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).

COURSE GOALS - 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.

INTENDED LEARNING OUTCOMES - 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) Statistical hypothesis testing of a mean

Part V - Relationships between two variables
10) Correlation analysis
11) Simple linear regression analysis: descriptive measures
12) Simple regression analysis: statistical inference
13) Simple regression analysis: variable scales and functional forms

Part VI - Relationships between multiple variables
14) Multiple regression analysis: estimation and interpretation
15) Multiple regression analysis: hypothesis tests for partial regression coefficients and overall goodness of fit
16) Multiple regression analysis: dummy variables and statistical problems

• 1.  (A) Margaret Lewis Applied Statistics for Economists Routledge, Abingdon, Oxon; New York, 2012 » Pagine/Capitoli: Chapters 1 to 8 and Chapters 11 to 18

Lecture slides, additional readings, information about this course, and important reminders will be made available on the course website.

• The main forms of teaching are lectures and practical activities of data acquisition, mining, and processing using Excel.

• 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.

English is the only language used for lecturing

English is the only language used for examinations