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Kinds of productivity indexes

Productivity indexes and production functions

Variation in labor productivity

Variation in efficiency

Productivity and wages

Productivity and employment


Productivity, as discussed here, refers to a class of empirical output-input ratios that is widely used in economic history, economic analysis, and economic policy. In one sense, productivity measures the fruitfulness of human labor under varying circumstances. In another sense, productivity measures the efficiency with which resources as a whole, including capital as well as manpower, are employed in production. In still another sense, productivity measures the forces that underlie the trend of real wages. And in a fourth sense, productivity measures a major factor in the determination of labor or capital requirements. Productivity measurements are addressed to important questions.

As we shall see, some of the questions are best answered with one kind of productivity measurement, and other questions with other kinds. For this reason, productivity ratios appear in a variety of forms. In addition, there are some forms that simply reflect the dearth of statistical information. These productivity ratios serve as the best available approximations to the desired measurements. To grasp the subject of productivity, therefore, it is necessary to begin by considering both the concept of productivity and its measurement.

Kinds of productivity indexes

In each of its forms, productivity appears as a comparison of an output with one or more inputs; that is, as a comparison of an output with the services of one or more of the resources used in producing the output. The comparison is most frequently put in the form of a ratio of the one to the other. Then, because the output-input ratio of a particular time and place has limited significance standing by itself, it is compared with the corresponding ratio of another time or place to estimate changes or differences in productivity levels. The comparison is usually expressed in relative form; that is, as an index of productivity.

In the output-input ratios with which we are concerned, both numerator and denominator are measured in physical units or (when heterogeneous items are combined, which is most frequently the case) in “constant-price” money values. This “physical productivity” is to be distinguished from “value productivity,” in which output is measured in current money values while input is measured in physical units or constant-price money values. It should be distinguished also from “cost of production per unit,” an input-output ratio in which input is measured in current-price money values and output in physical units.

Change in productivity can be measured by change in the relation between output and one or more inputs, either with other inputs kept constant, as in an experiment under controlled conditions, or with other inputs free to vary. We shall deal with the latter case. This means that a change in the relation between output and input, if the input is not the total input, may reflect substitution between the inputs covered by the productivity ratio and those not covered.

Finally, productivity in a given period can be measured by the ratio of the output to the input of the period, or it can be measured by the ratio of the increment in output to the increment in input during the period. That is, productivity may be “average productivity” or “marginal productivity.” We shall deal with average productivity. It should be noted, however, that under certain conditions (mentioned in the discussion of productivity and wages) indexes of average and marginal productivity are identical.

Our discussion is limited, then, to average physical productivity; that is, to the ratio of physical output to one or more physical inputs, other inputs not necessarily being constant. It is this subfamily of output-input ratios to which most productivity indexes relate.

Measure of input

While the field has been narrowed, it is still rather wide. To illustrate: (1) Output can be compared with the sum of all the hours of labor—“the manhours”—spent in production (output per manhour). Account is thus taken not only of the number of persons engaged but also of the long or short hours put in by those persons who work more or less than the average work week or year. When comparisons are made over time, allowance is thus made for the declines that have occurred in the length of the usual work week or year. When the comparisons are between nations, allowance is made for international differences in the length of the work period. (2) Output can be compared with the weighted sum of manhours employed (output per unit of labor input). That is, an hour of high-quality labor—a highly paid manhour of work—is counted as proportionately more than an hour of low-quality labor—a lower paid manhour. In this way, account is taken of differences in education, length of experience, and other factors determining the quality of labor. Thus, also, account is taken of the education and other intangible capital invested to improve the quality of labor. Or, (3) output can be compared with the services of the tangible capital employed in production—plant and equipment, tools and rolling stock, land and mines, and inventories of all sorts—as well as the services of the labor resources, each appropriately weighted (“output per unit of total input,” or “total productivity,” or most specifically, “output per unit of labor and tangible capital input”).

Obviously, of the three productivity ratios mentioned, output per manhour requires the least information and is easiest to calculate, and output per unit of labor and capital input requires the most information. It is not surprising, therefore, that the more complex measurements are also of more recent vintage and are less frequently available than the relatively simple output per manhour.

