对欧盟茶叶农药残留新标准的思考

欧盟茶叶农药最高残留限量新新标准自２０００年７月１日起生效实施。对此,我国茶业界应引起高度重视,除及时对相关的标准进行补充修订外,还应采取技术措施控制茶树用药。     

Explaining destinations and volumes of international arms transfers: A novel network Heckman selection model

What determines the volumes of international weapon transfers? And why do countries establish such arms trading relationships in the first place? We propose an innovative statistical strategy that builds on the gravity approach and combines a Heckman model with a network analysis. This allows us, for the first time, to analyze the impact of network structures on both the extensive and the intensive margins of the international arms trade simultaneously. We argue that the structure of the arms transfer network conveys important information for exporting and importing countries. Therefore, past topological properties of the trade network play a central role in its future evolution. Using data on the trade of major conventional weapons between 1955 and 2018, our estimation results and out-of-sample predictions show that network structures have considerable explanatory power with respect to the creation of trade links. They are far less relevant for the explanation of trade volumes, which are mainly determined by demand factors.     

Forecasting macroeconomic variables using collapsed dynamic factor analysis

We explore a new approach to the forecasting of macroeconomic variables based on a dynamic factor state space analysis. Key economic variables are modeled jointly with principal components from a large time series panel of macroeconomic indicators using a multivariate unobserved components time series model. When the key economic variables are observed at a low frequency and the panel of macroeconomic variables is at a high frequency, we can use our approach for both nowcasting and forecasting purposes. Given a dynamic factor model as the data generation process, we provide Monte Carlo evidence of the finite-sample justification of our parsimonious and feasible approach. We also provide empirical evidence for a US macroeconomic dataset. The unbalanced panel contains quarterly and monthly variables. The forecasting accuracy is measured against a set of benchmark models. We conclude that our dynamic factor state space analysis can lead to higher levels of forecasting precision when the panel size and time series dimensions are moderate.     

人才供应链管理模式

文章提出按照供应链管理的特点来建立一种全新的、动态的、快速反应的、结果导向的人才管理模式,以应对中国经济环境的不确定性。由于学术上并未对人才供应链的理论框架有过系统性地阐述,因此,文章运用扎根理论研究的方法,实地调研29家国内外企业,并通过大量的二手资料,利用Nvivo软件作为辅助工具,构建出人才供应链管理模式的框架,第一次系统性的提出将动态短期的人才规划、灵活标准的人才盘点、无时差的人才补给、ROI最大化的人才培养作为构成人才供应链管理模式的四大支柱。     

Extreme returns and the idiosyncratic volatility puzzle: African evidence

We examine the cross-sectional relationship between the expected stock return and both the maximum daily return (MAX) and the idiosyncratic volatility (IVOL) in the five largest emerging African stock markets over the period from 2001 to 2015. First, we find that there is a robust and significantly negative MAX effect in the pooled African stock markets. Second, though we initially document a negative IVOL effect, it disappears after controlling for MAX. Finally, the negative MAX effect is only significant in the small-SIZE, high-illiquidity and high-skewness portfolios. Our results suggest risk-seeking behaviour among African investors similar to that in other parts of the world.     

Protectionism indices for non-tariff measures: An application to maximum residue levels

We propose aggregation indices of Non-Tariff Measures (NTMs) to quantify their protectionism relative to international standards of stringency. We apply the indices to national Maximum Residue Limit (MRL) regulations on pesticides and veterinary drugs affecting agricultural and food trade and using a science-based criteria embodied in Codex Alimentarius international standards. The approach links two streams of the NTM literature, one concerned with the aggregation of various NTMs into operational indices for econometric and modeling purposes, and the other attempting to evaluate the protectionism of NTMs. The data used in the application come from a large international dataset on veterinary and pesticide MRLs and CODEX MRL standards for a large set of countries.     

The MAX effect: European evidence

The maximum daily return over the previous month (MAX) of Bali et al. (2011) is a strong and significant predictor of future stock returns in non-U.S. equity markets. Once it is controlled for MAX in the cross-section of average returns, the puzzling negative idiosyncratic volatility-return relation disappears. Consistent with the assumption that MAX is the true effect, for which idiosyncratic volatility is just a proxy, we find that MAX can be traced back to firm fundamentals in the manner of idiosyncratic volatility. The negative MAX-return relation is stronger among firms with high cash flow volatility and weaker among firms with high profitability.     

On stability of operational risk estimates by LDA: From causes to approaches

The stability of estimates is critical when applying advanced measurement approaches (AMA) such as loss distribution approach (LDA) for operational risk capital modeling. Recent studies have identified issues associated with capital estimates by applying the maximum likelihood estimation (MLE) method for truncated distributions: significant upward mean-bias, considerable uncertainty about the estimates, and non-robustness to both small and large losses. Although alternative estimation approaches have been proposed, there has not been any comprehensive study of how alternative approaches perform compared to the MLE method. This paper is the first comprehensive study on the performance of various potentially promising alternative approaches (including minimum distance approach, quantile distance approach, scaling-based bias correction, upward scaling of lower quantiles, and right-truncated distributions) as compared to MLE with regards to accuracy, precision and robustness. More importantly, based on the properties of each estimator, we propose a right-truncation with probability weighted least squares method, by combining the right-truncated distribution and minimizing a probability weighted distance (i.e., the quadratic upper-tail Anderson–Darling distance), and we find it significantly reduces the bias and volatility of capital estimates and improves the robustness of capital estimates to small losses near the threshold or moving the threshold, demonstrated by both simulation results and real data application.     

Gradient-based simulated maximum likelihood estimation for Lévy-driven Ornstein–Uhlenbeck stochastic volatility models

This paper studies the parameter estimation problem for Ornstein–Uhlenbeck stochastic volatility models driven by Lévy processes. Estimation is regarded as the principal challenge in applying these models since they were proposed by Barndorff-Nielsen and Shephard [J. R. Stat. Soc. Ser. B, 2001, 63(2), 167–241]. Most previous work has used a Bayesian paradigm, whereas we treat the problem in the framework of maximum likelihood estimation, applying gradient-based simulation optimization. A hidden Markov model is introduced to formulate the likelihood of observations; sequential Monte Carlo is applied to sample the hidden states from the posterior distribution; smooth perturbation analysis is used to deal with the discontinuities introduced by jumps in estimating the gradient. Numerical experiments indicate that the proposed gradient-based simulated maximum likelihood estimation approach provides an efficient alternative to current estimation methods.     

INFORMATION THEORETIC APPROACHES IN ECONOMICS

Economics has seen a recent rise in interest in information theory as an alternative framework to the conventional notion of equilibrium as a fixed state, such as Walrasian market‐clearing general equilibrium. The information theoretic approach is predicated on the notion of statistical equilibrium (SE) that takes a distribution over all possible states as an equilibrium, and therefore predicts the endogenous fluctuations of the system along with its central tendency simultaneously. For this reason, SE approaches can explain the observed data without relying on arbitrary assumptions about random noise and provide useful insights for many interesting economic problems that conventional methods have not been able to satisfactorily deal with. In this paper, we review the key elements of information theory focusing on the notions and applications of entropy and SE in economics, particularly paying attention to how entropy concepts open up a new frontline of economic research.