自举法与协整参数的FMOLS估计

考虑静态和动态两类数据生成过程,利用蒙特卡罗模拟方法,从估计偏差、实际检验水平和检验功效三个方面对FMOLS(Full Modified Ordinary Least Square)估计的渐近分析和自举分析进行全面比较.结果表明,与渐近分析相比,自举分析可以减小实际检验水平对名义水平的偏差,但要以检验功效的降低为代价.严格意义上,自举分析是降低了"拒真"错误出现的概率.相对稳健的选择是结合两方面的信息,渐近检验通过则接受原假设,自举检验拒绝则接受备择假设,对于其他情况,具体结论取决于人们的研究态度.     

自相关检验方法的检验功效研究

研究目标:探究DW检验和LM检验的检验功效及其渐近性。研究方法:运用蒙特卡罗模拟实验方法结合相关影响因素对两种检验方法进行分析与比较。影响因素包括样本容量、解释变量的随机性及自相关性、随机误差项的自相关程度以及分布形态。研究发现:DW和LM检验功效与样本容量和随机误差项的自相关程度正相关,与解释变量的自相关程度负相关;解释变量的随机性对DW和LM检验功效无显著影响;误差项的几种常见分布形态的变化对DW和LM检验功效的影响可以忽略;在误差项存在一阶自相关的情况下,DW检验效果优于LM检验效果。研究创新:以DW检验和LM检验的假设条件为出发点,探究比较不同条件下自相关检验方法的检验功效。研究价值:在实证研究背景下为有效地选择自相关检验方法提供借鉴参考。     

随机系数面板数据单位根联合LM检验的稳定性研究

本文从初始值的视角研究其对随机系数面板数据单位根联合LM检验稳定性的影响。推导当初始值不是依概率有界的随机变量而是渐近不可忽略的变量时联合LM检验统计量的渐近分布,并发现联合LM检验不再服从其原分布,且其与初始值有关,表明联合LM检验统计量的渐近性质不稳定。蒙特卡洛模拟结果显示,在有限样本情形下,初始值可能会导致联合LM检验统计量出现较严重的水平扭曲现象,即联合LM检验的统计性质不稳定,易受初始值影响。     

固定效应模型空间相关性的Bootstrap LM-error检验

基于Lee和Yu(2010)的正交转换消除固定效应,将FDB方法用于空间固定效应模型误差自相关的LM-error检验。在不同的误差结构、样本量、空间权重矩阵、序列相关系数和固定效应大小条件下,比较渐近LM-error检验和Bootstrap LM-error检验的水平扭曲和功效。蒙特卡洛模拟实验表明,当误差项为标准正态分布时,两者检验均具有较好的水平扭曲和功效表现。当误差项为异方差或者序列相关时,渐近LM-error检验存在严重的水平扭曲,而Bootstrap LM-error检验能够有效地校正其水平扭曲,且其检验功效与渐近LM-error检验功效近似相等,Bootstrap LM-error检验是更为理想的检验方法。     

ADF单位根检验法的替代方法

研究目标：ADF单位根检验法的替代方法——消除趋势检验法。研究方法：通过蒙特卡罗仿真估算了消除趋势法、ADF法和差分法的检验临界值和检验功效;估算了三种方法检验临界值关于样本容量的响应面函数;估算了消除趋势回归中趋势项和截距项的t统计量的检验临界值及其响应面函数。研究发现：在各种情形下,消除趋势法的检验功效均大于ADF法,而且在误差项相关时更为明显,说明消除趋势法优于ADF法,可以完全替代ADF法;在某些情况下,差分法的检验功效较大。研究创新：对ADF检验模型进行了改进,提出了消除趋势检验法。研究价值：在单位根检验时,可以用消除趋势法代替一直以来被广泛采用的ADF法,提高单位根检验的功效。     

空间动态面板非线性Logistic模型的稳健LM检验及应用

研究目标:探究空间动态面板Logistic平滑转移自回归(SDPD-LSTAR)模型的稳健LM检验的水准和效力。研究方法:重塑得分函数和方差-协方差矩阵,推导识别时间滞后、空间滞后和非线性效应的修正稳健LM检验及其联合效应检验,通过蒙特卡洛模拟和基于STIRPAT的中国284个城市碳排放影响因素实例评估检验的功效和实践性。研究发现:稳健LM检验具有中心卡方的极限分布性质,检验功效好、计算较简便,比一般的LM检验更精确、适用性更广,该优越性随参数局部偏误的出现而显著,应用实例展现了检验良好的实践性。研究创新:提出具有时空依赖和非线性空间区制平滑转换特征的SDPD-LSTAR模型,在ML和GMM框架下推导模型的稳健LM检验。研究价值:探究SDPD-LSTAR模型的选择问题,为空间动态非线性理论和应用提供重要支持。     

