Economics, Government and Administration | ECONOMIC STATISTICS

cod. 0223100011

ECONOMIC STATISTICS

	0223100011
	DEPARTMENT OF ECONOMICS AND STATISTICS
	EQF7
	ECONOMICS, GOVERNMENT AND ADMINISTRATION
	2022/2023

CURRICULUM ENVIRONMENTAL ECONOMICS AND ADMINISTRATION

	OBBLIGATORIO
	YEAR OF COURSE 2
	YEAR OF DIDACTIC SYSTEM 2018
	AUTUMN SEMESTER

TEACHING UNITS

	SSD	CFU	HOURS	ACTIVITY	TYPE OF ACTIVITY
	SECS-S/03	12	80	LESSONS	COMPULSORY SUBJECTS, CHARACTERISTIC OF THE CLASS

PROFESSORS

	GIUSEPPE STORTI T Curriculum
	VINCENZO CANDILA Curriculum

EXAMS

	Exam	Date	Session
	STATISTICA ECONOMICA	03/04/2023 - 09:00	SESSIONE ORDINARIA
	STATISTICA ECONOMICA	03/04/2023 - 09:00	SESSIONE DI RECUPERO

	Objectives
	KNOWLEDGE AND UNDERSTANDING AT THE END OF THE COURSE THE STUDENTS ARE EXPECTED TO MASTER THE MAIN STATISTICAL METHODS FOR PROGRAMME AND POLICY EVALUATION. IN PARTICULAR THE STUDENTS ARE EXPECTED TO GAIN -KNOWLEDGE OF THE ECONOMETRIC FOUNDATIONS OF PROGRAMME AND POLICY EVALUATION -KNOWLEDGE OF MAIN STATISTICAL METHODS AND MODELS FOR THE ANALYSIS OF PANEL DATA. -KNOWLEDGE OF THE MAIN METHODS FOR PROGRAMME AND POLICY EVALUATION IN EXPERIMENTAL AND NON-EXPERIMENTAL SETTINGS -KNOWLEDGE OF THE MAIN TECHNIQUES FOR THE TREATMENT OF SELECTION BIAS EFFECTS IN POLICY EVALUATION APPLYING KNOWLEDGE AND UNDERSTANDING THE STUDENTS ARE EXPECTED TO DEVELOP THE ABILITY TO USE ADVANCED MODELS FOR PROGRAMME AND POLICY EVALUATION. IN PARTICULAR THEY ARE EXPECTED TO GAIN THE FOLLOWING ABILITIES -ABILITY TO IDENTIFY IN REAL APPLICATIONS METHODS AND MODELS THAT ARE ADEQUATE TO THE SPECIFIC DATASET AND PROBLEM OF INTEREST -ABILITY TO USE A PC IN ORDER IMPLEMENT ON REAL DATA THE MAIN STATISTICAL METHODS TAUGHT IN THE COURSE -ABILITY TO INTERPRET, IN ECONOMIC AND POLITICAL TERMS, THE RESULTS OBTAINED FROM THE EMPIRICAL ANALYSES

KNOWLEDGE AND UNDERSTANDING
AT THE END OF THE COURSE THE STUDENTS ARE EXPECTED TO MASTER THE MAIN STATISTICAL METHODS FOR PROGRAMME AND POLICY EVALUATION.
IN PARTICULAR THE STUDENTS ARE EXPECTED TO GAIN
-KNOWLEDGE OF THE ECONOMETRIC FOUNDATIONS OF PROGRAMME AND POLICY EVALUATION
-KNOWLEDGE OF MAIN STATISTICAL METHODS AND MODELS FOR THE ANALYSIS OF PANEL DATA.
-KNOWLEDGE OF THE MAIN METHODS FOR PROGRAMME AND POLICY EVALUATION IN EXPERIMENTAL AND NON-EXPERIMENTAL SETTINGS
-KNOWLEDGE OF THE MAIN TECHNIQUES FOR THE TREATMENT OF SELECTION BIAS EFFECTS IN POLICY EVALUATION

