我国经济周期波动特征出现新现象

一、改革开放前后经济周期波动特征比较根据波谷—波谷这一经济周期划分的常用标准,新中国成立以来,从1953年起开始大规模的工业化建设至今,经济增长率的波动共经历了10个周期。而改革开放前后经济波动的周期性特征更有比较意义。1.改革开放前经济周期波动特征。第一,改革开放前,我国的经济周期属于古典型经济周期,在经济周期     

基于门限模型下教育经费支出对就业和经济的影响

本文阐述了就业率与经济发展之间的协调关系,并利用1991-2013年中国面板数据,根据就业率的门限特征进行了门限回归分析,分析表明,教育性经费支出占国内生产总值的比例存在门限值,门限值为3.95%,在此门限值下面就业率的提高显著促进了经济增长。针对此结论,最后提出了一些政策性建议。     

中国利率期限结构对经济周期波动的预测能力检验——基于动态Probit模型的研究途径

本文对我国利率期限结构对经济周期波动的预测能力进行实证研究.首先,利用时差相关分析方法选择我国经济周期波动的利差先行指标.然后,利用基于利差先行指标的动态Probit模型检验我国利率期限结构对经济周期波动状态的预测能力,并且对静态Probit模型和动态Probit模型、各种动态Probit模型之间的预测效果也进行了比较.研究结果表明,我国利率期限结构变动对未来3个月的经济周期波动状态具有比较稳定的指示作用,利用经济状态先验信息的动态Probit模型的预测效果优于静态Probit模型.     

经济周期与证券市场波动关联性——基于向量SWARCH模型的新证据

本文认为关于经济周期与证券市场波动关联性研究结论的分歧源自仅注重样本区间内整体关联性的检验,忽视了分析经济增长不同阶段与证券市场波动的特定关联性。基于向量SWARCH模型,本文实证检验了我国GDP增长率与证券收益率间的关联性,结论表明,虽然“整体关联性”检验不支持经济周期与市场波动间存在显著相关性的结论,但“状态相关系数”却显示两者间的关联性具有“区制转移”特征,并体现了对前者依赖的“门限效应”和“非对称效应”。     

2005年中国宏观经济波动态势与成因的动态分析

根据经济增长速度的高低、持续时间的长短、扩张和收缩的转变点等特征来刻画经济周期，一直是经典的经济周期分析模式(Bums和Mitchell，1946)。但随着古典经济周期(正增长和负增长交替出现)波动的逐渐消失，增长型经济周期(保持正的增长水平，但是水平高低出现周期变化)逐渐成为经济周期理论和实证研究的核心。随着增长型经济周期的出现和持续，一些能够保持经济快速稳定增长的国家，大都出现了产出波动性显著降低的现象，研究者们由此推断经济周期稳定性的增加是导致经济快速增长的主要条件(Ramsey和Ramsey，1995)。一些经验研究甚至还对经济周期波动性的降低原因以及产出增长率的周期性分解进行了研究。     

门限分位数自回归模型的预测方法及应用

金融经济系统预测是宏观经济管理的重要问题,系统中大多数变量具有非线性与异质性等特征,门限分位数自回归（TQAR）模型能够较好地揭示这一特征。本文研究TQAR模型的预测技术,给出其条件分位数预测和条件密度预测方法。数值模拟结果表明,与传统的门限均值自回归模型（TAR）和分位数自回归（QAR）模型相比,TQAR模型在预测的精度和准度方面更具优势。文章使用TQAR模型研究中国通货膨胀的非线性动态特征,并在此基础上预测通货膨胀的波动趋势。实证结果表明,TQAR模型不仅能够揭示通货膨胀的门限效应和异质效应,提供比TAR和QAR模型更高的预测精准度,而且能够通过条件密度预测曲线,细致刻画通货膨胀条件分布的位置、散布与形状等全景信息,从而为宏观经济政策的制定和调整提供科学合理的决策依据。     

我国经济增长与失业的非线性关系研究

本文选取我国改革开放以来（1978～2004）的年度GDP增长率与城镇登记失业率数据,使用HP滤波方法将我国的GDP增长率和失业率数据分解为趋势部分和波动部分,并应用门限估计法对变量的波动部分进行回归。结果发现,在以往的研究中被人们认为严重背离奥肯定律的我国经济增长和失业率的互逆关系,在我国存在非线性的表现形式,产出的变动可以引起失业率的非对称性的变动。具体来看,当经济处于衰退期（产出缺口为负）时,经济增长和失业之间存在互逆的关系;当经济处于扩张期（产出缺口为正）时,经济增长对失业有正向的拉动效应,且当期失业率受到前两期失业率的影响。     

