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EC221 – Econometrics II

Bachelor of Science in Economics

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Core Course

EC221 – Econometrics II

Course Unit Code: EC221

Type Of Unit: Core

Level of Course Unit: First cycle

Year of Study: Second year

Semester: On demand

Number of ECTS Credits: 7.5

Class Contact Hours: 36

Mode of Delivery

Face to Face

Prerequisites

None

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The objective of this course is to provide the theoretical and empirical skills, knowledge and tools for advanced econometric modelling and analysis in the economic, business and social science disciplines, focusing on time series, panel data and binary choice models.

Learning Outcomes

  • Define advanced elements of an econometric analysis.
  • Recognize the proper data and estimation method to be used.
  • Explain the outcome of the estimation and testing.
  • Evaluate various econometric models.
  • Interpret the results of advanced empirical analyses using time-series and panel data.
  • Compare the outcome of advanced alternative estimation and testing procedures.

Course Features

Planned learning activities and teaching methods
Lectures; in-class discussion and debates; in-class exercises; problem sets

Assessment methods and criteria
20% Class participation (including written class quizzes) and problem sets
30% Midterm
50% Final Exam

Language of Instruction
English

Readings

Textbooks:

1. Wooldridge, J. (2020). Introductory Econometrics: A Modern Approach, 7th ed.

 

Optional textbook:

2. Stock, J. and Watson, M. (2019). Introduction to Econometrics, 4th ed.

3. Greene, W. (2018). Econometric Analysis, 8th ed.

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Request Information Request Information ⟶

Informed Consent Form

Dear Participant,

You are invited to participate in a survey as part of the DiFiCy – Digital Transformation and FinTech: Shaping Cyprus’s Economy research project which is implemented by the University of Limassol, PwC Cyprus and Unity Growth Limited.

The project is co-funded by the European Union within the framework of the Cohesion Policy Programme “THALIA 2021-2027” through the Research and Innovation Foundation (RIF) in Cyprus [Pr. number: EXCELLENCE/0524/0568].

The study has been approved by the National Bioethics Committee of Cyprus (Approval no.: EEBK EΠ 2025.01.19 )

This project explores digital transformation and FinTech adoption in Cyprus, with a particular focus on SMEs and the broader business ecosystem. It uses a mixed-methods research design, combining survey data with interviews and case study evidence to generate evidence-based insights for policymakers and businesses.

Before deciding whether to participate, please read the following information carefully.

Purpose of Participation

The purpose of this research is to better understand the drivers, challenges, and impacts of digital transformation and FinTech adoption in Cyprus. The findings aim to support evidence-based policymaking, strengthen business practices, and contribute to innovation and economic development.

Your participation involves the following:

Completion of this survey, which takes approximately 15 minutes.

Invitation to take part in an optional interview.

Contribution to a case study or discussion session at a later stage.

Your participation is entirely voluntary, and you are free to decline or withdraw at any time without any consequences.

If you wish to withdraw from the study after submitting your responses, you may do so by contacting the Project Coordinator.

Data Confidentiality and Usage

All data collected will be handled in strict accordance with the General Data Protection Regulation (GDPR) and Cyprus Data Protection Law (125(I)/2018).

Your data will be treated confidentially, pseudonymised and anonymised, and no personally identifiable information will be disclosed. Data will be securely stored and accessed only by authorised members of the research team. In some cases, qualitative data may be processed using machine learning techniques, such as keyword identification or pattern detection, strictly to support analysis; however, all interpretation and conclusions will be made by the researchers.

Aggregated and anonymised findings derived from the data (e.g., statistical summaries, graphs, and thematic insights) may be used for dissemination activities, including scientific publications, policy reports, infographics, and training materials. These outputs will not contain any information that could directly or indirectly identify participants or their organisations.

Anonymised data may be shared publicly after a 24-month embargo period, while raw or sensitive data will not be publicly available. Access to raw or sensitive data will be granted only upon justified request and consortium approval.

Your participation in this study does not involve any risks.

On the contrary, your contribution may help improve digital and FinTech policies, support SME development and innovation strategies, and enhance the overall business environment in Cyprus.

Contact Information

If you have any questions, concerns, withdraw requests or complaints, please contact the Project Coordinator, Dr. Snezana Eminidou. Please include “DiFiCy Survey” in the subject line.

Email: snezana@uol.ac.cy

Phone number: +357 22462228

Partnership:

Thank you for your valuable contribution to this research.

The project is implemented under the programme of social cohesion “THALIA 2021-2027” co-funded by the European Union, through the Research and Innovation Foundation in Cyprus [Pr. no. EXCELLENCE/0524/0568]. The content reflects the views of the author(s) only. The European Commission and the Managing Authority of THALIA 2021–2027 cannot be held responsible for any use which may be made of the information contained therein.