面板协整检验有限样本性质的模拟比较

面板协整检验是基于渐近分布的检验,有限样本下统计量的检验水平和检验功效的表现涉及检验的可靠性。本文针对目前实证研究中应用最广的一类基于残差的统计量及文献中最新提出的基于准残差的统计量进行蒙特卡罗模拟,比较10个检验统计量在不同DGP设定下的检验水平和检验功效,尤其是在DGP误设时的表现。模拟结果表明:基于准残差的面板协整检验大多数情况下有着更好的检验水平和检验功效表现。这一研究为解决实证中面临的统计量可靠性甄别与选择问题提供了依据。     

空间经济计量模型Bootstrap检验的水平扭曲

本文使用回归残差的Bootstrap方法,对线性模型空间相关性进行检验.基于空间相关性检验统计量Moran's Ⅰ,在不同Bootstrap样本数及不同空间衔接结构下,研究并比较Bootstrap和渐近检验方法.通过Monte Carlo实验揭示了当空间经济计量模型中残差不满足经典正态假定条件时,空间相关性的渐近检验理论不再有效.本文把Bootstrap方法用于空间相关性检验,对水平扭曲进行了分析校正.研究同时发现,从水平扭曲角度来看,无论残差是否满足经典正态假定条件,空间经济计量模型Bootstrap检验通常都很有效.     

具有结构突变的CAPM的阶段异方差和自相关性的调整LM检验

由于金融市场是动荡不定的,资产定价模型CAPM往往会出现结构突变,异方差,序列相关,因此需要对CAPM的随机误差进行齐性检验。对于具有单个结构突变点的CAPM,本文得到了检验阶段异方差和自相关性的调整LM检验统计量。Monte Carlo模拟的结果显示,该调整LM检验统计量具有比普通LM检验统计量更好的检验功效。最后,我们用一个具体的实例论证了方法的有效性。     

线性模型中的GMM距离检验及其与LR、LM和Wald检验的关系

本文通过对线性模型中GMM距离检验的分析解读,阐释并证明了计量经济中的三大检验LR、LM和Wald检验可视为GMM检验的特殊情况,从而说明了GMM距离检验是更一般化的检验方法并有着广泛的应用价值。     

Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes

The BDS test is the best-known correlation integral–based test, and it is now an important part of most standard econometric data analysis software packages. This test depends on the proximity ( $\varepsilon )$ and the embedding dimension ( $m)$ parameters both of which are chosen by the researcher. Although different studies (e.g., Kanzler in Very fast and correctly sized estimation of the BDS statistic. Department of Economics, Oxford University, Oxford, 1999) have been carried out to provide an adequate selection of the proximity parameter, no relevant research has yet been done on $m$ . In practice, researchers usually compute the BDS statistic for different values of $m$ , but sometimes these results are contradictory because some of them accept the null and others reject it. This paper aims to fill this gap. To that end, we propose a new simple, yet powerful, aggregate test for independence, based on BDS outputs from a given data set, that allows the consideration of all of the information contained in several embedding dimensions without the ambiguity of the well-known BDS tests.     

基于参数空间的ST-ECM模型的协整检验问题研究

在非线性平滑转移误差修正模型（ST-ECM）的协整检验中,由于存在未识别参数而使协整检验统计量构造困难,同时由于目前文献普遍使用的泰勒展开近似法并不能精确替代原始非线性模型,从而导致协整检验统计量功效较低。本文首先在遍历未识别参数的参数空间的基础上构造了ST-ECM模型协整检验的supF统计量,推导了supF统计量的极限分布并说明了其收敛性质。接着,蒙特卡洛仿真模拟结果显示,supF统计量在ST-ECM模型协整检验中具有良好的检验水平和功效,且supF统计量的功效明显优于EG统计量、F*NEC统计量和inft统计量。最后,本文对亚洲六个国家的利率期限结构预期假说进行了验证,结果表明中国、新加坡和泰国三个国家的利率期限结构预期假说成立且存在非线性调整效应,supF统计量较其他统计量具有更高的检验功效。     

固化风沙土强度试验研究

对取自内蒙古高原鄂尔多斯库布其沙漠中的风沙土样进行了固化强度方面的研究,分别进行了筛分、击实、无侧限抗压等试验。试验的结果表明:在风沙土中加入固化剂后,试件抗压强度随固化剂掺量的增加,先增加后减小;随着龄期的增加,抗压强度的逐渐增加;加纤维试件与未加纤维的试件相比,后期强度增加的比较快,增加的幅度较大。通过两种情况下的抗压试验结果,得出固化剂的最佳配合掺量为10%。     

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.     

