Our systems are now restored following recent technical disruption, and we’re working hard to catch up on publishing. We apologise for the inconvenience caused. Find out more: https://www.cambridge.org/universitypress/about-us/news-and-blogs/cambridge-university-press-publishing-update-following-technical-disruption
We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Published online by Cambridge University Press: 26 March 2020
Both the models whose performance is reviewed here(1) made use of the concept of a ‘depreciated stock’, and consisted of a relationship between income and other variables and depreciated car stock. To quote the original article : “ Most forecasts of demand normally attempt first to establish some historical relationship between movements in the consumption of the commodity in question, and changes in incomes and relative prices; these relationships are then used for forecasting. With cars (as with other durables) there is a difficulty about the concept of consumption. A car is not ‘consumed ‘immediately upon purchase; it lasts a considerable number of years. Further, for cars (unlike most other durables) there is a big secondhand market.”
note (1) page 35 See the references in footnote (1), page 34.
note (1) page 35 This applies to the first model, used in the Review.
note (1) page 37 This car stock consumption—or replacement demand— is not the same as scrapping measured in numbers; in the early ‘fifties scrapping in numbers was close to zero, but replacement demand ran at about 10 per cent of the existing car stock.
note (2) page 37 These latter variables were transformed before being entered in the equation : see Appendix, page 62.
note (3) page 37 This can be divided into the error due to the ‘unex plained’ residual error and the ‘explained’ regression error; here these two are taken together.
note (4) page 37 A further source of error arises from the continual revision of official statistics; this is ignored in this article.
note (5) page 37 Most of the ‘conditions’ error arises from the incomes estimate. The predictions for the other independent variables were closer to the actual estimates, and in any case the associated elasticities of the other variables are low, so that errors in them would only make a small contribution to the total error.
note (1) page 38 In symbols this may be rewritten approximately as :
where each ratio is expressed as a percentage.
note (2) page 38 The five-year rate of growth of new registrations was 60 per cent in the five years to 1960; 85 per cent in the five years to 1961; 84 per cent in the five years to 1962; 82 per cent in the five years to 1963; 84 per cent in the five years to 1964; and 40 per cent in the five years to 1965.
note (1) page 39 Of the cars supplied in any year one-ninth were assumed to be scrapped after 10 years, two-ninths after 11 years, one- third after 12 years, two-ninths after 13 years, and the remaining one-ninth after 14 years.
note (1) page 40 This forecast was based on G. C. Chow's estimate of an income—stock elasticity in the United States of 1 1/2 and 2; but the car park was expected to grow more slowly than the car stock, as the average age of cars in use fell.
note (2) page 40 The income-car park elasticity assumed for 1965-70 was 1.1; the rise in real national product assumed was 3.3 per cent, compared with 3.6 per cent in the previous five years.
note (1) page 43 The figures at present available for 1960 differ from those used in the previous article : the share of imports in total supplies is now given as 69 per cent in 1960, as against 77 per cent in the calculations made in 1961.
