International Business Cycle Asymmetry and Time Irreversible Nonlinearities

Using tests of time reversibility, this paper provides further statistical evidence on the long-standing conjecture in economics concerning the potentially asymmetric behaviour of output over the expansionary and contractionary phases of the business cycle. A particular advantage of this approach is that it provides a discriminating test that is instructive as to whether any asymmetries detected are due to asymmetric shocks to a linear model, or an underlying non-linear model with symmetric shocks, and in the latter case is informative as to the potential form of that nonlinear model. Using a long span of international per capita output growth data, the asymmetry detected is overwhelmingly consistent with the long standing perception that the output business cycle is characterized by steeper recessions and longer more gentle expansions, but the evidence for this form of business cycle asymmetry is weaker in the data adjusted for the influence of outliers associated with wars and other extreme events. Statistically significant time irreversibility is reported for the output growth rates of almost all of the countries considered in the full sample data, and there is evidence that this time irreversibility is of a form implying an underlying nonlinear model with symmetrically distributed innovations for 15 of the 22 countries considered. However, the time irreversibility test results for the outlier-trimmed full sample data reveal significant time irreversibility in output growth for around one half of the countries considered, predominantly in Northern Europe and North America, and of a form implying a nonlinear underlying model in only a further half of those cases.     

Some non-parametric tests for duration dependence: an application to UK business cycle data

A distinction between Fisher's implied data-generating process for Monte Carlo cycles and the more general Markov process leads to non-parametric tests for duration dependence. Tests are based on the method of moments, Tauchen's generalized method of moments (GMM) procedure, and a statistic whose null distribution probability limit is zero. Using finite-sample critical values obtained by Monte Carlo methods, our test results are remarkably consistent. The null distribution of the GMM test statistic for samples of the size considered is distinctly non-normal, so that asymptotic critical values give erroneous results. The tests are applied to UK business cycle data for 1854-1992. There is evidence for duration dependence in expansions but not in contractions.     

全球价值链嵌入与国际经济周期非对称联动

剔除第三方效应测度双边价值链嵌入度,考察其与国际经济周期非对称联动间关联。研究发现:融入全球价值链使中国制造业陷入低增值率出口与中间投入高比例进口的困境,进而削弱了中国与贸易伙伴国经济扩张的联动,加强了中国与贸易伙伴国经济紧缩的联动,这在一定程度上导致国际经济周期呈扩张联动低于紧缩联动的非对称特征。该现象在金融危机前突出,危机后有所缓解但仍存在。相对而言,融入全球价值链大幅削弱了中国与经济增长较为稳健的发展中国家、非欧盟国家经济扩张的联动,又大幅加强了中国与发达国家、欧盟国家等危机多发国经济紧缩的联动,影响中国经济稳定增长。要规避全球价值链嵌入对稳增长的阻碍,中国须提升制造业出口国内增加值份额,并着力降低中间投入进口比例。本文发现了国际经济周期联动的非对称特征,并基于中国融入全球价值链的典型特征解释成因,研究结论可为制定实施稳增长政策提供决策参考。     

Business Cycle Duration Dependence Reconsidered

Sichel estimated a Weibull hazard model using the National Bureau of Economic Research business cycle chronology and found evidence of duration dependence only for prewar expansions and postwar contractions. The article updates the postwar sample through the end of the most recent expansion and uses a generalized Weibull model that provides much greater flexibility at the expense of one additional parameter. This model finds evidence of duration dependence for all samples and is statistically superior to the conventional Weibull model for all samples except postwar contractions.     

