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The Connection between Labour Productivity and Wages

by Christopher Bruce

This article first appeared in the summer/autumn 2002 issue of the Expert Witness.

Many readers of this newsletter will have received personal injury damage assessments in which the expert has argued that wages in a particular industry will increase at some rate – for example, 1.5 percent per year – “because” output per worker (productivity) in that industry is projected to increase at that rate.

What I wish to show in this article is that, as appealing as this argument may be to the layperson, it is wrong. Not only does economic theory predict that the connection between industry productivity and wages in that industry will be tenuous at best; empirical evidence reveals that there has been virtually no connection whatsoever between industry wages and industry productivity in Canada.

I proceed by first describing the method that agencies like Statistics Canada use to measure labour productivity. I then describe the economic theory of how wages are determined within industries and occupations. In a third section, I contrast that theory with the theory of national wage determination. Finally, I present some recent statistical data concerning the relationship between the rate of growth of productivity and the rate of growth of wages at the industry level in Canada.


Statistics Canada obtains an index of the “real” level of output in each industry by dividing the total revenues received by the firms in that industry by an index of the industry’s prices. For example, if total revenue in the clothing industry was $100 billion in 2001 and the clothing retail price index was 125, the index of real output would have been calculated to be 800 million. If revenues rose to $110.5 billion in 2002 and the price index rose to 130, the output index would have risen to 850 (million).

Labour productivity, or output per hour of work, is then found by dividing the (real) output index by the number of hours worked by individuals in that industry. If clothing workers worked 100 million hours in both 2001 and 2002, for example, output per worker hour would be found to have increased from 8.00 to 8.50 between those years, or by 6.25 percent.

Note that there is no connection between revenues per worker and output per worker. It is quite possible, for example, for revenue to rise because prices have risen while labour productivity has remained unchanged. Conversely, even if output per worker has risen substantially, if prices have fallen revenue per worker may have remained constant or even fallen.

Theory – Industry Wage Levels

Those who believe that there is a connection between labour productivity and wages within an industry (or occupation) implicitly assume the following: When output per worker increases, workers’ contributions to firm revenue increase causing demand for workers to increase also. As wages are determined by supply and demand, an increase in demand will imply an increase in wages.

This “theory” is wrong for two reasons. First, there is no necessary connection between output per worker and revenue per worker. As was pointed out above, if demand for the industry’s product is decreasing, the price that can be charged for that product will also be decreasing. Hence, even if output per worker rises, revenue per worker may fall.

Furthermore, when output per worker increases, the industry will have to sell additional units of output; that is, industry supply will rise. But, by the laws of supply and demand, when supply increases, prices decrease. That is, the increase in worker productivity may cause a decrease in prices.

In some cases, this decrease in prices is so extreme that an increase in worker productivity may actually cause a decrease in revenue per worker. The clearest example of this phenomenon has occurred in agriculture, where farm incomes are under constant downward pressure even though productivity gains have been greater in that sector than in most other industries.

Second, even if an increase in labour productivity does lead to an increase in revenues generated per worker, it is not necessarily the case that the consequent increase in demand will be associated with a long run increase in wages (relative to other industries). The reason for this is that, in the long run, additional workers can be supplied to that industry, which offsets the upward pressure on wages. That is, when demand for an industry’s workers increases, wages in that industry do not rise relative to wages in other industries. Rather, it is employment in the high productivity industry that will rise relative to employment in other industries.

Assume, for example, that there is a large group of workers who would be approximately indifferent between working as plumbers, carpenters, and electricians. Assume also that, initially, all three receive the same wage rate. Now, if productivity rises among electricians, there will be an increase in demand for electricians. In the short run, say a year or two, it will not be possible to train additional electricians and wages may be bid up.

But, when wages are higher among electricians than among plumbers and carpenters, students graduating from high school will prefer to train as electricians. Soon, the supply of new electricians will increase and the supply of new carpenters and plumbers will decrease. Wages will fall among electricians and will rise among plumbers and carpenters.