中国居民幸福—收入门限研究

基于对幸福-收入悖论的各种解释,尤其是在Clark et al (2008)的框架下,引入相对收入变量,并结合两个实验经济学结论,我们推知幸福-收入门限是存在的。使用CGSS2006年的微观数据,本文估计中国居民的幸福-收入门限值大致位于“人均收入”3300元的位置,收入对幸福感的影响从门限前显著正向变为门限后的不显著。门限回归中,收入和相对社会经济地位变量呈现“前高后低”特征,而其他控制变量的系数结果在门限前后通常也呈现差异性的特征,由门限值划分的不同群体的幸福感对变量的敏感度不同。对于从中等收入跨向中上等收入水平的转型国家来讲,提升居民的幸福感,需要更加关注非收入的因素,尤其是人们越来越关注的自身权利、平等和公平等软因素,这些因素的满足依赖于公平发展方向上的体制改进。     

我国省级经济周期对财政政策效果影响研究

财政政策在经济周期不同阶段体现出不同的政策效果,而财政政策对经济周期的调节不一定总是有效。也可能财政政策只在经济衰退时期具有拉动总产出的作用,而在经济繁荣时期对总产出不具有拉动作用。文章以我国省级经济数据为样本,利用向量自回归模型建模分析后发现:一方面,经济周期对财政政策效果存在明显的影响,财政政策效果在不同经济周期之间具有不对称性另一方面;考虑到经济周期的影响之后,各省财政政策体现出的操作方向不再是单一的顺周期调节方式。     

广东经济周期波动特征分析

本文对改革开放以来,广东经济周期波动的状态和特征、波动形成机制等进行了研究,对广东潜在经济增长的未来发展趋势作出客观判断,并提出启动经济要有新思路.     

Combination schemes for turning point predictions

We propose new forecast combination schemes for predicting turning points of business cycles. The proposed combination schemes are based on the forecasting performances of a given set of models with the aim to provide better turning point predictions. In particular, we consider predictions generated by autoregressive (AR) and Markov-switching AR models, which are commonly used for business cycle analysis. In order to account for parameter uncertainty we consider a Bayesian approach for both estimation and prediction and compare, in terms of statistical accuracy, the individual models and the combined turning point predictions for the United States and the Euro area business cycles.     

Forecasting with vector autoregressive (VAR) models subject to business cycle restrictions

In the last decade VAR models have become a widely-used tool for forecasting macroeconomic time series. To improve the out-of-sample forecasting accuracy of these models, Bayesian random-walk prior restrictions are often imposed on VAR model parameters. This paper focuses on whether placing an alternative type of restriction on the parameters of unrestricted VAR models improves the out-of-sample forecasting performance of these models. The type of restriction analyzed here is based on the business cycle characteristics of U.S. macroeconomic data, and in particular, requires that the dynamic behavior of the restricted VAR model mimic the business cycle characteristics of historical data. The question posed in this paper is: would a VAR model, estimated subject to the restriction that the cyclical characteristics of simulated data from the model “match up” with the business cycle characteristics of U.S. data, generate more accurate out-of-sample forecasts than unrestricted or Bayesian VAR models?     

FAMILY FIRM PERFORMANCE OVER THE BUSINESS CYCLE: A META-ANALYSIS

The financial performance of family firms has been widely studied in the literature. Combining the results of 155 primary studies from 35 countries with data about business cycles, we investigate how family firm performance changes over the business cycle. Using meta-analytic estimation methods, we find that family firms outperform nonfamily firms in developed markets, irrespective of economic circumstances. This outperformance, although statistically significant, is very small and practically negligible. With regard to the business cycle, we find evidence for a procyclical effect in which the relative performance of family firms is lower in economically difficult times. Our study extends the literature on how family firm performance depends on macroeconomic factors.     

What does a Monetary Policy Shock Do? An International Analysis with Multiple Filters*

What does a monetary policy shock do? We answer this question by estimating a new‐Keynesian monetary policy dynamic stochastic general equilibrium model for a number of economies with a variety of empirical proxies of the business cycle. The effects of two different policy shocks, an unexpected interest rate hike conditional on a constant inflation target and an unpredicted drift in the inflation target, are scrutinized. Filter‐specific Bayesian impulse responses are contrasted with those obtained by combining multiple business cycle indicators. Our results document the substantial uncertainty surrounding the estimated effects of these two policy shocks across a number of countries.     

