Forecast-error-based estimation of forecast uncertainty when the horizon is increased

Past forecast errors are employed frequently in the estimation of the unconditional forecast uncertainty, and several institutions have increased their forecast horizons in recent times. This work addresses the question of how forecast-error-based estimation can be performed if there are very few errors available for the new forecast horizons. It extends the results of Knüppel (2014) in order to relax the condition on the data structure that is required for the SUR estimator to be independent of unknown quantities. It turns out that the SUR estimator of the forecast uncertainty, which estimates the forecast uncertainty for all horizons jointly, tends to deliver large efficiency gains relative to the OLS estimator (i.e., the sample mean of the squared forecast errors for each individual horizon) in the case of increased forecast horizons. The SUR estimator is applied to the forecast errors of the Bank of England, the US Survey of Professional Forecasters, and the FOMC.     

Semiparametric time series regression modeling with a diverging number of parameters

Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite‐sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.     

双选信道下一种基于混沌交织的FBMC系统

高速移动环境下，无线信道具有时频双选性衰落的特性，使得滤波器组多载波(Filter Bank Multi-carrier，FBMC)系统产生长突发差错。将一种基于Baker映射的混沌交织算法应用在滤波器组多载波系统中，根据混沌密钥对发送数据进行分块和重新排列，按照Baker映射规则完成数据交织。此方法可以将长突发差错变为单突发差错，结合卷积编码能有效地纠正双选信道产生的长突发差错。仿真结果表明，在双选择信道中，基于混沌交织的滤波器组多载波系统误比特率性能优于传统基于块交织的滤波器组多载波系统。     

The asymptotic expansion of the regular discretization error of Itô integrals

We study an Edgeworth‐type refinement of the central limit theorem for the discretization error of Itô integrals. Toward this end, we introduce a new approach, based on the anticipating Itô formula. This alternative technique allows us to compute explicitly the terms of the corresponding expansion formula. Two applications to finance are given; the asymptotics of discrete hedging error under the Black–Scholes model and the difference between continuously and discretely monitored variance swap payoffs under stochastic volatility models.     

Is heterogeneous capital depreciation important for estimating firm-level productivity? Evidence from Chinese manufacturing firms

This paper contributes to the existing literature on estimating firm-level production functions. Using Chinese manufacturing survey data, we employ the firm-level heterogeneous capital depreciation rate to measure firms’ investment and assess its role using Olley and Pakes (1996) (OP) production function estimation technique. Although there is some ongoing debate on the econometric soundness of the OP technique, we argue quantitatively that the heterogeneous depreciation rate muffles the measurement error associated with the key input demand investment. In our sample, it significantly narrows the gap of total factor productivity (TFP) estimates between the OP technique and a state-of-the-art estimation method that works without investment. We further reveal that the improved performance primarily originates from the dynamic evolution in the distribution of the capital depreciation rate.     

真实型领导与团队创新绩效: 差错管理氛围与特质调节焦点的作用研究

团队创新是企业获取竞争优势,实现可持续发展的重要保证。差错管理氛围和特质焦点提供了理解团队创新的新视角。研究发现真实型领导通过营造差错管理氛围,对团队创新绩效产生正向影响;团队提升型特质调节焦点在差错管理氛围和团队创新绩效间起到正向调节作用。文章拓展了创新、差错管理氛围以及调节焦点等相关文献,并为提升团队创新绩效提供了管理建议。     

A preliminary theoretical examination of the targeted public distribution system in India

A theoretical model of targeting in the public distribution system is set out. In any system of targeting there could be inclusion and exclusion errors. These errors could be reduced by search by the state. The state aims to minimise the costs of food administration subject to keeping the magnitude of the exclusion error bounded. Targeting involves a consideration of the objective poverty level, the official poverty level and the targeted poverty level by the state. The targeted poverty level could be less than the official poverty level if the extent of search is not adequate. The objective poverty level is an increasing function of the above poverty line issue price of food due to exclusion errors, a decreasing function of the procurement price of food and by definition the below poverty line issue price of food. The instruments in the hands of the state are the official poverty level, the above poverty line issue price for food, the procurement price of food and the extent of search. The comparative static implications of the model are set out.     

Does Integrated Reporting Matter to the Capital Market?

Integrated reporting (<IR>) is an emerging international corporate reporting initiative to address limitations to extant corporate reporting approaches, which are commonly criticized for being both voluminous and disjointed. While <IR> is gaining in popularity, current momentum has been limited due to a lack of clear evidence of its benefits. Utilizing the most suitable setting currently available, being discretionary disclosures made by listed companies on the Johannesburg Stock Exchange, this study provides evidence that analyst forecast error reduces as a company's level of alignment with the <IR> framework increases. Further, the improved alignment is associated with a subsequent reduction in the cost of equity capital for certain reporting companies. The results are obtained after controlling for factors relating to financial transparency and the issuance of standalone non‐financial reports, which suggests that <IR> is providing incrementally useful information to the capital market over and above existing reporting mechanisms.     

Hedging of Asian options under exponential Lévy models: computation and performance

In this paper we consider the problem of hedging an arithmetic Asian option with discrete monitoring in an exponential Lévy model by deriving backward recursive integrals for the price sensitivities of the option. The procedure is applied to the analysis of the performance of the delta and delta–gamma hedges in an incomplete market; particular attention is paid to the hedging error and the impact of model error on the quality of the chosen hedging strategy. The numerical analysis shows the impact of jump risk on the hedging error of the option position, and the importance of including traded options in the hedging portfolio for the reduction of this risk.     

Fuzzy Chronic Poverty: A Proposed Response to Measurement Error for Intertemporal Poverty Measurement

A number of chronic poverty measures are now empirically applied to quantify the prevalence and intensity of chronic poverty, vis‐à‐vis transient experiences, using panel data. Welfare trajectories over time are assessed in order to identify the chronically poor and distinguish them from the non‐poor, or the transiently poor, and assess the extent and intensity of intertemporal poverty. We examine the implications of measurement error in the welfare outcome for some popular discontinuous chronic poverty measures, and propose corrections to these measures that seeks to minimize the consequences of measurement error. The approach is based on a novel criterion for the identification of chronic poverty that draws on fuzzy set theory. We illustrate the empirical relevance of the approach with a panel dataset from rural Ethiopia and some simulations.