A Bayesian approach to labour market modelling in dynamic microsimulation

Hans Bækgaard
Additional contact information
Hans Bækgaard: Danish Rational Economic Agents Model, DREAM, http://www.dreammodel.dk/

No 201301, DREAM Working Paper Series from Danish Rational Economic Agents Model, DREAM

Abstract: The paper presents a novel approach to modelling labour market processes in dynamic microsimulation. The method combines and integrates Bayesian simulation based estimation and simulation of the dependent variables. The approach is applied to a dynamic panel model for hourly wage rates for Danish employees using a large panel data set with 17 years of data for 1995 to 2011. The wage rate model and a parallel model for annual work hours are currently being implemented in SMILE (Simulation Model for Individual Lifecycle Evaluation), a new dynamic microsimulation model for the Danish household sector. The application benefits from the richness of Danish administrative panel data. Nevertheless, the results and the approach have several features that should be of interest to micro-simulators and others. Indeed, the model features both an extraordinarily comprehensive list of dependencies and a rich dynamic structure. Together, these features contribute to ensure that simulations produce realistic cross-sectional distributions and interactions as well as inter-temporal mobility – the key determinants of the quality of a dynamic microsimulation model. In addition to the 'usual' socio-demographic variables (gender, age, ethnicity, experience, education etc.), the dependencies include a more novel set of variables that represent a person’s labour market history, secondary school grade and social heritage (represented by the parent’s education level). The dynamic model structure includes a lagged dependent variable, an auto-correlated error term with a mixed Gaussian distribution for the white noise component, an individual random effect with a mixed Gaussian distribution and permanent effect of a person’s first wage after leaving the education system. The estimation sample is identical to the simulation sample, which allows us to use the same historical detail as well as estimated individual effects – i.e. random effect components – for the simulation of future wage rates. The Bayesian estimation method handles missing observations for the dependent variable – due to either non-employment or temporary non-participation – by treating missing observations as latent variables that are simulated alongside the Bayesian iterations. As a byproduct, the estimations produce model consistent latent wage rates for the unemployed that are useful for labour supply analysis.

Keywords: labour market; modelling; dynamic microsimulation (search for similar items in EconPapers)
Pages: 51 pages
Date: 2013-12
New Economics Papers: this item is included in nep-cmp and nep-ger
Note: Conference paper for the 4th General Conference of the International Microsimulation Association
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.dreammodel.dk/SMILE/N2013_05.pdf First version, 2013 (application/pdf)

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:dra:wpaper:201301

Access Statistics for this paper

More papers in DREAM Working Paper Series from Danish Rational Economic Agents Model, DREAM Amaliegade 44, DK - 1256 Copenhagen K. Contact information at EDIRC.
Bibliographic data for series maintained by Peter Stephensen (psp@dreammodel.dk).