Empirical Methods for Inequality Analysis
A.Y. 2022/2023
Learning objectives
The purpose of this course is to introduce the students to the empirical methods commonly used to analyze several forms of inequality --- e.g. income inequality, educational inequality, inequality in the labor market, inequality inside the firm --- and the policies that can be undertaken to tackle them. The course is structured in three modules. In a first, more theoretical, module students will learn the main methods used in counterfactual impact evaluation and policy evaluation. Each method will be illustrated through an application with the STATA software. In a second, more applied, module students will learn how to measure poverty and inequality and how to deal with inequality decomposition using STATA and several datasets (e.g., the Luxembourg Income Study, the Bank of Italy's Survey of Household Income and Wealth). The third module will be focused on the analysis of gender inequality. This module will provide an overview of the recent literature in economics on different dimensions of the gender gaps (e.g. the gender pay gap), with a focus on the econometric methods used to evaluate gender differentials and some policies aimed at mitigating them.
Expected learning outcomes
By the end of the course students must acquire the following skills: 1) learning the main concepts related to the measurement and analysis of inequality and of the policies aimed at reducing it; 2) learning how to use statistical software and real data to analyze inequality and evaluate public policies which may impact individuals and firms; 3) being able to critically read the academic literature and policy reports related to inequality.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
The first module of Daniele Checchi will deal with theoretical models of inequality generation. It will be based on some chapter of the volumes of the Handbook of Income Distribution, edited by Anthony B. Atkinson and François Bourguignon
1. Agnar Sandmo, The Principal Problem in Political Economy: Income Distribution in the History of Economic Thought, Chapter 1 pp.3-65 of volume 2
2. Frank Cowell, Measurement of inequality, Chapter 2 pp.87-166 of volume 1
3. Frank A. Cowell and Emmanuel Flachaire, Statistical Methods for Distributional Analysis, Chapter 6 pp.359-465 of volume 2
4. Rolf Aaberge and Andrea Brandolini, Multidimensional Poverty and Inequality, Chapter 3 pp.141-216 of volume 2
5. John E. Roemer and Alain Trannoy. Equality of Opportunity, Chapter 4 pp.217-300 of volume 2
6. Markus Jäntti and Stephen P. Jenkins. Income Mobility, Chapter 10 pp.807-935 of volume 2
7. Jesper Roine and Daniel Waldenström. Long-Run Trends in the Distribution of Income and Wealth, Chapter 7 pp.469-592 of volume 2
8. Andrew E. Clark and Conchita D'Ambrosio. Attitudes to Income Inequality: Experimental and Survey Evidence, Chapter 13 pp.1147-1208 of volume 2
9. Thomas Piketty and Gabriel Zucman. Wealth and Inheritance in the Long Run, Chapter 15 pp. 1303-1368 of volume 2
10. Daron Acemoglu, Suresh Naidu, Pascual Restrepo, James A. Robinson. Democracy, Redistribution, and Inequality. Chapter 21 pp. 1885-1966 of volume 2
The second module will propose empirical applications of inequality decomposition. It will take as a reference text the LIS Annual report (forthcoming September 2021) and will use the remote access Lissy system (www.lisdataproject.org) to replicate most of the analysis contained in the report.
1. Measuring inequality and poverty (theory and statistical methods)
2. Measuring inequality and poverty (empirical applications)
3. Worldwide trends in inequality and poverty (chapter 1 of LIS AR)
4. Replicating trends in LIS using Lissy (https://www.lisdatacenter.org/data-access/lissy/)
5. Earnings inequality along various dimensions (education, gender and age) (chapter 2 of LIS AR)
6. Replicating decompositions in LIS using Lissy (https://www.lisdatacenter.org/data-access/lissy/)
7. Inequality in wages and in worked hours (Checchi-Penalosa-Vivan - Hours inequality, mimeo 2022)
8. Inequality in schooling and competences using PIAAC data (Checchi-Gualtieri, mimeo 2022)
9. Inequality of opportunity (Bussolo-Checchi- Peragine, mimeo 2022)
10. Inequality of opportunity measured in the Italian case using SHIW
Papers and data will be made available before the classes.
