79216 - Measurements of Productivity, Competitiveness and Efficiency

Academic Year 2023/2024

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Statistics, Economics and Business (cod. 8876)

Learning outcomes

The course aims to provide students with the basic knowledge needed to define productivity, efficiency and competitiveness measurement models in order to address the issues of estimating panel data models in the analysis of convergence and economic growth.

Course contents

Measurement and analysis .

Measures of general and partial productivity of labor and capital. Global Productivity; lindices of Kendrick and Solow. Total factor productivity.Quality adjustment methods.

Methods of decomposition of productivity. Relationship between productivity, employment and growth.

Growth and development.

The theory of growth and development. Neoclassical model and conditional convergence tests. Clubs Convergence.Endogenous Models. Cross-countries based analysis: panel data models; measurement, estimation and tests.

Spatial growth models.

Exploratory data analysis, Moran test, local & global.

Spatial Weight Matrix: Spatial Contiguity; Geographical Distance; K-Nearest Neighbors.

Spatial Lag Variables: Spatial Independent Variables; Spatial Dependent Variables; Spatial Error Variable.

Spatial Models: Spatial Exogenous Model, Spatial Lag Mode, Spatial Mixed Model, Spatial Error Model (Spatial AR (1); Spatial MA (1); Spatial ARMA (1,1); Spatial Error Components Model).

Estimators: LS, ML, Moments, SHAC.

Specification Tests: ML based Tests. LM based Tests.


Eurostat, Methodologies and working papers, (2006), 31st CEIES Seminar: Are we measuring productivity correctly?

Mulas A., Bracalente B, Cossignani M. (2009), Statistica Aziendale, Mc Graw Hill, (Cap 6.1,6.2,6.3).

Anselin L. (2003), Spatial Econometrics, in A comparison to theoretical econometrics, BH Baldagi Ed, Blackwell Publishing Ltd.

Extra material will be provided by the Prof.Bernardini Papalia

Teaching methods

Teachers lectures supplemented with tutorials or experiment sessions

Assessment methods

Written exam

The final examination is in the form of a written test consisting of 1 exercise and 2 both theoretical and empirical questions; exam time: 50 minutes; it is not allowed to consult books or class notes.

For students attending the course

A group work is planned:

  • Two real data exemples related to the topics discussed in the course to be solved in lab (max 5 students) and to be completed by the date of the first exam.
  • Classroom presentation of one paper is scheduled by the end of the course (max 20 minutes; the material is partially provided by the teacher).

Group work evaluation can lead to an increase in the final evaluation from 0 to a maximum of 4 points.

Teaching tools

Teaching material available on the web.

Reference distribution list: rossella.bernardini.app

Teaching tools

Slides and teaching materials - exercises and examples - concerning lectures are prepared by the teacher and available on line (via Reference distribution list).

Topics are presented using pc and video-projector.

Office hours

See the website of Rosa Bernardini Papalia


Decent work and economic growth

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.