APPLYING KNOWLEDGE AND UNDERSTANDING
THE STUDENTS ARE EXPECTED TO DEVELOP THE ABILITY TO USE ADVANCED MODELS FOR PROGRAMME AND POLICY EVALUATION. IN PARTICULAR THEY ARE EXPECTED TO GAIN THE FOLLOWING ABILITIES
-ABILITY TO IDENTIFY IN REAL APPLICATIONS METHODS AND MODELS THAT ARE ADEQUATE TO THE SPECIFIC DATASET AND PROBLEM OF INTEREST
-ABILITY TO USE A PC IN ORDER IMPLEMENT ON REAL DATA THE MAIN STATISTICAL METHODS TAUGHT IN THE COURSE
-ABILITY TO INTERPRET, IN ECONOMIC AND POLITICAL TERMS, THE RESULTS OBTAINED FROM THE EMPIRICAL ANALYSES

	Prerequisites
	BASIC KNOWLEDGE OF PROBABILITY, DESCRIPTIVE STATISTICS AND INFERENCE.

	Contents
	MODULE A (40 HOURS) MODULE A OF THE COURSE WILL PROVIDE THE STUDENTS WITH THE BASIC STATISTICAL FOUNDATIONS OF REGRESSION ANALYSIS. SYLLABUS: A REMINDER ON PROBABILITY AND STATISTICAL INFERENCE. THE MULTIPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS, THE ANALYSIS OF CAUSAL EFFECTS IN THE MULTIPLE LINEAR REGRESSION MODEL, EFFECTS OF THE OMISSION OF RELEVANT EXPLANATORY VARIABLES, CONTROL VARIABLES : DEFINITION, SELECTION CRITERIA AND PROPERTIES OF THE OLS ESTIMATORS. NON-LINEAR REGRESSION FUNCTIONS: POLYNOMIAL FUNCTIONS, LOGARITHMIC TRANSFORMATIONS, INTERACTIONS. REGRESSION MODELS WITH PANEL DATA: REGRESSION MODELS WITH FIXED AND TIME VARYING EFFECTS, PROPERTIES OF ESTIMATORS: MAIN ASSUMPTIONS AND COMPUTATION OF STANDARD ERRORS IN THE FIXED EFFECTS REGRESSION. INTRODUCTION TO THE STATISTICAL ANALYSIS OF TIME SERIES. THE PRESENTATION OF THEORETICAL ISSUES WILL BE COMPLEMENTED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA. MODULE B (40 HOURS) MODULE B OF THE COURSE WILL INTRODUCE THE STUDENTS TO SOME ADVANCED TOPICS IN REGRESSION ANALISYS AND TO THE STATISTICAL FOUNDATIONS OF POLICY EVALUATION. SYLLABUS: MODELS WITH BINARY DEPENDENT VARIABLE: THE LPM MODEL, THE LOGIT MODEL, THE PROBIT MODEL. REGRESSION MODELS WITH INSTRUMENTAL VARIABLES: MOTIVATION, STATISTICAL DEFINITION OF “INSTRUMENT”, RELEVANCE AND EXOGENEITY OF THE INSTRUMENTS, THE TWO STAGE LEAST SQUARES (TSLS) ESTIMATOR. BASIC ASSUMPTIONS AND STATISTICAL PROPERTIES OF THE TSLS ESTIMATOR. AN ELEMENTARY INTRODUCTION TO REGRESSION MODELS FOR BIG DATA: RIDGE AND LASSO. THE ESTIMATION OF CAUSAL EFFECTS: POTENTIAL RESULTS, CAUSAL EFFECTS AND IDEAL EXPERIMENTS; THREATS TO THE VALIDITY OF EXPERIMENTS; QUASI-EXPERIMENTS; THREATS TO THE VALIDITY OF EXPERIMENTS; QUASI-EXPERIMENTS. THE “EVALUATION PROBLEM”. THE COUNTERFACTUAL APPROACH TO THE EVALUATION OF EFFECTS, THE EXPERIMENTAL METHOD, SPATIO-TEMPORAL COMPARISONS WITH NON-EXPERIMENTAL DATA AND THREATS TO THEIR VALIDITY: STRNGTHS AND DRAWBACKS OF THE DIFF-IN-DIFF APPROACH. SELECTION BIAS AND STATISTICAL APPROACHES TO ITS TREATMENT: METHODS BASED ON REGRESSION ANALYSIS AND STATISTICAL MATCHING. METHODS BASED ON TREATMENT DISCONTINUITY. APPLICATIONS TO THE ITALIAN ECONOMY. THE PRESENTATION OF THEORETICAL ISSUES WILL BE COMPLEMENTED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