However, the productivity measurements that are more complex in terms of data requirements are—from our point of view—less complex in terms of content or meaning. Output per unit of labor input, for example, describes more than does output per unit of labor and capital input. The former is equal to the latter multiplied by another ratio, the weighted combination of labor and capital input per unit of labor input. Output per unit of labor input will rise faster than output per unit of labor and capital input when tangible capital input grows more rapidly than labor input. Similarly, output per manhour will rise faster than output per unit of labor input when education and other investments cause the quality of labor to improve. In short, change in output per manhour may be viewed—and later we will find it useful so to view it—as reflecting the combined effect of change in three things: (1) efficiency, as measured by output per unit of labor and capital input; (2) the relative supply of tangible capital, as measured by labor and capital input per unit of labor input; and (3) average labor quality, as measured by labor input per manhour.

This chain of productivity ratios can be readily extended to include ratios that are more or less complex (in either of the senses mentioned) than the ratios included in our illustrative series. Thus, when the productivity of an industry or other sector of an economy is considered, and the information is available (which it seldom is), output can be compared not only with the services of the labor and tangible capital employed by the sector but also with these plus materials, components, fuel, supplies, and other commodities and services purchased from other sectors. This productivity ratio, “output per unit of labor, capital, and material input,” is another, and somewhat different, measure of output per unit of total input. Change in output per manhour can then be said to combine the effects of change in (1) efficiency, now measured by output per unit of labor, capital, and material input, and (2) total resources per manhour, measured by labor, capital, and material input per manhour.

When the data are severely limited (which is often the case), output can be compared simply with the average number of persons engaged in production. The productivity ratio would then be simply “output per man.” Change in output per man combines the effects of change in (1) efficiency and (2) total resources per manhour, as just defined, and (3) average hours worked per man.

Measures of output

Productivity ratios may differ also with regard to the output included in the numerator. The output of a country may be identified with the goods and services produced within its borders (net domestic product) or with the goods and services available to its normal residents (net national product). National product differs from domestic product by the amount of goods and services (or the equivalent in claims on foreigners) financed by net incomes received from abroad and by net gains from improvements in the terms of foreign trade. One must decide whether or not to define a country’s productivity in such a way as to make it depend in part on changes abroad, or at least one must recognize that its productivity has been so defined when it is measured by national product per unit of input.

The use of output concepts like gross national product and gross private domestic product reflects not so much a preference for these concepts over net national product or net domestic product as a serious doubt about the accuracy of the measurement of capital consumption in the former case and of the government component of national product in the latter case. This means, of course, that gross national product per manhour, for example, is only an approximation to net national product per manhour.

The output of an industry can also be assigned different meanings. It can be measured either by the “real value added” by the industry or by its “real value of product,” where the former excludes and the latter includes the value of purchased materials, fuel, and energy. To measure an industry’s “total productivity,” then, one can compare its real value added with its labor and tangible capital input, or its real value of product with its labor, tangible capital, and material input. Less consistent, but usually unavoidable because information is lacking, is the comparison of real value of products with labor and tangible capital input. The three productivity indexes will not necessarily parallel one another. Only the first index is directly comparable with the national index of output per unit of labor and tangible capital.

In most discussions of productivity, it is customarily assumed that the differences among the several output concepts are small and can therefore be safely ignored, largely because scarcity of information makes a choice impossible. It is certain, however, that the differences are not always negligible. But we shall have to follow the custom, except for a later comment or two, and concentrate on those differences among productivity indexes that arise from differences in the inputs.

Even when there is a choice among alternatives and even when the output and the input indexes can be made fully consistent, productivity indexes are at best crude and somewhat ambiguous measures. As with all index numbers, troublesome questions arise, and rather arbitrary decisions are made, concerning the aggregation of heterogeneous and qualitatively changing inputs or outputs. And there are special difficulties—for example, in the measurement of capital input and of the employment and hours of family workers. Users of productivity indexes must learn not to make fine comparisons.

Not every important productivity ratio has been mentioned. However, for the immediate purpose, which is to identify some of the major productivity ratios and to make clear why it is necessary to distinguish carefully among these and other ratios, our list is sufficient.

Productivity indexes and production functions

The differences among the several productivity indexes can be put more clearly in symbolic terms. The symbols are useful also for showing the relation between the indexes and statistical production functions.

Following the usual convention, let the following symbols stand for index numbers, on a common base, of the items specified: Y = output, N = manhour input (unweighted manhours), L = labor input (weighted manhours), and K = tangible capital input. To combine labor and capital input it is necessary to express them in comparable units, namely, a dollar’s worth of services in the base period or place; or, what is the same, to calculate the index of labor and capital input by taking a weighted arithmetic average of the indexes of labor input and of capital input, with the weights equal, respectively, to the total value of labor’s services and of capital’s services in the base period. We have, then, ah + bK – labor and tangible capital input, where a is the fraction of total input contributed by labor, b is the fraction of total input contributed by capital, and a + b = 1.

