Unveiling Disparities: Inequality and Poverty Measurement Techniques Training Course

Introduction

In an era of increasing global awareness, understanding and addressing inequality and poverty are central to achieving sustainable development and social justice. However, accurately measuring these complex phenomena is far from straightforward. The choice of metrics, data sources, and methodological approaches profoundly influences our perception of poverty's depth and inequality's extent, directly impacting policy design, resource allocation, and the effectiveness of interventions aimed at improving human well-being. A robust grasp of measurement techniques is therefore indispensable for anyone engaged in development, research, or public policy.

This intensive training course is meticulously designed to equip participants with a comprehensive and practical understanding of the most widely used and cutting-edge techniques for measuring poverty and inequality. From dissecting the theoretical underpinnings of various indices and exploring the nuances of income versus multidimensional approaches, to mastering the practical application of these tools using real-world data, you will gain the expertise to rigorously analyze and interpret socio-economic disparities. This empowers you to contribute to evidence-based policy formulation, monitor progress towards development goals, and effectively communicate the realities of poverty and inequality to diverse stakeholders.

Target Audience

  • Development practitioners and program managers.
  • Statisticians and data analysts in national statistics offices and research institutions.
  • Policy analysts and advisors in government ministries (e.g., planning, finance, social affairs).
  • Researchers and academics in economics, sociology, and public policy.
  • Monitoring & Evaluation (M&E) specialists.
  • Professionals from international organizations and NGOs working on poverty reduction and inequality.
  • Graduate students (Master's and PhD) in economics, development studies, or social statistics.
  • Anyone involved in designing, implementing, or evaluating social protection programs.

Duration: 10 days

Course Objectives

Upon completion of this training course, participants will be able to:

  • Understand the conceptual definitions of poverty and inequality and their various dimensions.
  • Grasp the theoretical properties and axioms of different poverty and inequality measures.
  • Analyze various unidimensional poverty measures (e.g., headcount ratio, poverty gap) and their limitations.
  • Comprehend the methodology and application of multidimensional poverty indices (MPIs).
  • Evaluate common measures of income inequality (e.g., Gini coefficient, Lorenz curve, Theil index).
  • Develop practical skills in using household survey data to calculate and interpret poverty and inequality statistics.
  • Navigate challenges in data collection, comparability, and robustness of poverty and inequality estimates.
  • Formulate evidence-based insights on poverty and inequality trends for policy dialogue and program design.

Course Content

  1. Introduction to Poverty and Inequality Concepts
  • Defining poverty: absolute vs. relative, monetary vs. non-monetary
  • Understanding different dimensions of poverty: income, consumption, capabilities, well-being
  • Defining inequality: income, wealth, consumption, opportunities
  • Why measure poverty and inequality? Policy relevance and monitoring SDGs
  • Data sources for poverty and inequality analysis: household surveys (HIES, LSMS), administrative data
  1. Unidimensional Poverty Measurement: Core Concepts
  • Welfare aggregates: income vs. consumption, and equivalence scales
  • Setting the poverty line: absolute, relative, subjective methods
  • The Foster-Greer-Thorbecke (FGT) family of poverty measures:
    • Headcount ratio
    • Poverty gap index
    • Squared poverty gap index (poverty severity)
  • Axiomatic properties of poverty measures: monotonicity, transfer, subgroup decomposability
  1. Multidimensional Poverty Measurement
  • Limitations of unidimensional poverty measures
  • Motivations for multidimensional approaches (e.g., Amartya Sen's Capability Approach)
  • Identification and aggregation methods for multidimensional poverty
  • The Alkire-Foster (AF) method and the global Multidimensional Poverty Index (MPI)
  • Dimensions, indicators, and weighting in MPI construction
  • Comparing MPI with income poverty measures and policy applications
  1. Measurement of Income Inequality
  • Visualizing inequality: Lorenz curve and its properties
  • The Gini coefficient: calculation, interpretation, and limitations
  • Entropy measures: Theil index, Atkinson index and their sensitivity to different parts of the distribution
  • Quantile ratios: S80/S20, decile ratios
  • Axiomatic properties of inequality measures: anonymity, scale invariance, population independence, Pigou-Dalton transfer principle
  1. Data Issues and Robustness Checks
  • Survey design and data quality challenges for poverty and inequality measurement
  • Non-sampling errors: non-response, measurement error
  • Adjusting for prices: Consumer Price Index (CPI), Purchasing Power Parity (PPP)
  • Spatial and temporal comparability of poverty and inequality estimates
  • Robustness of poverty lines and sensitivity analysis
  • Stochastic dominance: comparing distributions without choosing a specific poverty line
  1. Decomposing Poverty and Inequality
  • Subgroup decomposition of poverty measures: rural/urban, gender, regions
  • Decomposing the Gini coefficient by income sources and population subgroups
  • Understanding the drivers of changes in poverty and inequality over time
  • Growth-inequality-poverty (GIP) triangles and elasticities
  • Analyzing the pro-poorness of growth
  1. Poverty Dynamics and Vulnerability
  • Chronic vs. transient poverty: definitions and measurement challenges
  • Using panel data to analyze poverty dynamics and transitions
  • Determinants of poverty persistence and exit
  • Measuring vulnerability to poverty: ex-ante vs. ex-post approaches
  • Risk factors and coping strategies of vulnerable households
  1. Poverty and Inequality in Practice: Case Studies
  • Global poverty trends and the Sustainable Development Goals (SDGs)
  • Country-specific poverty assessments: methodology and findings
  • Analysis of within-country inequalities (e.g., rural-urban, regional disparities)
  • Impact of specific policies (e.g., social protection programs, tax reforms) on poverty and inequality
  • Challenges in measuring poverty and inequality in specific contexts (e.g., fragile states, humanitarian settings)
  1. Policy Relevance and Communication
  • Using poverty and inequality data to inform policy design and targeting
  • Monitoring progress towards national and international development goals
  • Data visualization for effective communication of complex statistics
  • Bridging the gap between data producers and data users
  • Ethical considerations in poverty and inequality measurement and reporting
  1. Advanced Topics and Emerging Issues
  • Asset-based poverty measures and wealth inequality
  • Distributional National Accounts (DINA): integrating micro and macro data
  • Measuring inequality of opportunity vs. inequality of outcome
  • Behavioral economics insights into poverty
  • Big data and machine learning for poverty mapping and nowcasting
  • Poverty and inequality in the context of climate change and shocks.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

Unveiling Disparities: Inequality And Poverty Measurement Techniques Training Course in Kenya
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