Barely 20 mathematical signs, an international team of researchers and a young researcher with flair for numbers by the name of Malene Kallestrup-Lamb. These are the main ingredients for achieving a potentially large saving for the Danish state.

Due to an aging Danish population significant amounts will be invested both in the public and private sector over the next decades. Pension funds will be forced to develop new products and the public sector will invest heavily in both healthcare and caretaking of elderly individuals. These investments are often based on population projections where mortality plays a significant role. Moreover, other factors such as fertility, immigration and emigration are accounted for in the forecast. 

As investments are often made five, ten or fifteen years in advance, it is vital that the projections are as accurate as possible. If suddenly there is unanticipated increase in the number of older individuals, the health care sector, care taking homes, pension funds and municipalities might have to resort to expensive short-term investments in order to meet the demand.

This is where postdoc Malene Kallestrup-Lamb from Aarhus University, School of Business and Socia Sciences might play a vital role.  Together with her Danish and international research colleagues; she has developed the so-called “Mortality Model with Covariates,” which has proven more accurate in terms of future predictions compared to the model previously used in Denmark.

Customised model for Denmark

The researchers are in the process of adjusting the model to account for country specific mortality patterns as big differences often are observed due to different life patterns. 

The model that has previously been used in Denmark was developed in 1992 but was initially intended for making population projections in the US. Malene Kallestrup-Lamb justifies the use of this model in Denmark so far as no relevant alternatives were available. At least until now. 

- We are developing a customised model based solely on Danish data. It has been fine-tuned to take into account the parameters that affect mortality in a small population such as Denmark, explains Malene Kallestrup-Lamb. 

The new model draws on very detailed Danish registry data derived from Statistics Denmark. After processing the anonymised data, the researchers calculate the expected mortality rate based on parameters such as civil status (married/single), which region and area you live in, your income and fortune.

Hope the model will be put to use

Malene Kallestrup-Lamb and her colleagues hope that they will get the opportunity to demonstrate what their specially designed model can accomplish:

- The next time the Danish Welfare Commission and the Ministry of Finance need population projections, we are very eager to contribute with our calculations. My focus is on putting our research to optimal use, she says.

In England both private consultancy firms and public organisations are also showing great interest in the work that this group of researchers are doing. But the great challenge here is that the English registry data is not as comprehensive as the Danish. Therefore the researchers are now working to develop a customised model for England. 

Contact:

Malene Kallestrup-Lamb, PhD, postdoc.

Aarhus University, School of Business and Social Sciences
Department of Economics and Business - CREATES - Center for Research in Econometric Analysis of Time Series
E-mail: mkallestrup@econ.au.dk
Tel.: + 45 87165547
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