A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Evolution of indigenous tourism among the Lacandon of Chiapas: an application of Weaver’s model

ABSTRACT

In this paper, Weaver’s six-stage indigenous tourism model is applied to the Lacandon Maya (Hach Winik) of Chiapas, Mexico. Based on a comprehensive review of the anthropological and historical literature on this indigenous group, combined with longitudinal ethnographic and collaborative research performed with tourism entrepreneurs, the Lacandon tourism experience is assessed from the pre-European period until present. By analysing a case study of indigenous tourism in Mexico, a developing country in another geographical region and with a different colonial past, this work supplements Weavers’ perspective. The results show that the fourth and fifth stages of Weaver’s model coincide in this case study, while the sixth stage is still incomplete. Although the Lacandon case has its peculiarities and bearing in mind that several different factors should be considered in the Latin American context, the model proves to be an interesting tool for indigenous tourism analysis in developing countries.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.     

Reconciling Alternative Theories for the Safety of Owner–Operators

Motor carrier safety is an important concern of shippers, carriers, policy makers, consignees, insurance providers, and the motoring public. One aspect of carrier safety that has garnered substantial attention is whether carriers making greater use of owner–operators are more or less safe vis‐à‐vis carriers making greater use of employee drivers. Currently, conflicting theoretical predictions exist regarding the direction of this relationship. In this article, we offer a reconciliation of the alternative theoretical predictions by developing a coherent theory that merges sociological rational choice theory and theory regarding motor carrier safety. We subject our theory to empirical testing by fitting a series of seemingly unrelated regression models to a vector of safety measures tracked as part of the Federal Motor Carrier Safety Administration's Compliance, Safety, and Accountability program. Our results are consistent with our proposed theory of owner—operator safety and provide meaningful theoretical and managerial implications and directions for future research.     

The sweet smell of advertising: the essence of matching scents with other ad cues

New technologies enable practitioners to communicate scents in advertisements on various media. The current research examines the importance of matching scent cues to the advertised product, and the joint effect of scent and other cues such as colour on consumer responses to advertising. A 4 × 2 experimental design was conducted, where participants (N = 603) were presented with scented colour print advertisements. Three hierarchical responses were measured: emotional response, attitude, and purchase intention. Findings reveal that higher congruence between scent and the advertised product heightens positive consumer response. Furthermore, this research stresses the significant joint effect of scent and colour cues, and supports the incongruence approach, suggesting that combining scents that are poorly congruent with other sensory cues enhance consumer response. Practical and theoretical implications are discussed.     

ECONOMIC TRANSITION AND LABOUR MARKET DYNAMICS IN CHINA: AN INTERPRETATIVE SURVEY OF THE ‘TURNING POINT’ DEBATE

Has the Chinese economy approached the ‘Lewisian turning point’ that marks the ending of the initial phase of industrial transformation fuelled by surplus labour? In this paper we undertake an interpretative survey of the literature on this issue, in the context of China's labour market conditions prior to the reforms and structural change of the past three decades. The available evidence is mixed, and our assessment makes a strong case for probing institutional constraints to labour mobility from an economy‐wide perspective, going beyond the confines of the rural economy.     

Labor market analysis through transformations and robust multivariate models

The work presents a robust approach to labor share analysis. The estimate of labor share presents various complexities related to the nature of the data sets to be analyzed. Typically, labor share is evaluated by using discriminant analysis and linear or generalized linear models, that do not take into account the presence of possible outliers. Moreover, the variables to be considered are often characterized by a high dimensional structure. The proposed approach has the objective of improving the estimation of the model using robust multivariate regression techniques and data transformation.     

Exploring the Intensive and Extensive Margins of World Trade

World trade evolves at two margins. Where a bilateral trading relationship already exists it may increase through time (intensive margin). But trade may also increase if a trading bilateral relationship is newly established between countries that have not traded with each other in the past (extensive margin). We provide an empirical dissection of post–World War II growth in manufacturing world trade along these two margins. We propose a “corner-solutions version” of the gravity model to explain movements on both margins. A Tobit estimation of this model resolves the so-called “distance puzzle”. It also finds more convincing evidence than recent literature that WTO-membership enhances trade. JEL no. F12, F15     

如何计算认股权证的资本成本

认股权证作为一种长期资金的筹资方式 ,其资本成本必须予以考虑。但是使用传统资本成本计算方法不能反映其真实成本。本文尝试使用B -S和CAPM模型来计算其资本成本 ,并用实例说明