Public Policy Sources #37:
Footnotes

See Barro and Sala-i-Martin 1995: ch. 10 for a more detailed discussion of growth accounting.

Many economists date the birth of modern growth theory in the 1920s with Frank Ramsey's (1928) seminal article on optimal savings over time.

As we noted earlier, constant returns to scale implies that a doubling of inputs doubles output (i.e. if the firm uses twice as many machines and twice as many workers, it produces twice as much output). Diminishing returns to, say, capital implies that as we add more capital (holding fixed the number of workers), we get more output but each additional unit of capital adds less to output than the previous unit.

In fact, these papers have antecedents in an earlier literature pioneered by Arrow (1962) and Sheshinski (1967).

In these models, knowledge enters the production function as an input, just as capital and labour do. Hence, the production function can now be written as Y = F[L, K, I] where Y is real output, L is the stock of labour, K is the capital stock, and I is the stock of knowledge. The assumption of increasing returns to scale in knowledge implies that an increase in I will result in a more than proportionate increase in Y.

This idea--that firms compete in the production of knowledge and that market power is necessary for technological advance--was first articulated by Schumpeter (1934) and is called the process of "creative destruction."

Loosely speaking, agglomeration effects arise when there are positive locational spill-overs associated with a particular industry. Agglomeration effects are often used to explain the clustering of firms in the same industry in particular locations--for instance, the clustering of high technology firms in Silicon Valley. Firms in the same (or similar) industry may benefit from locating near each other since, by being in close proximity, they can gain from (i) increased interaction that facilitates the transfer and development of ideas; (ii) economies of scale in the production of industry-specific infrastructure; (iii) the presence of a large pool of skilled personnel. See Krugman 1991 for an overview of some of this work; see also Grossman and Helpman 1991.

In particular, Easton and Walker (1997) estimate that an increase of one standard deviation in economic freedom (as measured by The Fraser Institute's Economic Freedom Index) raises the steady-state level of income by US$1,556. See Gwartney, Lawson and Block 1996 for more details about the construction of The Fraser Institute's Economic Freedom Index.

For a readable survey of some of the work undertaken for Industry Canada on these topics, see Policy Research Initiative 1999: ch. 2. Sharpe 1998 also provides an excellent summary of this work.

Indeed, according to the Policy Research Initiative 1999, Canada's relative living standards among OECD countries, measured by GDP per capita, have fallen from third place in 1979 to ninth place in 1996.

In particular, the official repsonse of Jean Chretien's government is that Canada does not have a productivity problem. Citing as evidence some of the findings from a recent KPMG study (1999), the Prime Minister has argued that this is so because Canada has the lowest overall business costs among the G-7 nations. This view is problematic for the KPMG study is a cost-comparison study not a productivity study. For a critique of the official government view, see Appendix 2.

Sharpe 1998 provides an excellent discussion of this issue. For lack of space, we shall not discuss it further in this paper.

According to Industry Canada (1997), foreigners seeking patent protection within Canada make most of the patent applications in Canada. Patent grants to foreigners out-number grants to Canadians by a factor of 12.

It is not unambiguously clear whether the location of R&D activity matters for an open economy like Canada's. If technological progress is cheaply available to all countries and there are no agglomeration effects, then whether R&D activity occurs in Canada or elsewhere is irrelevant. However, as I discussed earlier, in a world where technological transfer is costly and where there may be significant agglomeration effects associated with R&D activity, then the location of R&D activity matters. The empirical evidence suggests that the latter may be a better description of the real world. See Krugman (1991) for a summary of some of this work.

For a comparison of the dead-weight losses of various taxes in Canada, see Dahlby (1994).

The fundamental problem is, therefore, not insufficient investment in higher education and training but, rather, a misallocation of investment, likely brought about by widespread government intervention in the market for higher education and training. See West 1988 for a critique of government policy toward higher education.

For an overview of the economics of the brain drain, see Grubel 1998. Devoretz and Laryea (1998) estimate the value of human capital flows into and out of Canada and find that Canada's brain drain to the United States is economically costly.

Industry Canada (1999) has also emphasized this point. They write: "The improvement in Canada's cost competitiveness vis-à-vis the US in the 1990s has been entirely due to a depreciating Canadian dollar