Micro-econometrics, causal inference and time series econometrics

A.A. 2020/2021
12
Crediti massimi
80
Ore totali
SSD
SECS-P/05 SECS-S/01
Lingua
Inglese
Obiettivi formativi
The aim of this course is twofold. First, to learn how to analyse time-series (typically macro-) data. In particular, how to identify the effect of past shocks on the current state of the world, how to forecast future values and how to model the dynamic interaction between different series.
Second, to analyse the main challenges faced by economists and social scientists in answering empirical questions using micro‐data. The main emphasis will be on learning how to establish causal relationships between different variables and how to use this evidence to inform policy makers' decisions.
Risultati apprendimento attesi
By the end of the course students will be able to:
Understand the difference between a time series and an independent random sample.
Apply non-parametric and parametric techniques to model time series.
Choose and estimate parametric models for time series.
Compute the impulse response function.
Forecast future values.
Handle real‐world data.
Identify causal effects using micro-data
Link econometric theory with data work and produce an insightful and coherent empirical analysis.
Programma e organizzazione didattica

Edizione unica

Responsabile
Periodo
Primo trimestre
Programma
Il programma è condiviso con i seguenti insegnamenti:
- [B67-408](https://www.unimi.it/it/ugov/of/af2021000b67-408)
Moduli o unità didattiche
Module Micro-econometrics and Causal Inference
SECS-S/01 - STATISTICA - CFU: 6
Lezioni: 40 ore

Module Time Series Econometrics
SECS-P/05 - ECONOMETRIA - CFU: 6
Lezioni: 40 ore
Docente: Iacone Fabrizio

Docente/i
Ricevimento:
Su appuntamento via email
Ricevimento:
Martedi 16.30-19.00
Via Conservatorio 7
Ricevimento:
Durante il trimestre: Lunedi' 12.30-14.30.
Stanza 4 (DEMM Secondo piano)