The third part of the course will provide an overview of some recent literature in economics on different gender gaps dimensions, with a focus on econometric methods used to evaluate gender differentials and policies aimed at mitigating them.
Topics:
- The gender gap in labor market outcomes: Trends across countries
- Traditional explanations: Human capital and discrimination
- Psychological traits
- Culture
- Glass ceiling and public policies
Papers and data will be made available before the classes.
1. Agnar Sandmo, The Principal Problem in Political Economy: Income Distribution in the History of Economic Thought, Chapter 1 pp.3-65 of volume 2
2. Frank Cowell, Measurement of inequality, Chapter 2 pp.87-166 of volume 1
3. Frank A. Cowell and Emmanuel Flachaire, Statistical Methods for Distributional Analysis, Chapter 6 pp.359-465 of volume 2
4. Rolf Aaberge and Andrea Brandolini, Multidimensional Poverty and Inequality, Chapter 3 pp.141-216 of volume 2
5. John E. Roemer and Alain Trannoy. Equality of Opportunity, Chapter 4 pp.217-300 of volume 2
6. Markus Jäntti and Stephen P. Jenkins. Income Mobility, Chapter 10 pp.807-935 of volume 2
7. Jesper Roine and Daniel Waldenström. Long-Run Trends in the Distribution of Income and Wealth, Chapter 7 pp.469-592 of volume 2
8. Andrew E. Clark and Conchita D'Ambrosio. Attitudes to Income Inequality: Experimental and Survey Evidence, Chapter 13 pp.1147-1208 of volume 2
9. Thomas Piketty and Gabriel Zucman. Wealth and Inheritance in the Long Run, Chapter 15 pp. 1303-1368 of volume 2
10. Daron Acemoglu, Suresh Naidu, Pascual Restrepo, James A. Robinson. Democracy, Redistribution, and Inequality. Chapter 21 pp. 1885-1966 of volume 2
The second module will propose empirical applications of inequality decomposition. It will take as a reference text the LIS Annual report (forthcoming September 2021) and will use the remote access Lissy system (www.lisdataproject.org) to replicate most of the analysis contained in the report.
1. Measuring inequality and poverty (theory and statistical methods)
2. Measuring inequality and poverty (empirical applications)
3. Worldwide trends in inequality and poverty (chapter 1 of LIS AR)
4. Replicating trends in LIS using Lissy (https://www.lisdatacenter.org/data-access/lissy/)
5. Earnings inequality along various dimensions (education, gender and age) (chapter 2 of LIS AR)
6. Replicating decompositions in LIS using Lissy (https://www.lisdatacenter.org/data-access/lissy/)
7. Inequality in wages and in worked hours (Checchi-Penalosa-Vivan - Hours inequality, mimeo 2022)
8. Inequality in schooling and competences using PIAAC data (Checchi-Gualtieri, mimeo 2022)
9. Inequality of opportunity (Bussolo-Checchi- Peragine, mimeo 2022)
10. Inequality of opportunity measured in the Italian case using SHIW
Papers and data will be made available before the classes.
The third part of the course will provide an overview of some recent literature in economics on different gender gaps dimensions, with a focus on econometric methods used to evaluate gender differentials and policies aimed at mitigating them.
Topics:
- The gender gap in labor market outcomes: Trends across countries
- Traditional explanations: Human capital and discrimination
- Psychological traits
- Culture
- Glass ceiling and public policies
Papers and data will be made available before the classes.
Prerequisites for admission
Students must be familiar with the main concepts learned in an undergraduate course in descriptive and inferential statistics. Taking this course after having passed "Advanced labour economics + personnel economics" and "Data analysis and statistics" is strongly advised.
Teaching methods
The course is based both on traditional lectures in which the main economic and statistical concepts related to inequality and policy evaluation are explained, and on more applied sessions in which students learn how to replicate existing empirical work using STATA and to set up and write a research paper or an analytical report. STATA is available to students through UNIMI's campus license.
