中国居民储蓄率的内生断点分析：1953～2005

学术界存在一个主流观点,认为居民的消费行为从新中国成立至今发生过根本性改变,但是对改变发生的时间认识不一。本文用1953~2005年的储蓄率数据来刻画消费行为,从数据本身的角度寻找内生断点。通过引入一个内生断点,我们得出我国储蓄率1953~2005年表现出趋势平稳,再在平稳数据的基础上检验内生断点的存在性,得出经验判断类似,为1978年,从数据本身的角度支持经验研究结论。     

上海房地产市场的现状与政策建设

今年以来，上海房地产主管部门细化相关政策和操作办法，着力于加大房地产市场调控力度，努力实现供求总量基本平衡、结构基本合理，有效控制房价上涨过快的趋势，进一步改善市民住房条件，让市民得到实惠。随着市场调控工作的稳步推进，商品住房市场的供求关系、供应结构已经逐步调整和优化，呈现较为平稳的发展态势。     

随机事件冲击下的金融预期事件分析：模型与实证

为了全面研究金融市场的随机事件以及准确分析后续预期事件，从随机事件和预期事件全样本角度出发，首先，构建了统一框架下的双断点回归模型，并从理论分析的角度阐述了新模型的可行性、优越性和广义性；然后，以“长生疫苗”和“长生退市”为对象，进行两次断点回归和双断点回归的拟合实证，结果分别从拟合效果、参数趋势、稳健性、实际内涵上展示了新模型在预期事件研究中的优越性，表明中国医药市场属于成熟型市场，适合理性投资者关注。研究结论为相关投资者和监管者未来进一步处理随机事件对金融市场的冲击提供了参考。     

今年信贷投放额度多大适宜——兼论货币政策与转方式、调结构

为积极应对金融危机，消减其对我国经济的负面影响，2008年10月份政府迅速调整了货币政策方向，采取适度宽松的货币政策。2009年，信贷总量快速增长，信贷结构继续优化，对扭转经济增长下滑趋势、恢复市场信心发挥了重要作用，有力支持了经济平稳较快的发展。然而信贷增长过快使得通货膨胀预期上升，2009年的贷款高增长难以持续。     

江西能源消费、碳排放与低碳经济发展研究

发展低碳经济必须了解能源消费量和二氧化碳排放量,本文基于统计年鉴数据,对江西2000-2012年能源消费及其产生的二氧化碳特征和变化规律进行研究。结果显示,2000年以来江西能源消费总量呈上升趋势,煤炭是江西的主要能源。2000-2012年,江西二氧化碳排放量总体呈平稳上升趋势,碳排放强度总体呈下降态势。建议江西省应从优化能源结构、发挥森林碳汇潜力,发展绿色低碳经济等方面实行低碳发展。     

二0一0年信贷投放额度探析——兼论货币政策与转方式、调结构

为积极应对金融危机,消减其对我国经济的负面影响,2008年10月份,我国政府迅速调整了货币政策方向,采取适度宽松的货币政策。2009年,信贷总量快速增长,信贷结构继续优化,对扭转经济增长下滑趋势、恢复市场信心发挥了重要作用,有力地支持了经济平稳较快发展。     

我国绿色物流研究的演变及热点趋势——基于CiteSpace的可视化分析

为清晰了解绿色物流研究现状、热点分布以及发展趋势，运用可视化软件CiteSpace，对手动筛选出的相关研究领域文献进行可视化分析。根据得出的数据可知：自2009年以来，有关绿色物流研究数量呈现“上升—下降—平稳”的趋势，同时研究作者及机构之间存在合作过于分散的现象；该领域研究热点发展可分为爆发式发展和平稳发展两个主要阶段，且主要集中在农产品物流、低碳物流、冷链物流等绿色物流方面；而未来研究趋势主要体现在循环经济、逆向物流、绿色流通等主题。据此，为未来国内绿色物流发展创新提供了理论建议。     

茶叶总量略增边销下滑

茶叶总量略增边销下滑国内贸易部预测１９９４年茶叶购销价格稳中有升，全国茶叶总产量和内销量稳定增长，边销茶形势却严峻。国合商业主渠道收购量和经营比重都呈继续下降趋势。１９９３年全国茶叶种值面积１６５０万亩；与上年持平，茶叶总产量５６．４６万吨，比上年增...     

