Measuring the Connectedness of the Global Economy

We develop a technique to exploit forecast error variance decompositions to evaluate the macroeconomic connectedness embedded in any multi-country macroeconomic model with an approximate vector autoregressive (VAR) representation. We apply our technique to a large global VAR model covering 25 countries and derive vivid representations of macroeconomic connectedness. We find that the US exerts a dominant influence in the global economy and that Brazil, China, and the Eurozone are also globally significant. Recursive analysis over the period of the global financial crisis shows that shocks to global equity markets are transmitted rapidly and forcefully to real trade flows and real GDP.     

The seasonality of gold prices in China does the risk-aversion level matter?

This article aims to investigate the seasonality of gold prices at the Shanghai Gold Exchange over the 2002–2016 period. Our contributions rely in the distinction between risk-averse and risk-seeking investors regarding their investment strategies. The results show the existence of positive Monday and January effects. However, the Monday effect is more suitable to risk-seeking investors while the January effect is more suitable to risk-averse investors in bearish periods only. A robustness check shows that the Monday effect does not hold on gold futures prices. These results indicate the importance to consider the risk-aversion level of investors in seasonal investment strategies.     

Economic Loss Due to Reputation Damage: A New Model and Its Application to Fukushima Peaches

Consumers have responded negatively to agricultural products originating from the Fukushima prefecture after the 2011 Fukushima Daiichi nuclear power plant incident. These consumers’ behavioural changes have caused substantial economic losses for the producers located in contaminated regions through reductions in market prices, consumption quantities and market shares. Remarkably, these losses are observed also for uncontaminated products, posing an opportunity for research in reputation damage. However, existing literature is very rare on empirical modeling of such losses. We utilise the Dixit–Stiglitz demand framework to derive a simple but efficient empirical model that uses market data to quantify reputation damage. This model estimates changes in the perceived quality of a product originating in contaminated regions in relation to those products originating from other competing regions. The model also measures subsequent loss in market share for those products grown in contaminated regions. In our application to Fukushima, results suggest that consumers’ valuation of peaches from Fukushima decreased dramatically (between 22.5% and 23.6%) in the year the nuclear accident occurred, but rapidly recovered in the following years. The results also show that the degree of impact varies across wholesale markets. Fukushima farmers lost about 13.1–18.9% of sales due to reputation damage. Estimates from our proposed models deliver meaningful information in the context of policy interventions such as transfer programmes financed by gainers to compensate reputation losses.     

Human resource management systems,employee well-being,and firm performance from the mutual gains and critical perspectives: The well-being paradox

In this study, we explored the additive, interactive, and nonlinear relationships among human resource management (HRM) systems, employee well-being, and firm performance. Based on a sample of 14,384 employees nested within 1,347 firms, we obtained three main findings. First, HRM systems yield a performance effect that exceeds the effect of single practice, suggesting positive synergies among HRM practices. Second, the opportunity bundle has a positive impact on firm performance, but when integrating it with skills and motivation bundles, the result becomes negative, indicating dis-synergy of interactions among HRM bundles. Third, at moderate levels of adoption, HRM practices are positively correlated with employee well-being and higher levels of commitment, job satisfaction, and management relations, as well as lower levels of anxiety. However, at high levels, the relationship is less positive and even turns negative with lower levels of job satisfaction and management relations. To close, we present research implications and future directions after discussing our results.     

Algorithmic trading in a microstructural limit order book model

We propose a microstructural modeling framework for studying optimal market-making policies in a FIFO (first in first out) limit order book (order book). In this context, the limit orders, market orders, and cancel orders arrivals in the order book are modeled as point processes with intensities that only depend on the state of the order book. These are high-dimensional models which are realistic from a micro-structure point of view and have been recently developed in the literature. In this context, we consider a market maker who stands ready to buy and sell stock on a regular and continuous basis at a publicly quoted price, and identifies the strategies that maximize their P&L penalized by their inventory. An extension of the methodology is proposed to solve market-making problems where the orders arrivals are modeled using Hawkes processes with exponential kernel.

