Food Security, Poverty and Nutrition Policy Analysis

Statistical Methods and Applications

Suresh Babu, Shailendra Gajanan, Prabuddha Sanyal, Shailendra N. Gajanan

• Publisher: Academic Press
• Year: 2014
• eBook ISBN: 9780124059092
• Edition: 2
• Topic: Technology & Engineering
• Subtopic: Food Science
• Index: Technology & Engineering

Food insecurity, the lack of access at all times to the food needed for an active and healthy life, continues to be a growing problem as populations increase while the world economy struggles. Formulating effective policies for addressing these issues requires thorough understanding of the empirical data and application of appropriate measurement and analysis of that information.Food Security, Poverty and Nutrition Policy Analysis, Second Edition has been revised and updated to include hands-on examples and real-world case studies using the latest datasets, tools and methods. Providing a proven framework for developing applied policy analysis skills, this book is based on over 30 years of food and nutrition policy research at the International Food Policy Research Institute and has been used worldwide to impart the combined skills of statistical data analysis, computer literacy and their use in developing policy alternatives.This book provides core information in a format that provides not only the concept behind the method, but real-world applications giving the reader valuable, practical knowledge.- Updated to address the latest datasets and tools, including STATA software, the future of policy analysis- Includes a new chapter on program evaluation taking the reader from data analysis to policy development to post-implementation measurement- Identifies the proper analysis method, its application to available data and its importance in policy development using real-world scenarios- Over 30% new content and fully revised throughout

Section III: Special Topics on Poverty, Nutrition and Food Policy Analysis

Section III: Special Topics on Poverty, Nutrition, and Food Policy Analysis

Introduction

In this section, the book introduces more challenging tools and techniques of food security, poverty, and nutrition policy analysis. They include discriminant analysis, logistic regression models, cluster analysis, instrumental variable estimation, and linear programming. Developed with the needs for post-graduate level treatment policy analysis, these chapters enable the policy analysts to have an advanced set of quantitative methods in their tool box.

Chapter 11

This chapter introduces discriminant analysis as a tool to identify the most important determinant of food security and nutritional status that can predict best among a large pool of such independent variables. Such variables need to be identified for context and community-specific food and nutrition interventions. The chapter reviews selected case studies that attempt to identify good predictors of food insecurity, poverty, and malnutrition. Various steps of discriminant analysis, such as specifying the dependent and predictor variables, determining the method of selection criteria for entering the predictor variables in the modes and tests of a-priori assumptions of the model, interpretation of discriminant functions, and validation of results, are described with examples.

Chapter 12

The analysis of measurement and determinants of poverty and its relationship to food security and nutritional outcomes have become a major area of investigation by household welfare analysts. This chapter introduces various approaches to identifying the poor, measurement of poverty, construction of poverty lines, and deriving various measures of poverty including headcount index, poverty gap index, and squared poverty gap index. Poverty lines are calculated using food energy intake and cost of basic needs approaches. Analysis of determinants of poverty using binary logistic regression is also demonstrated. Interpretation of the results of logistic regression for deriving policy implications is given.

Chapter 13

This chapter introduces cluster analysis with a goal to find an optimal grouping of observations on food security and nutritional status that are similar in a cluster but are dissimilar to observations in other clusters. It is shown how targeted food and nutrition interventions could be designed for groups of households on the basis of certain socioeconomic characteristics or when certain program interventions are desirable to improve the welfare of specific groups of the population. Initial partitioning of observations, optimum number of clusters, describing characteristics of the clusters, and cluster centers are some of the topics covered under this chapter. Several food and nutrition related case studies that use cluster analysis are also reviewed.

Chapter 14

Using case studies from the child nutrition literature, this chapter introduces the instrumental variable model. The analysis is shown in two steps. Estimation of the determinants of child-care practices is carried out in the first stage while, in the second stage, the predicted value of child-care practices along with other control varieties are used to determine the impact of child nutrition outcomes.

Chapter 15

Nutrition planners face several programmatic challenges in designing appropriate interventions. Frequently asked field questions include: is it possible to design a diet with locally available food that meets the daily recommended allowances? How do we minimize the cost of achieving such diets?

These questions could be answered through a linear programming approach that helps to examine the compatibility of different mathematical inequalities in using simple mathematics to address the above questions. This chapter introduces elements of linear programming and demonstrates how food and nutrition problems could be solved using an Excel spreadsheet. Interpretations of the results of linear programming problems for policy applications are also given.

Chapter 16

Addressing problems of food security and malnutrition requires designing and implementing cost-effective intervention programs. However, much of the programs implemented to do go beyond the pilot stage. Projects that are not evaluated before scaling up to a large intervention program. Evaluating food security and nutrition interventions require a good understanding of the methods involved and appropriate application of these methods. In this chapter we review the methods for program evaluation and introduce the reader to the latest development in the field including the randomized control trials that have come to dominate the program evaluation literature.

11

Predicting Child Nutritional Status Using Related Socioeconomic Variables—Application of Discriminant Function Analysis

Abstract

This chapter introduces discriminant analysis as a tool to identify the most important determinant of food security and nutritional status that can predict best among a large pool of such independent variables. Such variables need to be identified for context and community specific food and nutrition interventions. We present a case study from the United States, which links economic conditions and participation in Nutrition Assistance Programs. We also present the impact of climate change on nutrition in Ethiopia and Asia. The chapter reviews selected case studies that attempt to identify good predictors of food insecurity, poverty and malnutrition. Various steps of discriminant analysis, such as specifying the dependent and predictor variables, determining the method of selection criteria for entering the predictor variables in the modes and tests of a-priori assumptio...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• Preface to the Second Edition
• Introduction
• I: Food Security Policy Analysis
• II: Nutrition Policy Analysis
• III: Special Topics on Poverty, Nutrition and Food Policy Analysis
• Section IV: Technical Appendix
• Statistical Tables
• References
• Index