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COURSE SYLLABUS

Intermediate Econometrics 7.5 credits

Ekonometri
First cycle, N0028N
Version
Course syllabus valid: Autumn 2020 Sp 1 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.


Education level
First cycle
Grade scale
U G VG *
Subject
Economics
Subject group (SCB)
Economics
Main field of study
Economics

Entry requirements

In order to meet the general entry requirements for first cycle studies you must have successfully completed upper secondary education and documented skills in English language and N0008N Introductory Microeconomics (7.5Hp) N0030N Applied Microeconomics (7.5Hp) N0011N Introductory Macroeconomics (7.5Hp) N0012N Applied Macroeconomics (7.5Hp) S0004M Statistics 1: survey methods (7.5Hp) S0005M Statistics 2: random models and inference (7,5Hp) N0005N Applied Mathematical Economics (7.5 Hp) Goda kunskaper i engelska, motsvarande Engelska 6.


More information about English language requirements


Selection

The selection is based on 1-165 credits.



Course Aim
The overall purpose with the course is that the student shall after the course have basic knowledge in econometrics theory and be able to apply it on current economic problems. In addition, the student shall have a good knowledge and ability to conduct critical analyses of quantitative economic relationships and development patterns. More concretely, this means that the student shall be able to:

a) make relevant hypotheses and specify testable models (T)
b) explain simple regression models, their properties and inference (T)
c) explain multiple regression models, their properties and inference (T)
d) explain estimation of equations systems (simultaneous equation models) (T)
e) formulate and quantify economic relationships (T and L)
f) explain, use and fix concepts and problems such as heteroscedasticity, autocorrelation, confident intervals, hypothesis testing and multicollinearity (T and L).
g) apply simple, multiple regression models and simultaneous equation models in order to estimate and analyse economic relationships (T and L)
h) present, explain and make understandable, to others within the profession as well as to laymen, econometric results (T and L)
i) based on economic theory and relationships, assess, critically scrutinise and discus model specifications and model results (L)
j) express oneself proficiently in both writing and in a scientifically correct way (L)
k) have the ability to motivate model choices and argue/defend its results (L)
l) in writing present econometric results within stipulated time frames (L)

Contents
The course is based on lectures and interspersed with practical computer laboratory exercises. The course is for students that already have basic knowledge in statistics. The course deals with problems to establish and quantify economic relationships and basic econometric methods. Main focus is on linear regression models (OLS). Another important part of the course is its practical computer based exercises. These exercises are conducted using the econometrics software NLogit/LimDep. The following topics are presented in detail:a) Review of basic statistical concepts and parameters
b) The simple regression model and its properties and inference
c) Linear regression models (OLS)
d) Multiple regression models and their properties and inference
e) Heteroscedasticity, autocorrelation, confident intervals and multicollinearity
f)  Dummy variables
g) Estimation of equations systems
h) Hypotheses testing

Realization
The course starts with a review of basic statistics and continues with simple and multiple regression models, both in theory and practical applications. Starting from economic theory and economic relationships different model specifications and interpretation of model results are than discussed. In connection to this, the analysis is broadened by the introduction of confidence intervals and hypothesis testing. The course continues with analyses of the consequences if one or several of the underlying assumption of the linear regression model is violated. Concepts and problems such as multicollinearity, heteroscedastiocity and autocorrelation is introduced and analysed in conjunction to an extended discussion regarding model specification. The course includes and analysis models which include dummy variables. Large segments of the course are based on computer exercises where the students learn how to practically implement the different models in specialised software and how to use large dataset.

Examination
Exam (T) 6,0 hp U G VG
Computer exercises (L) 1,5 hp U G

The grading of the exam is based on the students’ ability to fulfil the specified course aims a) though h) above. The grading of the computer laboratory exercises is based on the students’ ability to fulfil the specified course aims e) though l) above. In order to get the grade VG on the course the student need to achieve the grade VG on the exam and G on the computer exercises.


Remarks
Students must register for the courses themselves or contact ETS educational administration, eduets@ltu.se not later than three days after the quarter commences. Failure to do so can result in the place being lost. This rule also applies to students with a guaranteed place.

Examiner
Robert Lundmark

Literature. Valid from Spring 2014 Sp 3 (May change until 10 weeks before course start)
Dougherty, C. Introduction to Econometrics. Oxford University Press. Last edition.

Course offered by
Department of Business Administration, Technology and Social Sciences

Modules
CodeDescriptionGrade scaleHPStatusFrom periodTitle
0001Written ExamU G VG *6.00MandatoryS11
0002Laboratory workU G#1.50MandatoryS11

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.

Syllabus established
by Head of the Department of Business Administration and Social Sciences 19 Feb 2010

Last revised
by Director of Undergraduate Studies Daniel Örtqvist, Department of Business Administration, Technology and Social Sciences 14 Feb 2020