Measuring Inflation Expectations Uncertainty Using High‐Frequency Data

Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.     

Monetary Policy,Trend Inflation,and Unemployment Volatility

The literature has long agreed that the DMP model (after Diamond 1982, Mortensen 1982, Pissarides 1985) with search and matching frictions in the labor market can deliver large volatilities in labor market quantities, consistent with empirical data, only if there is at least some wage stickiness. I show, however, that the model can deliver nontrivial volatilities without wage stickiness, as long as it has price dispersion and nonzero long‐run inflation rates. I find that by keeping inflation at a positive rate, monetary policy may be accountable for the large standard deviations observed on labor market variables. In addition, the Shimer (2005) puzzle disappears under monetary policy shocks.     

Personality and older consumers’ green behaviour in the UK

The UK government has set an ambitious target of reducing greenhouse gas emissions by 80% before 2050. An interesting segment that could help to achieve this is older consumers, due to their growing numbers. There seems to be a lack of attention, in the research looking specifically at different age categories of older consumers’ green behaviour, and whether their level of greenness can be explained by their personality. Using Socioemotional Selectivity Theory and Time Perspective, the research presented here was designed to provide an exploratory analysis of how the green behaviour of older consumers is explained by their personality types. Based on the responses of 204 older consumers in the UK, our results find the openness personality trait to be positively linked to green behaviour, whilst the extraversion personality trait is negatively related to green behaviour. Although the level of green behaviour increased with older consumers’ age, this did not reach significance.     

中国货币国际化的趋势预测与人民币的范式选择

货币国际化是一个动态的历史过程。通过对其历史进程的考察,可以清晰地对未来货币国际化进程加以预测。文章认为,中国的人民币国际化进程刚刚起步,但却面临与以往世界货币迥异的道路、环境和结构,迫切需要走出一条符合中国国情的货币国际化道路。     

我国能耗监测管理现状及未来发展趋势

适应节能形势发展的新变化,能耗监测的内涵也正在逐步延伸。实践表明,建立有效的能耗监测管控体系,对于提高能效、推进节能减排作用明显。近年来我国能耗监测管理得到了不同程度的改善,但在管理理念、制度安排、技术创新、资金支持等方面还存在着较多问题。利用信息技术,建立能耗在线实时监测管理体系,将成为未来能耗监测的发展目标。适应这种发展要求,我国需要在计量设备基础管理、能耗监测考核制度、监测机构设置和人员培训、资金渠道等方面进行不断创新。     

Forecasting accuracy evaluation of tourist arrivals

This paper evaluates the use of several parametric and nonparametric forecasting techniques for predicting tourism demand in selected European countries. We find that no single model can provide the best forecasts for any of the countries in the short-, medium- and long-run. The results, which are tested for statistical significance, enable forecasters to choose the most suitable model (from those evaluated here) based on the country and horizon for forecasting tourism demand. Should a single model be of interest, then, across all selected countries and horizons the Recurrent Singular Spectrum Analysis model is found to be the most efficient based on lowest overall forecasting error. Neural Networks and ARFIMA are found to be the worst performing models.     

Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach

This paper investigates the informational efficiency hypothesis in the short and long term for four major commodity markets (oil, gas, electricity, and coal) from January 1997 to January 2016. Unlike previous studies, we provide a more concise comparative analysis by focusing on different classes of commodities for a large sample, including 5 developed and 3 emerging regions and covering 46 countries. We apply different parametric and non-parametric econometric tests. Our study provides two interesting findings. First, we show that commodity markets are informationally inefficient in the short term. Our portfolio simulations highlight that commodities might provide “good” investment opportunities, but those opportunities vary according to commodity class and regions. Second, we show that most commodity markets become informationally efficient in the long term, thereby reducing investors' interest for the duration. Thus, commodity markets might be used to hedge investor’s portfolios, particularly for speculators and chartists in the short term, while these investments might not be appealing in these markets in the long term.     

Solving the income fluctuation problem with unbounded rewards

This paper studies the income fluctuation problem without imposing bounds on utility, assets, income or consumption. We prove that the Coleman operator is a contraction mapping over the natural class of candidate consumption policies when endowed with a metric that evaluates consumption differences in terms of marginal utility. We show that this metric is complete, and that the fixed point of the operator coincides with the unique optimal policy. As a consequence, even in this unbounded setting, policy function iteration always converges to the optimal policy at a geometric rate.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.     

Time,space and accounting at Nonantola Abbey (1350–1449)

Accounting historians have provided several accounts of monastic life and accounting's role in it, considering important settings such as Montecassino and San Pietro abbeys in Italy and Durham Cathedral Priory in England. Research has shown how their governance arrangements and common values enabled the Benedictines to manage their monasteries in an efficient manner which was essential in tackling the misappropriation of resources by organisational actors, including abbots. Other studies have shed light on the use of practical and effective accounting practices by the Benedictines to manage their considerable wealth and pursue their spiritual and temporal goals. Nevertheless, this body of literature is yet to explicitly consider the dimensions of time and space and their relationship with accounting practices. This study begins to address this oversight by analysing the surviving accounting records of the Benedictine abbey of Nonantola in northern Italy from 1350 to 1449. In the accounting books of Nonantola Abbey linear and cyclical conceptions of time coexisted and had an impact on the way in which transactions were reflected in the accounts. At the same time, the abbey was at the centre of a complex network of accountabilities which included lay accountants, farmers and the lessees of the abbey's properties. The main characteristic of this system was not the accuracy of the records in detailing the assets, liabilities, expenses and revenue of the abbey but the maintenance of a control system to administer an extensive agricultural network and the identification of the relationships between the abbey and the stakeholders inhabiting its space.