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.     

Intensive and extensive margins of exports: What can India learn from China?

We decompose India's export performance in manufactured products during 2000–15 into changes at the intensive and extensive margins. India's performance, along different margins, is compared and contrasted with that of China. The results show that while China outperforms India at both the margins, the gap is particularly wide at the intensive margin. Decomposition of intensive margin along quantity and price margins shows that Chinese products are generally sold cheaper than Indian products. Higher price margin, however, has not translated into high intensive margin for India due to its abysmally low quantity margin. We examine different explanations for China's superior performance relative to India, along different margins, using a gravity model. Our results suggest that China's exchange rate policy was not the prime reason for its export success. Neither do we find that FDI inflows were significant in explaining the export performance gap between them. The results show that China's export relationship bias towards high‐income partner countries holds the key in understanding its superior performance. This bias is a natural consequence of China's high degree of specialization in labor‐intensive activities. India, by contrast, due to an idiosyncratic pattern of specialisation, has failed to exploit its export potential in high income countries.     

Natural resource rents and internal conflicts: Can decentralization lift the curse?

We study how natural resource rents affect the risk of internal conflict within countries and how the federal structure of countries influences this relationship. Natural resource abundance may induce excessive rent-seeking and thus increase the risk of internal conflict. Fiscal and political decentralization as an institutional arrangement for rent-sharing and political codetermination of regions within a country may limit the destructive effect of natural resource rents on internal stability. Using cross-country and panel data from more than 90 countries covering the period 1984–2004, we find evidence that natural resource rents indeed increase the risk of internal conflict, but this relationship is significantly mitigated by political decentralization.     

Identifying Worldviews on Corporate Sustainability: A Content Analysis of Corporate Sustainability Reports

Companies commonly issue sustainability or corporate social responsibility (CSR) reports. This study seeks to understand worldviews of corporate sustainability, or the corporate message conveyed regarding what sustainability or CSR is and how to enact it. Content analysis of corporate sustainability reports is used to position each company report within stages of corporate sustainability. Results reveal that there are multiple coexisting worldviews of corporate sustainability, but the most dominant worldview is focused on the business case for sustainability, a position anchored in the weak sustainability paradigm. We contend that the business case and weak sustainability advanced in corporate sustainability reports and by the Global Reporting Initiative are poor representations of sustainability. Ecological embeddedness, or a locally responsive strategy that is sensitive to local ecosystems, may hold the key to improved ecological sensemaking, which in turn could lead to more mature levels of corporate sustainability worldviews that support strong sustainability and are rooted in environmental science. This must be supported by government regulation. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

政府随机审计的动态博弈模型及政策启示

本文在一个三阶段动态博弈框架下，对政府随机审计过程中的政府审计机关与政府审计对象以及国家与政府审计对象之间的动态博弈特征进行了分析。分析结果显示：政府审计机关与政府审计对象之间存在一个纯策略纳什均衡，而国家和政府审计对象之间存在一个混合策略纳什均衡。政府审计对象接受国家实质性审计的概率是政府审计对象被政府机关审计发现违规或不作为后的惩罚倍数的单调递减函数，而政府审计对象的违规或不作为的概率分别是政府审计对象被政府机关审计发现违规或不作为后的惩罚倍数和政府审计对象的应尽义务或责任的单调递减函数，却是政府审计机关审计行为成本的单调递增函数。同时，结合研究结论和中国政府审计全覆盖的现实，给出了一些政策建议。     

Clearinghouse loan certificates as a lender of last resort

Looking across multiple panics of the nineteenth and twentieth centuries, this paper treats borrowing of clearinghouse loan certificates as borrowing from a lender of last resort. We evaluate individual bank use of clearinghouse loan certificates in New York City using bank balance sheet data. Bank capital ratios do not predict positive net borrowing. Lower pre-panic reserve ratios increased the probability of positive net borrowing of loan certificates. Bank borrowing behavior from a lender of last resort remained relatively constant across all three crises considered.     

Incorporating active adjustment into a financing based model of capital structure

The conventional partial adjustment model, which focuses on leverage evolution, has difficulty identifying deliberate capital structure adjustments as it confounds financing decisions with the mechanical autocorrelation of leverage. We propose and estimate a financing-based partial adjustment model that separates the effects of financing decisions on leverage evolution from mechanical evolution. The speed of adjustment (SOA) is firm-specific and stochastic, and active targeting of capital structure has a multiplier effect that depends on the size of financial deficit. Overall, we find expected SOA from active rebalancing (30%) more than doubles what is expected from mechanical mean reversion alone (13%).     

生态旅游视域下的岷江上游贫困山区生态安全评价

[目的]构建科学合理的评价指标体系,准确评价生态旅游影响下的区域生态安全状况,是推动少数民族山区实现旅游资源环境与区域社会、经济协同发展的前提和基础。[方法]以岷江上游贫困山区为例,应用灰色系统理论与熵值赋权法相结合,基于压力—状态—响应模型,构建生态旅游视域下的区域生态安全评估指标体系,并将评估指数与经济收入状况及贫困人口分布进行空间耦合。[结果](1)区域当前处于较安全水平,生态旅游开发适度;(2)综合评估指数与城镇居民可支配收入增长率、旅游收入对国民经济增长的贡献率呈正相关,且城镇居民在旅游开发中受益与机会较农牧民多;(3)综合评估指数与贫困人口比重呈负相关,与农牧民纯收入增长率没有必然联系。[结论]区域脱贫能够改善当地的生态安全状况,适度生态旅游开发是区域脱贫的有效手段,但应注重扶持农牧民在旅游业中的参与度,增加其旅游收益。     

Effects of scale economies and production seasonality on optimal hub locations: the case of regional fresh produce aggregation

Interest in supporting local and regional food systems is rising and food hubs have attracted considerable attention among Federal, State, and local policymakers. This study explores the problem of endogenous hub location in fresh produce value chains in the Northeastern United States. To overcome limitations in the literature, we incorporate the effects of economies of scale and production seasonality into our models. Three experimental models are designed to examine the effects of alternatively applying yearly, quarterly, and monthly data on model solutions. We explicitly assess how interactions of scale economies and seasonality influence the structure and spatial attributes of an optimal regional produce aggregation hub system. The three models generate marketed different solutions and in many respects they lead to different conclusions about developing local/regional supply chains. The monthly model allows for production seasonality and actual hub operation cycle frequency and thus leads to more efficient hub solution with rich policy implications.     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。