The Zellner Thesis Award in Business and Economic Statistics

We analyze the modifications that occur in indirect inference when a nuisance parameter is not identified under the null hypothesis. We develop a testing procedure adapted to this simulation-based estimation method, and detail its use for detecting the threshold effect in threshold moving average models with contemporaneous and lagged asymmetries. In contrast to existing threshold models, these models allow taking into account the presence of asymmetric effects of current and lagged random shocks. We use them to measure the persistence of shocks to U.S. output.     

THE UNEMPLOYMENT RATE WHEN THE LABOUR MARKET IS MODELLED BY A MARKOV CHAIN

Assuming a Markov chain model for the labour market flow, we study it in its equilibrium state, We compare the observed and the theoretical unemployment rates. It is found that the observed unemployment rate approximates very closely the theoretical one. The mean and variance of the observed unemployment rate are computed. It is shown that its asymptotic distribution is normal.     

基于行政大数据的失业率估计:以某四百万人口城市为例

我国城镇登记失业率指标稳定在4%左右,难以较为准确反映就业动态;而劳动力调查样本量有限,城镇调查失业率对省以下各级行政区域代表性不足。本文将针对大数据的机器学习算法与针对传统统计数据的核算思想结合起来,基于某四百万人口城市2016—2018年的全样本行政大数据,利用机器学习算法,对每个城镇居民每个月的就业状态进行预测,再利用统计核算方法,估计出该城市的失业率。在个人层面,本文的模型在样本外测试集上的准确率达到96.7%。经过统计核算加总,本文估计的当地失业率在合理区间范围内,并表现出明显的周期性特征,对就业形势动态变化的刻画明显优于当地一年发布一次的登记失业率数据。本文基于个人层面的预测结果,进一步探讨了当地失业人口 的性别与文化程度特征,以及再就业的时间规律。本文针对如何使用行政大数据辅助经济决策提出了新的范式,对大数据时代如何理解经济与制定政策具有参考意义。     

The Changing Transmission of Uncertainty Shocks in the U.S.

This article investigates if the impact of uncertainty shocks on the U.S. economy has changed over time. To this end, we develop an extended factor augmented vector autoregression (VAR) model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on a range of variables. We find that the impact of uncertainty shocks on real activity and financial variables has declined systematically over time. In contrast, the response of inflation and the short-term interest rate to this shock has remained fairly stable. Simulations from a nonlinear dynamic stochastic general equilibrium (DSGE) model suggest that these empirical results are consistent with an increase in the monetary authorities’ antiinflation stance and a “flattening” of the Phillips curve. Supplementary materials for this article are available online.     

Testing Business Cycle Asymmetries Based on Autoregressions With a Markov-Switching Intercept

Implications of two concepts of asymmetry—deepness and steepness—are investigated for autoregressive processes with a Markov-switching intercept. The formulas for the skewness of these processes and the skewness of the first differences of these processes are derived. The parameter restrictions leading to nondeepness and nonsteepness are presented for the special case of a first-order autoregression and two states. It is shown that these restrictions imply that previous tests for asymmetries in autoregressive processes with a Markov-switching intercept can lead to wrong conclusions. In an empirical application of the developed tests, the U.S. unemployment rate is found to be steep.     

BL-GARCH models and asymmetries in volatility

In this paper the class of Bilinear GARCH (BL-GARCH) models is proposed. BL-GARCH models allow to capture asymmetries in the conditional variance of financial and economic time series by means of interactions between past shocks and volatilities. The availability of likelihood based inference is an attractive feature of BL-GARCH models. Under the assumption of conditional normality, the log-likelihood function can be maximized by means of an EM type algorithm. The main reason for using the EM algorithm is that it allows to obtain parameter estimates which naturally guarantee the positive definiteness of the conditional variance with no need for additional parameter constraints. We also derive a robust LM test statistic which can be used for model identification. Finally, the effectiveness of BL-GARCH models in capturing asymmetric volatility patterns in financial time series is assessed by means of an application to a time series of daily returns on the NASDAQ Composite stock market index.     

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.     

