explore whether a liquidity factor plays a role in explaining the second moment (i.e. the volatility) of housing prices. Housing price volatility is measured as the conditional variance of a Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) model under the Adaptive Expectations framework. The empirical evidence reveals that volatility transmits from smaller housing units to larger housing units, which indirectly supports the trade-up effect discussed in the literature. In addition, less liquid housing classes are more sensitive to unexpected liquidity shocks, and the starter housing class is extraordinarily sensitive to negative liquidity shocks. Consistent with friction search theory, pricing errors are alleviated as the trading volume increases, because the valuation price tends to be more accurate as more information is available.     

Cross-country evidence on the relation between stock prices and the current account

This article explores the relation between stock prices and the current account for 17 Organization for Economic Co-operation and Development (OECD) countries in 1980–2007. A panel Vector Autoregressive (VAR) model is used to compare the effects of stock price shocks to those originating from monetary policy and exchange rates. While monetary policy shocks have little effects, shocks to stock prices and exchange rates have sizeable effects. A 10% contraction in stock prices improves the current account by 0.3% after 2 years. Hence a channel – in addition to the traditional exchange rate channel – is found through which external balance for an OECD country with a current account imbalance can be restored.     

Terms of trade and economic growth in Japan and Korea: an empirical analysis

This study examines the impact of terms of trade and terms of trade volatility on economic growth in Japan and Korea using time series data. The results of the Johansen (1988) cointegration method show that real gross domestic product (GDP) per capita and terms of trade are jointly determined. Generally, an increase in terms of trade volatility will lead to a decrease in real GDP per capita. An increase in oil price will lead to a decrease in terms of trade. The results of the generalised forecast error variance decompositions show that the important contributors to real GDP per capita are different between Japan and Korea. A favourable and a less volatile terms of trade are important for economic growth.     

Determinants of land value volatility in the U.S. Corn Belt

ABSTRACT

Understanding land value volatility and its reaction to exogenous shocks helps land owners, investors, and lenders assess risk. Land value volatility, the variance of the unpredictable component of land value growth rates, is modelled for each of the Corn Belt states in the U.S. using EGARCH. A pooled VAR system is then estimated to capture the interactions between land value determinants and land value volatility. The variables of the pooled VAR are split into negative and positive vectors to allow for asymmetric impacts. Impulse response functions are mapped. All states exhibit land value volatility clustering. Inflation, cash rent and population growth rates granger cause land value volatility. Land value volatility responses to negative shocks are greater than those to positive shocks. Lenders and investors should expect greater swings in land values after negative shocks to land value growth rates, but not an overreaction of land values from shocks to cash rent growth rates. Positive shocks to changes in interest rates increases land value volatility, but unexpected shocks to population growth rates do not have statistically significant impact on land value volatility.