Random Effects Misspecification Can Have Severe Consequences for Random Effects Inference in Linear Mixed Models

There has been considerable and controversial research over the past two decades into how successfully random effects misspecification in mixed models (i.e. assuming normality for the random effects when the true distribution is non‐normal) can be diagnosed and what its impacts are on estimation and inference. However, much of this research has focused on fixed effects inference in generalised linear mixed models. In this article, motivated by the increasing number of applications of mixed models where interest is on the variance components, we study the effects of random effects misspecification on random effects inference in linear mixed models, for which there is considerably less literature. Our findings are surprising and contrary to general belief: for point estimation, maximum likelihood estimation of the variance components under misspecification is consistent, although in finite samples, both the bias and mean squared error can be substantial. For inference, we show through theory and simulation that under misspecification, standard likelihood ratio tests of truly non‐zero variance components can suffer from severely inflated type I errors, and confidence intervals for the variance components can exhibit considerable under coverage. Furthermore, neither of these problems vanish asymptotically with increasing the number of clusters or cluster size. These results have major implications for random effects inference, especially if the true random effects distribution is heavier tailed than the normal. Fortunately, simple graphical and goodness‐of‐fit measures of the random effects predictions appear to have reasonable power at detecting misspecification. We apply linear mixed models to a survey of more than 4 000 high school students within 100 schools and analyse how mathematics achievement scores vary with student attributes and across different schools. The application demonstrates the sensitivity of mixed model inference to the true but unknown random effects distribution.     

Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence

This study investigates the level of risk due to fat tails of the return distribution and the changes of tail fatness (TF) through portfolio diversification. TF is not eliminated through portfolio diversification, and, interestingly, the positive tail has declining fatness until a certain level is reached, while the negative tail has rising fatness. This indicates that fat tails are highly relevant to common factors on systematic risk and that the relevance of common factors is higher for the negative tail compared to the positive tail. In the portfolio diversification effect, the declining fatness of the positive tail further reduces risk, but the rising fatness of the negative tail does not contribute to this effect. The asymmetry between the fatness of the positive and negative tails in the return distribution corresponds to the asymmetry of the trade-off relationship between loss avoidance and profit sacrifice that is expected as a consequence of portfolio diversification. Investors use portfolio diversification to reduce their risk of suffering high losses, but following this strategy means sacrificing high-profit potential. Our study provides empirical confirmation for the practical limitation of portfolio diversification and explains why investors with diversified portfolios suffer high losses from market crashes. An examination of the Northeast Asian stock markets of China, Japan, Korea, and Taiwan show identical results.     

国际生产分割视角下的中国双边贸易平衡--以东亚经济体为例

为了解释中国近年来对东亚经济体贸易逆差持续地增加的现象,文章在国际生产分割背景下,分别基于总体、国家（地区）和行业视角,对1992—2012年中国与东亚8个经济体间的零部件贸易面板数据进行实证分析。结果表明：中国作为东亚国际生产网络中的枢纽,从日韩等东亚经济体进口零部件会显著扩大中国对东亚经济体的贸易逆差,其中以ICT行业最为典型;生产分割效应弱化了汇率对双边贸易平衡的影响。只要中国在国际生产分割中所扮演的角色不变,中国对外贸易总体顺差和区域性逆差的局面将会持续存在。     

Fundamentals and Exchange Rate Prediction Revisited

This paper measures latent fundamental exchange rates with independent component‐based rates constructed from a cross‐section of exchange rates and then uses their deviations from exchange rates to forecast. Empirical results indicate that the independent component‐based model and its Taylor rule and purchasing power parity augmented models are superior to the random walk in predicting exchange rates. These results are robust to several scenarios and are likely to be observed if the U.S. sources and the recursive scheme are applied. Our results reveal that information regarding the third moment of exchange rate changes is helpful to explain exchange rate movements.     

