Training and Research

PhD Programme Courses/classes - 2023/2024

Mathematical Statistics

Credits: 5

Language: English

Teacher:  Catia Scricciolo

Microeconomics 1

Credits: 7,5

Language: English

Teacher:  Simona Fiore, Claudio Zoli, Martina Menon

Continuous Time Econometrics

Credits: 5

Language: English

Teacher:  Cecilia Mancini

Probability

Credits: 7,5

Language: English

Teacher:  Marco Minozzo

Macroeconomics I

Credits: 7,5

Language: English

Teacher:  Tamara Fioroni, Alessia Campolmi

Game Theory

Credits: 5

Language: English

Teacher:  Francesco De Sinopoli

Mathematics

Credits: 4,5

Language: English

Teacher:  Andrea Mazzon, Jonathan Yick Yeung Tam

Advice to Young Economists

Credits: 4

Language: English

Teacher:  Marco Piovesan

Stochastic Optimization and Control

Credits: 5

Language: English

Teacher:  Athena Picarelli

Financial Time Series

Credits: 5

Language: English

Teacher:  Giuseppe Buccheri, Francesca Rossi

Mean Field Games (part I)

Credits: 2,5

Language: English

Teacher:  Luciano Campi

Job Market Orientation

Credits: 1

Language: English

Teacher:  Joan Madia, Simone Quercia

Discretization of Processes

Credits: 4,5

Language: English

Teacher:  Jean Jacod

Topics in applied economics with administrative data

Credits: 1

Language: English

Teacher:  Edoardo Di Porto

Multivariate Analysis with Latent Variables: The SEM Approach

Credits: 3

Language: English

Teacher:  Albert Satorra

Financial Mathematics

Credits: 5

Language: English

Teacher:  Alessandro Gnoatto

Political Economy

Credits: 4

Language: English

Teacher:  Emanuele Bracco, Roberto Ricciuti

Finite Mixture Models in Health Economics: Theory and Applications

Credits: 1

Language: English

Teacher:  Paolo Li Donni

Inequality

Credits: 4

Language: English

Teacher:  Francesco Andreoli, Claudio Zoli

Behavioral and Experimental Economics

Credits: 4

Language: English

Teacher:  Simone Quercia, Maria Vittoria Levati, Marco Piovesan

Health Economics

Credits: 4

Language: English

Teacher:  Paolo Pertile, Catia Nicodemo

Development economics

Credits: 4

Language: English

Teacher:  Federico Perali

Finance

Credits: 4

Language: English

Teacher:  Giorgio Vocalelli

Mean Field Games (part II)

Credits: 2,5

Language: English

Teacher:  Giulia Liveri

Stochastic Processes in Finance

Credits: 5

Language: English

Teacher:  Sara Svaluto Ferro, Christa Cuchiero

Dynamic Corporate Finance

Credits: 2

Language: Englìsh

PhD school courses/classes - 2023/2024

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.

Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, no confirmation e-mail will be sent after signing up.

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

Credits

1

Language

English

Class attendance

Free Choice

Learning objectives

The course will provide an overview on the methods to compute sample size necessary to achieve an adequate precision in estimating proportions or an adequate statistical power to compare the means of two independent or dependent samples, or the proportions of two independent samples. The concepts of statistical power, statistical precision, sample size and effect size will be reviewed. Statistical power computations will be illustrated by Excel files and Stata software. Participants will be encouraged to bring power calculation problems, to be used as examples in the class.

Prerequisites and basic notions

Students should have basic knowledge of Mathematics and Statistics.

Program

Confidence interval and precision of the estimate. Methods to compute sample size necessary to achieve an adequate precision in estimating proportions.
Probability of type II error and power of a statistical test. Methods to compute sample size necessary to achieve an adequate statistical power to compare the means of two independent or dependent samples, or the proportions of two independent samples.

When and where

Lessons will take place in the computer room. Statistical power computations will be illustrated by Excel files and Stata software (Stata and R-commander). Participants will be encouraged to bring power calculation problems, to be used as examples in the class.

Learning assessment procedures

A written exam will be administered. Students will have to compute sample size in a given problem.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

The exam will evaluate not only the acquisition of statistical knowledge, but also the ability to adopt it critically to solve health problems.