Contents

MODULE A (40 HOURS)
MODULE A OF THE COURSE WILL PROVIDE THE STUDENTS WITH THE BASIC STATISTICAL FOUNDATIONS OF REGRESSION ANALYSIS.
SYLLABUS:
A REMINDER ON PROBABILITY AND STATISTICAL INFERENCE.
THE MULTIPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS, THE ANALYSIS OF CAUSAL EFFECTS IN THE MULTIPLE LINEAR REGRESSION MODEL, EFFECTS OF THE OMISSION OF RELEVANT EXPLANATORY VARIABLES, CONTROL VARIABLES : DEFINITION, SELECTION CRITERIA AND PROPERTIES OF THE OLS ESTIMATORS.
NON-LINEAR REGRESSION FUNCTIONS: POLYNOMIAL FUNCTIONS, LOGARITHMIC TRANSFORMATIONS, INTERACTIONS.
REGRESSION MODELS WITH PANEL DATA: REGRESSION MODELS WITH FIXED AND TIME VARYING EFFECTS, PROPERTIES OF ESTIMATORS: MAIN ASSUMPTIONS AND COMPUTATION OF STANDARD ERRORS IN THE FIXED EFFECTS REGRESSION. INTRODUCTION TO THE STATISTICAL ANALYSIS OF TIME SERIES.
THE PRESENTATION OF THEORETICAL ISSUES WILL BE COMPLEMENTED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

MODULE B (40 HOURS)
MODULE B OF THE COURSE WILL INTRODUCE THE STUDENTS TO SOME ADVANCED TOPICS IN REGRESSION ANALISYS AND TO THE STATISTICAL FOUNDATIONS OF POLICY EVALUATION.
SYLLABUS:
MODELS WITH BINARY DEPENDENT VARIABLE: THE LPM MODEL, THE LOGIT MODEL, THE PROBIT MODEL.
REGRESSION MODELS WITH INSTRUMENTAL VARIABLES: MOTIVATION, STATISTICAL DEFINITION OF “INSTRUMENT”, RELEVANCE AND EXOGENEITY OF THE INSTRUMENTS, THE TWO STAGE LEAST SQUARES (TSLS) ESTIMATOR. BASIC ASSUMPTIONS AND STATISTICAL PROPERTIES OF THE TSLS ESTIMATOR. AN ELEMENTARY INTRODUCTION TO REGRESSION MODELS FOR BIG DATA: RIDGE AND LASSO.
THE ESTIMATION OF CAUSAL EFFECTS: POTENTIAL RESULTS, CAUSAL EFFECTS AND IDEAL EXPERIMENTS; THREATS TO THE VALIDITY OF EXPERIMENTS; QUASI-EXPERIMENTS; THREATS TO THE VALIDITY OF EXPERIMENTS; QUASI-EXPERIMENTS.
THE “EVALUATION PROBLEM”. THE COUNTERFACTUAL APPROACH TO THE EVALUATION OF EFFECTS, THE EXPERIMENTAL METHOD, SPATIO-TEMPORAL COMPARISONS WITH NON-EXPERIMENTAL DATA AND THREATS TO THEIR VALIDITY: STRNGTHS AND DRAWBACKS OF THE DIFF-IN-DIFF APPROACH. SELECTION BIAS AND STATISTICAL APPROACHES TO ITS TREATMENT: METHODS BASED ON REGRESSION ANALYSIS AND STATISTICAL MATCHING. METHODS BASED ON TREATMENT DISCONTINUITY. APPLICATIONS TO THE ITALIAN ECONOMY.
THE PRESENTATION OF THEORETICAL ISSUES WILL BE COMPLEMENTED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