Size and Power of the Error Correction Model Cointegration Test. A Bootstrap Approach

The size and power of the ECM cointegration test are investigated by using the 'bootstrap critical values'. The purpose of this paper is to show the ability of the bootstrap technique to produce critical values which are much more accurate than the asymptotic ones. The properties of the test have been studied, using Monte Carlo methods, for three different data generating processes. As regards the size of the test, we find that the ECM cointegration test together with the bootstrap critical values perform better than the ECM cointegration test based on the asymptotic critical values. While as regards the power of the tests, the results prove to be similar for the different versions.     

Some comparisons of tests for a shift in the slopes of a multivariate linear time series model

Our objective is to find a simple, robust, reasonably powerful test for a shift in one or more of the slopes in a linear time series model at some unknown point of time. Two such tests are ‘Chow's test’ (1960) for a shift at the midpoint of the record and the ‘Farley-Hinich test’ (1970b); both can be performed easily with standard regression programs. In section 2, we compare the asymptotic properties of these tests when the disturbance variance is known. As expected, Chow's test is superior when the true shift is near the middle of the record; with a single, uniformly-distributed explanatory variable, the Farley-Hinich tests dominates over the remaining eighty-four percent of the record. In section 3, we describe the results of some Monte Carlo experiments with a finite sample, which can be summarized as follows. (i) The asymptotic results of section 2 were appropriate for finite sample power comparisons. (ii) The relative performance of the two tests does not depend appreciably on whether the variance is known. (iii) The likelihood ratio test, which is far more costly to perform than the other two tests, does not dominate either Chow's test or the Farley-Hinich test; it has moderately more power at the ends of the record, moderately less in the middle. The conclusion is clear: at low cost (in terms of computer cost and lost power), one can reduce the probability of over- looking a structural shift by routinely performing Chow's test or the Farley-Hinich test.     

平滑转移误差修正模型的转移函数选取问题研究

针对非线性平滑转移误差修正模型转移函数选取中存在的统计量极限分布非标准、检验统计量功效较低的问题,本文在推导非线性平滑转移协整检验统计量极限分布的基础上构造了如下转移函数选取步骤。首先,计算F_NST统计量,进行非线性平滑转移协整检验;其次,计算t_EST和t_LST统计量及相依概率P_est和P_lst;最后,比较P_est和P_lst大小并与临界值相比,得出结论。蒙特卡洛仿真模拟结果显示,转移函数选取中各统计量具有良好的功效和势,且转移函数选取中各统计量的功效明显优于其他统计量的功效。实证分析表明我国利率期限结构具有明显的非线性对称调整效应,非线性平滑转移误差修正模型中转移函数应该选取指数函数。     

中国建筑业与国家产业结构变动

国家产业结构变动时各种生产要素在产业间不断流动,以达到最优配置。在这种结构变动过程中,建筑业的生产效率和产出水平是否受到影响,或者建筑业的生产力水平提高是否有助三次产业的结构变动,至今是个论述较少的问题。本文以Granger因果检验的方法检验了我国建筑业产出增长和第三产业从业人员比重之间的相互预测能力。结果发现在双向因果关系的基础上,第三产业的发展是建筑业增长的长期Granger因。     

The Hausman test and weak instruments

We consider the following problem. There is a structural equation of interest that contains an explanatory variable that theory predicts is endogenous. There are one or more instrumental variables that credibly are exogenous with regard to this structural equation, but which have limited explanatory power for the endogenous variable. Further, there is one or more potentially ‘strong’ instruments, which has much more explanatory power but which may not be exogenous. Hausman (1978) provided a test for the exogeneity of the second instrument when none of the instruments are weak. Here, we focus on how the standard Hausman test does in the presence of weak instruments using the Staiger–Stock asymptotics. It is natural to conjecture that the standard version of the Hausman test would be invalid in the weak instrument case, which we confirm. However, we provide a version of the Hausman test that is valid even in the presence of weak IV and illustrate how to implement the test in the presence of heteroskedasticity. We show that the situation we analyze occurs in several important economic examples. Our Monte Carlo experiments show that our procedure works relatively well in finite samples. We should note that our test is not consistent, although we believe that it is impossible to construct a consistent test with weak instruments.     

合约变异在测试数据优化中的研究及应用

软件测试是保证Web服务质量的重要技术手段,测试数据生成是Web服务测试的重要内容,而生成的初始测试数据量大,数据冗余,为了减少初始测试数据数量,提高测试数据的有效性,本文在变异测试方法的基础上,使用合约变异方法对初始测试数据进行优化,据此可以生成一批达到一定变异充分度的有效测试数据,并通过实验验证了方法的有效性。