A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.     

Resource Dependence and Network Relations: A Test of Venture Capital Investment Termination in China

This study examines how venture capital (VC) firms terminate investments in an emerging economy context. We contend that due to the weak institutional environment, it is appropriate to draw on insights from power and social relation perspectives for a better understanding of the phenomenon. Specifically, we argue that a termination decision hinges on not only the dependence relationship between a VC firm and its portfolio companies, but also the social relationships among VC firms. Event history analyses of approximately 12,000 VC deals made in China between 2001 and 2012 reveal that when a VC firm has a greater number of investments in an industry, it is more likely to terminate investments on a portfolio company in that industry. Moreover, such effect on termination is moderated by the focal VC's embeddedness with its syndicate partners and collaboration opportunities with other VC firms outside the immediate access of the syndicate partners. Our study sheds light on research on VC decision making in emerging markets by integrating insights from resource dependence relationships and interorganizational network characteristics.     

Exchange market pressure and primary commodity – exporting emerging markets

This paper studies short-term sensitivity between exchange market pressure and various domestic and external factors in primary commodity-exporting emerging markets. The paper focuses on the top country-commodity groups in sugar, cereal, fuels, ores and coffee during the pre-peak and post-peak commodity price periods across floating and pegged exchange rate regimes, using the price of crude oil as a general benchmark. Employing a panel model and panel VAR analysis, the paper finds the heterogeneity of response patterns unique to country-commodity groups and exchange rate regimes. According to the results, in flexible regimes, volatility occurs via the foreign exchange market, interest rates, and domestic credit cycles, feeding into the social costs for structurally weaker economies. Hard exchange-rate pegs often result in a drain on international reserves as the terms of trade deteriorate following post-price peaks, leading to unpopular depreciation. These results accentuate concerns over uneven international trade patterns, an open economy’s short-term foreign exchange policy, and speculative capital flows. Such sensitivity has broad implications for macroeconomic balance and the sustainability of implied exchange rate targets in the presence of a foreign exchange constraint across emerging markets.     

基于引力模型的省域创新产出空间联系研究

基于引力模型，结合社会网络分析法的凝聚子群分析，对31个省（区、市）的创新产出空间联系进行探究，研究发现：我国省域创新产出空间联系主要集中于京津冀和长三角一带，呈现出严重的分布不均状况，具有较强的区域集中性和空间依赖性；北京、天津、上海、浙江、江苏作为区域创新产出引力较强的节点省（区、市），对周边区域的创新产出具有较强的辐射作用；总体来看，省域创新产出空间联系并没有形成贯穿东西南北的交叉网状结构，中心省（区、市）数量较少且分布不均，辐射范围有限。基于此，提出加大区域创新投入、减少区域创新产出联系的政策性障碍、营造区域创新产出联系的良好环境等政策建议。     

Reference points for measuring social performance: Case study of a social business venture

We present a longitudinal qualitative case study to elaborate on how a social venture forms reference points for social performance. Although organizations increasingly use various social performance targets to direct their operations, the scholarly knowledge on social performance reference points remains limited. We make use of the prior accounting literature and draw on the idea of compromising accounts to discuss how provisional and performative metrics can have a significant role in how organizations develop new ways to evaluate their social performance. Given that the social performance reference point criteria are ambiguous and the corresponding referents malleable, performative accounts are helpful as they can intervene in the organizational life by making particular things visible, providing space for interpretations, and facilitating discussion, thus creating temporary settlements and enabling opportunities for productive compromises between different organizational groups and evaluative principles. The recursive feedback loops between reference point referents, criteria and accounting artefacts help the organization to make sense of its own social performance and interpret the associated performance feedback, and thereby provide ground for organizational decisions on further action. Moreover, we discuss how imperfect accounts can be useful for social businesses in their pursuit of developing their activities and achieving social impact.     

A spatial approach to the FDI-growth nexus in Spain: Dealing with the headquarters effect

This paper examines the effects of inward FDI on economic growth across the Spanish regions over the period 1996–2013, paying particular attention to the ‘headquarters effect’, namely that FDI is not always registered where it is effectively made but in the region in which the firm’s headquarters is located. By estimating a panel Spatial Durbin Model to allow for the detection of spatial spillovers, two main findings are reported. First, FDI does foster economic growth. Second, only when the headquarters effect is properly addressed do spatial spillovers arise. Hence, this effect is masking the impact of regional FDI spillovers on growth, which affects the reliability of the results and, consequently, FDI policies choice. Importantly, the results are: a) robust to the way of computing the headquarters effect; b) independent of the spatial weight matrix specification; and c) confirmed when splitting FDI into different industrial and service branches.     