The several productivity indexes are Y/N = output per manhour, Y/L = output per unit of labor input, Y/(aL + bK) = output per unit of labor and capital input. In these terms, output per manhour is related to output per unit of labor and capital input as follows:

Y/N = [Y/(aL + bK)][a + bK/L] [L/N].

When L and K are combined by means of a weighted geometric mean, which is quite rare in the calculation of productivity indexes, this relationship becomes

Y/N = [Y/(LaKb)][(K/L)b][L/N].

Statistical production functions are empirically determined relationships between output (or an index of output) taken as the dependent variable and the two inputs (or the corresponding indexes) taken as the independent variables. The most widely used function assumes a logarithmic-linear relationship between output and input, and a uniform rate of shift over time in this relationship as technology and other determinants change. The function is

Y = La*Kb*(1+r)t

with a* + b* taken equal to 1. The coefficients a* and b* are, in effect, the weights of L and K, respectively, as determined by fitting the function to the statistics by one of the usual regression methods. Under competition and certain other conditions, to be discussed later, a* tends to be equal to a, and b* tends to be equal to b. The coefficient r measures the average annual rate of shift in the relationship between output and input when t is measured in years. The variable t is used as a proxy for changes in technology, the scale of operations, and the other factors that change over time and cause this shift, and r is therefore usually (and loosely) called the rate of technological change. In our terminology, r is the average annual rate of change in output per unit of labor and tangible capital input. To illustrate: When input is the same in the given as in the base period, output will be greater in the given period, t years after the base period, by the amount (1 + r)’. When the comparison is between places rather than periods, t can no longer be used as a proxy for technology and the other factors that determine shifts in the relation between output, Y, and the inputs, L and K.

In most cases, N rather than L is used to measure labor input. The production function is then more accurately expressed as

Y = Na*Kb*(1+r)t

In this case, (1 + r)* is equal to (Y/L a *K b *)(L/N) a* not to (Y/L a *K b *) alone. That is, r measures the average annual rate of change in output per unit of labor and capital input combined with the change in the quality of labor.

An alternative function, which assumes an arithmetic-linear relationship, is

Y = (a*L + b*K)(1+r)t

with a*+b* = 1. Here (1+r)t = Y/(a*L + b*K), which is identical with the index of output per unit of labor and capital input, as usually calculated, except for possible differences between a and a*, and therefore between b and b*. There may also be a difference arising from the fact that r is the trend rate of increase over the whole period covered by the function, and not just the rate of change between the base year and the given year. Obviously, either type of equation can be modified so as to treat separately the input of (unweighted) manhours and the input of intangible capital invested in education, to take account of materials, fuel, and other purchased inputs, to include the terms of foreign trade as an independent variable, and so on.

Statistical production functions provide an alternative way of calculating productivity indexes, particularly indexes of output per unit of labor and capital input, and of their rates of change. So viewed, the production function approach has the advantage of requiring no direct information on the weights needed to combine L (or N) and K. The approach also has the advantage of requiring explicit recognition of the assumptions made about the character, or “shape,” of the relationship between output and input. At any rate, it provides a better way to state these assumptions and a better setting in which to study them, as we shall see.

Variation in labor productivity

Indexes of output per manhour—commonly called “labor productivity” indexes–state the yield of commodities and services obtained, under varying circumstances, from the expenditure of an hour of human labor. In these terms they report on facts of high economic importance–the relative power of men of different generations or different nations, or of men of the same nation and generation under different conditions, to produce the things men want.

