Applied Econometrics
- Social Sciences
- 400 level
- 2 credit units
- 217 pages
- 14 units
This course, Applied Econometrics I, provides undergraduate Economics students with a detailed understanding of econometric theory and its applications in data analysis for policy interpretations. It covers essential topics such as time series components, simple linear regression, multicollinearity, autoregressive processes, stationarity, cointegration analysis, and panel data regression models. Students will gain practical skills in model estimation using real-life data and econometric software, enabling them to evaluate and discuss econometric literature effectively.
About this course
- Difficulty
- Intermediate
- Study hours
- 156 hours
- Maths
- Intermediate
- Content
- Theoretical, practical, problem solving
- Practical work
- Yes
- Assignments
- Tutor marked assignments
- Final examination
What you'll read
The real module and unit structure of ECO453, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
ECO453 · UNIT 1: Meaning of Applied Econometric Research Contents
The basic tool for econometrics is the multiple linear regression model. Econometric theory uses statistical theory and mathematical statistics to evaluate and develop econometric methods. Econometricians try to find estimators that have desirable statistical properties including unbiasedness, efficiency, and consistency. Applied econometrics uses theoretical econometrics and real-world data for assessing economic theories, developing econometric models, analyzing economic history, and forecasting.
What you should be able to do
- Explain simple and multiple regression in economics
- Evaluate Nonlinear Regression Models
- Discuss Panel Data Regression Models
- Examine Econometric Models
- Evaluate Autoregressive and Distributed-Lag Models
What it prepares you for
- Economist
- Data Analyst
- Financial Analyst
- Policy Analyst
- Researcher
- Finance
- Economics
- Government
- Consulting
- Research
- EViews
Where it gets hard
The units students slow down on, and what makes each one heavy.
- MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 2: Concept of Stationarity
Advanced calculus integration techniques require strong mathematical foundation and understanding of stochastic processes.
- MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 3: Cointegration Analysis
Understanding the underlying mathematics and assumptions of the Johansen test requires a solid background in linear algebra and statistical inference.
A suggested way through it
13 weeks, about 39 hours in total. Yours will differ.
- Week 1MODULE 1 INTRODUCTION TO ECONOMETRIC RESEARCH USING SOFTWARE
Unit 1: Meaning of Applied Econometric Research · 3 hours
Understand the definition of econometrics and its applications. Explore the basic tools used in econometric analysis. Learn the stages of applied econometric research. Discuss the assumptions underlying econometric models. Critique econometric research methods.
- Week 2MODULE 1 INTRODUCTION TO ECONOMETRIC RESEARCH USING SOFTWARE
Unit 2: Time Series and Its Components · 3 hours
Define time series data and its components. Understand secular trends, seasonal variations, cyclical variations, and irregular variations. Learn methods for estimating trends, including free hand, regression, and moving average methods. Graphically represent and estimate trends.
- Week 3MODULE 1 INTRODUCTION TO ECONOMETRIC RESEARCH USING SOFTWARE
Unit 3: Simple Linear Regression Model · 3 hours
Explain the linear regression approach. Discuss parameter estimation procedures. Evaluate the assumptions of stochastic variables. Analyze the assumptions of explanatory variables. Estimate simple regression using algebraic and software methods.
- Week 4MODULE 1 INTRODUCTION TO ECONOMETRIC RESEARCH USING SOFTWARE
Unit 4: Time Series Data Analysis · 3 hours
Discuss the history of Time Series Data Analysis. Explain the Stochastic Process. Evaluate Stationary and Nonstationary Variables. Determine weakly Stationarity and Strict Stationarity. Run Time Series Data in Eviews 12.
- Week 5MODULE 1 INTRODUCTION TO ECONOMETRIC RESEARCH USING SOFTWARE
Unit 5: Multicollinearity · 3 hours
Define multicollinearity. Explain types of multicollinearity. Discuss consequences of multicollinearity. Highlight solutions to multicollinearity problems.
- Week 6MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 1. Autoregressive Process · 3 hours
Discuss the meaning of the term Autoregressive (AR). Explain estimation of an Autoregressive Model (AR). State autocorrelation or Serial Correlation. Analyze consequences of Serial Correlation. Carry out the LM Test.
- Week 7MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 2: Concept of Stationarity · 3 hours
Discuss stationarity and non-stationarity. Explain the meaning of unit root and its importance. Explain how to stationarise non-stationary series. Conduct unit roots test in the AR(1) Model. Estimate stationarity of variables in EViews software.
- Week 8MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 3: Cointegration Analysis · 3 hours
Discuss the meaning of cointegration. Learn how to conduct cointegration Test. Discuss the types of cointegration tests. Conduct cointegration test using EViews.
- Week 9MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 4: Autoregressive Distributed Lag (ARDL) Model · 3 hours
Discuss ARDL Cointegration Equations. Explain the justification for the choice of ARDL model. Compute ARDL in Eviews. Design the ARDL Bound cointegration test model. Conduct a diagnostic check for Serial Correlation in ARDL.
- Week 10MODULE 2 STATIONARITY AND AUTOREGRESSIVE PROCESS
Unit 5: ARDL Post Estimation Tests · 3 hours
Know why post estimation tests are carried. List various types of post estimation tests required. Interpret appropriate post estimation tests result. Conduct Hypotheses Testing Using Wald-Test.
- Week 11MODULE 3: PANEL DATA ESTIMATION
Unit 1: Panel Data Regression Model · 3 hours
Know the meaning of Panel Data Regression Model. Explain panel Data Examples. Discuss the advantages of Panel Data. List the importance of Panel Data. Design the format of a Panel Data. List types of Panel Data.
- Week 12MODULE 3: PANEL DATA ESTIMATION
Unit 2: Fixed Versus Random Effects Panel Data · 3 hours
Discuss fixed versus random effects model. Explain the advantages of fixed effect model. Discuss the advantages of random effect model. Explain the difference between fixed and random effects model.
- Week 13MODULE 3: PANEL DATA ESTIMATION
Unit 3: Testing Fixed and Random Effects · 3 hours
Test fixed and random effects. Discuss Breusch-Pagan LM Test for Random Effects. Discuss Hausman Test for Comparing Fixed and Random Effects. Understand guidelines of Model Selection.
Preparing for the exam
- Review all units, focusing on key concepts and formulas
- Practice with EViews software to estimate models
- Solve past examination questions to understand question patterns
- Create concept maps linking different econometric models
- Focus on understanding assumptions and limitations of each model
Questions students ask about this course
What is ECO453 about?
This course, Applied Econometrics I, provides undergraduate Economics students with a detailed understanding of econometric theory and its applications in data analysis for policy interpretations. It covers essential topics such as time series components, simple linear regression, multicollinearity, autoregressive processes, stationarity, cointegration analysis, and panel data regression models. Students will gain practical skills in model estimation using real-life data and econometric software, enabling them to evaluate and discuss econometric literature effectively.
How many units does ECO453 have?
ECO453, Applied Econometrics, has 14 units across 3 modules, over 217 pages of course material. You can read it one unit at a time.
How many credit units is ECO453?
ECO453 carries 2 credit units, at 400 level in Social Sciences.
Is ECO453 hard?
ECO453 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, practical and problem solving work, and it has a practical component.
How long does ECO453 take to study?
About 156 hours of study, spread across its 14 units.
How is ECO453 assessed?
ECO453 is assessed by assignments, tutor marked assignments and final examination.
What can I do with ECO453?
Economist, Data Analyst, Financial Analyst, Policy Analyst and Researcher.