Giuseppe STORTI | ECONOMIC STATISTICS

cod. 0223100011

ECONOMIC STATISTICS

	0223100011
	DEPARTMENT OF ECONOMICS AND STATISTICS
	EQF7
	ECONOMICS, GOVERNMENT AND ADMINISTRATION
	2024/2025

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
	ANTONIO NAIMOLI Curriculum

EXAMS

Exam	Date	Session
STORTI	16/12/2024 - 09:00	SESSIONE ORDINARIA
STORTI	16/12/2024 - 09:00	SESSIONE DI RECUPERO
STORTI	13/01/2025 - 09:00	SESSIONE ORDINARIA
STORTI	13/01/2025 - 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 (58 HOURS) MODULE A WILL PROVIDE THE STATISTICAL FOUNDATIONS OF REGRESSION ANALYSIS. TOPICS: A REMINDER OF STATISTICS AND PROBABILITY (10 HRS). THE SIMPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS (8 HRS). THE MULTIPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS, ANALYSIS OF CAUSAL EFFECTS IN THE MULTIPLE LINEAR REGRESSION MODEL, EFFECTS OF OMITTING RELEVANT VARIABLES, CONTROL VARIABLES: DEFINITION, CRITERIA FOR SELECTING VARIABLES AND PROPERTIES OF OLS ESTIMATES (20 HRS). NON-LINEAR REGRESSION FUNCTIONS: POLYNOMIAL FUNCTIONS, LOGARITHMIC TRANSFORMATIONS, INTERACTIONS, ELASTICITY (14 HRS). REGRESSION MODELS WITH PANEL DATA: REGRESSION WITH FIXED EFFECTS AND TIME EFFECTS, PROPERTIES OF ESTIMATORS: BASIC ASSUMPTIONS AND CALCULATION OF STANDARD ERRORS IN REGRESSION WITH FIXED EFFECTS. SOME REMARKS ON THE STATISTICAL ANALYSIS OF TIME SERIES (6 HRS). THE PRESENTATION OF THEORETICAL ARGUMENTS WILL BE ACCOMPANIED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA. MODULE B (22 HOURS) MODULE B WILL EXPLAIN SOME ADVANCED ASPECTS OF REGRESSION ANALYSIS AND PROVIDE AN INTRODUCTION TO STATISTICAL METHODS FOR POLICY EVALUATION. TOPICS: MODELS WITH BINARY DEPENDENT VARIABLE: THE LPM MODEL, LOGIT MODELS, AND PROBIT MODELS (6 HOURS). REGRESSION MODELS WITH INSTRUMENTAL VARIABLES: MOTIVATION, DEFINITION OF ‘INSTRUMENT’, INSTRUMENT RELEVANCE AND EXOGENEITY, THE TWO STAGE LEAST SQUARES (TSLS) ESTIMATOR. BASIC ASSUMPTIONS AND PROPERTIES OF THE TSLS ESTIMATOR (4 HOURS). THE ‘VALUATION’ PROBLEM. THE COUNTERFACTUAL APPROACH TO EFFECT EVALUATION, THE EXPERIMENTAL METHOD (ESTIMATION OF CAUSAL EFFECTS, THREATS TO THE VALIDITY OF EXPERIMENTS), SPATIOTEMPORAL COMPARISONS WITH NON-EXPERIMENTAL DATA AND THREATS TO THEIR VALIDITY: LIMITATIONS AND ADVANTAGES OF THE DIFF-IN-DIFF APPROACH. SELECTION BIAS AND STATISTICAL APPROACHES TO ITS TREATMENT: METHODS BASED ON REGRESSION ANALYSIS, STATISTICAL MATCHING. METHODS BASED ON DISCONTINUITY IN TREATMENT. APPLICATIONS TO THE ITALIAN ECONOMY (12 HOURS). THE PRESENTATION OF THEORETICAL ARGUMENTS WILL BE ACCOMPANIED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

