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Quantitative Methods Lab

lauree magistrali

The course aims at providing students with the quantitative methods for the economic and policy analysis. The course is structured in three modules. Each module covers different concepts and methods with a quantitative applied approach:

Module 1 (Paglialunga): Dynamic CGE models for ex-ante climate and energy policy impact evaluation (20 h)
Module 2 (Giua): Counterfactual evaluation of public policies ex-post impact (20 h)
Module 3 (Lelo): Geospatial information for socio-economic and environmental analysis (20 h)

Module 1: The purpose of this module is to provide students with an introduction to dynamic global computable general equilibrium (CGE) modelling using a dynamic-energy version of Global Trade Analysis Project (GTAP) model. The course objective is to provide analytical and empirical tools for constructing and implementing large-scale, dynamic, multisectoral general equilibrium models for ex-ante climate and energy policy impact evaluation. The main emphasis is on developing a level of understanding about the model, data and the formulation of policy experiments that allows the use of the dynamic-energy GTAP model to conduct practical modelling exercises for climate and energy policy analyses.

Module 2: This module focuses on the ex-post assessment of public policies. The purpose is to provide students with the concepts and the quantitative skills for approaching the counterfactual policy evaluation framework. Students will become familiar with the empirical methods for the policy assessment. In particular, they will learn 1) the theoretical elements of the relevant econometric methodologies; 2) how to assess the impact of different policies according to their principal characteristics (firms/individual incentives, regional development program, spatially targeted interventions); 3) how to implement a counterfactual evaluation with respect to different policies (practical applications).

Module 3: The purpose of this module is to introduce techniques of geospatial analysis applied to socio-economic and environmental studies. Students will become familiar with concepts such as georeferenced data, database management systems, remote sensing and spatial analysis, and their potential uses in different fields of applied economics. The objective is to follow a complete workflow from multisource data acquisition and management up to the generation of new spatial information and spatial models, in conformity with the research questions previously defined. Expected outputs will consist in the generation of spatial quantitative indicators and their cartographic representation.

Teaching material
Exam textbooks, reading list, lecture notes and lab materials will be provided at the beginning of each module of the course.

The course assessment will be based on a written exam. Students attending the class regularly will have the possibility to substitute the final exam with assignments on the quantitative methods covered in the three modules.

Il corso si svolge nel I semestre (dal 16/9/2019 al 14/12/2019)

Docenti: Elena Paglialunga (docente titolare), Mara Giua (docente titolare), Keti Lelo (docente titolare)

Crediti: 9

Numero moduli: 3

Date di esame


Module 1

- Introduction to dynamic general equilibrium modelling for environmental policy analysis
- Model structure, overview of CGE-based analysis and data requirement
- Designing the model: regional and sector aggregation, timing, calibration and sensitivity
- Formulating scenarios and running policy simulations
- Reporting and interpreting the results
- Modelling tradable pollution permits
- Modelling carbon taxes
- Modelling EU energy and climate policy mix
- Modelling international climate negotiation
- Modelling the cost of climate change 

Module 2

- Introduction to the impact assessment of public policies
- Theoretical framework of counterfactual evaluation
- Overview of the principal methods: Matching; Difference-in-differences; Regression discontinuity designs; Synthetic control
- Elements of a counterfactual evaluation: conditions for the as good as random scenario; identification strategy; model; testing the validity; robustness
- Implementation of counterfactual evaluation in practice (e.g., evaluating the impact of the European regional policy on growth and employment via Regression Discontinuity Design)

Module 3

- Introduction to spatial data models
- Introductions to database management systems
- Geographic Information Systems and their applications
- Geospatial databases: how, where and when
- Retrieving and using socio-economic and environmental spatial data
- Defining and applying specific spatial data models
- Generating new spatial information
- Mapping and representing socio-economic and environmental information
- Modelling spatial phenomena
- Working with spatio-temporal scenarios





[ ultimo aggiornamento 18/7/2019 ]


Module I

Burfisher, M. (2017).Introduction to Computable General Equilibrium Models. Cambridge: Cambridge University Press. doi:10.1017/9781316450741
Chapters: 1, 2, 3, 4, 5, 6

Antimiani, A., Costantini, V., Paglialunga, E., Kuik, O. (2016). Mitigation of adverse effects on competitiveness and leakage of unilateral EU climate policy: An assessment of policy instruments. Ecological Economics, 128, pp. 246-259. https://doi.org/10.1016/j.ecolecon.2016.05.003

Corradini, M., Costantini, V., Markandya, A., Paglialunga, E., Sforna, G. (2018). A dynamic assessment of instrument interaction and timing alternatives in the EU low-carbon policy mix design. Energy policy, 120, pp. 73-84. https://doi.org/10.1016/j.enpol.2018.04.068

Antimiani, A., Costantini, V., Markandya, A., Paglialunga, E., Sforna, G. (2017). The Green Climate Fund as an effective compensatory mechanism in global climate negotiations. Environmental Science and Policy, 77, pp. 49-68. https://doi.org/10.1016/j.envsci.2017.07.015

Module II

Angrist, J. and Pischke, J.S. (2009): Mostly harmless econometrics, Princeton University Press, NJ.
Chapters: 1, 2, 3, 5, 6.

Blundell, R. and Costa-Dias, M. (2009): Alternative Approaches to Evaluation in Empirical Microeconomics, Journal of Human Resources, 44(3).

Dell, M. (2010): The Persistent Effects of Peru's Mining Mita, Econometrica,78, 1863–1903.


Module III

de By, R.A (ed.) (2001): Principles of Geographic Information Systems. An introductory textbook, ITC. Educational Textbook Series 1, Enschede.
Chapters: 1, 2, 3, 5, 6

Martínez, J.A., Pfeffer, K. and Baud, I. (2016): Factors shaping cartographic representations of inequalities: maps as products and processes, Habitat International: A Journal for the Study of Human Settlements, 51 (2016) pp. 90-102.

ISTAT (2015) La nuova geografia dei sistemi locali, on-line: http://www.istat.it/it/archivio/172444
ISTAT (2014) Rapporto BES, on-line: www.istat.it/it/archivio/126613





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