Purpose -The purpose of this paper is to analyze the variety of relations existing in tourism networks, identified as complex and mutable entities, where a vast range of stakeholders coexist.Design/methodology/approach -After a deep review on stakeholder theory, the research applies techniques of network analysis to a case study. Specifically, the analysis focuses on 354 hospitality firms acting in Molise Region (Italy). Each operator was asked to judge the importance to collaborate with other stakeholders to enhance the effectiveness of their management and marketing activities. The answers highlight the degree of preference among stakeholders and the resulting information is the level of confidence in the network.Findings -Results confirm the importance of intensifying relationships between tourism companies themselves and between them and policy makers. It appears that public stakeholders are more important for both management and marketing activities than private sector, since they place a much higher position in the scale of preference.Research limitations/implications -The paper provides a starting-point for further research about non-quantitative destination performance measurement, such as trust and commitment between the stakeholders in tourism destination, and the use of network analysis' techniques.Practical implications -Destination managers and policy-makers may use techniques of network analysis to elaborate useful information for planning and managing the relationships inside the tourism network.Originality/value -The paper offers a novel approach for developing network analysis in tourism network literature. It explores non-quantitative destination performance measurements and uses management and marketing activities to analyze relationships between public and private stakeholders.

The gravity model is a workhorse tool applicable in a wide range of empirical fields. It is regularly used to estimate the impact of reciprocal trade agreements (RTAs) on trade flows between partners. The studies report very different estimates since there is a significant difference in datasets, sample sizes, and independent variables. This paper combines, explains, and summarizes a large number of results using a meta-analysis approach. We provide pooled estimates, obtained from fixed and random effects models of the RTAs' effect size on bilateral trade: the hypothesis that there is no effect of RTAs on trade is robustly rejected at standard significance levels. The information collected on each estimate allows us to test the sensitivity of the results to alternative specifications and differences in the control variables considered, as well as the impact of the publication selection process. Copyright � 2010 Blackwell Publishing Ltd.

Over the time a large number of reciprocal preferential trade agreements (RTAs) have been concluded among countries. Recently many studies have used gravity equations in order to estimate the effect of RTAs on trade flows between partners. These studies report very different estimates, since they differ greatly in data sets, sample sizes, and independent variables used in the analysis. So, what is the "true" impact of RTAs? This paper combines, explains, and summarizes a large number of results (1827 estimates included in 85 papers), using a meta-analysis (MA) approach. Notwithstanding quite an high variability, studies consistently find a positive RTAs impact on bilateral trade: the hypothesis that there is no effect of trade agreements on trade is easily and robustly rejected at standard significance levels. We provide pooled estimates, obtained from fixed and random effects models, of the increase in bilateral trade due to RTAs. Finally, information collected on each estimate allows us to test the sensitivity of the results to alternative specifications and differences in the control variables considered.

The theoretical literature has discussed different channels through which foreign direct investments (FDI) promote host country’s economic growth, but empirical analyses have so far been rather inconclusive. In this paper, exploiting the information of a disaggregated data set on a panel of 14 manufacturing sectors for (a sample of) developed and developing countries over the period 1992–2004, we are able to provide robust evidence on the positive and statistically significant growth effect of FDI in recipient countries. Moreover, we find that this effect is stronger in capital‐intensive and technologically advanced sectors. The growth enhancing effect comes primarily from an increase in total factor productivity (TFP) and from factors accumulation. Our results are robust to the inclusion of other determinants of economic growth and to controlling for potential endogeneity.

We assess the impact on agricultural trade of European Union (EU) trade policies, using a gravity model based on disaggregated trade flows from 161 developing countries (DCs) to 15 EU member countries. We use a sample selection framework to account for potential selection bias of positive trade flows and provide an explicit measure for relative preference margins. From a policy perspective, our results debunk some of the most widespread criticisms of preferential policies: EU preferences matter and have a positive impact on DCs agricultural exports at both the extensive and intensive margins, although with significant differences across sectors.preferential trade policy, agricultural trade, gravity model, European trade policy,