Secular trends

A glance at secular trends over the last hundred years or so, which is about as far back as most of the information goes, suggests a remarkably general, perhaps world-wide, development. In all countries for which acceptable estimates are available for at least fifty years—mostly today’s developed countries–trends in national output per manhour have been upward. We cannot be sure about the more remote decades of the past century, when the records even of the developed countries are poor. And there is doubt about the trends even over the more recent decades in the rest –the larger part–of the world, which is heavily weighted with countries in which present levels of labor productivity are very low by Western standards. Yet even for the latter, there are grounds–scraps of direct information, and information on the causes and the consequences of higher labor productivity–for supposing that the present low levels are probably no lower, and in most countries are in fact higher, than the levels of a hundred years ago. The exceptions, if any, are likely to be the countries suffering the effects of war or social upheaval. Their current levels of productivity are below the secular trend lines rather than on them

While nearly all countries, if not quite all, have probably raised their labor productivity levels over the past century, the rates of advance have been highly varied. Most of the countries for which direct estimates are available for a sufficiently long period fall in the range between 1.5 and 2.5 per cent per annum. There are none higher than about 2.5, and only a few lower than 1.5, with none much below 1.0. This sample is bound to be biased, however, because it consists largely of the developed countries. Including the other countries, which are probably mostly in the lower portion of the distribution, it is a fair guess that a range of 0.5 to 2.5—almost surely, of 0.0 to 2.5—would embrace virtually all the countries of the world. This range is wide indeed. Over a century it means the difference between little or no change and an 11-fold increase. It means, also, that countries have differed greatly in the degree of change of their tangible capital per worker, or the quality of their labor, or the efficiency with which they use capital and labor, or in all three respects.

Even if there has been no improvement in some parts of the world, it is clear that for mankind as a whole the average level of labor productivity has risen. Over the century taken as a whole— though not in recent years—it has been pushed up also by a more rapid population growth in countries with high levels of output per manhour. It is hazardous to express these developments in quantitative form, but it seems reasonable to believe that the average rate of increase in the productivity of all human labor during the past century has been something over 1 per cent per annum and perhaps closer to 1.5 than to 1. This much is certain: the rise in labor productivity over the past century has been far greater than the average rate of increase experienced during man’s existence on earth. It is also certain that it has been far less than the rate of increase the world now assumes in its plans for the future.

Over the century as a whole, the earth’s population has risen less than 1 per cent per annum, and manhours worked per capita have probably fallen a bit. It is highly probable, therefore, that the average rate of increase in output per manhour has been higher than the average rate of increase in the aggregate amount of work done. In other words, the present generation of men produces far more than earlier generations because there are more men; but, even more important, also because each man today is able on the average to get more from an hour of his labor than were his ancestors. He has less land to work, it is true, but far more capital of other kinds—largely inherited—to work it with. And on the whole, the use of his time and capital is more efficiently organized.

International differences

The disparities in output per capita that appear over the surface of the earth are also to be explained very largely, if not entirely, by differences in output per manhour. In the poorer half of the earth, output per manhour in 1960 was probably at a tenth or less of the western European level, and the latter was half the level of the United States. International differences in manhours per capita are very small compared with those differences in output per manhour and cannot account for much of the variation in per capita output. It may be, in fact, that per capita output is greater in the countries working fewer manhours per capita.

Some part of the present differences among nations in levels of labor productivity is the result of differences in the long-term rates of growth of labor productivity. But today’s large variation cannot be accounted for entirely by differences in trends, over a single century, of the order of magnitude mentioned. A difference even of 2 per cent per annum would make the current productivity level of western Europe, for example, no more than seven times the level of southern Asia, had these areas started from equal levels. The current disparities between the highly productive and the less productive countries must therefore bear a resemblance to those of a century ago but be on the whole much wider. This is not inconsistent with important shifts in the rank of individual nations, which have also occurred. A century ago the labor productivity level of the United Kingdom, for example, was about the same as that of the United States and about double that of Sweden. In 1960, the British level was less than half the U.S. level and somewhat below that of Sweden.


The average rate of growth in labor productivity over the century as a whole is not the whole story. The upward march of labor productivity has often been speeded up and as often slowed down, sometimes to the point of declining absolutely for a time. Among the sources of these fluctuations have been the weather, which has often put a visible mark on national output per manhour in agricultural countries; business cycles, of particular importance in industrialized countries; and the catastrophes of war and political and social upheaval. Not only domestic conditions but also conditions abroad, it should be noted, have caused fluctuations in the yield from an hour of labor as measured by national product.

The impress of business cycles on labor productivity is pronounced when output is compared with the manhours that might be supposed to be “available” for work under conditions of full employment. But it is visible also in the more usual comparison of output with the manhours actually worked. Annual figures show a more rapidly rising labor productivity during business expansions than during business contractions. [SeeBusiness cycles.] Quarterly figures, confined largely to the commodity-producing industries of the United States, suggest that the rise is slower during the second half than during the first half of expansions, and especially slow during the first half of contractions. This cyclical behavior (which could hardly have been foreseen on the basis of a priori considerations alone) is evidence of a systematic swing in the balance between the factors that make for rise and those that make for decline in labor productivity—the factors that determine the average quality of labor input, the volume of capital services available per worker, and the efficiency with which labor and capital are utilized. It has interesting implications for the explanation of the cyclical behavior of labor costs, of profit margins, and thus also of decisions to invest.

