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The Economic Perspective of Food Poverty and (In)security: An Analytical Approach to Measuring and Estimation in Italy

Author

Listed:
  • Stefano Marchetti

    (University of Pisa)

  • Luca Secondi

    (University of Tuscia, Agro-Food and Forest Systems (DIBAF))

Abstract

The UN Sustainable Development Goals have set clear targets on global poverty, hunger and malnutrition to be achieved by 2030, which have prompted academics and policymakers to identify useful strategies and drivers. Moreover, the COVID19 pandemic has exacerbated inequalities at national and sub-national levels thus hampering the achievement of these goals. On considering the multifaceted nature of poverty, a recent research strand focuses on food poverty and insecurity issues in terms of economic access to food and healthy diet consumption, with moderate and extreme food insecurity affecting almost 9% of the population in Europe and North America. This paper aims to analyse food poverty and insecurity at regional level in Italy. Using micro-data from the Italian Household Budget Survey carried out by ISTAT, an analytical approach was proposed to define and measure the different degree of food poverty and insecurity. Moreover, to obtain insights into whether food poverty and insecurity can afford population healthy nutrition, inequality of the distributions of food expenditure categories are estimated. The results provided us with information on other important aspects of the poverty. Indeed, in Italy individuals who are at-risk-of-food-poverty or food insecure amount to 22.3% of the entire population. Furthermore, the at-risk-of-food-poverty-rate varies at regional level from 14.6% (Umbria) to 29.6% (Abruzzo), with high levels of food consumption inequalities observed above all for vegetables, meat and fish. All these issues could help policy makers to define economic intervention policies aimed at reducing social exclusion and achieving more equitable and sustainable living conditions for the entire population.

Suggested Citation

  • Stefano Marchetti & Luca Secondi, 2022. "The Economic Perspective of Food Poverty and (In)security: An Analytical Approach to Measuring and Estimation in Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(3), pages 995-1020, August.
  • Handle: RePEc:spr:soinre:v:162:y:2022:i:3:d:10.1007_s11205-021-02875-5
    DOI: 10.1007/s11205-021-02875-5
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    1. Cowell, Frank A. & Kuga, Kiyoshi, 1981. "Additivity and the entropy concept: An axiomatic approach to inequality measurement," Journal of Economic Theory, Elsevier, vol. 25(1), pages 131-143, August.
    2. Romina Boarini & Marco Mira d'Ercole, 2006. "Measures of Material Deprivation in OECD Countries," OECD Social, Employment and Migration Working Papers 37, OECD Publishing.
    3. Chaudhuri, Shubham & Ravallion, Martin, 1994. "How well do static indicators identify the chronically poor?," Journal of Public Economics, Elsevier, vol. 53(3), pages 367-394, March.
    4. Leonardo S. Alaimo & Filomena Maggino, 2020. "Sustainable Development Goals Indicators at Territorial Level: Conceptual and Methodological Issues—The Italian Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 383-419, January.
    5. Elena Carrillo-Álvarez & Blanca Salinas-Roca & Lluís Costa-Tutusaus & Raimon Milà-Villarroel & Nithya Shankar Krishnan, 2021. "The Measurement of Food Insecurity in High-Income Countries: A Scoping Review," IJERPH, MDPI, vol. 18(18), pages 1-57, September.
    6. Drieda Zaҫe & Maria Luisa Di Pietro & Laura Reali & Chiara de Waure & Walter Ricciardi, 2021. "Prevalence, socio-economic predictors and health correlates of food insecurity among Italian children- findings from a cross-sectional study," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 13-24, February.
    7. Aaberge, Rolf & Mogstad, Magne & Peragine, Vito, 2011. "Measuring long-term inequality of opportunity," Journal of Public Economics, Elsevier, vol. 95(3), pages 193-204.
    8. Sayema Haque Bidisha & Tanveer Mahmood & Md. Biplob Hossain, 2021. "Assessing Food Poverty, Vulnerability and Food Consumption Inequality in the Context of COVID-19: A Case of Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 187-210, May.
    9. Madhabendra Sinha & Anjan Ray Chaudhury, 2021. "Assessing the Between-Group Inequality Through Alternative Measures of Grouping: An Indian Evidence," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(3), pages 1021-1045, October.
    10. Bai, Yan & Alemu, Robel & Block, Steven A. & Headey, Derek & Masters, William A., 2021. "Cost and affordability of nutritious diets at retail prices: Evidence from 177 countries," Food Policy, Elsevier, vol. 99(C).
    11. Luca Secondi, 2021. "Estimating Household Consumption Expenditure at Local Level In Italy: The Potential of the Cokriging Spatial Predictor," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 651-674, January.
    12. Smith, Lisa C. & Subandoro, Ali, 2007. "Measuring food security using household expenditure surveys:," Food security in practice technical guide series 3, International Food Policy Research Institute (IFPRI).
    13. Stefano Marchetti & Luca Secondi, 2017. "Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 215-234, March.
    14. Joanna B. Upton & Jennifer Denno Cissé & Christopher B. Barrett, 2016. "Food security as resilience: reconciling definition and measurement," Agricultural Economics, International Association of Agricultural Economists, vol. 47(S1), pages 135-147, November.
    15. Sugasawa, Shonosuke & Kubokawa, Tatsuya, 2017. "Transforming response values in small area prediction," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 47-60.
    16. Cowell, Frank, 2011. "Measuring Inequality," OUP Catalogue, Oxford University Press, edition 3, number 9780199594047.
    17. Penne, Tess & Goedemé, Tim, 2021. "Can low-income households afford a healthy diet? Insufficient income as a driver of food insecurity in Europe," Food Policy, Elsevier, vol. 99(C).
    18. Lillian Mookodi, 2021. "Decomposition analysis of the Gini coefficient of consumer expenditures in Botswana," Development Southern Africa, Taylor & Francis Journals, vol. 38(4), pages 622-642, July.
    19. Secondi, Luca & Principato, Ludovica & Laureti, Tiziana, 2015. "Household food waste behaviour in EU-27 countries: A multilevel analysis," Food Policy, Elsevier, vol. 56(C), pages 25-40.
    20. Timo Schmid & Fabian Bruckschen & Nicola Salvati & Till Zbiranski, 2017. "Constructing sociodemographic indicators for national statistical institutes by using mobile phone data: estimating literacy rates in Senegal," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1163-1190, October.
    21. Drieda Zaҫe & Maria Luisa Di Pietro & Laura Reali & Chiara de Waure & Walter Ricciardi, 2021. "Correction to: Prevalence, socio-economic predictors and health correlates of food insecurity among Italian children- findings from a cross-sectional study," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 243-243, February.
    22. Ana Moltedo & Nathalie Troubat & Michael Lokshin & Zurab Sajaia, 2014. "Analyzing Food Security Using Household Survey Data : Streamlined Analysis with ADePT Software," World Bank Publications - Books, The World Bank Group, number 18091, December.
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