	Teaching Methods
	CLASSROOM LECTURES (EQUALLY ALLOCATED BETWEEN THE TWO MODULES). THE LECTURES WILL INCLUDE THE DEVELOPMENT AND DISCUSSION OF REAL CASE STUDIES,

	Verification of learning
	THE SATISFACTORY ACHIEVEMENT OF THE AIMS OF THE COURSE IS ASSESSED THROUGH AN EXAM WITH MARKS OUT OF THIRTY. THE EXAM IS BASED ON A WRITTEN TEST THAT INCLUDES NUMERICAL EXERCISES AS WELL AS THEORETICAL QUESTIONS. THE PASS MARK IS 18/30. THE WRITTEN TEST, OF DURATION APPROXIMATELY EQUAL TO 90 MINUTES, IS AIMED AT ASSESSING THE KNOWLEDGE AND THE ABILITY TO UNDERSTAND THE SUBJECTS INDICATED IN THE COURSE PROGRAMME, THE ABILITY TO MASTER AND APPLY THE ANALYTICAL TOOLS REQUIRED AND THE ABILITY TO APPLY THE THEORETICAL NOTIONS TAUGHT. THE WRITTEN TEST REQUIRES I) THE SOLUTION OF NUMERICAL EXERCISES RELATED TO THE MAIN TOPICS COVERED DURING THE COURSE (E.G. IMPLEMENTING METHODS FOR POLICY EVALUATION OR EVELUATION OF THEIR PROPERTIES) II) ANSWERING TO THEORETICAL QUESTIONS ON THE TOPICS INCLUDED IN THE COURSE PROGRAMME III) FORMULATING CRITICAL CONSIDERATIONS ON THE RESULTS OF REAL CASE STUDIES. DURING THE WRITTEN TEST STUDENTS ARE NOT ALLOWED TO READ TEXTBOOKS, USE PCS, TABLETS AND MOBILE PHONES; THEY ARE ONLY ALLOWED TO USE A BASIC ELECTRONIC CALCULATOR AND THE USUAL STATISTICAL TABLES. IN PARTICULAR, IN THE ASSESSMENT PROCESS, THE FOCUS WILL BE ON EVALUATING THE ABILITY TO CORRECTLY APPLY THE TAUGHT METHODS, THE RIGOUR AND CLARITY OF EXPRESSION.

Verification of learning

THE SATISFACTORY ACHIEVEMENT OF THE AIMS OF THE COURSE IS ASSESSED THROUGH AN EXAM WITH MARKS OUT OF THIRTY.
THE EXAM IS BASED ON A WRITTEN TEST THAT INCLUDES NUMERICAL EXERCISES AS WELL AS THEORETICAL QUESTIONS. THE PASS MARK IS 18/30.

THE WRITTEN TEST, OF DURATION APPROXIMATELY EQUAL TO 90 MINUTES, IS AIMED AT ASSESSING THE KNOWLEDGE AND THE ABILITY TO UNDERSTAND THE SUBJECTS INDICATED IN THE COURSE PROGRAMME, THE ABILITY TO MASTER AND APPLY THE ANALYTICAL TOOLS REQUIRED AND THE ABILITY TO APPLY THE THEORETICAL NOTIONS TAUGHT.
THE WRITTEN TEST REQUIRES I) THE SOLUTION OF NUMERICAL EXERCISES RELATED TO THE MAIN TOPICS COVERED DURING THE COURSE (E.G. IMPLEMENTING METHODS FOR POLICY EVALUATION OR EVELUATION OF THEIR PROPERTIES) II) ANSWERING TO THEORETICAL QUESTIONS ON THE TOPICS INCLUDED IN THE COURSE PROGRAMME III) FORMULATING CRITICAL CONSIDERATIONS ON THE RESULTS OF REAL CASE STUDIES.
DURING THE WRITTEN TEST STUDENTS ARE NOT ALLOWED TO READ TEXTBOOKS, USE PCS, TABLETS AND MOBILE PHONES; THEY ARE ONLY ALLOWED TO USE A BASIC ELECTRONIC CALCULATOR AND THE USUAL STATISTICAL TABLES.