The effects on labor productivity of wars, revolutions, and other serious disturbances have been less frequent but usually more violent and prolonged than those of crop cycles or business cycles. Disorganization, undermaintenance and destruction of plant and equipment, and the loss or diversion of trained personnel have sometimes caused labor productivity to fall drastically. During recovery, labor productivity has often risen for some time at an exceptionally rapid pace, but these high rates have not always continued long enough to erase the effects of the catastrophe from the long-term trend.

Apart from these fluctuations, there have also been significant, though less obvious, differences among trends measured over a decade or more. In most countries, for example, the decade beginning about 1952—which is presumably free of most of the immediate effects of World War II—witnessed rates of growth in labor productivity that appear high in comparison with the long-term averages.

What is revealed by the fuller record may be illustrated by reference to the United States. Something like five long waves, of irregular length, are discernible in the rate of increase in output per manhour in the United States between 1870 and 1960, excluding the war periods. Rather clearer is a change in the long-term trend at about the time of World War I. During the thirty years before 1919, output per manhour rose at an average annual rate of 2.0 per cent, as measured by real gross private domestic output per manhour; during the forty years after 1919, the rate was 2.6 per cent per annum. These changes, and roughly similar changes in some other countries, have fed speculations about long cycles and about a tendency of labor productivity, and of the technological change that contributes to it, to accelerate. However, the available evidence is too scanty and irregular to be conclusive. Of course, the net balance among the factors that influence trends in labor productivity (among which are changes abroad, as well as domestic factors) may be larger at one time than at another, without necessarily generating systematic patterns of change.

Whether the fluctuations are more or less systematic, it is clear that growth of labor productivity has been subjected to them. Yet the main impression conveyed by the records of labor productivity in various countries is not so much one of fluctuation as of a persistent and often powerful upward push. This impression is also conveyed by the records of individual industries within countries. Even industries not obviously adapted to mass production methods, such as the service industries, seem to have raised output per manhour, to judge from studies now under way. And this is also true of industries in which natural-resource limitations might be expected to play a considerable role, such as mining and agriculture. Technological changes, and in some cases also the opening of new sources of supply, have prevented the appearance in these industries of the “diminishing returns” that would otherwise be apparent.

Sometimes, perhaps because the term “labor productivity” is misunderstood, it is believed that wage earners (or “labor” as a whole) are wholly responsible for these widespread changes in output per manhour. It is true that among the factors that can cause labor productivity to rise (or to be higher in one place than in another) is change in the quality of labor, for labor productivity is measured by output per manhour and not by output per unit of labor input. But also involved are changes in the volume of tangible capital per worker and in the whole host of factors—besides those embodied in labor—that determine the efficiency with which manpower and capital resources are utilized in production.

Variation in efficiency

When efficiency in the use of resources as a whole is in question, the appropriate index of national productivity is output per unit of labor and tangible capital input. It is hardly the perfect index, for reasons to be mentioned, but it provides the best practical approximation. Yet measurement of efficiency even in this way has hardly begun, except in the United States. It is therefore to the U.S. figures that we turn for a first view of the relevant magnitudes.

It is no surprise to learn that the average quality of labor improved—by 0.3 per cent per annum, over the period 1889–1960, according to data on labor input (weighted manhours) per manhour; and that tangible capital per manhour also rose— by 1.5 per cent per annum, over the same period. Efficiency in the use of resources therefore went up less rapidly than labor productivity–by 1.6 per cent per annum, as compared with 2.2 per cent per annum. What may be surprising is the difference of only 0.6 percentage points between the two rates of increase.

One reason for the small difference is the relatively heavy weight given labor input when it is combined with tangible capital input. The U.S. weights, based on national income data, are currently 8 to 2. There may be a second reason: understatement of the rise in the quality of labor and, therefore, overstatement of the rise in efficiency. The estimate of 0.3 per cent per annum increase in labor quality, based on the use of weighted manhours, assumes all the labor within an industry to be homogeneous. Perhaps more important, it takes no account of the broad advances in education, health, and the like, which improve the quality of labor in industries generally. An estimate based mainly on the amount of schooling received by workers and therefore free of most of the deficiencies mentioned (but suffering from others) suggests a much higher rate of increase in the quality of labor—some 0.8 or even 0.9 per cent per annum.

