Impact of an urban growth boundary across the entire house price spectrum: The two-stage quantile spatial regression approach

This study provides evidence for the impact of an urban growth boundary (UGB) on house prices. The study employs a two-stage quantile spatial regression method on a dataset that inventories sales transactions of single-family houses within two miles of either side of the eastern boundary of the primary UGB in King County, Washington. The results show that while the UGB decreases house prices across the entire house price spectrum, the impact is uneven; it is most pronounced for houses in the 5th to 8th decile of prices. These findings should encourage policy makers to adopt sub-housing-market-level policy approaches to address UGB and other urban and regional development policies’ potential impacts on house prices.     

Combining wavelet decomposition with machine learning to forecast gold returns

This paper combines the discrete wavelet transform with support vector regression for forecasting gold-price dynamics. The advantages of this approach are investigated using a relatively small set of economic and financial predictors. I measure model performance by differentiating between a statistically-motivated out-of-sample forecasting exercise and an economically-motivated trading strategy. Disentangling the predictors with respect to their time and frequency domains leads to improved forecasting performance. The results are robust compared to alternative forecasting approaches. My findings on the relative importances of such wavelet decompositions suggest that the influences of short-term and long-term trends are not stable over the full evaluation period.     

Going abroad to play: Motivations,challenges, and support of sports expatriates

Professional athletes moving abroad for their career is a novel phenomenon in international human resource management (IHRM). This exploratory article charts the motivations of sports expatriates to move abroad to play, as well as adjustment challenges and sources of support. A survey was conducted with 77 professional athletes in 10 different sports. The main motivations to move abroad were interest to experience life abroad, followed by the search for new challenges. In terms of challenges, different coaching style and communication issues were most often mentioned. Support was mainly informal, through team mates rather than professional providers. Our article contributes to the literature because it is one of the first studies focusing on sports expatriates from an international HR perspective. Our study provides information on a vulnerable group of expatriates; they are young in age and under extreme performance pressure. Sports expatriates need all the support they can get, and yet, little professional support is offered.     

Secrets to design an effective message on Facebook: an application to a touristic destination based on big data analysis

The objective of this research is to identify which are the key variables for designing a message in a social network that can be used by an advertiser to generate Positive/Negative Engagement. The message’s design variables have been classified into four main groups: (i) Message Tools (presence of text, images, video, labels, applications, interactive games and events calendar or others), (ii) Appropriate Message Structure (length and intelligibility), (iii) Informative Cues (links to the brand, orientation towards the product or the brand, topics relevant to the audience, and a remuneration’s promise) and (iv) Persuasive and Emotional Cues (emotional signals, valence, endorsement and influencer mentions). The focus has been a tourist destination: Brand Spain that is advertised through Facebook. A content analysis was carried out and regression analysis with optimal scaling was used on 180 Spain brand’s publications; 57,626 audience reactions to such publications; and 1361 audience comments on the Brand Spain Official Fan Page. According to our results, from the four blocks of predictive variables, only two of them are useful to predict Positive/Negative Engagement: (i) the use of Message Tools (videos), and (ii) the use of informative cues (relevant topics, links on posts, and post’s orientation towards product).     

The empowerment expectation–perception gap: An examination of three alternative models

Previous empowerment research has focused on subordinate perceptions of empowering leadership and its outcomes. Met‐expectations theory suggests that subordinate expectations of leader behaviours are essential in forming their a posteriori evaluations. To address the lack of investigation of individual expectations in the empowerment literature, in this study, we explore how subordinates' empowerment expectations and perceptions combine to influence their job satisfaction and psychological empowerment based on three alternative, theoretically derived met‐expectation models, namely, the disconfirmation model, the ideal‐point model, and the experiences‐only model. The results of a 2‐stage study of 114 respondents indicate that employees are more satisfied with their work when perceived empowerment exceeds expectations. However, both empowerment perceptions and expectations positively contribute to higher psychological empowerment. We then discuss implications and directions for future research.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

The impact of conservation tillage on maize yield and input demand: the case of smallholder farmers in north‐west Ethiopia

This study analyses the economics of conservation tillage (CT) with respect to its effect on maize yield and chemical fertiliser, herbicide, and female and male labour demand. We estimate production and input demand functions using seemingly unrelated regressions on plot‐level cross‐sectional farm household data collected in the north‐west of Ethiopia. A two‐step control function is applied to address potential endogeneity bias due to the inclusion of the CT adoption decision as an explanatory variable. Our results show that CT increases maize yield and chemical fertiliser demand. Additionally, the results show that the adoption of CT reduces female and male labour required for crop production. However, this is achieved through the increased use of herbicides, which might have an undesirable health and environmental effects.     

Trade-threshold Effect on Inflation in Tunisia: New Evidence Resulting from a Nonlinear Approach

Trade openness is an important determinant of the inflation process. The effect of trade openness on inflation, however, is still an issue of debate at both theoretical and empirical levels. This study tried to provide a contribution to the literature by examining the relationship between inflation and trade openness in Tunisia over the period 1975Q1-2015Q4 using a nonlinear model. The originality of this study stems from the fact that it is the first investigation considering both the Residual-Based Tests for Cointegration in Models with the Regime Shifts and Threshold Regression model. The linear model confirms the existence of a positive relationship between inflation and trade in Tunisia. Yet, considering the nonlinear model, trade openness growth and Consumer Price Index (CPI) inflation growth show a statistically significant negative link as long as the trade openness evolution does not exceed the threshold. Nevertheless, if the trade openness growth is higher than the threshold, integrating the trade positively affects CPI inflation. Furthermore, a positive influence of Money supply growth on this type of inflation was noticed in Tunisia in all the considered regimes proving the effect of monetary factors on inflation level. Consequently, trade openness could be used to control inflation in Tunisia.     

Why We Should Change Our Attitude Towards Distressed Firms

This article surveys ‘creditor‐friendly’ and ‘enterprise‐friendly’ bankruptcy regimes with a focus on the methodology underlying the filter test in distress, as reflected both in its academic treatment and in legal practice. I find that the test exhibits pro‐liquidation bias in designating liquidation of a firm with recovery potential as the Type II error, and in underplaying the benefits of a possible turnaround. Further influences militating against continuation include the power conferred on creditors through the balance sheet criterion and the undervaluation of intangible assets. I make the case for reversing such biases to establish a presumption in favour of continuation.     

“双低一代”的社会经济特征研究

由于即将退休与刚退休的这一代人拥有低赡养比与低抚养比，本文称其为“双低一代”。本文基于宏观统计数据与微观调查数据，利用分位回归等方法对“双低一代”的社会学特征与经济学特征进行研究，发现其具有人口总量较多、教育背景优良、社会阅历丰富、消费倾向明显等特征。此外，通过对“双低一代”的人力资本存量进行测算，提出充分发挥“双低一代”余热、缓解老龄化问题的政策建议。