1. Methodology
  2. Dynamic microsimulation
Download icon

Increasing the impact of dynamic microsimulation modelling

  1. Cathal O’Donoghue  Is a corresponding author
  2. Gijs Dekkers  Is a corresponding author
  1. National University of Ireland, Ireland
  2. Federal Planning Bureau, Belgium
  3. Centre for Sociological Research (CESO), KU Leuven, Belgium
Research article
Volume 11(1) Spring 2018
Cite this article as: C. O’Donoghue, G. Dekkers; 2018; Increasing the impact of dynamic microsimulation modelling; International Journal of Microsimulation; 11(1); 61-96. doi: 10.34196/ijm.00174
1 figure and 5 tables

Figures

Figure 1
Download asset Open asset
Complexity in dynamic microsimulation models – inter-temporal microsimulation models.

Tables

Table 1
Proportion of articles published in different formats 2013+.
Journal Mimeo Book Conference Proceedings
0.67 0.16 0.09 0.07

  1. Source: Google Scholar.

Table 2
Share of articles by application area 2013+.
Application Area Share of Papers
Labour Market 0.23
Education 0.03
Wealth 0.04
Income Distribution & Social Protection 0.03
Pensions 0.13
Health 0.18
Elderly Care 0.07
Demography 0.14
Energy, Environment and Land Use 0.10
Spatial 0.04

  1. Source of bibliographic analysis: Google Scholar.

Table 3
Progress achieved.
Classification in Hoschka (1986)4 Achievement
Behaviour Better Micro-Econometrics, albeit often limited to comparative statics.
Access to Data Vastly improved access, especially in administrative data; although some reversals in survey panel data.
Model Development Development of open-source microsimulation platforms with shared models (MODGEN, LIAM2, JAS-mine, FEM).
Computer Hardware Huge improvements.
Policy Areas New policy areas, e.g. “health microsimulation”.
Validation About 10% of the investment time in developing a dynamic microsimulation model is taken up by the actual construction, the remaining 90% is validation (Caldwell & Morrison, 2000).
Complexity Constant struggle.
Table 4
Who are the participants in world congresses of microsimulation?
World Congress Research University Government Private Sector
Turin 21% 54% 21% 4%
Canberra 20% 42% 34% 4%

  1. Source: Google Scholar.

Table 5
Where to next?
Classification in Hoschka (1986) Requirement
Behaviour Still too little focus on causality. However much of existing literature is not possible to extrapolate.
Access to Data Era of big data: how to utilise?
Model Development What are the best methods to use? The need for more methodological research.
Computer Hardware Cloud computing.
Policy Areas Big global questions like impact of climate change and greater market risk; other policy areas.
Validation Confidence intervals and Monte Carlo.
Complexity Constant trade-off.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)