Financial Statement Comparability and Idiosyncratic Return Volatility

This study examines the association between financial statement comparability and idiosyncratic return volatility (IRV). A greater degree of comparability lowers information acquisition costs, reduces the uncertainties associated with performance evaluation, and increases the overall quantity and quality of information available to corporate outsiders, which, in turn, helps investors to understand and evaluate the cash flow and performance of firms more accurately. Therefore, we hypothesize a negative association between financial statement comparability and IRV. Using a large US sample from 1981 to 2013, we show that financial statement comparability is associated with lower level of IRV significantly. We also find this association to be more pronounced in a poor information environment. This study contributes to the emerging research that stresses the benefits of financial statement comparability.     

GOVERNMENT BOND YIELDS AT THE EFFECTIVE LOWER BOUND: INTERNATIONAL EVIDENCE

Empirical evidence on the potential impact of central bank policies on government bond yields at the effective lower bound (ELB) is presented for nine economies. We quantify the content of central bank communications and consider international policy spillovers. Yields at the medium‐to‐longer end of the yield curve remain responsive to news for a few years after the ELB is reached. Yields become more sensitive to the content central bank communication at the ELB. Our results provide further evidence that central bank communication is an important element of monetary policy making when the interest rate tool loses efficacy. (JEL E52, E58, G12, F42)     

Optimal annuitisation in a deterministic financial environment

Decisions in Economics and Finance - The global reforms to public pension schemes over the last thirty years have progressively reduced individuals’ post-retirement social security income. In...     

Metal prices made in China? A network analysis of industrial metal futures

In addition to being the world's greatest consumer and producer of industrial metals, China now also features the most actively traded industrial metal futures contracts worldwide. To examine China's role in the global price formation process of industrial metal futures markets, we use a sample of 29 futures contracts traded on exchanges in the United States, the United Kingdom, India, and China. We estimate vector autoregressive models and conduct variance decompositions, which are then visualized in the form of networks. The results indicate that China, despite its role as key actor in both real and financial industrial metal markets, is a price taker.     

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.     

Global migration in the twentieth and twenty-first centuries: the unstoppable force of demography

Review of World Economics - This paper sheds light on the global migration patterns of the past 40 years, and produces migration projections for the 21st century. To do this, we build a simple...     

Policy impact assessment in developing countries using Social Accounting Matrices: The Kenya SAM 2014

This paper describes the structure and estimation of a Social Accounting Matrix (SAM) of Kenya for the year 2014. Among its specificities, this SAM includes a very high disaggregation of the agri‐food sector and accounts for the double role of households as producers and consumers. Accounting for these characteristics is crucial to provide robust socioeconomic analysis in the context of developing countries. Indeed, this type of database is valuable to perform ex‐ante evaluations of economic policies with various economic models and techniques. In this paper, we present an application with a linear multiplier analysis (backward linkages and value chain decomposition). The results show the capacity of the primary sector in Kenya to generate value added and employment, with this growth distributed more intensely in rural households whose main livelihood is semi‐subsistence agriculture.     

Economic Complexity and Inflation: An Empirical Analysis

Atlantic Economic Journal - This study examines the relationship between inflation and economic complexity, the set of productive capabilities and know-how embedded in the structure of an economy....     

Disclosure quality vis-à-vis disclosure quantity: Does audit committee matter in Omani financial institutions?

Review of Quantitative Finance and Accounting - We examine the impact of audit committee (AC) characteristics (e.g. AC foreign members, AC female members, AC members with multiple directorships, AC...