Quantitative methods for economics
- A.A. 2019/2020
- CFU 8, 8(m)
- Ore 40, 40(m)
- Classe di laurea LM-52, LM-62(m)
The economic questions raised throughout the course are based on the assumption that students possess a basic knowledge of micro- and macroeconomic theory, since it is the goal for students to learn the quantitative methods useful to conduct empirical analysis in economics. A basic background in statistics is also suggested (but not required).
The goal of this course is to equip students with the knowledge of quantitative methods
frequently used by economists to make connections between economic theory and empirical observation. The methods examined are divided into two categories: descriptive statistics used to measure individual economic variables, and statistical inference used to measure relationships between economic variables and to test hypotheses about them. Upon successful completion of this course, students will have the skills needed to generate numerical results with each of the methods by applying them to specific economic questions. Successful completers will be also able to provide economic interpretations of the statistical results and to explain the strengths and limitations associated with each method.
The course covers the following parts and topics:
Part I - Introduction
1) The role of statistics in economics
2) Visual presentations of economic data
Part II - Descriptive statistics of an economic variable
3) Observations and frequency distributions
4) Measures of central tendency
5) Measures of dispersion
Part III - Temporal descriptive statistics
6) Measuring changes in price and quantity
7) Descriptions of stability: short-run changes
8) Patterns of long-term change
Part IV - Statistical inferences about a single variable
9) Basic concepts in statistical inference
10) Statistical estimation
11) Statistical hypothesis testing of a mean
Part V - Relationships between two variables
12) Correlation analysis
13) Simple linear regression analysis: descriptive measures
14) Simple regression analysis: statistical inference
15) Simple regression analysis: variable scales and functional forms
Part VI - Relationships between multiple variables
16) Multiple regression analysis: estimation and interpretation
17) Multiple regression analysis: hypothesis tests for partial regression coefficients and overall goodness of fit
18) Multiple regression analysis: dummy variables and statistical problems
- 1. (A) Margaret Lewis Applied Statistics for Economists Routledge, Abingdon, Oxon; New York, 2012
Lecture notes, additional readings, information about this course, handouts, and important reminders will be made available on the course website. For non-attending students, the final evaluation is based on all topics covered in the course outline and all chapters of the assigned textbook. For attending students, topics 9 and 10 are to be excluded from the syllabus, as well as the corresponding textbook chapters in which these topics are discussed.
- Frontal lecturing and practical activities are the main forms of teaching.
- The assessment of learning will be through a written exam composed of open questions and problems (similar to those included in the textbook) to be solved with explanations. Students who have recorded attendance of at least 80% of the classes have the option to undertake the final exam in the form of a short essay to be discussed (in max. 30 minutes) via a 15- to 20-page PowerPoint presentation, illustrating goals, methodology, analysis and final results.
English is the only language used in the classroom
English is the only language used for examinations