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1991-1995. Also, a standard multinomial Logit model was estimated. The
parameter estimates differ between these two specifications suggesting
serially correlated errors and firm specific effects have important
implications in modelling switches towards energy saving heating
technologies.
The results show that an increase of the price of energy encourages
the adoption of a highly energy efficient energy saving technology ( i.e. co-
generators combined with heat storage), but discourages the adoption of
heat storage. This result implies that an ad valorem tax on energy 7 would
enhance the adoption of co-generators in combination with heat storage.
The results also show that adoption of new heating technologies depends
on firm capital and capital allocation. Incentives to invest in new heating
technologies increase with low levels of capital in structures. Capital in
heating technologies and structures are substitutes such that incentives to
invest in energy saving heating technologies are higher at firms with a
small stock of investments in structures. Firms that have already invested
much in machinery and installations have a larger probability of adopting a
co-generator than firms with low initial investments in machinery and
installations. Firm size has a positive impact on investments in storage and
a negative impact on investments in co-generators implying that scale
economies are more important in investments in storage than in co-
generators. The probability of investing in different energy saving
technologies differs across firm types.
The method of Simulated Maximum Likelihood that was adopted
in this chapter allows for an error structure, with random effects and serial
correlation. The random effects specification accounts for unobservable
variables related to the firm operator and firm thereby exploiting the panel
data that were available in this study. Firm operator specific factors are e.g.
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