Demographic forecasts and fiscal policy rules
Jukka Lassila,
Tarmo Valkonen and
Juha M. Alho
International Journal of Forecasting, 2014, vol. 30, issue 4, 1098-1109
Abstract:
All quantitative evaluations of fiscal sustainability that include the effects of population ageing must utilize demographic forecasts. It is well known that such forecasts are uncertain, and some studies have taken that into account by using stochastic population projections jointly with economic models. We develop this approach further by introducing regular demographic forecast revisions that are embedded in stochastic population projections. This allows us to separate, for each demographic outcome and under different policy rules, the expected and realized effects of population ageing on public finances. In our Finnish application, demographic uncertainty produces a considerable sustainability risk. We consider policies that reduce the likelihood of getting highly indebted and demonstrate that, although demographic forecasts are uncertain, they contain enough information to be useful in forward-looking policy rules.
Keywords: Public finance; Fiscal sustainability; Stochastic population simulations; Changing demographic forecasts (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207014000570
Full text for ScienceDirect subscribers only
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:eee:intfor:v:30:y:2014:i:4:p:1098-1109
DOI: 10.1016/j.ijforecast.2014.02.009
Access Statistics for this article
International Journal of Forecasting is currently edited by R. J. Hyndman
More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).