An empirical analysis of housing allowance recipients 2010- 2020 and a forecast of the near future
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- Master of Science 
This study seeks to identify the attributes of recipients of housing allowance in Norway and formulate an econometric model capable of predicting the inflow of new recipients of housing allowance in the near future. As the Norwegian State Housing Bank receives funding via the state budget, such a model will help to ensure that the bank receives proper funding. The study finds that the number of applicants, recipients and new recipients has decreased significantly over the past ten years, despite that the number of people considered poor in Norway has increased. Moreover, the anticipated effect of income and housing expenses are minimalised through the politically decided income and approved housing expenses limits. Furthermore, we find the inflow of new recipients to be a function of previous inflow, average housing expenses, age, regulations, employment, and unemployment. The chosen model to forecast the inflow is Vector Autoregression (VAR) model. Moreover, through an Impulse Response Function (IRF), we find that Regulation and Employment are the two variables that has the greatest effect on the inflow of new recipients. The accuracy of the model is tested by comparing the VAR forecast to a forecast with linear regression and actual values. Moreover, it is evaluated using mean error (ME), mean percentage error (MPE) root mean squared errors (RMSE), mean absolute errors (MAE), mean absolute percentage errors (MAPE). The study concludes that given the available data, the VAR model is able to produce satisfactory results, although the precision and the usage of external data can be better.
Masteroppgave(MSc) in Master of Science in Business Analytics- Handelshøyskolen BI, 2020