国际商业周期对中国出口的影响

 国际商业周期变化对中国出口有着怎样的影响？本文在重力方程中引入不可观测的周期性因素,用于分析中国出口的变化及其决定因素。与已有研究相比,本文允许周期性因素的影响具有个体异质性,因此更具一般性,也更符合典型贸易事实。在此基础上,本文使用Pesaran (2006)的异质性面板、Bai（2003）的共同因子等新提出方法分别估计重力方程和周期性因素。结果表明,中国出口具有明显的供给推动特征,国内产出是引起出口增长的最主要因素;国外产出和汇率是导致出口波动的重要因素;周期性因素的影响因贸易伙伴而异,中国对美国、日本等贸易伙伴的出口受周期性影响较为明显。进一步分析发现,金融危机对中国出口的负面冲击在2009年还将进一步显现。     

ASSESSING AND TESTING FOR THRESHOLD NONLINEARITY IN STOCK RETURNS

This paper proposes a test for threshold nonlinearity in a time series with generalized autore‐gressive conditional heteroscedasticity (GARCH) volatility dynamics. This test is used to examine whether financial returns on market indices exhibit asymmetric mean and volatility around a threshold value, using a double‐threshold GARCH model. The test adopts the reversible‐jump Markov chain Monte Carlo idea of Green, proposed in 1995, to calculate the posterior probabilities for a conventional GARCH model and a double‐threshold GARCH model. Posterior evidence favouring the threshold GARCH model indicates threshold nonlinearity with asymmetric behaviour of the mean and volatility. Simulation experiments demonstrate that the test works very well in distinguishing between the conventional GARCH and the double‐threshold GARCH models. In an application to eight international financial market indices, including the G‐7 countries, clear evidence supporting the hypothesis of threshold nonlinearity is discovered, simultaneously indicating an uneven mean‐reverting pattern and volatility asymmetry around a threshold return value.     

Estimation of the frequency in cyclical long-memory series

Time series with cyclical long memory are characterized by a spectral pole at some frequency ω between 0 and π such that the series has a persistent cycle of period 2π/ω, implying a quasi-periodic behaviour that slightly evolves with time. Accurate estimation of ω is needed for a precise determination of the characteristic of the series (e.g. for business cycle determination or signal estimation). We propose a simple iterative algorithm of estimation of ω based on the maximizer of the periodogram evaluated at an increasingly finer grid of frequencies and compare its performance with more usual methods of estimation restricted to Fourier frequencies. We also apply this technique to the estimation of the frequency of the sunspot index and the business cycle of the differenced unemployment level of the USA.     

中国与“一带一路”沿线国家经济周期协同性及其传导机制

本文采用CM同步化指数测算中国与“一带一路”沿线国家经济周期协同变化的动态特征,并运用面板联立方程模型检验周期协同性的传导机制。研究发现：(1)中国与“一带一路”沿线国家经济周期协同性经历了波动上升期、逆转期和持续下降期三个阶段,且“脱钩”趋势明显。(2)中国与不同发展类型国家的协同性有显著差异,在波动上升期和持续下降期,中国与转型国家的协同度最高,发达国家居中,发展中国家最低,而在逆转期,协同性由高到低依次为发达、发展中和转型国家。(3)双边贸易、双边直接投资、专业化分工、金融一体化是引起跨国经济周期协同性变化的主要传导路径。双边贸易和金融一体化会强化协同性,专业化分工和双边直接投资则产生弱化作用。此外,较大的制度距离和较低的货币政策协调性会降低周期协同性。(4)各传导渠道对经济周期协同性的相对重要性从大到小依次为：双边直接投资、金融一体化、专业化分工及双边贸易,但在后危机时期,全球价值链主导的国际分工使专业化分工成为最重要因素。上述结论为“一带一路”区域合作模式与路径选择提供了重要的理论依据和政策启示。     

经济周期中产出波动与通货膨胀不对称动态关系研究

建立不对称动态菲利普斯曲线理论研究经济周期中产出波动与通货膨胀不对称动态关系。该理论蕴含了经济扩张与收缩期中通胀持续性、产出波动对通胀的长短期影响差异特征及相关检验方法。运用该理论对中国相关季度数据进行了实证分析,结果表明:产出波动对通货膨胀短期中具有"顺周期"的正相关性,充当了"晴雨器"作用;长期中具有"逆周期"的负相关性,充当了"稳定器"作用。统计检验表明,经济周期中通货膨胀持续性及产出波动对通货膨胀的长短期影响具有显著不对称性,这种不对称性是中国经济转型期经济运行质量的历史检验,对现阶段追求经济增长质量具有深刻的政策启示。     