IN PARTICULAR, IN THE ASSESSMENT PROCESS, THE FOCUS WILL BE ON EVALUATING THE ABILITY TO CORRECTLY APPLY THE TAUGHT METHODS, THE RIGOUR AND CLARITY OF EXPRESSION.

	Texts
	FOR MODULE A JAMES H. STOCK, MARK W. WATSON (2020) INTRODUCTION TO ECONOMETRICS (GLOBAL EDITION), IV EDITION. CAP. 1-10. PEARSON. FOR MODULE B JAMES H. STOCK, MARK W. WATSON (2016) INTRODUCTION TO ECONOMETRICS (GLOBAL EDITION), IV EDITION. CAP. 11-14. ALBERTO MARTINI, LUCA MO COSTABELLA, MARCO SISTI, BARBARA ROMANO (2006) VALUTARE GLI EFFETTI DELLE POLITICHE PUBBLICHE/METODI E APPLICAZIONI AL CASO ITALIANO (ITALIAN), FORMEZ. DOWNLOADABLE FROM THE URL HTTP://FOCUS.FORMEZ.IT/CONTENT/VALUTARE-EFFETTI-POLITICHE-PUBBLICHEMETODI-E-APPLICAZIONI-CASO-ITALIANO. FOR DEEPER INSIGHTS ON THE TOPICS ILLUSTRATED IN MODULE B THE STUDENTS CAN ALSO REFER TO THE PAPER: GUIDO W. IMBENS, JEFFREY M. WOOLDRIDGE (2009) RECENT DEVELOPMENTS IN THE ECONOMETRICS OF PROGRAM EVALUATION, JOURNAL OF ECONOMIC LITERATURE, VOL. 47, NO. 1, MARCH 2009 (PP. 5-86).

Texts

FOR MODULE A
JAMES H. STOCK, MARK W. WATSON (2020) INTRODUCTION TO ECONOMETRICS (GLOBAL EDITION), IV EDITION. CAP. 1-10. PEARSON.

FOR MODULE B
JAMES H. STOCK, MARK W. WATSON (2016) INTRODUCTION TO ECONOMETRICS (GLOBAL EDITION), IV EDITION. CAP. 11-14.

ALBERTO MARTINI, LUCA MO COSTABELLA, MARCO SISTI, BARBARA ROMANO (2006) VALUTARE GLI EFFETTI DELLE POLITICHE PUBBLICHE/METODI E APPLICAZIONI AL CASO ITALIANO (ITALIAN), FORMEZ.
DOWNLOADABLE FROM THE URL
HTTP://FOCUS.FORMEZ.IT/CONTENT/VALUTARE-EFFETTI-POLITICHE-PUBBLICHEMETODI-E-APPLICAZIONI-CASO-ITALIANO.

FOR DEEPER INSIGHTS ON THE TOPICS ILLUSTRATED IN MODULE B THE STUDENTS CAN ALSO REFER TO THE PAPER:

GUIDO W. IMBENS, JEFFREY M. WOOLDRIDGE (2009) RECENT DEVELOPMENTS IN THE ECONOMETRICS OF PROGRAM EVALUATION, JOURNAL OF ECONOMIC LITERATURE, VOL. 47, NO. 1, MARCH 2009 (PP. 5-86).