EconPapers    
Economics at your fingertips  
 

Teaching Economic Growth Theory with Data

Bruce T. Elmslie and Edinaldo Tebaldi

The Journal of Economic Education, 2010, vol. 41, issue 2, 110-124

Abstract: Many instructors in subjects such as economics are frequently concerned with how to teach technical material to undergraduate students with limited mathematical backgrounds. One method that has proven successful for the authors is to connect theoretically sophisticated material with actual data. This enables students to see how the theory relates to the real world, allowing for a deeper understanding of both. The authors developed a simple and insightful empirical application of the Solow growth model that can be used in an undergraduate macroeconomics or economic growth course. The exercise uses a data set on perception of corruption levels by country to look at the relationship between corruption and the level and rate of growth of output per worker across 70 countries. The results not only allow students to see for themselves the impact that corruption has on gross domestic product per worker but also improve their understanding of the distinction between level effects and long-run growth effects.

Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1080/00220481003617244 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jeduce:v:41:y:2010:i:2:p:110-124

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/VECE20

DOI: 10.1080/00220481003617244

Access Statistics for this article

The Journal of Economic Education is currently edited by William Walstad

More articles in The Journal of Economic Education from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-22
Handle: RePEc:taf:jeduce:v:41:y:2010:i:2:p:110-124