基于小波变换和支持向量的国际原油价格预测

本文将小波分析与支持向量回归结合应用于国际原油价格预测,通过小波多尺度分析方法将油价时间序列分解为长期趋势和随机扰动项,然后采用支持向量回归对分解后的油价长期趋势进行预测。油价长期趋势的预测采用多因素预测方法,主要考虑市场供需基本面、库存、经济、投机等因素对石油价格走势的影响,建立多输入单输出的支持向量回归模型。实证研究表明,支持向量回归模型具有较高的预测性能,对原油价格长期趋势预测中,该方法比回归方法的预测精度高。     

金融危机的演化阶段及其美国检视

过度自由却缺少监管的资产证券化,最终酿成了美国的次贷危机。次贷危机是一次非传统的金融危机,但可以体现所有金融危机的共同特征,即信用扩张背景下的资产价格泡沫。从资产价格泡沫的形成和发展过程来把握金融危机的生成机理,将有助于我们在把握金融危机本质的基础上极大限度地加以防范。     

基于Panel Data模型的住宅价格影响因素研究——以河北省为例

文章引入Panel Data模型,结合河北省住宅市场相关数据,建立住宅价格影响因素模型,通过实证分析找出了影响河北省住宅价格的主要因素。在此基础之上,结合河北省住宅市场的具体情况,提出了调控河北省住宅价格的措施和建议。     

从中石油A股上市事件看我国的价格垄断

中石油A股上市,影响到了整个股市,套牢了所有散户股民,带给社会长久的震撼。中石油属于国有控股企业,直接执行国家的有关政策,具有一定意义上的行政垄断色彩,但由于其经营产品的重要性和特殊性,又具有一定的自然垄断色彩。因此,对中石油价格垄断性质的界定,是新出台的《反垄断法》和其他相关制度对其规制的前提。     

农产品价格上涨的经济学分析——以陕西省为例

农业的深层危机来源于农民和土地。工业化、城市化的发展使农村大量耕地被占用;伴随农村劳动力向城市的转移,农业劳动力老龄化、文化程度低、以女性为主的特点导致农业生产技术利用率低,单位面积产量低;土地质量的下降又进一步制约着农产品产量增长。然而,在农产品市场供给降低的同时,人口消费、饲料消耗、工业用粮的增长却使消费需求不断增加。农产品供给与需求的失衡是农产品价格不断上涨的根本原因。     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

油价冲击、货币政策调整与产出波动——基于中国的经验证据

本文基于我国2001-2010年宏观经济月度数据,采用SVAR模型分析了国际油价波动时,央行货币政策在排除回应油价干扰与未排除干扰下的反应差异及油价波动对产出的影响。研究发现,在排除货币政策回应油价波动干扰后,通过脉冲响应函数反映的油价波动对产出的短期负面影响消失。方差分解结果显示,长期内产出波动由油价冲击和货币政策解释的比例分别为5716%和32480%,比排除干扰前分别下降了2569%和4560%。这说明我国油价冲击带来的经济衰退主要是因为货币政策及其回应油价冲击紧缩所致。此外,面对油价的短期冲击,CPI指数并未随着生产者购进价格指数上升而上升,产出也未发生明显的衰减;但在较长时间内,油价上升会因为相对价格的改变,而影响CPI水平和货币政策,从而对产出产生显著的负面影响。     

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.     

The Effects of Megamergers on Efficiency and Prices: Evidence from a Bank Profit Function

This paper examines the efficiency and price effects of mergers by applying a frontier profit function to data on bank megamergers. We find that merged banks experience a statistically significant 16 percentage point average increase in profit efficiency rank relative to other large banks. Most of the improvement is from increasing revenues, including a shift in outputs from securities to loans, a higher-valued product. Improvements were greatest for the banks with the lowest efficiencies prior to merging, who therefore had the greatest capacity for improvement. By comparison, the effects on profits from merger-related changes in prices were found to be very small.     

What moves housing markets: A variance decomposition of the rent–price ratio

We apply the dynamic Gordon growth model to the housing market in 23 US metropolitan areas, the four Census regions, and the nation from 1975 to 2007. The model allows the rent–price ratio at each date to be split into the expected present discounted values of rent growth, real interest rates, and a housing premium over real rates. We show that housing premia are variable and forecastable and account for a significant fraction of rent–price ratio volatility at the national and local levels, and that covariances among the three components damp fluctuations in rent–price ratios. Thus, explanations of house-price dynamics that focus only on interest rate movements and ignore these covariances can be misleading. These results are similar to those found for stocks and bonds.