Do the poor benefit from globalization regardless of institutional quality?

Despite significant progress towards the Millennium goals, more than one billion people live on less than 1.25 US dollars per day. Previous research suggests that globalization stimulates poverty reduction, but does not investigate what role institutions play in this relationship. Theoretically, globalization could act as either a complement or a substitute to institutional quality in reducing poverty. We find that the poverty-reducing effect of globalization is stronger when institutions are weak. In particular, increasing social globalization reduces poverty more when corruption is high and democratic accountability is low. Thus, globalization has the power to reduce poverty even in countries with low institutional quality.     

Financial openness and Chinese regional growth imbalance: New insight from spatial spillovers

This paper uses spatial panel methods and Chinese provincial data from 2003 to 2017 to study the spatial spillovers of financial openness on economic growth. The results show, first, a positive direct effect and an overall negative spatial spillover of financial openness on provincial growth. Second, there are two spatial spillover channels: a positive growth externality and a harmful resource competition among provinces. Third, we estimate the state dependence and dynamics of spatial spillover, and find that the negative spatial spillover is smaller in provinces with high levels of financial openness and in the long term; thus, the negative spatial spillover declined over time. These results are robust to the choice of SDM and GNS spatial econometrics methods and under different spatial weight matrices.     

农业创业情境下商业模式设计的影响机制研究——基于模糊集定性比较分析

农业创业者如何通过整合与管理资源与能力，设计新颖型商业模式创造更多价值，是实现乡村振兴战略的关键措施。文章基于资源编排、商业模式理论，以央视《致富经》栏目40个案例为样本，运用模糊集定性比较分析（fsQCA）方法，剖析资源编排、机会能力、创业学习所构成的前因变量组态对农业创业活动中商业模式设计的影响机制。研究发现，资源编排在农业创业活动中发挥不可或缺的关键作用；相较于资源结构化和资源捆绑，资源利用在新颖型商业模式设计中的作用更为突出；机会能力须与资源编排共同作用，方可实现新颖型商业模式设计；在资源编排作用缺乏时，创业学习的发挥有助于新颖型商业模式设计的形成。研究成果诠释了农业创业情境下资源编排、机会能力与创业学习对商业模式设计的影响机制，为开展农业创业活动提供指导。     

FIPIA with information entropy: A new hybrid method to assess airline service quality

This study proposes “FIPIA with information entropy” as a new, hybrid method to assess airline service quality by identifying the most important priorities for airline passengers and producing recommendations to airline management for optimal resource allocation to improve service quality and customer satisfaction. The proposed method is an improvement over IPA, IPIA and FIPA methods, through the introduction of information entropy and fuzzy logic to the analysis of importance, performance and impact dimensions of airline service quality to improve interpretability and actionability of analysis results. This study also offers airline managers a list of what they should improve in resource allocation in order to increase service quality considering customer satisfaction and create value by managing the relational capital more effectively. The new hybrid method was field-tested by administering a 26-item questionnaire to passengers of a major airline operator, analyzing the responses using the Importance-Performance-Impact Analysis (IPIA) method, fuzzy logic and information entropy. The analysis revealed four main dimensions of airline service quality, namely reliability, assurance, tangibles, empathy and responsiveness with 17 constituent attributes. The case study revealed that (1) resource allocation was adequate only on four attributes; (2) seven service quality attributes were identified as needing further management focus on resource allocation; (3) six service quality attributes received more resources than necessary which should be shifted to other attributes; (4) dimensions of reliability and tangibles needed more focus than others. The proposed hybrid method of FIPIA with information entropy can be employed for any industry where service quality depends on multiple attributes.     

Customer and Supplier Portfolios: Can Credit Risks be Managed Through Supply Chain Relationships?

While supply chain risk has been the subject of an ever‐increasing amount of research attention, the importance of credit risk has been less studied, at least by supply chain researchers. Yet, there may be risks inherent within a firm's portfolios of supply chain relationships that are manifested in the credit risk of a firm. Moreover, portfolio characteristics may serve as a signal to the external market regarding these risks. While customer and supplier portfolio characteristics may impact the firm's exposure to risks, the specific issue of how portfolio characteristics relate to credit risk has rarely been examined by supply chain scholars. This research bridges extant works in supply chain management and finance to relate supply chain characteristics to a critical reputational outcome, namely credit ratings. In this research, we utilize a sample of firms that recently underwent an initial public offering to empirically examine the theoretical predictions of Resource Dependence Theory regarding the relationships between different supply chain portfolio characteristics and credit risk.     

