00915 - Economic Statistics

Academic Year 2022/2023

  • Moduli: Andrea Guizzardi (Modulo 1) Cristina Bernini (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Rimini
  • Corso: First cycle degree programme (L) in Finance, Insurance and Business (cod. 8872)

Course contents

Introduction to economic and statistics: The measure of economic phenomena: sources for statistical and economic information

Index numbers for the comparison of financial and economic aggregates over time. Official index numbers; Stock prices and financial assets index.

Time series analysis: graphical representations. The unobservable components of a time series: the trend, the cycle, the seasonal component, the erratic component. The signal extraction: deterministic parametric methods; nonparametric methods: moving averages and filters. Inference: bias and variance of the trend estimates. Estimate of the noise variance and confidence interval for the trend. Introduction to stochastic processes and their properties. Processes AR, MA and ARMA; global and partial autocorrelation functions; conditions of stationarity and invertibility. non-stationary processes: ARIMA processes. Time series forecasting. The evaluation of forecasts: descriptive approach.

Business and labor: Methods of analysis of enterprises' the structure. Measurement of labour supply and demand. Measures of output and productivity. Production and cost functions. Efficiency measures (hints). Indicators of specialization and location of economic activity. The shift and share analysis.

Consumption analysis: the main surceys on consumption; modelling consumption. Analysis of the income distribution; poverty and welfare measures.

Production factors: the measure of labour's supply and demand. Production and productivity measures

Readings/Bibliography

Material (in English) will be provided by the teacher on request.

Teaching methods

Teacher's lectures supplemented with smaller discussion sections,tutorials or laboratory experiment sessions.

Attendance is not mandatory. However, it is recommended to make the exercises (examples are provided in the teaching material) to be prepared for the exam.

For students who intend to attend the laboratory session in person, it is necessary to carry out a training session regarding safety [https://elearning-sicurezza.unibo.it/] in e-learning mode (modules 1 and 2 )

Assessment methods

The final test aims to assess the achievement of the following learning objectives:

• in-depth knowledge of the statistical tools discussed during the lectures

• ability to use these tools to analyze the economic and financial phenomena

• ability to use the results in order to interpret the phenomenon under study and achieve decision-making processes.

The final test is oral, usually preceded by a written test with both theoretical questions and exercices

During the test is not allowed any materials such as textbooks, notes, computer media.

There will be a partial test at the end of each course module. The final mark is calculated weighting the two marks by the number of credits of each module.

To take the exam you must pre-register on AlmaEsami

Those who do not succeed to enroll by the due date, are required to report promptly (and in any event before the official closing of the subscription lists) the problem to the Secretary's office. The teacher shall have the right to admit to the examinations.

It will be possible to discuss the test and ask for clarification at the date of verbalization

The possibility of using alternative hours of receipt to inspect the task is reserved for exceptional cases, with a valid reason.

The verbalization can occur in the absence of the student.

Teaching tools

Teacher's slides. Excel and E-views software

Office hours

See the website of Andrea Guizzardi

See the website of Cristina Bernini

SDGs

No poverty Good health and well-being Decent work and economic growth Reduced inequalities

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.