Dynamic Asymmetries in U.S. Unemployment

We examine dynamic asymmetries in U.S. unemployment using nonlinear time series models and Bayesian methods. We find strong statistical evidence in favor of a two-regime threshold auto-regressive model. Empirical results indicate that, once we take into account both parameter and model uncertainty, there are economically interesting asymmetries in the unemployment rate. One finding of particular interest is that shocks that lower the unemployment rate tend to have a smaller effect than shocks that raise the unemployment rate. This finding is consistent with unemployment rises being sudden and falls gradual.     

Correlations among centrality indices and a class of uniquely ranked graphs

Various centrality indices have been proposed to capture different aspects of structural importance but relations among them are largely unexplained. The most common strategy appears to be the pairwise comparison of centrality indices via correlation. While correlation between centralities is often read as an inherent property of the indices, we argue that it is confounded by network structure in a systematic way. In fact, correlations may be even more indicative of network structure than of relationships between indices. This has substantial implications for the interpretation of centrality effects as it implies that competing explanations embodied in different indices cannot be separated from each other if the network structure is close to a certain generalization of star graphs.     

China’s first priority in post-war state building: A wealthy state,or a strong army?

This analysis examined causal links in China’s defence–growth nexus in 1960–2016. The results show that better growth significantly reduces military-civilian ratio and propels military reforms. The unidirectional threshold causality from growth to defence shows that the military impact on a positive change in China’s growth is little in the long term. Conversely, the growth impact of a positive change in defence has accelerated after it reaches the threshold year in 1987. This finding explains why Chinese economy stagnated when defence was prioritised and why China has risen dramatically in the Far East after three decades of fast economic growth.     

规模的门限效应、综合化经营与我国商业银行系统性风险

综合化经营已经成为我国商业银行应对传统业务收入比重不断降低、谋求突破性发展的重要战略。现有研究常采用非利息收入占比作为综合化经营程度的测量指标，这种做法具有明显的技术缺陷。本文将非金融企业产品多样化熵的测量指标引入到商业银行综合化经营分析，较好地解决了综合化经营程度的测量问题。基于宏观审慎与微观审慎相结合的监管理念，本文在利用成分期望损失方法测量商业银行层面系统性风险基础上，借助于动态面板门限模型重点探讨并识别了商业银行规模的门限效应，并借此区分不同的机制状态来分析综合化经营对商业银行系统性风险的影响作用。研究结果表明：综合化经营对于我国商业银行系统性风险的影响作用具有规模的门限效应，表现为规模小的商业银行开展综合化经营会降低系统性风险，规模大的商业银行开展综合化经营会增加系统性风险。     

当前农村人情文化的负面效应和正向功能——以温州农村为例

在我国的广大农村,无处不在的人情文化已成为一种人际关系创设与维持的常识与准则.人情作为一种传统习俗,是在长期发展过程中代代传承而逐渐积淀起来的文化现象,它以非正式的形式规定了农民所应遵守的行为规范和价值观念.在当前的温州农村,浓郁的人情文化显现不少负面效应,如加重农民经济和精神负担、容易形成狭隘封闭的圈子而有损道德建设、交易色彩浓郁有损社会公正、规则意识淡薄而有违法治精神.但是,当前人情文化依然被广大农民所认同,源于它也承担了较多的经济社会功能,人情来往是获得社会资源的重要途径,人情交往有经济协作功能、社会福利与民间互助功能、娱乐团聚和社会评价功能、行为约束和社会稳定功能等,只有辩证地加以分析和引导,才能扬长避短.     

Between group variance component interval estimation for the unbalanced heteroscedastic one-way random effects model

The studied topic is motivated by the problem of interlaboratory comparisons. This paper focuses on the confidence interval estimation of the between group variance in the unbalanced heteroscedastic one-way random effects model. Several interval estimators are proposed and compared by means of the simulation study. The most recommended (safest) is the confidence interval based on Bonferroni's inequality.     

Flexible Threshold Models for Modelling Interest Rate Volatility

This paper focuses on interest rate models with regime switching and extends previous nonlinear threshold models by relaxing the assumption of a fixed number of regimes. Instead we suggest automatic model determination through Bayesian inference via the reversible jump Markov Chain Monte Carlo (MCMC) algorithm. Moreover, we allow the thresholds in the volatility to be driven not only by the interest rate but also by other economic factors. We illustrate our methodology by applying it to interest rates and other economic factors of the American economy.     

Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models

We propose a new estimator, the thresholded scaled Lasso, in high-dimensional threshold regressions. First, we establish an upper bound on the ?_∞ estimation error of the scaled Lasso estimator of Lee, Seo, and Shin. This is a nontrivial task as the literature on high-dimensional models has focused almost exclusively on ?₁ and ?₂ estimation errors. We show that this sup-norm bound can be used to distinguish between zero and nonzero coefficients at a much finer scale than would have been possible using classical oracle inequalities. Thus, our sup-norm bound is tailored to consistent variable selection via thresholding. Our simulations show that thresholding the scaled Lasso yields substantial improvements in terms of variable selection. Finally, we use our estimator to shed further empirical light on the long-running debate on the relationship between the level of debt (public and private) and GDP growth. Supplementary materials for this article are available online.     

开征环境税对经济增长影响的实证研究——基于十二个发达国家二氧化碳税开征经验的面板数据分析

本文利用芬兰等十二个已开征二氧化碳税的发达国家1980～2009年间的跨国面板数据进行随机效应估计.结果发现:开征环境税在短期内可能给经济增长带来负向冲击；但环境税对经济增长的影响更多地体现为长期冲击,且这种长期冲击是显著的负向影响.因此,开征环境税时,不仅要通过税收体系调整缓解企业成本上升在短期内给经济增长带来的不利冲击,更应从长期影响的视角出发,设计配套政策,降低环境税在长期内对经济增长和社会福利可能存在的不利影响.     

Empirical Likelihood for Threshold Autoregressive Models

This article develops empirical likelihood for threshold autoregressive models. We propose general estimating equations based on moment constraint. Under some suitable conditions, we show the empirical likelihood estimators for parameter are asymptotically normally distributed, and the proposed log empirical likelihood ratio statistic asymptotically follows a standard chi-squared distribution.