Teaching Resources
The first module of Daniele Checchi will deal with theoretical models of inequality generation. It will be based on some chapter of the volumes of the Handbook of Income Distribution, edited by Anthony B. Atkinson and François Bourguignon
1. Agnar Sandmo, The Principal Problem in Political Economy: Income Distribution in the History of Economic Thought, Chapter 1 pp.3-65 of volume 2
2. Frank Cowell, Measurement of inequality, Chapter 2 pp.87-166 of volume 1
3. Frank A. Cowell and Emmanuel Flachaire, Statistical Methods for Distributional Analysis, Chapter 6 pp.359-465 of volume 2
4. Rolf Aaberge and Andrea Brandolini, Multidimensional Poverty and Inequality, Chapter 3 pp.141-216 of volume 2
5. John E. Roemer and Alain Trannoy. Equality of Opportunity, Chapter 4 pp.217-300 of volume 2
6. Markus Jäntti and Stephen P. Jenkins. Income Mobility, Chapter 10 pp.807-935 of volume 2
7. Jesper Roine and Daniel Waldenström. Long-Run Trends in the Distribution of Income and Wealth, Chapter 7 pp.469-592 of volume 2
8. Andrew E. Clark and Conchita D'Ambrosio. Attitudes to Income Inequality: Experimental and Survey Evidence, Chapter 13 pp.1147-1208 of volume 2
9. Thomas Piketty and Gabriel Zucman. Wealth and Inheritance in the Long Run, Chapter 15 pp. 1303-1368 of volume 2
10. Daron Acemoglu, Suresh Naidu, Pascual Restrepo, James A. Robinson. Democracy, Redistribution, and Inequality. Chapter 21 pp. 1885-1966 of volume 2
The second module will propose empirical applications of inequality decomposition. It will take as a reference text the LIS Annual report (forthcoming September 2021) and will use the remote access Lissy system (www.lisdataproject.org) to replicate most of the analysis contained in the report.
Third module
A reading list will be provided during the course and posted on the ARIEL website.
1. Agnar Sandmo, The Principal Problem in Political Economy: Income Distribution in the History of Economic Thought, Chapter 1 pp.3-65 of volume 2
2. Frank Cowell, Measurement of inequality, Chapter 2 pp.87-166 of volume 1
3. Frank A. Cowell and Emmanuel Flachaire, Statistical Methods for Distributional Analysis, Chapter 6 pp.359-465 of volume 2
4. Rolf Aaberge and Andrea Brandolini, Multidimensional Poverty and Inequality, Chapter 3 pp.141-216 of volume 2
5. John E. Roemer and Alain Trannoy. Equality of Opportunity, Chapter 4 pp.217-300 of volume 2
6. Markus Jäntti and Stephen P. Jenkins. Income Mobility, Chapter 10 pp.807-935 of volume 2
7. Jesper Roine and Daniel Waldenström. Long-Run Trends in the Distribution of Income and Wealth, Chapter 7 pp.469-592 of volume 2
8. Andrew E. Clark and Conchita D'Ambrosio. Attitudes to Income Inequality: Experimental and Survey Evidence, Chapter 13 pp.1147-1208 of volume 2
9. Thomas Piketty and Gabriel Zucman. Wealth and Inheritance in the Long Run, Chapter 15 pp. 1303-1368 of volume 2
10. Daron Acemoglu, Suresh Naidu, Pascual Restrepo, James A. Robinson. Democracy, Redistribution, and Inequality. Chapter 21 pp. 1885-1966 of volume 2
The second module will propose empirical applications of inequality decomposition. It will take as a reference text the LIS Annual report (forthcoming September 2021) and will use the remote access Lissy system (www.lisdataproject.org) to replicate most of the analysis contained in the report.
Third module
A reading list will be provided during the course and posted on the ARIEL website.
Assessment methods and Criteria
At the end of the course students must write a research paper or an analytical report on a given topic related to inequality. In the paper, students must apply some of the empirical methods they learned in the course. Both the paper with the final analysis and the dataset and programs that reproduce the results in the paper must be handed in. The paper can be single-authored or can be coauthored in groups of two or three students. The paper should contain a declaration of the contribution of each author to the whole analysis.
Professor(s)