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We employed a non-parametric causality test based on Singular Spectrum Analysis (SSA) and used the Vector Error Correction Model (VECM) and Information Share Model (IS) to measure the relationship between the futures and spot prices for seven major agricultural commodities in China from 2009 to 2017. We found that the agricultural futures market has potential leading information in price discovery. The results of an Impulse Response Function (IRF) analysis also showed that the spot prices react to shocks from the future market and have a lasting impact. This confirms our findings reported for the causality test and information share analysis. [ABSTRACT FROM AUTHOR]

This study investigates the valuation usefulness of fair values and related information disclosure in China and examines how regional‐level market institutions influence the valuation usefulness of fair value information. Based on a sample of Chinese listed companies during 2007 to 2016, the empirical results show a negative association between overall fair values and analyst forecast accuracy. Further analyses suggest that the negative association is likely driven by biases and/or errors in fair value estimates. Using a difference‐in‐difference research design, the study also documents that the implementation of ASBE 39 in 2014 has improved the valuation usefulness of fair values. There is evidence that different aspects of market institutions—including the extent of government intervention in the market and the legal environment—influence analysts' use of fair value information. This study contributes to the literature by providing new and different evidence on the usefulness of fair values to financial analysts outside developed countries. Moreover, by taking advantage of the uneven institutional development across China, the study shows that different aspects of market institutions influence the valuation usefulness of fair value information. [ABSTRACT FROM AUTHOR]

This study introduces the Ensemble Empirical Mode Decomposition (EEMD) technique to forecasting popular vote shares in general elections. The technique is useful when using polling data. Our main interest in this study is shorter- and longer-term forecasting and, thus, we consider from the shortest forecast horizon of 1-day to three months ahead. The EEMD technique is used to decompose the election data for the two most recent US presidential elections; 2016 and 2020. Three models, Support Vector Machine (SVM), Neural Network (NN) and ARIMA models are then used to predict the decomposition components. Subsequently, the final hybrid model is constructed by comparing the prediction performance of the decomposition components. The predicting performance of the combination model is compared with the benchmark individual models: SVM, NN, and ARIMA. Finally, this is also compared to the single prediction market IOWA Electronic Markets. The results indicate that the prediction performance of combined EEMD model is better than that of the individual models. [ABSTRACT FROM AUTHOR]

A study uses data from the British Household Panel Survey (BHPS) to investigate the accuracy and usefulness of household subjective forecasts of personal finance. The study evaluates the intended criteria at the household level using the methods of , which are then extended to be applied to the household panel or longitudinal survey.

Most countries use either the Dutot or Jevons index number formula for the compilation of their consumer price index at the elementary level of aggregation. The difference between the formulas is shown to be accounted for by changes in price dispersion. In turn, some of this difference is shown to be explained by product heterogeneity. Scanner data on television sets (TVs) are used to calculate Dutot and Jevons indexes. The difference between them is successfully explained in terms of changes in price dispersion and much reduced using an hedonic, heterogeneity-controlled Dutot index. Keywords: Consumer price index; Elementary aggregate indexes; Hedonic regression; Index numbers; Relative price dispersion; Scanner data

This paper investigates how well survey data depicting consumer sentiment forecasts household's consumption behavior for the UK. We consider whether consumer sentiment is able to predict the growth of household's consumption, in addition to the growth of labor income. The empirical analysis finds that Consumer Confidence Indices (CCI) does predict the household's consumption of durable goods. We also draw comparisons with recent analysis for the US. In addition, we analyze whether both the UK and US CCI are accurate and useful predictors of household's consumption growth using directional analysis. We find that the UK confidence indicators predict better the US. JEL classification: C14; C22; C53; E21; E27 Keywords: Consumer sentiment; Forecastability; Household consumption behavior; Instrumental variables, Directional analysis

The purpose of this note is to consider the effect of perception noise when voters form public opinions. We provide a simple theoretical framework that will form the basis to investigate empirically the effect of news uncertainty on voters' attentiveness when forming public opinion, or nowcasts. An attentive voter will consistently update their information set. Therefore, if voters' nowcasts are consistent, any revision of the nowcasts must only reflect new information. We specifically consider how news uncertainty may affect voter attentiveness. The paper focuses on US presidential competence and popularity indices. We find that the nowcasts are consistent during periods of low news uncertainty but highly persistent when news uncertainty is high. [ABSTRACT FROM AUTHOR]

The purpose of the present paper is to investigate forecasted inflation gap persistence using professionals' survey‐based data, differentiating between financial and nonfinancial sectors professionals. We derive the forecasted inflation gap persistence, and using a state‐dependent model, we estimate the nonlinear persistence coefficient of the inflation gap. We distinguish between the pre‐Great Moderation, Great Moderation, and Great Recession periods. Our main results indicate that although the estimates of persistence for gross domestic product inflation largely confirm the results obtained using a linear model, for consumer price index inflation, we find that there is strong evidence for state dependence and time variation. By and large, the results are consistent with the price stability policy pursued in the Great Moderation period and perceived disinflationary pressures during the Great Recession period. [ABSTRACT FROM AUTHOR]

Byline: Gheorghita Ghinea, Johnson P. Thomas, George D. Magoulas, Saeed Heravi The vision of a new generation of network communication architectures, which deliver a Quality of Service based on intelligent decisions about the interactions that typically take place in a multimedia scenario, encourages researchers to look at novel ways of matching user-level requirements with parameters characterising underlying network performance. In this paper, we suggest an integrated architecture that makes use of the objective-technical information provided by the designer and the Quality of Perception metric for intelligent decision making in the construction of user-centred adaptable communication protocols. This approach, based on the Analytic Hierarchy Process, incorporates not only classical Quality of Service considerations, but indeed, user preferences as well, and opens the possibility for the suggested protocols to dynamically adapt based on a changing operating environment. Results show that the proposed approach does provide an enhanced user multimedia experience when compared with legacy communication protocols.