数字经济发展促进我国产业结构升级的机理与路径

通过数字经济发展来推动产业结构升级已经成为我国经济发展的重要战略。数字经济发展可以为产业结构升级提供技术创新、产品创新、商业应用模式创新、产业融合创新及需求侧结构创新等支持。然而,当前我国区域经济发展不平衡、数字技术的依赖效应、数字经济的垄断性、企业创新动力不足、复合型数字技术人才供给不足及数字化公共服务体系缺失等因素降低了数字经济推动产业结构升级的作用。基于此,我国应从完善数字经济治理体系,加强平台反垄断,加大需求侧改革,加强数字技术人才培养,加快数字经济与三次产业融合等方面提升数字经济对产业结构升级的促进作用。     

论转型期我国煤炭企业产业链的整合与分化

煤炭企业的发展不仅受其本身的资源与能力的影响,还与其所在产业链的上下游企业的协作有关。煤炭企业应利用战略转型的时机,合理规划产业链的整合与分化,以谋求基于产业链效率的竞争优势。     

Examining dynamic currency linkages amongst South Asian economies: An empirical study

In this paper, we examine the currency market linkages of South Asian member countries using daily data from 6 January 2004 to 31st March 2016. Time invariant and varying Copula GARCH models show that South Asian countries, except for India and Nepal/Bhutan, have low levels of currency market linkages which can be ascribed to poor levels of intra-regional trade intensity and portfolio flows. We reconfirm the copula results through Diebold and Yilmaz methodology and document that currency market connectedness is very limited in the South Asian region. The trends of the fundamental determinants of currency co-movements for the South Asian member countries were compared with its neighbouring regional economic bloc in Asia which has a much longer history and a wider membership base i.e ASEAN + 6. From a comparative analysis, it was found that South Asia member states have to work on their governance parameters, improve on their trade linkages and trade tariffs and work towards greater degree of capital account convertibility with adequate safeguards to achieve higher levels of currency market linkages.     

Central banks and macroeconomic policy choices: Relaxing the trilemma

Macroeconomic policy choices in open economies are constrained by the trilemma according to which the objectives of exchange rate stability, monetary independence and capital mobility cannot be attained jointly. This paper shows that foreign exchange interventions provide an effective instrument to relax the trilemma. An active reserve policy allows central banks to pursue independent monetary and exchange rate policies when the capital account is liberalised.We use the framework of the portfolio balance model to show that exchange market interventions may substitute for capital controls. Both allow a country to achieve the other two objectives of the trilemma. Our empirical analysis of a large country panel data set covering the period 1970–2010 confirms this theoretical insight: the weighted sum of the three trilemma objectives increases in the degree of foreign exchange market intervention. The capacity to relax the trilemma constraint has increased over time and has been most effective in emerging markets.     

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.     

An Exploratory Study on Nonlinear Causality Among the MILA Markets

According to conventional portfolio theory, an increase in the interconnectedness of international financial markets may reduce the potential for constructing diversified portfolios. This article explores the implications of the creation of the Latin American Integrated Market (MILA)¹ over the dependence structure of its members using correlation and cointegration analysis as well as linear and nonlinear Granger causality tests. The creation of MILA aimed to enhance the integration process that Latin American financial markets “naturally” present while still providing diversification opportunities to investors. The results of our empirical analysis suggest that such objective is being achieved. Evidence of a rise in cross-country linear correlations and their linear causal relationship supports the idea of an increasing financial integration process in the region, while the absence of cointegration and the weakening of the nonlinear causal relationship favors the creation of diversified regional portfolios. These findings provide valuable insights for investment portfolio designers, regulators, and supervisors.     

中国区域一体化协议发展的特点与战略研究

大国的经济外交时代已然到来，而外商直接投资在中国实现工业化和经济发展的过程中起着至关重要的作用。因此，应从中国自身的区域一体化协议的发展特点出发，将外商直接投资因素包含到制定区域经济一体化的战略过程中去，在此基础上研究并制定适合中国的区域一体化协议发展战略，主要是：有选择地开展与发达国家的区域一体化谈判，加强与西亚地区的区域经济合作和在区域一体化协议中重点突出服务业投资自由化。     

DEFINING AND OPERATIONALIZING SUPPLY CHAIN PROCESS INTEGRATION

Integration has been recognized as critical to successful supply chain management. However, an extensive literature review revealed no consensus in its conceptualization. The current study attempts to address this research gap by providing a better definition and operationalization of supply chain process integration. With empirical support, it is proposed that internal and external supply chain process integration should be treated as two separate constructs, each comprised of two dimensions: connectivity and simplification.     

Does retail type matter? Consumer responses to channel integration in omni-channel retailing

A critical issue faced by marketing practitioners today is orchestrating strategies that provide a smooth consumer experience in an omni-channel environment. The extant literature offers limited guidance on managing the consumer journey in an omni-channel environment across different retail types. Using the S–O-R framework as its basis, this study generates novel insights by examining how different types of retailers influence consumer perceptions of channel integration (CPCI) as well as consumer empowerment, trust, satisfaction, and patronage intention. Data from 736 consumers was collected using purposive sampling to target those who interact with retailers from high-end specialty stores, department stores, and hypermarkets. The data was then analysed using partial least squares structural equation modelling (PLS-SEM). We find that consumers from high-end specialty stores, hypermarkets, and department stores have different perceptions when patronising the omni-channel retail business. The implications of the study are discussed and suggestions for future research are presented.     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.