We apply the theory of Markov Decision Processes and dynamic programming method to characterize analytically the solutions to our optimal market-making problem. The second part of the paper deals with the numerical aspect of the high-dimensional trading problem. We use a control randomization method combined with quantization method to compute the optimal strategies. Several computational tests are performed on simulated data to illustrate the efficiency of the computed optimal strategy. In particular, we simulated an order book with constant/ symmetric/ asymmetrical/ state dependent intensities, and compared the computed optimal strategy with naive strategies. Some codes are available on https://github.com/comeh.     

Trade configurations in Asia: Assessing de facto and de jure regionalism

Given the backdrop of significant uncertainties largely propelled by the ongoing trade spat between the United States and China, to what degree can the Asian region move forward in terms of de facto trade integration? Drawing on the new economic geography literature, this paper offers new insights into the literature on trade regionalism in Asia by empirically illustrating how Asian economies can tap into the regional market potential. Specifically, the paper examines the scope for further de facto integration among the Asian countries engaged in the negotiation for the Regional Comprehensive Economic Partnership (RCEP) Agreement by estimating foreign market potential (FMP) indices. To preview the main findings, the empirical analysis demonstrates that the share of intra-regional trade in total RCEP trade flows and, consequently, the ratio between within- and outside-RCEP trades are significantly lower than what they could potentially be. The paper makes a case that the enhancement of de jure integration among these economies through the RCEP must be accompanied by efforts to improve de facto integration.     

Developing service climate in local vs. foreign firms in smaller Asian emerging markets: a resource-based and social exchange perspective

While research on drivers of service climate has focused on organisational resources and human resource practices such as training, employee autonomy and inter-departmental support, how these resources interrelate and influence service climate has not been examined, especially in the context of smaller Asian emerging market. Drawing on the resource-based view and its extension on dynamic capability, and social exchange theory, this qualitative study investigates how local and foreign firms in smaller Asian emerging markets create a favourable service climate. Our findings suggest three inter-related groups of factors that influence service climate, namely firm-based, market-based and culture-based drivers. Notably, foreign service firms perform better than their local counterparts in several firm-based drivers (e.g. service-oriented human resource management practices, work facilitation resources). Our study proposes a conceptual framework that integrates inter-relationships of organisational resource-based factors and explains how internal and external factors drive service climate in firms in smaller Asian emerging markets.     

Responding to the global financial crisis: Vietnamese exchange rate policy, 2008–2009

The paper presents an analysis of exchange rate policy in Vietnam during 2008–2009. In early 2008, the country faced a sudden reversal of capital flows as signs of developing domestic vulnerabilities became evident. The downward pressure on the dong then intensified with the onset of the global financial crisis in the fall. In these environments, the Vietnamese authorities responded with various exchange rate policy measures. The paper documents a shift in Vietnam's de facto exchange rate regime, from a basket peg to a simple US dollar peg, when the domestic vulnerabilities became compounded by the evolving global crisis. The authorities utilized additional measures to relieve pressure on the parallel exchange rate. An event study methodology finds little evidence of systematic effectiveness for these policy actions; any effectiveness was short-lived. A close examination of individual actions suggests that the impact of foreign exchange market intervention appeared more consistent than any other type of measure and most effective when combined with other measures.     

Incorporating Both Positive and Negative Association Rules into the Analysis of Outbound Tourism in Hong Kong

This article presents a novel approach to data mining that incorporates both positive and negative association rules into the analysis of outbound travelers. Using datasets collected from three large-scale domestic tourism surveys on Hong Kong residents' outbound pleasure travel, different sets of targeted rules were generated to provide promising information that will allow practitioners and policy makers to better understand the important relationship between condition attributes and target attributes. This article will be of interest to readers who want to understand methods for integrating the latest data mining techniques into tourism research. It will also be of use to marketing managers in destinations to better formulate strategies for receiving outbound travelers from Hong Kong, and possibly elsewhere.