Is green growth relevant for poor economies?

To be relevant to developing countries, green growth must be reconciled with the two key structural features of natural resource use and poverty in these countries. First, primary products account for the majority of their export earnings, and they are unable to diversify from primary production. Second, many economies have a substantial share of their rural population located on less favored agricultural land and in remote areas, thus encouraging “geographic” poverty traps. If green growth is to be a catalyst for economy-wide transformation and poverty alleviation in developing countries, then it must be accompanied by policies aimed directly at overcoming these two structural features. Policies and reforms should foster forward and backward linkages of primary production, enhance its integration with the rest of the economy, and improve opportunities for innovation and knowledge spillovers. Rural poverty, especially the persistent concentration of the rural poor on less favored agricultural lands and in remote areas, needs to be addressed by additional targeted policies and investments, and where necessary, policies to promote rural-urban migration.     

Does institutional quality resolve the Lucas Paradox?

The Lucas Paradox observes that capital flows predominantly to relatively rich countries, contradicting the neoclassical prediction that it should flow to poorer capital-scarce countries. In an influential study, Alfaro, Kalemli-Ozcan, and Volosovych (AKV) argue that cross-country variation in institutional quality can fully explain the Paradox, contending that if institutional quality is included in regression models explaining international capital inflows, a country’s level of economic development is no longer statistically significant. We replicate AKV’s results using their cross-sectional IFS capital flow data. Motivated by the importance of conducting inference in statistically adequate models, we focus on misspecification testing of alternative functional forms of their empirical model of capital flows. We show that their resolution of the Paradox relies on inference in a misspecified model. In models that do not fail basic misspecification tests, even though institutional quality is a significant determinant of capital inflows, a country’s level of economic development also remains a significant predictor. The same conclusions are reached using an extended dataset covering more recent IFS international capital flow data, first-differenced capital stock data and additional controls.     

FX Intervention in the New Keynesian Model

We develop an open-economy New Keynesian Model with foreign exchange (FX) intervention in the presence of a financial accelerator and shocks to risk appetite in international capital markets. We obtain closed-form solutions for optimal monetary and FX intervention policies assuming the central bank cannot commit to future policies, and we compare the solution to that under policy commitment. We show how FX intervention can help reduce the volatility of the exchange rate, of inflation, and of the output gap, thus mitigating welfare losses associated with shocks in the international capital markets. We also show that, when the financial accelerator is strong, there is a risk of indeterminacy (self-fulfilling currency and inflation movements) although FX intervention can reduce this risk and thus reinforce the credibility of the inflation targeting regime. Model simulations match well the impact of a VIX shock obtained by local projections on a panel of inflation targeting emerging markets.     

Designing awareness campaigns to counter human trafficking: An analytic approach

Human trafficking – the trade of persons for the gain of others – is a pervasive societal issue. Ongoing trafficking recruitment calls for targeted prevention strategies for individuals and communities at risk. Awareness campaigns, arguably the most common form of trafficking prevention, are intended to alert individuals to the tactics used by traffickers and provide them with practical strategies to avoid deception and exploitation. However there is a shortage of technical solutions regarding the analysis, impact assessment, and evaluation of alternatives related to implementing awareness campaigns. We present a resource allocation model that can be used to determine the allocation of funds that maximizes increases in trafficking awareness among at-risk populations. We apply this model to determine the allocation of a limited budget among different types of prevention programs in at-risk populations in Nepal. For each awareness campaign, we estimate a production function that relates the amount invested to the associated change in awareness. When allocating limited resources, decision makers must balance competing interests, and we illustrate the impact of three allocation policies on trafficking awareness. The model presented in this article is a first attempt to help decision makers evaluate how to allocate funds in the context of trafficking awareness.     

Adverse selection,commitment and exhaustible resource taxation

This paper studies the contractual relationship between a government and a firm in charge of the extraction of an exhaustible resource. Governments design taxation scheme to capture resource rent and they usually propose contracts with limited duration and possess less information on resources than the extractive firms do. This article investigates how information asymmetry on costs and an inability to commit to long-term contracts affect tax revenue and the extraction path. This study gives several unconventional results. First, when information asymmetry exists, the inability to commit does not necessarily lower tax revenues. Second, under asymmetric information without commitment, an efficient firm may produce during the first period more or less than under symmetric information. Hence, the inability to commit has an ambiguous effect on the exhaustion date. Third, the modified Hotelling's rule is such that an increase in the discount factor does not necessarily reduce the first-period extraction.