Contents

MODULE A (58 HOURS)
MODULE A WILL PROVIDE THE STATISTICAL FOUNDATIONS OF REGRESSION ANALYSIS.
TOPICS:
A REMINDER OF STATISTICS AND PROBABILITY (10 HRS).
THE SIMPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS (8 HRS).
THE MULTIPLE LINEAR REGRESSION MODEL: THE MODEL, ESTIMATION AND DIAGNOSTICS, ANALYSIS OF CAUSAL EFFECTS IN THE MULTIPLE LINEAR REGRESSION MODEL, EFFECTS OF OMITTING RELEVANT VARIABLES, CONTROL VARIABLES: DEFINITION, CRITERIA FOR SELECTING VARIABLES AND PROPERTIES OF OLS ESTIMATES (20 HRS).
NON-LINEAR REGRESSION FUNCTIONS: POLYNOMIAL FUNCTIONS, LOGARITHMIC TRANSFORMATIONS, INTERACTIONS, ELASTICITY (14 HRS).
REGRESSION MODELS WITH PANEL DATA: REGRESSION WITH FIXED EFFECTS AND TIME EFFECTS, PROPERTIES OF ESTIMATORS: BASIC ASSUMPTIONS AND CALCULATION OF STANDARD ERRORS IN REGRESSION WITH FIXED EFFECTS. SOME REMARKS ON THE STATISTICAL ANALYSIS OF TIME SERIES (6 HRS).
THE PRESENTATION OF THEORETICAL ARGUMENTS WILL BE ACCOMPANIED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

MODULE B (22 HOURS)
MODULE B WILL EXPLAIN SOME ADVANCED ASPECTS OF REGRESSION ANALYSIS AND PROVIDE AN INTRODUCTION TO STATISTICAL METHODS FOR POLICY EVALUATION.
TOPICS:
MODELS WITH BINARY DEPENDENT VARIABLE: THE LPM MODEL, LOGIT MODELS, AND PROBIT MODELS (6 HOURS).
REGRESSION MODELS WITH INSTRUMENTAL VARIABLES: MOTIVATION, DEFINITION OF ‘INSTRUMENT’, INSTRUMENT RELEVANCE AND EXOGENEITY, THE TWO STAGE LEAST SQUARES (TSLS) ESTIMATOR. BASIC ASSUMPTIONS AND PROPERTIES OF THE TSLS ESTIMATOR (4 HOURS).
THE ‘VALUATION’ PROBLEM. THE COUNTERFACTUAL APPROACH TO EFFECT EVALUATION, THE EXPERIMENTAL METHOD (ESTIMATION OF CAUSAL EFFECTS, THREATS TO THE VALIDITY OF EXPERIMENTS), SPATIOTEMPORAL COMPARISONS WITH NON-EXPERIMENTAL DATA AND THREATS TO THEIR VALIDITY: LIMITATIONS AND ADVANTAGES OF THE DIFF-IN-DIFF APPROACH. SELECTION BIAS AND STATISTICAL APPROACHES TO ITS TREATMENT: METHODS BASED ON REGRESSION ANALYSIS, STATISTICAL MATCHING. METHODS BASED ON DISCONTINUITY IN TREATMENT. APPLICATIONS TO THE ITALIAN ECONOMY (12 HOURS).
THE PRESENTATION OF THEORETICAL ARGUMENTS WILL BE ACCOMPANIED BY THE DEVELOPMENT AND DISCUSSION OF CASE STUDIES ON REAL DATA.

	Teaching Methods
	CLASSROOM LECTURES. 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).

	More Information
	FURTHER MATERIAL (DATA, SOFTWARE, SLIDES) WILL BE DISTRIBUTED THROUGH THE INSTITUTIONAL INSTRUCTOR'S WEBSITE. HTTPS://DOCENTI.UNISA.IT/005005/RISORSE

Lessons Timetable

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Giuseppe STORTI | ECONOMIC STATISTICS