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Regular version of the site
Postgraduate course 2019/2020

Empirical Methods and Applications in Economics and Management

Type: Compulsory course
Area of studies: Economics
When: 1 year, 1 semester
Mode of studies: offline
Instructors: Elena Shakina
Language: English
ECTS credits: 3
Contact hours: 36

Course Syllabus

Abstract

This course introduces PhD students to sources and analytical techniques of data commonly used in management and business studies. A conceptual part of the course is dedicated to the overview of appropriate data sources, indicators and statistical metrics, basic and advanced techniques for data analysis and econometrics Practical approach to learning is based on professional tools for data collection and processing and analysis – Stata.
Learning Objectives

Learning Objectives

  • to have knowledge of commonly used data sources, their benefits and limitations
  • to understand the meaning of various statistical indicators in principle fields of social science
  • be able to identify suitable statistical sources for a defined research problem
  • be able to run descriptive analysis using Stata
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to select and apply relevant for study research methods
  • be able to conduct comprehensive studies based on system research approach
  • be able to set purposes and tasks of a research project on fundamental and applied research
  • be able to solve research problems using the updated national and international experience and modern ICT
  • be able to develop new research methods and apply them for research activity in economics and management
  • be able to conduct research activity in an educational institutions and management of students' research activity
Course Contents

Course Contents

  • Introduction into principles of collecting and using business data
    Research in business. Ethics in business research. Research questions and associated techniques. Screening data prior to analysis. Normality, linearity, and homoscedasticity. Data transformations.
  • Probability and statistics in advanced data analysis
    Exploratory data analysis. Data and sampling distributions. Statistical experiments and significance testing. Experimental and quasi-experimental techniques. Regression and prediction. Correlation vs causation. Endogeneity. Guide to entering, editing, saving, and retrieving large quantities of data using Stata.
  • Data visualization and reporting
    Presenting insights and findings. Written report: research report components, writings, presentation of statistics. Oral presentation: planning, organizing, supporting, visualizing, delivering.
Assessment Elements

Assessment Elements

  • non-blocking Test 1
  • non-blocking Test 2
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • Interim assessment (1 semester)
    0.4 * Exam + 0.3 * Test 1 + 0.3 * Test 2
Bibliography

Bibliography

Recommended Core Bibliography

  • Lancaster, Geoff. Research Methods in Management : A Concise Introduction to Research in Management and Business Consultancy, Routledge, 2004.
  • Lancaster, Geoff. Research Methods in Management : A Concise Introduction to Research in Management and Business Consultancy, Routledge, 2004. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=297137.
  • Tong, H., Huang, Y. X., & Kumar, T. K. (2011). Developing Econometrics. Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=473846

Recommended Additional Bibliography

  • Neugeboren, R. H. (2005). The Student’s Guide to Writing Economics. New York: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=123192