Hierarchical Bayes estimation of spatial statistics for rates

The U.S. Bureau of Labour Statistics publishes monthly unemployment rate estimates for its 50 states, the District of Columbia, and all counties, under Current Population Survey. However, the unemployment rate estimates for some states are unreliable due to low sample sizes in these states. Datta et al. (1999) proposed a hierarchical Bayes (HB) method using a time series generalization of a widely used cross-sectional model in small-area estimation. However, the geographical variation is also likely to be important. To have an efficient model, a comprehensive mixed normal model that accounts for the spatial and temporal effects is considered. A HB approach using Markov chain Monte Carlo is used for the analysis of the U.S. state-level unemployment rate estimates for January 2004-December 2007. The sensitivity of such type of analysis to prior assumptions in the Gaussian context is also studied.     

消费替代弹性、经济开放与中国经济外部失衡

 本文通过求解一个动态随机一般均衡(DSGE)的两国模型,分析不同消费替代弹性下技术冲击和货币冲击对一国经济外部失衡的影响。指出随着一国经济的对外开放,当存在粘性价格且消费替代弹性很小时,负的技术冲击和正的货币冲击都会使得一国的均衡汇率水平升值和外部资产盈余,且都会收敛于偏离封闭经济的“0均衡”的新稳态。这给中国当前的经济外部失衡提供了一个比较好的解释,本文也依此提出了相应的政策建议。     

Compositional Changes of the Labor Force and the Icrease of the Unemployment Rate: An Estimate for the United States

This article estimates how demographic changes in the composition of the labor force affect the unemployment rate in the United States. In addition to the effect from changes in the weights of the individual groups composing the total, the impact of compositional changes on the individual unemployment rates is estimated by using a dummy-variables model and incorporated into the estimate on the overall unemployment rate. The results suggest that the incorporation of the latter effect is significant. Indedd, the estimates presented in this article are almost twice as high as those provided by the fixed-weight method used in previous studies.     

The Increasingly Mixed Proportional Hazard Model: An Application to Socioeconomic Status,Health Shocks,and Mortality

We introduce a duration model that allows for unobserved cumulative individual-specific shocks, which are likely to be important in explaining variations in duration outcomes, such as length of life and time spent unemployed. The model is also a useful tool in situations where researchers observe a great deal of information about individuals when first interviewed in surveys but little thereafter. We call this model the “increasingly mixed proportional hazard” (IMPH) model. We compare and contrast this model with the mixed proportional hazard (MPH) model, which continues to be the workhorse of applied single-spell duration analysis in economics and the other social sciences. We apply the IMPH model to study the relationships among socioeconomic status, health shocks, and mortality, using 19 waves of data drawn from the German Socio-Economic Panel (SOEP). The IMPH model is found to fit the data statistically better than the MPH model, and unobserved health shocks and socioeconomic status are shown to play powerful roles in predicting longevity.     

System reliability under δ-shock model

δ-shock model is one of the widely studied shock models in reliability. Under this model, the system fails when the time between two consecutive shocks falls below a fixed threshold δ. In this paper, the survival function and the mean time to failure of the system are obtained when the times between successive shocks follow proportional hazard rate model.     

基于STAR模型的中国货币政策对产出影响的非对称性研究

对中国GDP增长率建立以可预期到的货币冲击、未预期到的正向货币冲击和未预期到的负向货币冲击滞后三期为转移变量的LSTAR模型,拟合效果良好,分析不同类型的货币冲击对产出的非线性和非对称性影响,给出可预期到的货币冲击、未预期到的正向货币冲击和未预期到的负向货币冲击的阀值,分别为20.03%、2%和1.58%,说明不同类型的货币冲击对产出呈现不同的非对称性影响,强弱机制的转换区间存在差异,且负向货币冲击的阀值小于正向货币冲击的阀值。研究结果表明中国的货币政策存在显著的非线性和非对称性特征,且紧缩性货币政策比扩张性货币政策更有效。     

A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks

Theoretical models of contagion and spillovers allow for asset-specific shocks that can be directly transmitted from one asset to another, as well as indirectly transmitted across uncorrelated assets through some intermediary mechanism. Standard multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, however, provide estimates of volatilities and correlations based only on the direct transmission of shocks across assets. As such, spillover effects via an intermediary asset or market are not considered. In this article, a multivariate GARCH model is constructed that provides estimates of volatilities and correlations based on both directly and indirectly transmitted shocks. The model is applied to exchange rate and equity returns data. The results suggest that if a spillover component is observed in the data, the spillover augmented models provide significantly different volatility estimates compared to standard multivariate GARCH models.     

