UNIVERSITY OF MILAN · ITALY
Causal Inference and Policy Evaluation
Master's · Taught in en
At a glance
24 mo
Duration
—
IELTS
—
Tuition / yr
en
Language
Master's
Level
- 6 ECTSCredits
- 40 HoursOverall hours
- EnglishLanguage of Instruction
- First four month periodLesson Period
- SECS-P/01Subject Area
This course introduces students to the fundamental concepts of causality and counterfactual impact evaluation. It covers statistical methods for assessing causality, including instrumental variables, difference-in-differences, regression discontinuity design, and randomized control trials. These methods are then applied to real-world examples in labor, education, and health economics to evaluate policies.
Curriculum
The course delves into key methodologies for understanding cause and effect in economic contexts. Students will explore theoretical underpinnings and practical applications.
- Year 1 (Implied)
- The counterfactual and causality
- Recap of Ordinary Least Squares (OLS) and causality
- Randomized Control Trials (RCTs)
- Instrumental Variables (IVs)
- The Local Average Treatment Effects (LATE) of IVs
- Difference-in-Differences (DID)
- Regression Discontinuity Design (RDD)
- Recent developments of causal inference and policy evaluation methods
Careers
While this is a single course, it is part of Master's programs like 'Data Science for Economics' and 'Finance and Economics'. Graduates from these programmes are prepared for roles in data analysis, economic consulting, financial markets, and academic research.
- Data Analyst
- Economic Consultant
- Financial Market Operator/Analyst
- Academic Researcher
Frequently asked questions
- What are the entry requirements for the Causal Inference and Policy Evaluation course?
- You should have an undergraduate background in statistics and/or econometrics, be familiar with multivariate regression analysis, and have proficiency in statistical/econometric software like R or STATA. Knowledge of demand and production theory is also required.
- Is this a full degree program or a single course?
- This is offered as a single course and can also be part of Master's programs like 'Data Science for Economics' and 'Finance and Economics'.
- What is the language of instruction for this course?
- The language of instruction for the Causal Inference and Policy Evaluation course is English.
- How do I apply to take this course as a single module?
- To apply for this course as a single module, you need to visit the University of Milan website, locate the course, check prerequisites, find the 'Single Course' information, and follow the specific online application procedure and deadlines.
- What are the tuition fees for this course?
- Information on specific tuition fees for this single course is not available; fees for degree programmes at the University of Milan vary and should be checked on their relevant fee pages.
- What career paths can this course lead to?
- As a single course, it contributes to Master's programs preparing graduates for roles such as Data Analyst, Economic Consultant, Financial Market Operator/Analyst, and Academic Researcher.
Entry requirements
Undergraduate-level statics and/or econometricsFamiliarity with multivariate regression analysis is expected. Proficiency in statistical/econometric software (e.g., R, STATA) is necessary. Knowledge of demand and production theory is required. Familiarity with empirical strategies for assessing causality (as taught in specific undergraduate econometrics courses) is also needed.
Students are expected to be able to use statistical/econometric software like R or STATA. Basic STATA knowledge can be acquired through specific courses.
Fees
Tuition (international)Information on international tuition fees is not available for this single course. Fees for degree programmes vary.
Tuition (home)Information on home tuition fees is not available for this single course. Fees for degree programmes vary.
LivingEstimated living costs are not provided.
This course can be attended as a single course. Tuition fees for degree programmes at the University of Milan vary and should be checked on the relevant fee pages.
How to apply
1. Identify the courseLocate the 'Causal Inference and Policy Evaluation' course on the University of Milan's degree programme course list.
2. Check prerequisitesEnsure you meet the expected background knowledge in statistics, econometrics, and microeconomics, and are familiar with statistical software.
3. Visit the 'Single Course' informationNavigate to the section on attending the course as a single module.
4. Follow application procedureAdhere to the specific application steps and deadlines provided by the University of Milan for single-course enrollment. This typically involves an online application process.
Frequently asked questions
What are the entry requirements for the Causal Inference and Policy Evaluation course?
+
You should have an undergraduate background in statistics and/or econometrics, be familiar with multivariate regression analysis, and have proficiency in statistical/econometric software like R or STATA. Knowledge of demand and production theory is also required.
Is this a full degree program or a single course?
+
This is offered as a single course and can also be part of Master's programs like 'Data Science for Economics' and 'Finance and Economics'.
What is the language of instruction for this course?
+
The language of instruction for the Causal Inference and Policy Evaluation course is English.
How do I apply to take this course as a single module?
+
To apply for this course as a single module, you need to visit the University of Milan website, locate the course, check prerequisites, find the 'Single Course' information, and follow the specific online application procedure and deadlines.
What are the tuition fees for this course?
+
Information on specific tuition fees for this single course is not available; fees for degree programmes at the University of Milan vary and should be checked on their relevant fee pages.
What career paths can this course lead to?
+
As a single course, it contributes to Master's programs preparing graduates for roles such as Data Analyst, Economic Consultant, Financial Market Operator/Analyst, and Academic Researcher.