UE391 - Measurement of socioeconomic facts and policy outcomes

Type d'UE
Méthodologie
Disciplines
Économie, Histoire, Sociologie
Page web
-
Langues
anglais
Mots-clés
Développement Économie politique Enquêtes Inégalités Méthodes et techniques des sciences sociales Méthodes quantitatives Politiques publiques Politiques sociales
Aires culturelles
-

How do we assess the effectiveness of measures taken to pursue social objectives? This course aims to discuss the quantitative measurement of the main socioeconomic variables used in the evaluation of public policy, in both developed and developing countries. These include GDP, poverty and inequality, employment and unemployment, health and education, segregation, environmental indicators. First, the course surveys the conceptual debates around definitions of variables: wealth and growth, poverty and inequality, labor productivity, education, health etc. Second, it develops the axiomatic arguments (with their varying degrees of mathematical reasoning) that may lead one to choose an indicator over another. Special attention is given to the issues raised by agent heterogeneity and multidimensional welfare. Then, the course will analyze how those theoretical indicators are materialized and calculated on actual data, such as can be obtained from national accounts, administrative sources or sample surveys. A central goal of the course is to enable students to better understand several controversial issues, in which measurement problems play a major role: is poverty declining or rising? What about unemployment? How do different countries compare, in terms of development, living conditions or education?

1. Constructing social facts: conceptual and axiomatic issues

2.  Constructing social facts: measurement and sampling

3. Health

4.  National Accounts

5.  Prices and Purchasing Power

6.   Income and monetary poverty

7.   Inequality

8.  Labor and unemployment

9. Education

  • Politiques publiques et développement – M1/S1
    Suivi et validation – semestriel hebdomadaire = 3 ECTS
    MCC – autre (contrôle continu et examen final)
  • Denis Cogneau [référent·e]   directeur d'études, EHESS - directeur de recherche, IRD / Paris School of Economics (PJSE)
  • Julien Grenet   chargé de recherche, CNRS / Paris School of Economics (PJSE)
  • Pauline Charousset   doctorante, EHESS / Paris School of Economics (PJSE)
Contacts additionnels
-
Informations pratiques

Lucia-Roxana Ban. Secrétariat des études du master PPD. Ecole d'Economie de Paris

Direction de travaux des étudiants
-
Réception des candidats

Lucia-Roxana Ban. Secrétariat des études du master PPD. Ecole d'Economie de Paris

Pré-requis

Some knowledge in microeconomics is needed (especially consumer theory from the household microeconomics course).

Notions of statistics: conditional probabilities, expectation and conditional expectation, variance and covariance, density function and cdf, simple and multiple regression.

  • 48 bd Jourdan
    48 bd Jourdan 75014 Paris
    1er semestre / hebdomadaire, jeudi 14:00-16:00
    du 10 septembre 2020 au 10 décembre 2020


Intervenant·e·s


  • Denis Cogneau [référent·e]   directeur d'études, EHESS - directeur de recherche, IRD / Paris School of Economics (PJSE)
  • Julien Grenet   chargé de recherche, CNRS / Paris School of Economics (PJSE)
  • Pauline Charousset   doctorante, EHESS / Paris School of Economics (PJSE)

Planning


  • 48 bd Jourdan
    48 bd Jourdan 75014 Paris
    1er semestre / hebdomadaire, jeudi 14:00-16:00
    du 10 septembre 2020 au 10 décembre 2020


Description


Type d'UE
Méthodologie
Disciplines
Économie, Histoire, Sociologie
Page web
-
Langues
anglais
Mots-clés
Développement Économie politique Enquêtes Inégalités Méthodes et techniques des sciences sociales Méthodes quantitatives Politiques publiques Politiques sociales
Aires culturelles
-

How do we assess the effectiveness of measures taken to pursue social objectives? This course aims to discuss the quantitative measurement of the main socioeconomic variables used in the evaluation of public policy, in both developed and developing countries. These include GDP, poverty and inequality, employment and unemployment, health and education, segregation, environmental indicators. First, the course surveys the conceptual debates around definitions of variables: wealth and growth, poverty and inequality, labor productivity, education, health etc. Second, it develops the axiomatic arguments (with their varying degrees of mathematical reasoning) that may lead one to choose an indicator over another. Special attention is given to the issues raised by agent heterogeneity and multidimensional welfare. Then, the course will analyze how those theoretical indicators are materialized and calculated on actual data, such as can be obtained from national accounts, administrative sources or sample surveys. A central goal of the course is to enable students to better understand several controversial issues, in which measurement problems play a major role: is poverty declining or rising? What about unemployment? How do different countries compare, in terms of development, living conditions or education?

1. Constructing social facts: conceptual and axiomatic issues

2.  Constructing social facts: measurement and sampling

3. Health

4.  National Accounts

5.  Prices and Purchasing Power

6.   Income and monetary poverty

7.   Inequality

8.  Labor and unemployment

9. Education


Master


  • Politiques publiques et développement – M1/S1
    Suivi et validation – semestriel hebdomadaire = 3 ECTS
    MCC – autre (contrôle continu et examen final)

Renseignements


Contacts additionnels
-
Informations pratiques

Lucia-Roxana Ban. Secrétariat des études du master PPD. Ecole d'Economie de Paris

Direction de travaux des étudiants
-
Réception des candidats

Lucia-Roxana Ban. Secrétariat des études du master PPD. Ecole d'Economie de Paris

Pré-requis

Some knowledge in microeconomics is needed (especially consumer theory from the household microeconomics course).

Notions of statistics: conditional probabilities, expectation and conditional expectation, variance and covariance, density function and cdf, simple and multiple regression.