Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

Comparison of public perception and risk management decisions of aircraft noise near Taoyuan and Kaohsiung International Airports

This study uses multiple linear regression to identify factors contributing to perceived risk among residents near Taoyuan and Kaohsiung International Airports, the effect of perceived risk on their willingness to reduce risk, and consumption preferences that can reduce risk. Results indicated that residents' risk perception near Taoyuan Airport is lower than that near Kaohsiung Airport. Noise pollution experience, perceived probability of environmental contamination and negative effects, and perceived severity of catastrophic consequences significantly increase residents' perceived risks. Residents are willing to recognize and participate in mitigating the risks of aircraft noise pollution. The more risk residents perceive, the more willing they are to participate in disaster reduction and investigate means of improving the risk environment.     

The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis

In this paper, we use the quantile regression technique along with coexceedance, a contagion measure, to assess the extent to which news events contribute to contagion in the stock markets during the crisis period between 2007 and 2009. Studies have shown that, not only the subprime crisis leads to a global recession, but the effects on the global stock markets have also been significant. We track the news events, both in the UK and the US, using the global recession timeline. We observe that the news events related to ad hoc bailouts of individual banks from the UK have a contagion effect throughout the period for most of the countries under investigation. This, however, is not found to be the case for the news events originating from the US. Our findings regarding the evidence of contagion effects in the UK reinforce the argument that spreads and contagion—an outcome of the risk perception of financial markets—are solely a result of the behaviour of investors or other financial market participants.     

村级尺度耕地产能空间分异及其影响因子分析

[目的]通过探究耕地产能空间分异规律与影响因子,识别地区粮食生产关键制约因素,提升高标准基本农田建设的针对性和建设效果。[方法]采用空间自相关模型刻画了村级尺度耕地产能空间分异规律,对比分析了线性回归模型和地理加权回归模型在耕地产能影响因子识别的效果,并依此划分产能提升类型区。[结果](1)海伦市耕地产能呈现中西部高北部偏低的态势,且具有较强的空间自相关特征。(2)海伦市耕地产能与黑土层厚度、出现障碍层深度、耕作距离、田块状况和质地等变量显著相关,且均呈正相关,但在空间上表现出不同程度的异质性。(3)基于地理加权回归模型的耕地产能影响因子,提出了产能保持区、耕作条件改良区、质地改良区、障碍层改良区和保护性耕作区5类耕地产能提升类型区。[结论]文章所采用的基于村级尺度耕地产能及其空间分异因素模型相关研究,能够较好揭示村级耕地产能空间分布特点、空间自相关性特征及影响因子分布特征,基于此所划分的耕地产能提升类型区较已有研究对耕地分类管理具有更精准的支撑作用。     

Methods for Scalar‐on‐Function Regression

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorising the basic model types as linear, non‐linear and non‐parametric. We discuss publicly available software packages and illustrate some of the procedures by application to a functional magnetic resonance imaging data set.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

Impacts of seasonal patterns of climate on recurrent fluctuations in tourism demand: Evidence from Aruba

This study estimates the effect of seasonal patterns of pull and push climate elements (rainfall, temperature, wind, and cloud coverage) on recurrent fluctuations in tourism demand from the United States (USA) and Venezuela to Aruba. The seasonal patterns were first isolated from the series using the Census X-12 decomposition method, after which the analysis included panel data unit root testing, panel data regression, and Euclidean distance calculation. The results show that both pull and push seasonal factors of climate were relevant in determining the seasonal variations in tourism demand from both countries. The study derives two theoretical propositions: (1) climate is a significant push and pull factor affecting tourism demand; and (2) tourism demand and climate are bounded by intertemporal climate constraints.     

The Effect of Cross‐Border Mergers and Acquisitions on Earnings Quality: Evidence from China

Despite the fruitful research on the motives and outcomes of cross‐border mergers and acquisitions (M&As) of Chinese multinational corporations (MNCs), there has been scant research on the impact of cross‐border M&As on corporate governance. In this article, we fill the research gap by exploring whether cross‐border M&As may lead to an improvement in corporate governance of Chinese acquirers. In particular, we examine the impact of cross‐border M&As on earnings quality of Chinese MNCs. We find that the acquisition of a target firm from a developed country leads to a significant improvement on the acquirer's earnings quality. In comparison, the acquisition of a target from an emerging market does not have such an impact. Our results are robust to various corporate governance measures, alternative econometric methods, and controls of relevant firm characteristics and macroeconomic variables. Finally, we show that the effect of cross‐border M&As on earnings quality is more pronounced in non‐state‐owned enterprises (non‐SOEs) that have conducted large M&A deals. Our article offers new insight to the international business literature on latecomer perspective and liability of foreignness. © 2016 Wiley Periodicals, Inc.     

PERSONALITY TRAITS AND THE PERCEPTION OF MACROECONOMIC INDICATORS: SURVEY EVIDENCE

I examine the determinants of both perceived inflation and unemployment in one single survey and include Big Five traits in the analysis. This is the first survey on this topic in Germany. My sample consists of 1771 students from different fields and levels. Using PhD students’ estimates as a reference, I create categories for underestimation and overestimation of both variables. Multinomial logit regressions show that females overestimate both variables. Education and news consumption reduce misestimation. A higher level of Neuroticism is related with a higher probability to overestimate unemployment. Overstating (understating) one indicator is associated with overstating (understating) the other.     

Value for money in energy efficiency retrofits in Ireland: grant provider and grant recipients

The Sustainable Energy Authority of Ireland (SEAI) administers the Better Energy Homes scheme to provide a financial incentive for home owners to engage in energy efficiency retrofits. This study analyses data from the scheme and Building Energy Rating data for participants to the scheme to examine the value for money achieved by households. In addition, this research identifies which retrofit combinations provide greatest value for money, in terms of energy efficiency gains, for the grant provider. We utilize an error-in-variables approach to model the variation in benefits accruing to households of varying characteristics. We find that household and grant provider surplus can be maximized in the short term by retrofitting less energy efficient and larger homes, timber or steel frame homes and houses rather and apartments. The types of retrofits leading to the greatest surplus for both household and grant provider include cavity wall insulation paired with either a boiler with heating controls or heating controls only retrofit.