A Kernel Variogram Estimator for Clustered Data

Abstract.  The variogram provides an important method for measuring the dependence of attribute values between spatial locations. Suppose that the nature of the sampling process leads to the presence of clustered data; it would be advisable to use a variogram estimator that aims to adjust for clustering of samples. In this setting, the use of a non-parametric weighted estimator, obtained by considering an inverse weight to a given neighbourhood density combined with the kernel method, seems to have a satisfactory behaviour in practice. This paper pursues a theoretical study of the cluster robust estimator, by proving that it is asymptotically unbiased as well as consistent and by providing criteria for selection of the bandwidth parameter and the neighbourhood radius. Numerical studies are also included to illustrate the performance of the considered estimator and the suggested approaches.     

Semiparametric Whittle estimation of a cyclical long-memory time series based on generalised exponential models

This paper considers a semiparametric estimation of the memory parameter in a cyclical long-memory time series, which exhibits a strong dependence on cyclical behaviour, using the Whittle likelihood based on generalised exponential (GEXP) models. The proposed estimation is included in the so-called broadband or global method and uses information from the spectral density at all frequencies. We establish the consistency and the asymptotic normality of the estimated memory parameter for a linear process and thus do not require Gaussianity. A simulation study conducted using Monte Carlo experiments shows that the proposed estimation works well compared to other existing semiparametric estimations. Moreover, we provide an empirical application of the proposed estimation, applying it to the growth rate of Japan's industrial production index and detecting its cyclical persistence.     

Comment on state space modeling of multiple time series

This paper raises some interpretative issues that arise from univariate trend–cycle decompositions with correlated disturbances. In particular, it discusses whether the interpretation of a negative correlation as providing evidence for the prominence of real, or supply, shocks, can be supported.

For this purpose it determines the conditions under which correlated components may originate from the underestimation of the cyclical component in an orthogonal decomposition; from the presence of a growth rate cycle, rather than a deviation cycle; or alternatively, as a consequence of the hysteresis phenomenon. Finally, it considers interpreting correlated components in terms of permanent–transitory decompositions, where the permanent component has richer dynamics than a pure random walk.

The consequences for smoothing and signal extraction are discussed: in particular, it is documented that a negative correlation implies that future observations carry most of the information needed to assess cyclical stance. As a result, the components will be subject to underestimation in real time and thus to high revisions. The overall conclusion is that the characterization of economic fluctuations in macroeconomic time series largely remains an open issue.     

Estimation of the degree of dependence in the temperatures in the northern hemisphere using semi-parametric techniques

We are concerned in this article with the estimation of the degree of dependence between the observations of the monthly temperatures in the northern hemisphere from 1854 to 1989 by means of using fractionally integrated semi-parametric techniques. We use several estimation procedures proposed by P. M. Robinson in a number of papers, and the results indicate that the order of integration of the series is around 0.37, implying that the time series is stationary but with long memory behaviour. Separating the data in two subsamples (1854-1921 and 1922-89), the results show that there has been an increase in the degree of dependence across time by about 0.05-0.10, the order of integration oscillating around 0.3 (0.35) for the time period 1854-1921, and around 0.35 (0.40) for the period 1922-89.     

Trend-Cycle Decompositions with Correlated Components

This paper raises some interpretative issues that arise from univariate trend-cycle decompositions with correlated disturbances. In particular, it discusses whether the interpretation of a negative correlation as providing evidence for the prominence of real, or supply, shocks, can be supported.

For this purpose it determines the conditions under which correlated components may originate from the underestimation of the cyclical component in an orthogonal decomposition; from the presence of a growth rate cycle, rather than a deviation cycle; or alternatively, as a consequence of the hysteresis phenomenon. Finally, it considers interpreting correlated components in terms of permanent-transitory decompositions, where the permanent component has richer dynamics than a pure random walk.