Criteria for the composition of the final grade

The final mark will be expressed on a scale ranging from 0 to 30. A minimum mark of 18 will be required in order to pass the exam.

Scheduled Lessons

When Classroom Teacher topics
Thursday 02 May 2024
14:00 - 18:00
Duration: 4:00 AM
https://univr.zoom.us/j/92638650019 Giuseppe Verlato DETERMINATION OF SAMPLE SIZE TO ACHIEVE A PREDEFINED PRECISION OR POWER

Faculty

A B C D F G L M N P Q R S T V Z

Andreoli Francesco

symbol email francesco.andreoli@univr.it symbol phone-number 045 802 8102

Bracco Emanuele

symbol email emanuele.bracco@univr.it symbol phone-number 045 802 8293

Buccheri Giuseppe

symbol email giuseppe.buccheri@univr.it symbol phone-number 045 8028525

Bucciol Alessandro

symbol email alessandro.bucciol@univr.it symbol phone-number 045 802 8278

Campolmi Alessia

symbol email alessia.campolmi@univr.it symbol phone-number 045 802 8071

Cipriani Giam Pietro

symbol email giampietro.cipriani@univr.it symbol phone-number 045 802 8271

Demo Edoardo

symbol email edoardo.demo@univr.it symbol phone-number 045 802 8782 (VR) 0444.393930 (VI)

De Sinopoli Francesco

symbol email francesco.desinopoli@univr.it symbol phone-number 045 842 5450

Fiore Simona

symbol email simona.fiore@univr.it

Fioroni Tamara

symbol email tamara.fioroni@univr.it

Gnoatto Alessandro

symbol email alessandro.gnoatto@univr.it symbol phone-number 045 802 8537

Levati Maria Vittoria

symbol email vittoria.levati@univr.it symbol phone-number 045 802 8640

Mancini Cecilia

symbol email cecilia.mancini@univr.it

Mazzon Andrea

symbol email andrea.mazzon@univr.it

Menon Martina

symbol email martina.menon@univr.it

Minozzo Marco

symbol email marco.minozzo@univr.it symbol phone-number 045 802 8234

Nicodemo Catia

symbol email catia.nicodemo@univr.it symbol phone-number +39 045 8028340

Perali Federico

symbol email federico.perali@univr.it symbol phone-number 045 802 8486

Pertile Paolo

symbol email paolo.pertile@univr.it symbol phone-number 045 802 8438

Picarelli Athena

symbol email athena.picarelli@univr.it symbol phone-number 045 8028242

Piovesan Marco

symbol email marco.piovesan@univr.it symbol phone-number 045.80.28.104

Quercia Simone

symbol email simone.quercia@univr.it symbol phone-number 045 802 8237

Renò Roberto

symbol email roberto.reno@univr.it symbol phone-number 045 802 8526

Ricciuti Roberto

symbol email roberto.ricciuti@univr.it symbol phone-number 0458028417

Rossi Francesca

symbol email francesca.rossi_02@univr.it symbol phone-number 045 802 8098

Scricciolo Catia

symbol email catia.scricciolo@univr.it symbol phone-number 045 8028341

Sommacal Alessandro

symbol email alessandro.sommacal@univr.it symbol phone-number 045 802 8716

Svaluto Ferro Sara

symbol email sara.svalutoferro@univr.it symbol phone-number 045 8028783

Veronesi Marcella

symbol email marcella.veronesi@univr.it

Vocalelli Giorgio

symbol email giorgio.vocalelli@univr.it

Zarri Luca

symbol email luca.zarri@univr.it symbol phone-number 045 802 8101

Zoli Claudio

symbol email claudio.zoli@univr.it symbol phone-number 045 802 8479

PhD students

PhD students present in the:

Nicodemo Catia

symbol email catia.nicodemo@univr.it symbol phone-number +39 045 8028340
Course lessons
PhD Schools lessons

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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2023/2024.

Documents

Title Info File
File pdf Guidelines PhD students pdf, en, 334 KB, 19/04/24
File pdf Linee guida dottorandi pdf, it, 251 KB, 19/04/24
File pdf Percorso formativo pdf, it, 283 KB, 19/04/24
File pdf Training program pdf, en, 358 KB, 19/04/24