Estimation of structural impulse responses: short-run versus long-run identifying restrictions

There is evidence that estimates of long-run impulse responses of structural vector autoregressive (VAR) models based on long-run identifying restrictions may not be very accurate. This finding suggests that using short-run identifying restrictions may be preferable. We compare structural VAR impulse response estimates based on long-run and short-run identifying restrictions and find that long-run identifying restrictions can result in much more precise estimates for the structural impulse responses than restrictions on the impact effects of the shocks.     

我国城镇自然失业率及应用——通货紧缩：忽视失业对宏观调控作用的后果

 在20世纪50-60年代,西方经济处于战后高速增长之中,事业与通货膨胀率的关系成为当时几乎所有西方国家宏观经济政策讨论的焦点。事业与通货膨胀在市场经济中从来都是如影随形,难以分离。90年代中期当我国物价指数达2位数的时候,由于种种原因,诸多理论研究以及调控措施近单纯地进行了通货膨胀与产出变动的分析和操作。过高的经济增长速度所引发的严重的通货膨胀是当时众人关注的焦点,而失业问题无论在理论研究上,还是在政策调控上都涉及很少。显然理论上和实际操作上是不完整的。随着市场经济在我国主导地位的确立,失业问题完全应该回复到经济生活中所应占有的位置,全面分析失业、通货膨胀和产出变动之间关系的必要性和紧迫性已日渐显现。     

Time‐change models for asymmetric processes

Many records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.     

Sample Path Asymmetries in Non‐Gaussian Random Processes

We tackle an important although rarely addressed question of accounting for a variety of asymmetries frequently observed in stochastic temporal/spatial records. First, we review some measures intending to capture such asymmetries that have been introduced on various occasions in the past and then propose a family of measures that is motivated by Rice's formula for crossing level distributions of the slope. We utilize those asymmetry measures to demonstrate how a class of second‐order models built on the skewed Laplace distributions can account for sample path asymmetries. It is shown that these models are capable of mimicking not only distributional skewness but also more complex geometrical asymmetries in the sample path such as tilting, front‐back slope asymmetry and time irreversibility. Simple moment‐based estimation techniques are briefly discussed to allow direct application to modelling and fitting actual records.     

Missing data and small area estimation in the UK Labour Force Survey

Summary.  We apply multivariate shrinkage to estimate local area rates of unemployment and economic inactivity by using UK Labour Force Survey data. The method exploits the similarity of the rates of claiming unemployment benefit and the unemployment rates as defined by the International Labour Organisation. This is done without any distributional assumptions, merely relying on the high correlation of the two rates. The estimation is integrated with a multiple-imputation procedure for missing employment status of subjects in the database (item non-response). The hot deck method that is used in the imputations is adapted to reflect the uncertainty in the model for non-response. The method is motivated as a development (improvement) of the current operational procedure in which the imputed value is a non-stochastic function of the data. An extension of the procedure to subjects who are absent from the database (unit non-response) is proposed.     

Asymptotics for Panel Models with Common Shocks

This article develops a novel asymptotic theory for panel models with common shocks. We assume that contemporaneous correlation can be generated by both the presence of common regressors among units and weak spatial dependence among the error terms. Several characteristics of the panel are considered: cross-sectional and time-series dimensions can either be fixed or large; factors can either be observable or unobservable; the factor model can describe either a cointegration relationship or a spurious regression, and we also consider the stationary case. We derive the rate of convergence and the limit distributions for the ordinary least square (OLS) estimates of the model parameters under all the aforementioned cases.