The consequences for smoothing and signal extraction are discussed: in particular, it is documented that a negative correlation implies that future observations carry most of the information needed to assess cyclical stance. As a result, the components will be subject to underestimation in real time and thus to high revisions. The overall conclusion is that the characterization of economic fluctuations in macroeconomic time series largely remains an open issue.     

Temporal aggregation of cyclical models with business cycle applications

This paper focuses on temporal aggregation of the cyclical component model as introduced by Harvey (1989). More specifically, it provides the properties of the aggregate process for any generic period of aggregation. As a consequence, the exact link between aggregate and disaggregate parameters can be easily derived. The cyclical model is important due to its relevance in the analysis of business cycle. Given this, two empirical applications are presented in order to compare the estimated parameters of the quarterly models for German and US gross domestic products with those of the corresponding models aggregated to annual frequency.     

On Non-parametric Testing, the Uniform Behaviour of the t-test, and Related Problems

Abstract.  In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [ Ann. Math. Statist . 25 (1956) 1115] to other testing problems, and we answer a conjecture of theirs. Other examples considered are testing whether or not the mean is rational, testing goodness-of-fit, and equivalence testing. Next, we discuss the uniform behaviour of the classical t -test. For most non-parametric models, the Bahadur–Savage result yields that the size of the t -test is one for every sample size. Even if we restrict attention to the family of symmetric distributions supported on a fixed compact set, the t -test is not even uniformly asymptotically level α . However, the convergence of the rejection probability is established uniformly over a large family with a very weak uniform integrability type of condition. Furthermore, under such a restriction, the t -test possesses an asymptotic maximin optimality property.     

Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation

Abstract.  Wang & Wells [ J. Amer. Statist. Assoc. 95 (2000) 62] describe a non-parametric approach for checking whether the dependence structure of a random sample of censored bivariate data is appropriately modelled by a given family of Archimedean copulas. Their procedure is based on a truncated version of the Kendall process introduced by Genest & Rivest [ J. Amer. Statist. Assoc. 88 (1993) 1034] and later studied by Barbe et al . [ J. Multivariate Anal. 58 (1996) 197]. Although Wang & Wells (2000) determine the asymptotic behaviour of their truncated process, their model selection method is based exclusively on the observed value of its L ²-norm. This paper shows how to compute asymptotic p -values for various goodness-of-fit test statistics based on a non-truncated version of Kendall's process. Conditions for weak convergence are met in the most common copula models, whether Archimedean or not. The empirical behaviour of the proposed goodness-of-fit tests is studied by simulation, and power comparisons are made with a test proposed by Shih [ Biometrika 85 (1998) 189] for the gamma frailty family.     

Business-Cycle Analysis With a Markov-Switching Model

This article explores the Hamilton Markov-switching model through an analysis of the business cycles of eight developed market economies. Forecasting and specification tests suggest only marginal improvements over linear autoregressive models. Yet filtered and smoothed conditional probabilities indicate turning points in business cycles that closely correlate with turning points from traditional methods. Tests regarding the asymmetry of business cycles reject the null of symmetry for most countries.     

Survey response and survey characteristics: microlevel evidence from the European Community Household Panel

Summary.  The paper presents microlevel evidence on the role of the sociodemographic characteristics of a population and the characteristics of the data collection process as predictors of survey response. Our evidence is based on the public use files of the European Community Household Panel, a longitudinal household survey covering the countries of the European Union, whose attractive feature is the high level of comparability across countries and over time. We model the response process as the outcome of two sequential events: contact between the interviewer and an eligible interviewee, and co-operation by the interviewee. Our model allows for dependence between the ease of contact and the propensity to co-operate, taking into account the censoring problem caused by the fact that we observe whether a person is a respondent only if she has been contacted.     

An investigation of duration dependence in the American stock market cycle

This paper investigates the duration dependence of the US stock market cycles. A new classification method for bull and bear market regimes based on the crossing of the market index and its moving average is proposed. We show evidence of duration dependence in whole cycles. The half cycles, however, are found to be duration independent. More importantly, we find that the degree of duration dependence of the US stock market cycles has dropped after the launch of the NASDAQ index.