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ES20173: Introduction to econometrics

[Page last updated: 03 June 2024]

Academic Year: 2024/25
Owning Department/School: Department of Economics
Credits: 12 [equivalent to 24 CATS credits]
Notional Study Hours: 240
Level: Intermediate (FHEQ level 5)
Period:
Academic Year
Assessment Summary: CWPI 50%, EXCB 50%
Assessment Detail:
  • ES22015 Unseen closed book written exam (EXCB 50%)
  • ES22015 Coursework (CWPI 50%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must ( take ES10005 AND take ES10003 ) OR ( take MA10211 AND take MA10212 ) OR ( take ES10158 AND take ES10003 )
In taking this module you cannot take ES20069
Learning Outcomes: At the end of the unit students should be able to:
* Outline core concepts in regression analysis;
* Explain underlying assumptions made for regression results to be valid;
* Undertake regression analysis using statistical software;
* Interpret regression results using a variety of techniques as applied to cross-sectional and time-series data;
* Appraise the adequacy of regression results and formulate appropriate diagnostic procedures when dealing with data;
* Communicate econometric concepts clearly and effectively;
* Plan, manage and reflect on their own learning and practice


Synopsis: Gain knowledge of cross-section and time series econometric methods. Youll build on your statistical hypothesis testing and least-squares regression knowledge from Year 1. Our systematic approach to model building, focuses on formulation and estimation of regression functions, interpretation of results and diagnostic tests to judge reliability. Your understanding of statistical concepts will be furthered in seminars and computer classes, as you develop analytical and applied software skills.

Content: This course provides thorough background to cross-sectional econometrics and an introduction to time-series econometrics. Cross-sectional topics covered:
  • Ordinary Least Squares Regression, its properties and inference - bivariate and multivariate
  • Non-linear regressions
  • OLS diagnostics and bias
  • Introduction to other estimation methods for cross-sectional data sets
Time series topics covered:
  • Characteristics of time series data
  • Autocovariance and autocorrelation functions
  • Stationary processes
  • Diagnostic testing and model selection
  • Nonstationary processes


    • Course availability:

    ES20173 is Optional on the following courses:

    Department of Mathematical Sciences
    • USMA-AFB15 : BSc(Hons) Mathematical Sciences (Year 3)
    • USMA-AAB16 : BSc(Hons) Mathematical Sciences with Study year abroad (Year 4)
    • USMA-AKB16 : BSc(Hons) Mathematical Sciences with Year long work placement (Year 4)
    • USMA-AFB13 : BSc(Hons) Mathematics (Year 3)
    • USMA-AAB14 : BSc(Hons) Mathematics with Study year abroad (Year 4)
    • USMA-AKB14 : BSc(Hons) Mathematics with Year long work placement (Year 4)
    • USMA-AFB01 : BSc(Hons) Mathematics and Statistics (Year 3)
    • USMA-AAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 4)
    • USMA-AKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 4)
    • USMA-AFB20 : BSc(Hons) Mathematics, Statistics, and Data Science (Year 3)
    • USMA-AAB20 : BSc(Hons) Mathematics, Statistics, and Data Science with Study year abroad (Year 4)
    • USMA-AKB20 : BSc(Hons) Mathematics, Statistics, and Data Science with Industrial Placement (Year 4)
    • USMA-AFM14 : MMath(Hons) Mathematics (Year 3)
    • USMA-AKM15 : MMath(Hons) Mathematics with Year long work placement (Year 4)
    School of Management
    • UMMN-AFB02 : BSc(Hons) Accounting and Finance (Year 3)
    • UMMN-AKB02 : BSc(Hons) Accounting and Finance with Year long work placement (Year 4)

    Notes:

    • This unit catalogue is applicable for the 2024/25 academic year only. Students continuing their studies into 2025/26 and beyond should not assume that this unit will be available in future years in the format displayed here for 2024/25.
    • Courses and units are subject to change in accordance with normal University procedures.
    • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
    • Find out more about these and other important University terms and conditions here.