Applied Economics for Decision Making 30 hp

Undervisningen bedrivs på engelska.

Kursinnehåll

This course is designed to provide students with the tools and knowledge in how to solve economic problems that the student might encounter later in his/her career. The course combines a variety of theories and perspectives to enable students to develop theoretical and practical knowledge about different economic fields, as well as an understanding of which methods to use to solve problems and provide material for decision making within these fields. As such, the knowledge gained by students in the course will help them to assess which information is needed, how to produce such information, and how to analyse it to make decision regarding economic problems.
The course consists of 5 modules of 6 credits each. The individual modules are explained below:

Module 1: Quantitative methods
The objective of this module is to offer the students a toolbox for the upcoming modules, covering an understanding on how to use descriptive statistics to illustrate the underlying patterns as well as statistical methods relevant for quantitative analysis. The programming language Python is introduced with a focus on predictive modelling using some of the main econometrical methods such as OLS regressions. There is also Geoprahical Information System (GIS) part focusing on the skill to create maps to visualize a pattern. The maps can be used as a tool that enables individuals to grasp, analyze, and understand a given pattern and relationship. The part that covers statistical methods concerns quantifying and interpreting economical relationships using the appropriate statistical techniques. The knowledge of this module is not only useful for the next coming modules, but also relevant for analyzing policy evaluations and governmental reports, as well for the upcoming thesis writing.


Module 2: Platform Economics
Students learn to use economic theory and tools to analyze digital platforms, such as online marketplaces, search engines, and social media. The course proposes an analytical framework that examines platform types, revenue models, competitive dynamics, and implications for policymaking and society. Students learn to apply large language models and deep learning techniques to analyze unstructured data (e.g., sentiment analysis based on transformers using Python), alongside methods for causal inference from observational data generated on platforms (e.g., difference-in-differences estimation using Stata). When applying these methods, emphasis is placed on best practices for reproducibility of empirical research as well as guidelines for compiling replication packages.

Module 3: Geographical economics
The objective of this module is to give students knowledge about the location aspects of economic phenomena, based on various forms of scale economies, externalities, and transport costs. The course will provide the student with a capacity to critically analyze economic problems relating to location, specialization, and trade between regions/countries. It will give students an understanding of the sources of the geographic concentration of economic activity. It will deal with the questions regarding the trade-off between economic efficiency and geographic inequalities and related policy choices. The content of the module is tightly linked to research in the field of geographical economics and New Economic Geography (NEG).

Module 4: Public economics
This module concerns the effect of regulations, taxation, social insurance and public spending on households and firms. Theoretical models will be combined with empirical evidence. The module discusses how the government intervenes in different markets and the distributional effects of such interventions. The role of the government will also be discussed in situations of market failures and how the government can either act as an supporting party by providing incentives but can also discourage economic agents in different ways. There is also an introduction to Cost-Benefit Analysis (CBA) both of its theoretical basis as well as the typical steps to follow when performing a CBA. Contemporary issues of CBA are covered such as discounting, benefit transfer and optimism bias.

Module 5: Case study in applied economics
This module includes several different components. The first part focus on (i) the skills to write reports for public organizations and/or private companies, and (ii) presentation skills. This module will further provide students with a real case that they will have to solve in a group. The case will be presented by an external stakeholder and the task of the students is to solve the case in the best possible way, using all the tools and skills learned during the course. The students will have to present the case for a group of individuals consisting of both external stakeholders and researchers within the field, who will also evaluate the case based on both the written material and the presentation. This module will provide students with knowledge about report writing, presentation skills, and in depth knowledge about a case.

Connection to Research and Practice
Parts of this course are directly related to the focus areas at Jönköping International Business School (JIBS): entrepreneurship and renewal. Parts of the course are also tightly connected to the Center of Entrepreneurship and Spatial Economics (CEnSE) at JIBS, which focus on entrepreneurship and regional development/growth.
Throughout the course connections will be made to real-word applications to enhance the students learning and ability to make use of the taught skills in their later careers. The students will also appreciate how these skills can be used in policymaking to influence the development of society, and how theory and empirical work can be used to guide policy.

Förkunskapskrav

A Bachelor's degree equal to 180 credits (or the equivalent), including 60 credits in Economics, and a minimum of 15 credits in mathematics, statistics and/or econometrics.

Utbildningsnivå: Avancerad nivå
Kurskod/Ladokkod: JEDR24
Kursen ges vid: Jönköping International Business School Last modified 2024-11-13 13:38:22