我国整车与零部件产业共聚的空间分布研究

本研究利用我国整车与零部件产业2002～2012年的数据,分析了中国整车和零部件产业协同共聚的空间布局及其空间演化趋势,以期为我国汽车、零部件产业和区域经济发展提供借鉴意义。研究发现：我国整车产业布局与零部件产业布局存在显著的空间相关性;2002年我国省域样本中,山东、安徽、北京与天津的整车与零部件产业空间共聚趋势明显;而在2012年的样本中,辽宁、北京、天津、河北、湖北、安徽、江苏的共聚趋势明显,这些省份逐步形成了2个整车与零部件空间上协同共聚的群落,一个是以北京为中心,天津、河北、辽宁环绕的共聚群;另外一个则是以安徽为中心,湖北、江苏环绕的共聚群。     

Does global liquidity drive commodity prices?

This paper tackles the question of whether a cross-sectional perspective on monetary policy is capable of explaining movements in global commodity prices. In this vein, we contribute to the rich literature on global liquidity in two different ways: on the one hand, to achieve a global series in terms of common monetary policy shocks, we propose a distinction between common and idiosyncratic factors across economies, as proposed by Bai and Ng (2004). Our second innovation stems from the consideration of a Markov-switching vector error correction model when analyzing time-varying short-run dynamics. Having identified the long-run structure which includes a proportional relationship between commodity prices and global liquidity in the first step, our results indeed show that the impact of a global liquidity measure on different commodity prices is significant and varies over time. One regime approximately accounts for times where commodity prices significantly adjust to disequilibria, while the second regime is characterized by either a weak or no commodity price adjustment. The fact that global liquidity also reacts to disequilibria in a specific regime demonstrates the two-way causality between monetary policy and commodity prices.     

零部件拆装及测绘实践

针对工程制图的课程特点,简要介绍在建构主义教育理念的基础上,进行的零部件拆装实践教学。在教学内容上,给定真实的拆装与测绘环境,用逆向设计模式,画出相应的零部件装配图和零件图。教学手段上加强了数字化教学资源的建设。教学方法上,更注重于以项目为载体,理论教学与实践教学相结合。     

Sparse estimation of dynamic principal components for forecasting high-dimensional time series

We present the sparse estimation of one-sided dynamic principal components (ODPCs) to forecast high-dimensional time series. The forecast can be made directly with the ODPCs or by using them as estimates of the factors in a generalized dynamic factor model. It is shown that a large reduction in the number of parameters estimated for the ODPCs can be achieved without affecting their forecasting performance.     

Conditional Persistence of Earnings Components and Accounting Anomalies

We suggest that the failure of investors to distinguish between an earnings component's autocorrelation coefficient (unconditional persistence) and the marginal contribution of that component's persistence to the persistence of earnings (conditional persistence) provides a partial explanation of post‐earnings‐announcement drift, post‐revenue‐announcement drift, and the accrual anomaly. When the conditional persistence of revenue surprises is high (low) relative to its unconditional persistence, both the post‐earnings‐announcement drift and the post‐revenue‐announcement drift are high (low), because investors’ under‐reaction to revenues and earnings is stronger when the persistence of revenue surprises is more strongly associated with the persistence of earnings surprises. Also, the mispricing of accruals decreases substantially when the conditional persistence of accruals is high relative to its unconditional persistence, because investors’ over‐reaction to accruals is mitigated when the persistence of accruals is indeed more strongly associated with the persistence of earnings. Our findings also suggest that financial analysts’ failure to distinguish between unconditional and conditional persistence of revenues and accruals results in more biased revenue and earnings predictions.     

Non-linear exchange rate relationships: An automated model selection approach with indicator saturation

This paper examines whether the explanatory power of exchange rate models can be improved by allowing for cross-country asymmetries and non-linear effects of fundamentals. Both appear to be crucial. The samples include the USD versus pound and yen from 1982:10 to 2013:10, and automated model selection is conducted with indicator saturation. Several non-linear effects are significant at 1%. Further, many of the indicators present in the linear models are eliminated once allowing for non-linearities; suggesting some of the structural breaks found in previous work were an artifact of the misspecified linear functional form. These conclusions are robust to estimation using principal components.