Statistics for environmental policy
The aim of the course is to provide the skills necessary to understand and apply statistical tools for the analysis of environmental data and the evaluation of the main national and European environmental policies. The course aims to integrate the theoretical and applied approaches, on each topic empirical exercises with real data are provided.
Expected learning outcomes:
knowledge and understanding: The students will have to demonstrate understanding the fundamental concepts of the discipline. The students will have to know how to use the main tools to analyze the social and economic impact of environmental issues. It is essential to be able to consult the main statistical sources as well as to use statistical tools to interpret environmental phenomena.
Applying knowledge and understanding: the students must know how to build matrices of data and manage them through software. They must be able to correctly interpret the outputs provided by the statistical software. The students must be able to understand the interdependence between the socio-economic system and the environmental one.
Making judgements: the students should develop the skills necessary to assess the effectiveness of environmental policies and the factors that can determine their success/failure. The students should also demonstrate interest in analyzing an environmental phenomenon as well as the ability to assess its implications.
Communication: the students should be able to answer with clearly and competently to the questions of the oral exams. The students should also be able to explain with clearly and competently the results obtained from the analyses conducted (with the professor and/or independently) and to contextualize the environmental phenomenon analyzed highlighting the interdependencies with the socio-economic system.
Lifelong learning skills: The students should be able to show a good learning ability and autonomy in investigating in-depth the matters of the Course using the references provided by the professor.
It is required the knowledge of the basic concepts of Statistics (descriptive, and inferential) and Economic.
Part I (24 HOURS):
The role of statistics in the analysis of environmental phenomena. Types and sources of environmental data. The main national environmental regulations and the European guidelines. Descriptive and inferential statistics. The moments of the distribution. The ordinary least square estimation. The properties of the ordinary least squares estimators. The simple linear regression model. Inference in the simple linear regression model.
Part II (24 HOURS):
Multiple linear regression. The assumptions of the multiple linear regression model. Inference in the multiple linear regression model. Regression with binary variables. Construction of the optimal model. Models comparison. Logit and probit regressions for binary, ordinal and multinational data.
Traditional lectures. Empirical applications. Periodic exercises.
Levine, D.M., Szabat, K.A., Stephan, D.F. Statistica (settima edizione). Pearson (cap. 2, 3, 12, 13)
Stock, J.H., Watson, M.H. Introduzione all’Econometria. Pearson (cap. 11)
ISPRA. Ambiente in Italia Trend e Normative 2019. Annuario dei dati ambientali 2019
The learning assessment is based on intermediate verification tests. It is required the discussion of an essay in which the students should demonstrate the achievement of the educational objectives of the course; the minimum score is 18 points out of 30. The oral exam consists in questions on the main contents of the course; the minimum score is 18 points out of 30. The students should be able to clearly explain the fundamental concepts learned during the course. The final grade will be obtained as an average of the results obtained in the intermediate tests. If the total score is less than 18 or if one of the intermediate verifications is insufficient, the student must repeat the entire exam. Without doing the intermediate tests, the learning assessment is verified by an oral exam on the entire course program.