中国分行业资本存量估算：1990~2014年

通过借鉴中国资本存量已有研究文献的成果,以细分行业差别化的折旧率估算为基础,通过分析投资结构和折旧率的关系,估算出第二、第三产业和总量的时变折旧率,系统地估算出1990~2014年总量、三次产业和细分行业的资本存量。估算结果及分析表明:由于投资结构的变化,总量、第三产业折旧率呈下降趋势,第二产业折旧率呈先上升再下降趋势;目前在我国,“过度投资”和“投资不足”并存,且“过度投资”的是资本效率比较低的行业,“投资不足”的是资本效率比较高的行业。解决“投资不足”问题的关键是打破行业垄断,尤其是行政垄断,引入市场竞争机制。     

基于次贷危机的汇市、股市动态关联性研究

本文采用误差修正模型、向量自回归模型等经济计量的方法,研究了2007年3月2日至2009年12月31日上证、深证综指日收盘价和人民币兑美元名义汇率日数据之间的关联性。考虑到重大金融事件可能会对此关联性产生影响,通过Quandt-Andrews断点检验得到汇率和股票价格的结构断点,将得到的时间断点结合重大金融事件,对整个样本区间做合理划分,并在每个子区间中通过实证分析讨论两市的动态关联性。     

Testing Integration of Macroeconomic Time Series in Transitional Socialist Economies. A Modification of Perron Test

The presence of structural breaks reduces the power of integration tests. A number of methods were suggested to improve the statistical properties of integration tests in the presence of structural breaks. The most known are Perron tests, which allow to test for the level of integration of time series with one structural break. Perron tests allow for two types of structural breaks: additive outlier an innovative outlier. These tests are, however, not very useful in testing the level of integration of macroeconomic time series in countries in transition from centrally-planned to market economy. In such case one should expect two structural breaks to affect the time series: one at the beginning and one at the end of the transformation process. Test that allows for two additive outlier type structural breaks in time series is developed in this paper. This test has superior power as compared to standard Dickey-Fuller and Perron tests. This paper provides asymptotic distribution as well as finite sample properties of proposed test. Therefore practitioners receive a reliable tool for analyzing macroeconomic processes in transitional economies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Unemployment hysteresis in Australia: evidence using nonlinear and stationarity tests with breaks

This study is an attempt to test the hysteresis versus the natural rate hypothesis in unemployment rate using time series data of the Australia covering the period 1978: 2–2010:12. For the analysis, we employed nonlinear as well as different linear tests (with incorporation of endogenously determined structural breaks) of unit root. We found that the Australian unemployment rate is nonlinear process, has a partial unit root and trend reverting. Therefore, we provide support for the structuralist hypothesis. This finding provides the importance of accounting for exogenous shocks in the series and gives support to the shifting natural-rate hypothesis of the Australian unemployment rate.     

Nonparametric simultaneous testing for structural breaks

In this paper we consider a regression model with errors that are martingale differences. This modeling includes the regression of both independent and time series data. The aim is to study the appearance of structural breaks in both the mean and the variance functions, assuming that such breaks may occur simultaneously in both the functions. We develop nonparametric testing procedures that simultaneously test for structural breaks in the conditional mean and the conditional variance. The asymptotic distribution of an adaptive test statistic is established, as well as its asymptotic consistency and efficiency. Simulations illustrate the performance of the adaptive testing procedure. An application to the analysis of financial time series also demonstrates the usefulness of the proposed adaptive test in practice.     

Tests for Multiple Breaks in the Trend with Stationary or Integrated Shocks

In this paper, we propose new tests of the presence of multiple breaks in the trend of a univariate time‐series where the number and dates of the breaks are unknown and that are valid in the presence of stationary or unit root shocks. These tests can also be used to sequentially estimate the number of breaks. The behaviour of the proposed tests is studied through Monte Carlo experiments.     

