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| Abstract |
The model includes seven sectors (Central Bank, central government, banks mortgage institutions, private and social insurance, non-financial business and households, foreign) and nine asset categories (certificates, bonds, bank deposits, loans, equity, net foreign assets, notes and coin, insurance savings and claims on the National Savings Scheme). Emphasis was laid on modelling demand for bonds and certificates, which in turn affects the bond rate and the money stock. Sector demand for equity is - with two exceptions - determined exogenously, due to problems with modelling yield on equity and changes in market value.
Despite the relatively large number of assets the model is rather simple, any refinements having been left to subsequent model versions. The approach is eclectic. At the core of it lies the portfolio balance model, but the portfolio in question is defined narrowly to include only net foreign assets, certificates, bonds and (bank deposit) money. The remaining assets are assumed to be acquired for other reasons than pure portfolio investment and their purchase is assumed to be effected before any portfolio decision is taken. Furthermore, the portfolio choice is assumed to take place in two steps, the first decision referring to the choice between foreign and domestic assets.
The model`s data base consists of a flow-of-funds matrix (or its stock-value counterpart) derived from the Financial Accounts published by Statistics Sweden. Annual Financial Accounts time series for 1986-94 were distributed by half-years (and in some instances quarters) using other sources, in particular the data compiled by the Central Bank. Despite much effort, we were not always able to reconcile time series coming from different sources.
The quality of the data is in some respects rather poor, although a major effort has been made to compile a good statistical data base for the project. One of the problems, but definitely not the only one, is the uncertainty regarding the extent to which assets are reported at market value as opposed to nominal value.
The poor quality of the data and the limited number of observations available affected the estimation strategy. While statistical inference often is difficult in small samples (in particual when only asymptotic distributions for the test variables are known), data problems and apparent measurement errors made test results the more dubious. In formulating equations, theory and considerations relating to the desired simulation properties of the model were given precedence over test results. Furthermore, the OLS estimator was employed, since instrumental variable methods can result in large small-sample bias when instruments are correlated with the error term or are only weakly correlated with the endogenous explanatory variables (cf. Bound, Jaeger and Baker (1995)). Standard computer printout is shown for all the equations as a general information for the reader.
A rather uncommon approach was employed in order to improve the reliability of the estimates. Regressions were - whenever possible - based on quarterly data, the resultant equations being subsequently transformed into semi-annual form to conform with the requirements of KOSMOS. To this end, a theory of temporal aggregation of equations was developed in Ruist (1996)).
The structure of the paper is as follows. A theoretical portfolio model is outlined in the next chapter. Thereafter, the empirical model is described in general terms. The two subsequent chapter deal with the determination of the exchange rate and of the interest rates, respectively. The seven final chapters deal with the seven sectors of the model, giving an account of the demand for and supply of assets by sector.
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This page was last updated on 2009-10-22.