Volatility of volatility is (also) rough

Using high-frequency data for major volatility indexes, we compute the volatility of volatility and show that its logarithm follows a fractional Brownian motion with Hurst parameter smaller than 1/2 thereby extending to the volatility asset class the recent findings obtained for the equity index markets. The results confirm that the volatility of volatility is a rough process and it possesses the long memory property. We also show that the correlation between the volatility and the volatility of volatility is positive, consistent with observations in the volatility option market. Lastly, a robustness check using volatility futures confirms the findings.     

Impact of distance on the arrivals,behaviours and attitudes of international tourists in Hong Kong: A longitudinal approach

This study revisits the impact of distance on international tourist behaviours in Hong Kong. This work divides and cross-validates the concept of distance into physical and cultural distance. This work also proposes an alternative cultural distance measure by introducing optimal weight amongst Hofstede's dimensions and then compares the proposed measure with the traditional Kogut and Singh's and Kandogan's measures. By using data from the Visitor Profile Report of the Hong Kong Tourism Board and the World Trade Organisation from 2002 to 2017, along with latent growth curve modelling, multivariate regression and panel data analysis, findings confirmed the significant role of physical and cultural distance. In addition, quadratic relationships are detected using cross-validation methods. The effect of physical distance on tourist demands clearly dominates that of cultural distance in the overall market. The problem of spurious correlation and the results of three cultural distance measures are also discussed.     

利用大数据分析技术的智能化网络故障诊断系统

随着网络技术的快速发展以及各种新网络业务的出现，网络的规模日益扩大和复杂。同时，各种网络服务对于网络可靠性的要求也逐渐提高，这就对网络的维护提出了更高的要求。在这种情况下，传统的网络维护模式逐渐不能适应现代网络发展的需求。针对现代大型网络的故障诊断问题，利用大数据分析技术，设计并完成了一套整体的智能化故障诊断系统。在此系统中，针对不同的故障类型，利用能够获取到的数据类型，针对性地设计了相关的故障诊断模块和算法。系统整体基于开源的数据处理平台构建，具备良好的可扩展性。通过实际案例数据的验证，结果表明此系统具备良好的处理实际网络故障的能力，将大数据分析技术应用于网络故障诊断领域也具备较强的可行性。     

Markups of Exporters and Importers: Evidence from Hungary

In this paper, we study the relationship between different proxies of firm‐level markups and trade status, using balance sheet information linked to detailed trade data from Hungary between 1995 and 2003. We find that importing is strongly positively correlated with markup measures, both across and within firms. We argue that this correlation can reflect three channels: self‐selection, higher physical productivity resulting from access to a larger variety of inputs, and quality upgrading based on high‐quality imported intermediate inputs. We present evidence for the relevance of the third channel by showing that importers’ markup premium is higher when inputs arrive from developed countries, and that importing is correlated with higher‐quality (price‐adjusted revenue) exports. We find no robust evidence for exporter premium when controlling for importing. We argue that the non‐existent exporter premium might result from the stronger competition in export markets relative to domestic markets.     

Big data hedonic pricing: Econometric insights into room rates’ determinants by hotel category

This research uses a big dataset of online prices published on Booking.com by three-, four- and five-star hotels located in Madrid (Spain). Data is broadened by other sources, resulting in a rich set of context-, hotel- and offer-based variables. This research aims to determine the impact of these variables on the online room prices set by one representative sample, featuring the total pricing behaviour as well as per hotel categories. The variables considered, their extent and the insight per category represent a novelty and complement the literature on demand forecasting and hedonic pricing, enabling the improvement of optimisation techniques. The models, based on regression analysis with random effects, reveal a significant impact of the variables on room prices and a clearly distinct behaviour for five-star hotels. This research contributes to the scientific community and practitioners by showing the pricing dynamics behaviour of an important urban destination by star rating.     

耕地质量监测预警研究进展

耕地质量是人类社会赖以生存与发展的物质基础,是农业发展的基本生产资料。为发挥监测预警体系在耕地质量建设中的主体作用,实现耕地质量的可持续利用,本文采用文献综述法和系统分析法综述了耕地质量监测和预警体系在国内外的研究进展,并着重对时间序列分析模型、灰色预测模型和回归分析模型三种耕地质量预警模型进行阐述。耕地质量监测预警体系具有实时、动态、全方位的监测与预警功能,对监测预警指标体系、方法、周期、模型和理论实践探究还需要进一步完善,同时还需要借助应用大数据,以期为耕地质量精准化监测预警提供实时的数据及模型支持服务。     

Spatial wage disparities: Sorting matters!

Spatial wage disparities can result from spatial differences in the skill composition of the workforce, in non-human endowments, and in local interactions. To distinguish between these explanations, we estimate a model of wage determination across local labour markets using a very large panel of French workers. We control for worker characteristics, worker fixed effects, industry fixed effects, and the characteristics of the local labour market. Our findings suggest that individual skills account for a large fraction of existing spatial wage disparities with strong evidence of spatial sorting by skills. Interaction effects are mostly driven by the local density of employment. Not controlling for worker heterogeneity leads to very biased estimates of interaction effects. Endowments only appear to play a small role.     

State dependence in youth labor market experiences, and the evaluation of policy interventions

We investigate the extent and type of state dependence in labor market outcomes for young low-skilled Australians. Our model allows for three labor force states, employment, unemployment and out of the labor force, and for observed and unobserved heterogeneity. We find evidence of occurrence dependence, but no lagged duration dependence. A past employment spell increases the probability of employment in the future, but the length of the spell does not matter. A past spell of unemployment undoes the positive benefits from a spell in employment. Interpretations of these effects and implications for labor market policies are discussed.     

Pooling data for the analysis of dynamic marketing systems

Vector autoregressive (VAR) models have become popular in marketing literature for analyzing the behavior of competitive marketing systems. One drawback of these models is that the number of parameters can become very large, potentially leading to estimation problems. Pooling data for multiple cross-sectional units (stores) can partly alleviate these problems. An important issue in such models is how heterogeneity among cross-sectional units is accounted for. We investigate the performance of several pooling approaches that accommodate different levels of cross-sectional heterogeneity in a simulation study and in an empirical application. Our results show that the random coefficients modeling approach is an overall good choice when the estimated VAR model is used for out-of-sample forecasting only. When the estimated model is used to compute Impulse Response Functions, we conclude that one should select a modeling approach that matches the level of heterogeneity in the data.