A perspective on recent methods on testing predictability of asset returns

This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictors are highly persistent and their innovations are contemporarily correlated with dependent variable, the ordinary least squares estimator has a finite-sample bias, and its limiting distribution relies on some unknown nuisance parameter, which is not consistently estimable. Without correcting these issues, conventional test statistics are subject to a serious size distortion and generate a misleading conclusion in testing pre- dictability of asset returns in real applications. In the past two decades, sequential studies have contributed to this subject and proposed various kinds of solutions, including, but not limit to, the bias-correction procedures, the linear projection approach, the IVX filtering idea, the variable addition approaches, the weighted empirical likelihood method, and the double-weight robust approach. Particularly, to catch up with the fast-growing literature in the recent decade, we offer a selective overview of these methods. Finally, some future research topics, such as the econometric theory for predictive regressions with structural changes, and nonparametric predictive models, and predictive models under a more general data setting, are also discussed.

A new nonparametric stability test with an application to major Chinese macroeconomic time series

In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable.

Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review

In this paper,we highlight some recent developments of a new route to evaluate macroeconomic policy effects,which are investigated under the framework with potential outcomes.First,this paper begins with a brief introduction of the basic model setup in modern econometric analysis of program evaluation.Secondly,primary attention goes to the focus on causal effect estimation of macroeconomic policy with single time series data together with some extensions to multiple time series data.Furthermore,we examine the connection of this new approach to traditional macroeconomic models for policy analysis and evaluation.Finally,we conclude by addressing some possible future research directions in statistics and econometrics.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

Past Experiences,Personality Traits,and Risk Aversion:Evidence from Individual Risk Attitudes during the COVID-19 Pandemic

Individuals’risk attitudes play an important role in economic decision making and policy evaluation,particularly in the midst of unprecedented uncertainty caused by the COVID-19 pandemic.We adopt a multiple-price-list elicitation method with real money incentives to measure precisely individuals’risk attitudes at different stake levels and the extent to which they are affected by personal and social shocks following the COVID-19 outbreak in China.We find that subjects who had previously experienced negative personal shocks are more risk-averse at medium and large stakes but more risk loving at very small stakes.For our sample,COVID-19 has no significant impact on risk attitudes,as it is more likely to be regarded as a social shock.The result indicates that the impact of COVID-19 on individual risk attitudes is not as influential as expected,unless the individual’s personal life is affected directly.

Business Cycle Asymmetry in China:Evidence from Friedman's Plucking Model

Friedman＇s plucking model of business fluctuations suggests that output cannot exceed an upper limit, but it is occasionally ＂plucked＂ downward below trends as a result of economic recessions. This paper investigates China＇s business fluetuations using quarterly real GDP data for the period 1978 2009. Our results show some evidence supporting Friedman＇s plucking model. We find that a ceiling effect of real output exists, and that negative asymmetric shocks significantly affect the transitory component, which captures the plucking downward behavior during the recession. The results also suggest that the basic asymmetric unobserved component model is not appropriate for directly modeling China＇s real output because the business＂ cycle is inaccurately measured, but it works quite well when considering a structural break in the second quarter of 1992. The results reveal that although China＇s economy strengthened in the second quarter of 2009, it is essential for China＇s government to take further positive and effective measures to maintain sustainable development of the economy.

Does Chinese OFDI really promote export?

Does Chinese outward foreign direct investment really promote export?Most papers have come to positive conclusions.Upon reviewing these papers,this paper contributes by correcting model misspecification,wrong variable selection and estimation methods which are prevalent in existing studies,and reexamines the relationship using panel data from 2003 to 2014.The results indicate that:on average,the point estimate of the elasticity between Chinese outward foreign direct investment and export trade is at most 0.073,and it’s not statistically significant.Sub-sample regressions show that,Chinese investment in developed economies slightly substitutes export while investment in developing economies complements export.But these effects disappear when country specific effects are controlled.Year-by-year regressions show that,the complementary effect of OFDI on export is on a steady rise.But if we take the regression coefficients and the quantitative difference between OFDI and export into consideration,the effect is indeed negligible.

Estimation of partial derivative functionals with application to human mortality data analysis

To better describe and understand the time dynamics in functional data analysis,it is often desirable to recover the partial derivatives of the random surface.A novel approach is proposed based on marginal functional principal component analysis to derive the representation for partial derivatives.To obtain the Karhunen-Lo`eve expansion of the partial derivatives,an adaptive estimation is explored.Asymptotic results of the proposed estimates are established.Simulation studies show that the proposed methods perform well in finite samples.Application to the human mortality data reveals informative time dynamics in mortality rates.