Economic Modeling with Applications, 10 Credits

Contents

This course equips students with the core mathematical and econometric methods used by economists, both theoretical and practical.

Module 1: Mathematics for Economic Analysis (3 credits)

The module aims to give the students the mathematical tools essential for economic analysis.

The module covers the fundamental mathematical concepts crucial for theoretical economic and econometric work. It explores mathematical concepts like functions, systems of equations, logarithms, derivatives, and optimisation.

Module 2: Modeling Data using Econometrics (7 credits)

The module aims to equip students with the econometric tools essential for economic analysis and have students develop the ability to apply these tools to solve economic problems and interpret results.

This module is designed to provide a practical foundation in econometrics, focusing on hands-on applications. Students learn the essential tools (such as linear regression model and ordinary least squares) and gain the ability to analyse real economic data, making the concepts relevant.

Expected learning outcomes

Module 1: Mathematics for Economic Analysis (3 credits)

Having completed the module, the student is expected to be able to:

Knowledge and understanding

• Explain and appropriately use different functions such as exponential, logarithmic, and linear quadratic.
• Solve systems of equations.
• Differentiate functions.
• Optimise functions.

Competence and skills

• Communicate economic ideas and arguments in English effectively.

Module 2: Modeling Data using Econometrics (7 credits)

Having completed the module, the student is expected to be able to:

Knowledge and understanding

• Define the key components of econometric modelling, including dependent and independent variables, coefficients, and the error term, and describe the process of choosing the appropriate functional form for a model.
• Explain the assumptions underlying the model, such as linearity, homoskedasticity, and endogeneity.
• Use OLS to estimate the coefficients in the linear regression model, and to interpret the estimated coefficients in the context of the economic relationship being studied.
• Identify potential issues that can affect the model's reliability and explain their consequences.

Competence and skills

• Use econometric software to specify and estimate different types of econometric models including cross section, time series, panel, experimental, binary dependent variable.
• Communicate economic ideas and arguments in English effectively.

Judgement and approach

• Critically evaluate the appropriateness of an econometric model for a given dataset and research question.
• Choose appropriate econometric modelling techniques based on the characteristics of the data and research question.
• Interpret the results of the econometric modelling with caution and awareness of potential limitations.
• Read and discuss applied papers published in economic journals.

Required Knowledge

30 credits in economics and Mathematics 3b/3c or equivalent. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Form of instruction

Learning is supported by lectures and practical tutorials.

Examination modes

In the course, the following grading scale is used: Fail (U), Pass (G), or Pass with Distinction (VG). To achieve a Pass (G) grade, the student needs to obtain a passing result in both modules. For a Pass with Distinction (VG) grade, the student must also achieve a Pass with Distinction (VG) result in module 2.

Module 1: Mathematics for Economic Analysis (3 credits)

The examination consists of an individual written hall exam.

The following grading scale will be used: Pass (Godkänd, G) and Fail (Underkänd, U).

Module 2: Modeling Data using Econometrics (7 credits)

The examination consists of three written individual assignments.

The grade for module is based on a summary assessment of the results of the included assignments and is set when the module has finished, and all assignments have been assessed. The following grading scale will be used for the module: Fail (U), Pass (G), or Pass with Distinction (VG). To receive the grade of Pass (G) for the module, it is required that all assignments are passed.

A student who does not pass the first examination will be offered an opportunity to sit a re-examination within two months. An additional examination opportunity is normally offered every academic year, one week prior to the start of the autumn term. If required by specific circumstances, other forms of examination may be used.

A student that has failed an examination on two occasions has a right to have another examiner or grading teacher appointed, unless there are special reasons against it. A written request addressed to the Director of Studies should be made no later than two weeks before the next examination opportunity.

Exceptions from examination form as stated in the syllabus can be made for a student who has a decision on pedagogical support for disabilities. Individual adaptations of the examination form should be considered based on the student's needs. The examination form shall be adapted within the framework of the expected learning outcomes stated in the course syllabus. At the request of the student, the course responsible teacher, in consultation with the examiner, must promptly decide on the adapted examination form. The decision must then be notified to the student.

Academic integrity and cheating

As a student, you are expected to act with academic integrity. This means writing and presenting within the limits of the academic rules and expectations communicated in the university's regulations and what is otherwise specified by the responsible department.

Disciplinary action may be taken against students who use unauthorized help aids or in some other way try to mislead on a test or on another type of task for examination. Rules and regulations concerning the production of academic texts and correct referencing will be applicable to written assignments. Submitted material may be subject to plagiarism control. In addition, Umeå University rules and regulations for education and research apply.