我国物价总水平波动路径研究

利用时间序列分析方法研究了PPI和CPI的结构突变特征,并通过建立时间序列模型刻画了我国物价水平(CPI)的波动路径。结果表明,CPI序列在2003年7月、2007年5月以及2008年7月三个时间点上存在结构突变现象,从而将CPI的运行过程分为四个阶段。另外,PPI的结构突变时点一般较CPI滞后1-2个月,这说明CPI触发了PPI的上涨,而PPI又会给予CPI以上涨支撑。最后,分别对以上四个子样本区的CPI序列波动性进行了建模研究,结果表明1997年1月至2003年6月间的CPI波动具有条件异方差性,可由GARCH(1,1)模型来描述。而其他阶段的CPI波动均可由AR(1)模型描述。     

Structural breaks and GARCH models of exchange rate volatility

We investigate the empirical relevance of structural breaks for GARCH models of exchange rate volatility using both in‐sample and out‐of‐sample tests. We find significant evidence of structural breaks in the unconditional variance of seven of eight US dollar exchange rate return series over the 1980–2005 period—implying unstable GARCH processes for these exchange rates—and GARCH(1,1) parameter estimates often vary substantially across the subsamples defined by the structural breaks. We also find that it almost always pays to allow for structural breaks when forecasting exchange rate return volatility in real time. Combining forecasts from different models that accommodate structural breaks in volatility in various ways appears to offer a reliable method for improving volatility forecast accuracy given the uncertainty surrounding the timing and size of the structural breaks. Copyright © 2008 John Wiley & Sons, Ltd.     

Price-wage dynamics in a transition economy: The case of Poland

In this paper we analyse the wage-price relationship of an economy in transition characterized by important structural changes. It is known (see Perron, 1989) that structural breaks in stationary time series can induce apparent unit roots. The stationarity analysis of the series employed in the present model is conducted jointly with the assumption that the breakpoint location is unknown. We follow a testing procedure recently proposed by Zivot and Andrews (1992). Cointegration analysis of wages and prices in the presence of structural breaks finds empirical evidence in favour of two cointegrating vectors involving prices and wages. Our analysis focuses on the different structural behaviour of the price-wage dynamic relationship in the short and long term; we also demonstrate the relative importance of import prices as a source of wage-price fluctuations.     

Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics

Trend breaks appear to be prevalent in macroeconomic time series, and unit root tests therefore need to make allowance for these if they are to avoid the serious effects that unmodelled trend breaks have on power. Carrion-i-Silvestre et al. (2009) propose a pre-test-based approach which delivers near asymptotically efficient unit root inference both when breaks do not occur and where multiple breaks occur, provided the break magnitudes are fixed. Unfortunately, however, the fixed magnitude trend break asymptotic theory does not predict well the finite sample power functions of these tests, and power can be very low for the magnitudes of trend breaks typically observed in practice. In response to this problem we propose a unit root test that allows for multiple breaks in trend, obtained by taking the infimum of the sequence (across all candidate break points in a trimmed range) of local GLS detrended augmented Dickey–Fuller-type statistics. We show that this procedure has power that is robust to the magnitude of any trend breaks, thereby retaining good finite sample power in the presence of plausibly-sized breaks. We also demonstrate that, unlike the OLS detrended infimum tests of Zivot and Andrews (1992), these tests display no tendency to spuriously reject in the limit when fixed magnitude trend breaks occur under the unit root null.     

An efficient Bayesian approach to multiple structural change in multivariate time series

This paper provides a feasible approach to estimation and forecasting of multiple structural breaks for vector autoregressions and other multivariate models. Owing to conjugate prior assumptions we obtain a very efficient sampler for the regime allocation variable. A new hierarchical prior is introduced to allow for learning over different structural breaks. The model is extended to independent breaks in regression coefficients and the volatility parameters. Two empirical applications show the improvements the model has over benchmarks. In a macro application with seven variables we empirically demonstrate the benefits from moving from a multivariate structural break model to a set of univariate structural break models to account for heterogeneous break patterns across data series.     

Inference and prediction in a multiple-structural-break model

This paper develops a new Bayesian approach to structural break modeling. The focuses of the approach are the modeling of in-sample structural breaks and forecasting time series allowing out-of-sample breaks. The model has several desirable features. First, the number of regimes is not fixed but is treated as a random variable. Second, the model adopts a hierarchical prior for regime coefficients, which allows for the coefficients of one regime to contain information about coefficients of other regimes. Third, the regime coefficients can be integrated analytically in the posterior density; as a consequence the posterior simulator is fast and reliable. An application to US real GDP quarterly growth rates links groups of regimes to specific historical periods and provides forecasts of future growth rates.