Also involved, although the direction of its effect on the index of efficiency is less certain, is the fact that labor and tangible capital input do not cover investment in the intangible capital of science, technology, and social organization that serves to increase production. It is clear that “research and development,” for example, is an alternative to investment in other types of resources. Whatever its origin—whether in activities economically motivated or not–scientific, technological, and other useful knowledge is in some degree a substitute for other resources. But the services of the national stock of knowledge cannot be included in input because the concept of such a stock, or of changes in it, is elusive and not yet within the domain of practical measurement. Only in a few studies of industries or parts of industries–not entire economies–has it been possible to include some investments in technology among the inputs. This omission means that the available index of total input is biased downward if intangible capital in the form of technology has risen more rapidly than the resources that can be included. But no one knows what the difference is between these rates of growth, or can even be sure that that of intangible capital is the higher. This ignorance is also one reason why the index of output per unit of labor and tangible capital input is not a good measure of technological change, as some suppose it to be.

An alternative and more widely used estimate of growth in efficiency is available for the United States in the form of an index of gross private domestic product per unit of labor and capital input. This index went up by 1.7 per cent per annum, as compared with the 1.6 per cent increase of net national product per unit of labor and capital input. The latter measure is preferable on conceptual grounds because it covers the large and growing government sector as well as the private sector and because of other reasons already given. But the former index is more reliable because it avoids the conventional, and probably erroneous, assumption that labor productivity in government has not changed. The difference between the two—and between these and other alternative indexes—underscores the lack of precision even in the best of available productivity indexes.

Two conclusions are suggested by the United States figures, subject to the reservations required by this lack of precision. First, the growth in labor productivity reflects upward trends in all three of its component factors—labor quality, tangible capital per manhour, and efficiency—and not a net difference among positive and negative factors. Second, of the three factors, it is increase in efficiency that appears to have made the largest contribution to the increase in labor productivity. This means, also, that it has made the largest contribution to the growth of output per capita.

As for countries other than the United States, there are grounds for supposing that they too have experienced not only the rather general growth of labor productivity already mentioned but also–at least in some degree–improvements in the quality of labor and increases in the volume of tangible capital per manhour. If the first conclusion drawn from U.S. experience holds for them also, we may expect that efficiency has generally risen, although less rapidly than labor productivity; and we may infer that international differences in efficiency will be smaller than the corresponding differences in labor productivity.

The measures of efficiency that have been calculated—and they are far fewer than the indexes of labor productivity–seem consistent with these expectations. It must be noted, however, that for countries other than the United States, efficiency is measured (when it is measured at all) by a comparison of output with a combination of unweighted manhours and the services of tangible capital. The use of unweighted rather than weighted manhours means that the measure of changes in efficiency also covers the changes in the quality of labor. In the case of the United States during the period 1889–1960, the index of efficiency so calculated went up 0.3 per cent per annum more rapidly than output per unit of labor and tangible capital input.

Growth in efficiency does seem to have been a rather general phenomenon. Efficiency has risen in each of the dozen or so countries for which trends over a decade or more have been calculated, although always less rapidly than labor productivity. There is evidence for some of these countries that efficiency has also risen in most, if not all, industries, and—again—generally less rapidly than labor productivity. And there is some evidence, as well, that when the average level of efficiency of a country is high relative to other countries, efficiency is generally high also in each of its industries relative to comparable industries in other countries. Further, as with labor productivity, the average rate of increase of efficiency has differed widely among countries, although somewhat less widely than labor productivity. Efficiency has differed also—and to a greater extent—among industries within countries, and it has differed among periods as well.

If increase in efficiency has in fact been general, but highly varied, something is suggested about the factors involved. Advances in technology, for example, must consist not only of the major innovations that revolutionize this or that industry but also of a host of smaller innovations that arise over the whole range of economic life. Also, knowledge of innovations, even of those quite specific to particular industries or regions, is sooner or later adapted, to some extent, to the peculiar conditions of other industries and other places.

The available figures also support the second conclusion suggested by the U.S. data. Increase in efficiency seems to be important, judged by its contribution to the growth of output, output per capita, and output per manhour; and international differences in the level of efficiency seem to be important in explaining international differences in these quantities.