CES technology and business cycle fluctuations

We contribute to an emerging literature that brings the constant elasticity of substitution (CES) specification of the production function into the analysis of business cycle fluctuations. Using US data, we estimate by Bayesian-Maximum-Likelihood methods a standard medium-sized DSGE model with a CES rather than Cobb–Douglas (CD) technology. We estimate a elasticity of substitution between capital and labour well below unity at 0.15–0.18. In a marginal likelihood race CES decisively beats the CD production and this is matched by its ability to fit the data better in terms of second moments. We show that this result is mainly driven by the implied fluctuations of factor shares under the CES specification. The CES model performance is further improved when the estimation is carried out under an imperfect information assumption. Hence the main message for DSGE models is that we should dismiss once and for all the use of CD for business cycle analysis.     

Keynesian impulses versus Solow residuals: identifying sources of business cycle fluctuations

We employ a neoclassical business‐cycle model to study two sources of business‐cycle fluctuations: marginal efficiency of investment shocks, and total factor productivity shocks. The parameters of the model are estimated using a Bayesian procedure that accommodates prior uncertainty about their magnitudes; from these estimates, posterior distributions of the two shocks are obtained. The postwar US experience suggests that both shocks are important in understanding fluctuations, but that total factor productivity shocks are primarily responsible for beginning and ending recessions. Copyright © 2000 John Wiley & Sons, Ltd.     

An endogenously clustered factor approach to international business cycles

Factor models have become useful tools for studying international business cycles. Block factor models can be especially useful as the zero restrictions on the loadings of some factors may provide some economic interpretation of the factors. These models, however, require the econometrician to predefine the blocks, leading to potential misspecification. In Monte Carlo experiments, we show that even a small misspecification can lead to substantial declines in fit. We propose an alternative model in which the blocks are chosen endogenously. The model is estimated in a Bayesian framework using a hierarchical prior, which allows us to incorporate series‐level covariates that may influence and explain how the series are grouped. Using international business cycle data, we find our country clusters differ in important ways from those identified by geography alone. In particular, we find that similarities in institutions (e.g., legal systems, language diversity) may be just as important as physical proximity for analyzing business cycle comovements.     

Consumer misperceptions,uncertain fundamentals,and the business cycle

This paper estimates the importance of shocks to consumer misperceptions “noise shocks” for U.S. business cycle fluctuations. I embed imperfect information as in Lorenzoni (2009) into a Smets and Wouters (2007)-type DSGE model. Agents only observe aggregate productivity and a signal about the permanent component contaminated with noise. Based on this information agents form beliefs about the temporary and the permanent component of productivity. Shocks to the signal (noise shocks) trigger aggregate fluctuations unrelated to changes in productivity. Bayesian estimation shows that noise shocks explain up to 14 percent of output and up to 25 percent of consumption fluctuations. Nominal rigidities and the specification of the monetary policy rule are crucial for the importance of noise shocks. These features help to resolve conflicting results in the previous literature.     

Bayesian interval estimation for the difference of two independent Poisson rates using data subject to under‐reporting

Comparing occurrence rates of events of interest in science, business, and medicine is an important topic. Because count data are often under‐reported, we desire to account for this error in the response when constructing interval estimators. In this article, we derive a Bayesian interval for the difference of two Poisson rates when counts are potentially under‐reported. The under‐reporting causes a lack of identifiability. Here, we use informative priors to construct a credible interval for the difference of two Poisson rate parameters with under‐reported data. We demonstrate the efficacy of our new interval estimates using a real data example. We also investigate the performance of our newly derived Bayesian approach via simulation and examine the impact of various informative priors on the new interval.     

Demographics and Business Cycle Volatility: A Spurious Relationship?

This paper replicates the estimation results of three studies on the impact of the age composition of the labor force on business cycle volatility and investigates whether they signal a meaningful long‐run relationship. We show that both the volatile‐age labor force share variable and the business cycle volatility measure exhibit non‐stationary behavior but find no robust evidence of cointegration. Hence the estimation results reported in the literature may be spurious. This conclusion is further supported by the finding that the strong relationship (i) disappears when cross‐sectional dependence is accounted for using the CCEP estimator and (ii) is highly sensitive to small changes in the composition of the sample, to data revisions, and to the exact definition of the volatile‐age labor share. Copyright © 2016 John Wiley & Sons, Ltd.