{"title":"Vulnerability and resilience to food and nutrition insecurity: A review of the literature towards a unified framework","authors":"P. Montalbano, D. Romano","doi":"10.36253/bae-14125","DOIUrl":null,"url":null,"abstract":"Current approaches to measuring food and nutrition security (FNS) mainly consider past access to food, while assessing vulnerability and resilience to food insecurity requires a dynamic setting and sound predictive models, conditional to the entire set of food-related multiple-scale shocks and stresses as well as households’ characteristics. The aim of this work is twofold: i) to review the state of the relevant literature on the conceptualization and the empirical measurement of vulnerability and resilience to food insecurity; ii) to frame the main coordinates of a possible unifying framework aiming at improving ex-ante targeting of policy interventions and resilience-enhancing programs. Our argument is that clarifying the relationships existing between vulnerability and resilience provides a better understanding and a more comprehensive picture of food insecurity that includes higher-order conditional moments and non-linearities. Furthermore, adopting the proposed unified framework, one can derive FNS measures that are: scalable and aggregable into higher-level dimensions (scale axiom); inherently dynamic (time axiom); conditioned to various factors (access axiom); applicable to various measures of food and nutrition as dependent variables (outcomes axiom). Unfortunately, the proposed unified framework shows some limitations. First, estimating conditional moments is highly data-demanding, requiring high-quality and high-frequency micro-level panel data for all the relevant FNS dimensions, not mentioning the difficulty of measuring risks/shocks and their associated probabilities using short panel data. Hence, there is a general issue of applicability of the proposed approach to typically data-scarce environments such as developing contexts. Second, there is an inherent tradeoff between the proposed approach in-sample precision and out-of-sample predictive performance. This is key to implement effective early warning systems and foster resilience-building programs.","PeriodicalId":44385,"journal":{"name":"Bio-based and Applied Economics","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bio-based and Applied Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36253/bae-14125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Current approaches to measuring food and nutrition security (FNS) mainly consider past access to food, while assessing vulnerability and resilience to food insecurity requires a dynamic setting and sound predictive models, conditional to the entire set of food-related multiple-scale shocks and stresses as well as households’ characteristics. The aim of this work is twofold: i) to review the state of the relevant literature on the conceptualization and the empirical measurement of vulnerability and resilience to food insecurity; ii) to frame the main coordinates of a possible unifying framework aiming at improving ex-ante targeting of policy interventions and resilience-enhancing programs. Our argument is that clarifying the relationships existing between vulnerability and resilience provides a better understanding and a more comprehensive picture of food insecurity that includes higher-order conditional moments and non-linearities. Furthermore, adopting the proposed unified framework, one can derive FNS measures that are: scalable and aggregable into higher-level dimensions (scale axiom); inherently dynamic (time axiom); conditioned to various factors (access axiom); applicable to various measures of food and nutrition as dependent variables (outcomes axiom). Unfortunately, the proposed unified framework shows some limitations. First, estimating conditional moments is highly data-demanding, requiring high-quality and high-frequency micro-level panel data for all the relevant FNS dimensions, not mentioning the difficulty of measuring risks/shocks and their associated probabilities using short panel data. Hence, there is a general issue of applicability of the proposed approach to typically data-scarce environments such as developing contexts. Second, there is an inherent tradeoff between the proposed approach in-sample precision and out-of-sample predictive performance. This is key to implement effective early warning systems and foster resilience-building programs.
期刊介绍:
The journal Bio-based and Applied Economics (BAE) provides a forum for presentation and discussion of applied research in the field of bio-based sectors and related policies, informing evidence-based decision-making and policy-making. It intends to provide a scholarly source of theoretical and applied studies while remaining widely accessible for non-researchers. BAE seeks applied contributions on the economics of bio-based industries, such as agriculture, forestry, fishery and food, dealing with any related disciplines, such as resource and environmental economics, consumer studies, regional economics, innovation and development economics. Beside well-established fields of research related to these sectors, BAE aims in particular to explore cross-sectoral, recent and emerging themes characterizing the integrated management of biological resources, bio-based industries and sustainable development of rural areas. A special attention is also paid to the linkages between local and international dimensions.