自然资源依赖对城乡收入差距的影响研究

［目的］针对全国31个省（市、区）（不含港澳台地区）、自然资源依赖度高的地区和自然资源依赖度低的地区，从整体和分区域研究自然资源依赖对城乡收入差距的影响，探究不同区域其影响程度的差异性，进而为弱化各区域城乡收入差距，解决由城乡收入差距拉大造成的各类社会矛盾具有重要的现实意义。［方法］从理论上分析了自然资源依赖对城乡收入差距的影响，并利用1999—2017年的省级面板数据，运用固定效应模型，从全国和分区域实证分析了自然资源依赖对城乡收入差距的影响。［结果］针对全国，自然资源依赖会拉大城乡收入差距； 分区域结果，针对自然资源依赖度高的地区，自然资源依赖拉大城乡收入差距； 针对自然资源依赖度低的地区，自然资源依赖对城乡收入差距影响不显著。［结论］为缩小城乡收入差距，需要降低经济体对自然资源的依赖，针对自然资源依赖度高的地区，政府通过将部分自然资源收益转化为农业创新基金和农村基础设施投入，促进自然资源收益向农村公共资本转化，完善现有的自然资源收益分配及转化制度； 鼓励资源型产业技术创新，加大研发投入，延长资源产业链； 加大农村教育投入、提升农村人力资本质量。     

Fuelled Power: Oil,Financiers and Central Bank Policy in Nigeria

While the literature on business power and global finance has illuminated the ways in which financial institutions limit the policy autonomy of states in developing countries, we know much less about the circumstances under which the power of financiers is undermined. In this article, I advance explanations of these circumstances by arguing that state access to natural resource revenues reduces the power of financial institutions and enhances the capacity of the state to pursue central bank policies which violate the interests of major financiers. I employ a case study of central bank policy in Nigeria to probe this argument and find evidence that supports the claim that whenever the Nigerian government's access to resource revenues increased, the state's capacity to diverge from financiers’ preferred central bank policies and to advance its own preferences increased as well. The analysis provides the basis for broader propositions about the policy space of developing countries vis-à-vis financial institutions and the variability of structural power.     

Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?

Nonlinear, symmetric, and asymmetric dependence characteristics in energy equity sectors matter to portfolio investors and risk managers because of the risks and diversification opportunities they entail. Specifically, nonlinear dependence dynamics between assets are harder to predict, monitor, and manage, and can make investment positions go wrong unexpectedly. In this paper, we investigate whether the dependence dynamics of US and Canadian large-capitalized energy equity portfolios are nonlinear, symmetric, or asymmetric. We draw our results by implementing a robust copula approach based on time-varying parameter copulas and vine copula methods. Both time varying parameter and vine-copula methods indicate that the Canadian energy sector portfolio is driven by nonlinear negative tail asymmetric dependence during the global financial crisis and when the full sample period is employed. On the other hand, it displays nonlinear symmetric dependence during the oil price crisis, implying the need for close monitoring and rebalancing and a more continuous assessment of long investment positions. The US energy sector portfolio is driven by positive tail asymmetric dependence, and by symmetric dependence dynamics during crisis and non-crisis periods.     

Modelling tourist flow association for tourism demand forecasting

The purpose of this study is to examine tourism demand for Singapore from 1995 to 2013 by six major origin countries which belong to three different regions. Unlike prior tourism research, we take into account the dependence relations among the different tourist flows via copula. Copula is a statistical model of dependence and measurement of association. Specifically, we investigate the association between two tourist flows in each region. Based on empirical copula estimation, the Frank function has been identified as the most appropriate to capture the pairwise dependence structures of tourist flows. The copula-based approach combined with econometric models is proposed for tourism demand analysis that can be used to predict tourist arrivals. We apply the copula-ARDL and copula-ECM frameworks to generate joint forecasts of tourist arrivals from three regions. The findings show that the forecast performance of the Frank copula-based model outperforms the benchmark model which corresponds to the independence structure (no association) of tourist flows.