Understanding how an adequate food security may be determined, how nutritional intakes evolve over time and are influenced by global dynamics are few of the questions scholars are trying to answer. In addition, a great interest is devoted to the changes in consumers' preferences and expectations as well as to the analysis of food innovations and their impact on the global market.We review the recent and emerging trends in food supply chains of selected sectors (fruits and vegetables, meat, and seafood), and deepen on emerging trends in the food industry. By presenting the evidence provided by the literature and emphasizing the unresolved research questions, we offer a critical view of future directions that should be followed by research agenda.

The increasing policy interest and academic debates on non-tariff measures (NTMs) has stimulated a growing literature on how NTMs affect agri-food trade. The empirical literature provides contrasting and heterogeneous evidence, with some studies supporting the 'standards as catalysts' view, and others favouring the 'standards as barriers' explanation. To the extent that NTMs can influence trade, understanding the prevailing effect, and the motivations behind one effect or the other, is a pressing issue. We review a large body of empirical evidence on the effect of NTMs on agri-food trade and conduct a meta-analysis to disentangle potential determinants of heterogeneity in estimates. Our findings show the role played by the publication process and by study-specific assumptions. Some characteristics of the studies are correlated with positive significant estimates, others covary with negative significant estimates. Overall, we found that the effects of NTMs vary across types of NTM, proxies used for NTMs, and levels of detail of studies. The estimated effects are also influenced by methodological issues and publication processes.The importance of understanding the trade effects of NTMs in agri-food sector is attested by the large and increasing number of papers hosted in top journals (e.g.

Abstract

The factors affecting the demand for agricultural insurance in the USA have been extensively studied over the last two decades. However, the determinants of a farm's entry and exit decisions in the insurance market have received relatively little attention. Turnover in the insurance book of business is an important issue in most private and public crop insurance plans. Moreover, insurance markets in the EU are still largely under‐investigated. We investigate empirically the determinants of crop insurance participation in Italy. We show that the participation rate is high for large firms and that it is negatively correlated with crop diversification, which is itself a form of insurance. High premiums tend to inhibit both entry and exit from the insurance market. Larger and wealthier farms are more likely to adopt insurance and renew coverage over time. We discuss implications of our results for public intervention and the private industry. In particular, we demonstrate that the decision to drop coverage by an insured grower may differ significantly from the corresponding decision to enroll in an insurance programme by an uninsured farmer. To the extent that policymakers want to encourage participation in subsidized crop insurance programmes, education and outreach efforts toward uninsured farmers may differ substantially from those directed toward keeping insured farmers enrolled in the programme. We investigate these differences.

During the past decades, there has been much debate on food security. A variety of indicators have been proposed in order to establish which countriesare in need of improved food security status. The heterogeneity of existing indicators and the lack of consensus on how to compare and rank countries have motivated international organizations to build composite indexes to synthesize the information. The process of building composite indexes involves multiple choices that influence the outcome. Our analysis aims at understanding how relevant and discretional may be the analyst's choice of algorithms to compute composite indexes for food security. To this extent, we have computed several composite indexes for food security by using data provided by the Food and Agricultural Organization, which includes a large set of proxies for food security, as emerged from the Committee on World Food Security Round Table. We compare different methods to impute, homogenize, weight and aggregate data, in order to compute composite indexes and show how relevant are the choices to be made. We show that normalization and weighting are not very crucial decisions, whereas special attention has to be paid in choosing the data imputation and aggregation methods. By commenting on the implications that different measurement choices may have in terms global index, we show that the index construction decisions matter.