Adaptive Test for Periodicity in Self-Exciting Threshold Autoregressive Models

This article is devoted to the study of the periodicity testing problem in a self-exciting threshold autoregressive (SETAR) model. The local asymptotic normality (LAN) property is shown via the adapted sufficient conditions due to Swensen (1985 Swensen , A. R. ( 1985 ). The asymptotic distribution of the likelihood ratio for autoregressive time series with a regression trend . Journal of Multivariate Analysis 16 : 54 – 70 .[Crossref], [Web of Science ®] , [Google Scholar]). Moreover, the LAN of the central sequence is established. First, we consider the case where the innovation density is specified and we obtain a parametric local asymptotic test. Second, we construct an adaptive test in the case where this density is unspecified but symmetric. The performances of these established tests are shown via simulation studies.     

An Integral Bhattacharyya Type Bound for the Bayes Risk

In this article, some results are derived on stochastic comparisons of the residual and past lifetimes of an (n ? k + 1)-out-of-n system with dependent components. These findings generalize some recent results obtained on systems with independent components and provide some interesting results for a system with dependent components following an Archimedean copula. An illustrative example is provided.     

The effect of board size on shareholder value: Evidence from bank mergers and acquisitions

This study examines the effect of board size on the economic impact of bank mergers and acquisitions (M&A) in the US. Using a hand-collected dataset of 508 M&A between 2012 and 2018, we find that board size is negatively related to acquirer excess returns. In an additional analysis, we show that large boards have positive value implications for banks that combine the CEO and chairman roles as well as for large banks. Our findings indicate that a “one-size-fits-all” approach to board size is not necessarily in the interests of shareholders; instead, a more flexible and proactive formulation is needed.     

Credit access,macroprudential rules and policy interventions: Lessons for potential first time buyers

Given the increased popularity of macroprudential measures in the aftermath of the great financial crisis (GFC), a key policy question to arise in certain mortgage markets is whether a significant access to credit issue exists amongst prospective homeowners because of these new policies. In this paper we assess whether such a problem arises in the context of the Irish mortgage market – a market particularly adversely impacted by the GFC. We use a microsimulation model to estimate the level of latent credit demand that could be serviced by the market given prudent credit risk assessment and the current macroprudential regulations. We then compare this demand to current market provision to explore whether a credit gap exists. Finally, we simulate how a public mortgage credit scheme or equity “help-to-buy” type instrument may help credit access. We find both instruments to be effective but would lead to somewhat higher house prices.     

Bias-corrected confidence bands in nonparametric regression

Bias-corrected confidence bands for general nonparametric regression models are considered. We use local polynomial fitting to construct the confidence bands and combine the cross-validation method and the plug-in method to select the bandwidths. Related asymptotic results are obtained. Our simulations show that confidence bands constructed by local polynomial fitting have much better coverage than those constructed by using the Nadaraya–Watson estimator. The results are also applicable to nonparametric autoregressive time series models.     

基于议程设置的高校思想政治教育创新

议程设置作为传播学、政治学等学科的经典理论之一,在传播效用和舆论导向方面具有独特优势.思想政治教育与议程设置作为特殊的信息及文化传播活动,旨在引导受众的价值观念和塑造客体行为习惯,二者在目标、过程和载体等方面具有内在一致性,运用议程设置的原理和方法有助于高校思想政治教育的创新.新时代高校思想政治教育应把握受众导向需求,科学设置议题;当好信息把关人,掌控舆论主导权;优化传播机制,营造育人氛围;加强平台建设,实现多元化传播,从而提升高校思想政治教育的亲和力与实效性,实现立德树人的根本目的.     

Understanding exponential smoothing via kernel regression

Exponential smoothing is the most common model-free means of forecasting a future realization of a time series. It requires the specification of a smoothing factor which is usually chosen from the data to minimize the average squared residual of previous one-step-ahead forecasts. In this paper we show that exponential smoothing can be put into a nonparametric regression framework and gain some interesting insights into its performance through this interpretation. We also use theoretical developments from the kernel regression field to derive, for the first time, asymptotic properties of exponential smoothing forecasters.     

1949年国民党上海市银行的接收清理与结束

上海市银行于1929年由上海市政府设立,是国民党政府时期的一家典型地方政府银行。上海解放后,根据新民主主义经济政策的规定,被新中国政府列入接管的范围。1949年原国民党上海市银行被接收、清理和结束表明,原上海市银行的体制、机制、组织人事,更多地带有政府机关的特征,其业务经营也主要服务于原上海地方政府的财政收支及日常运作,这是该银行的基本属性使然。上海市银行与四行二局往来联系较密切,是整个官僚资本金融体系的重要组成部分。     

本地市场效应与出口增长二元边际——基于中国1996～2009年制造行业面板数据的实证研究

本文采用6位数级微观贸易数据,计算了1996～2009年在中国制造业行业层面的出口增长二元边际;并运用制造行业面板数据,实证分析了本地市场效应对中国出口增长二元边际的影响.实证结果表明,本地市场效应对中国出口增长的深度边际和广度边际都有促进作用,但对深度边际的影响更大;同时,本地市场效应对中高技术行业出口增长二元边际的促进作用大于中低技术行业.