Steady State, Factor Income, and Technological Progress
Karl Farmer and
Matthias Schelnast
Additional contact information
Matthias Schelnast: University of Graz
Chapter 3 in Growth and International Trade, 2021, pp 57-82 from Springer
Abstract:
Abstract This chapter continues the analysis of the basic OLG growth model of the previous chapter. First, the GDP growth rate is defined and related to the growth factor of the (efficiency-weighted) capital intensity. Second, assuming the GDP growth is constant over time and equals the natural growth rate, sufficient conditions for the existence of a unique and globally stable steady state are presented. Third, intergenerational efficiency of the steady state is discussed. Fourth, the comparative dynamics of changes in basic OLG model parameters is illustrated graphically. Fifth, the evolution of the main economic variables, associated with capital intensity along the intertemporal equilibrium path and in steady state, is investigated. Sixth, different concepts of neutral technological progress are compared. Finally, an example of growth accounting is presented in order to demonstrate the empirical significance of technological progress for GDP growth.
Keywords: Technological progress; Real interest rate; Real wage rate; Capital intensity; Natural growth rate (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Chapter: Steady State, Factor Income, and Technological Progress (2013)
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:spr:sptchp:978-3-662-62943-7_3
Ordering information: This item can be ordered from
http://www.springer.com/9783662629437
DOI: 10.1007/978-3-662-62943-7_3
Access Statistics for this chapter
More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().