Ultimately, the wages of all three occupations will equalize. All three will enjoy higher wages than they did initially. But, among plumbers and carpenters this will have occurred without any increase in productivity. And, among electricians, the wage increase will have been much smaller than the productivity increase, because the effect of that increase will have been diluted by the influx of workers from other occupations.

Indeed, if the initial number of electricians had been considerably smaller than the number of plumbers and carpenters, it is possible that the wage increase experienced by all three groups would have been negligible. The number of workers who would have to leave the plumbing and carpentry trades would have been so small, relative to the total numbers in those trades, that their exit would have had very little effect on wages in those occupations.

The primary effect of the productivity increase among electricians is that the number of electricians will increase and the numbers of plumbers and carpenters will decrease.

Similar effects can be seen in other industries. We know, for example, that in the last 50 years there have been far greater productivity gains in “fast food” restaurants than in restaurants serving “classic cuisine.” Yet, wages have not increased in the former relative to the latter. The primary reason is that every increase in demand for fast food workers has been met by an influx of workers from other unskilled industries.

This is not to say that there is no connection between productivity and wages at the industry level. If the number of workers in an industry is not responsive to changes in wages, an increase in productivity may produce a permanent wage increase. There may, for example, be institutional barriers preventing additional workers from entering an industry – such as union regulations or restrictions on the numbers of students training for that industry at university or college. Alternatively, there may simply be a limited number of individuals who have the aptitude to enter certain industries or occupations. Once that number had been exhausted, further wage increases might not call forth additional labour supply.

Theory – National Wage Levels

Even if there is only a limited connection between wages and productivity at the industry level, there may still be a strong connection at the national level. When productivity gains drive up wages in one industry or occupation, it is anticipated that workers will be drawn from other industries and occupations, thereby returning relative wages to their initial level. If productivity increases at the national level, however, the equivalent effect would require that workers be drawn from other countries. But, as Canada restricts the number of immigrants, this effect will be much less important for national wage levels than it was for industry wage levels.

Also, a productivity gain at the national level is less likely to lead to a reduction in output prices than is an equivalent gain at the industry level. When output increases in an industry, everything else being constant, the industry may have to lower prices in order to sell that increase. When output increases in the nation as a whole, however, all workers will have higher incomes and those incomes may be used to purchase the increased output. In a sense, the increased output “creates” the increased demand to purchase that output. Prices need not fall.

And if prices do fall, the “real” incomes of all workers will increase. That is, even if observed (or nominal) wages do not change, workers will be able to buy more goods and services with their incomes. They will be better off in a “real” sense. Thus, an economy-wide increase in productivity could cause an increase in the welfare of workers, not through an increase in observed money wages, but through a decrease in average prices.


The evidence concerning the connection between industry-level wages and productivity is clear. In its recent publication, Productivity Growth in Canada, Statistics Canada provided information concerning relative productivity growth and relative changes in wages for 46 Canadian industries, from 1961-1995.

These statistics have been plotted in the figure below, with industries ranked from lowest to highest productivity growth over that period. It is seen clearly in that figure that there is virtually no correlation at all between an industry’s relative productivity growth and its growth in relative wages. Indeed, regardless of an industry’s growth in productivity, its relative wages remained unchanged.

Figure 1


There are sound theoretical reasons for predicting that there will be very little correlation between an industry’s productivity growth and its wage growth. The empirical evidence provides strong support for this prediction. Indeed, that support is so strong that it is incumbent on any expert who would argue that a correlation exists between productivity and wages to justify that argument.


Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).


In this article Christopher Bruce examines the theory and evidence behind the assertion that wage growth among workers in a specific industry can be linked to the productivity growth of those workers. He finds that there are sound theoretical reasons for predicting that there will be very little correlation between an industry’s productivity growth and its wage growth. He also finds that the empirical evidence supports this prediction.

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