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| Abstract |
Chapter I gives a brief introduction to the topic of the thesis and summarizes the main results.
Chapter II an aggregated consumption function based on the life cycle hypothesis using the error correction methodology is estimated for Sweden. Wealth in its disaggregated form (financial and housing wealth) is incorporated in the consumption function, along with basic standard explanatory variables including the unemployment variable. Applying Hendry’s general to specific modelling strategy one final model is deduced. The study finds that each of the primary components of wealth has an equal role for consumer’s expenditure. In addition the study finds significant effects from employment and interest rates.
Chapter III a stock-flow model serves as the theoretical basis for the fundamental determinants of real estate construction and prices. A housing market model for Sweden has been estimated on semi-annual data for 1970-1998 by separately modelling the demand and the supply sides, specified in error correction form. The supply side is based on Tobin’s q-index. The results indicate that even in a turbulent period, Swedish house prices and housing investment are tracked quite well with this specification. The importance of the simulations and their usefulness to Swedish policy makers is discussed. Both ex post and ex ante forecasts using the model gives reasonable results.
Chapter IV (with Zan Yang), we estimate quarterly dynamic housing demand and investment supply models for Sweden and the UK for the sample period 1970-1998, using an Error Correction Method (ECM). In order to facilitate comparisons of results between Sweden and the UK we model both countries similarly using comparable exogenous variables. The long run income elasticity for Sweden and the UK are both constrained to be equal to one. The long run semi-elasticity for interest rate is 2.1 for Sweden and 0.9 for the UK. The speed of adjustment on the demand side is 12% and 23% for Sweden and the UK, respectively, while on the supply side it is 6% and 48%. Tobin’s q Granger causes housing investment.
Chapter V (with Lars-Erik Öller), evaluates the one-year ahead forecasts by the OECD and by national institutes of GDP growth and inflation in 13 European countries. RMSE was large 1.9% for growth and 1.6% for inflation. Six (11) OECD and ten (7) institute growth forecasts records were significantly better than an average growth forecast (the current year forecast). All full record-length inflation forecasts were significantly better than both naive alternatives. There were no significant differences in accuracy between the forecasts of the OECD and the institutes. Two forecasts were found to be biased and one had auto-correlated errors.
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This page was last updated on 2008-9-25.