This may be the most striking lesson learned from the measurements, to judge by the surprise expressed by many economists. Between 1928 and 1948, under the influence of empirical work with the production function, Y = N a *K b * (with a* + b* = 1), it was rather widely held that increases in output per worker or manhour, and also differences among countries in this respect, could be accounted for very largely, if not entirely, by the volume of tangible capital per worker or per manhour. Improvements and extensions of the empirical data, and calculations of indexes of output per unit of labor and capital or of production functions which allow for changes in efficiency, such as Y = Na* K b *(l +r)t have radically revised this opinion. It is now generally recognized that neither tangible capital alone nor even weighted manhours and tangible capital alone are sufficient to explain differences in output per manhour. Indeed, only a third of the average annual increase in the U.S. national output per manhour of 2.2 per cent between 1889 and 1960 is accounted for by the increase in measured input—weighted manhours plus tangible capital input–per manhour. The rest is accounted for by the increase in measured efficiency. Figures available for Norway, Finland, Russia, and West Germany, covering periods of two to five decades, and for these and a few other countries for the postwar decade, tell a similar story.

The issue now takes the form: How much would an adequate measure of investment in education and other forms of human capital leave to be explained by efficiency more narrowly defined and measured? It seems questionable, however, to consider as negligible such factors as the growth and diffusion of knowledge (apart from what is covered by investment in human beings); widened markets, which give more scope to the specialization of workers, machines, and business establishments; reductions in hours of work, which enhance labor productivity and may also enhance efficiency; improvements in economic organization; and perhaps also changes in the character of consumption and in the way in which leisure time is used. Something is known about each of these factors, but to improve this knowledge and to determine the relative importance of each factor continues to be a major task in the analysis of economic growth.

Productivity and wages

The major determinants of the average real hourly earnings of a nation’s labor force are the nation’s efficiency in using labor and tangible capital, the scarcity of labor in relation to tangible capital, and the quality of the labor force. The productivity index that combines these factors is the index of national output per manhour. It is this index, therefore, that is used in the analysis of trends and of international differences in real wages, enters wage negotiations, and is looked upon as a guidepost in wage policy.

Theoretical considerations

National output per manhour is a particular combination of particular measures of efficiency, relative labor–capital scarcity, and labor quality. It is the appropriate combination for the purposes mentioned only under certain conditions that need to be made explicit. Even with these conditions satisfied, it is the appropriate combination only in relation to the average hourly earnings of all workers combined. These are workers of changing–usually improving–quality. Most often, however, the earnings in question are those of workers of a substantially fixed quality, in a particular occupation or industry. In this case, the appropriate productivity index –if just one index is to be chosen–is national output per unit of labor input; that is, output per weighted manhour, not output per unweighted manhour.

This will be understood if we first note that real labor income includes the earnings from the services of the intangible capital invested in education and other improvements in the quality of labor, as well as from the services of labor of minimum quality–roughly, “unskilled” labor. When this total labor income, per manhour, moves identically with national output per manhour, the fraction of national output that goes to workers in the form of real labor income and the fraction that goes to owners of tangible capital are constant. We can then ask under what conditions these fractions will in fact be constant.

Such fractions will be constant when an increase in the quantity of tangible capital’s services relative to the quantity of labor’s services is accompanied by an exactly proportionate decline in the price of tangible capital’s services relative to the price of labor’s services. Now, it is clear that a rise in the capital-labor quantity ratio will tend to push up the usefulness of labor relative to that of capital. In more technical language, it will tend to raise the ratio of the marginal product of labor to that of capital.

The required conditions are, then: (1) The rise in the capital-labor ratio must be accompanied by an exactly equal and opposite proportionate change in the ratio of the marginal products of labor to capital–which means that the elasticity of substitution between capital and labor must be exactly equal to unity. (2) The ratio of the marginal products must be unaffected by changes in the composition of output and in the technology and other factors that underline efficiency–which means that changes in the product-mix and in efficiency must be “neutral.” (3) The ratio of the marginal products must be equal to the ratio of the prices of labor to capital services–which means that competition must prevail in the markets for commodities, labor, and capital, so that change in the volume of tangible and intangible capital per manhour and increase in efficiency are free to bring appropriate adjustments in the rates of return to labor and to capital.

This reasoning may be put in terms of the logarithmic-linear aggregative production function described earlier, for this function (but not the arithmetic-linear function) assumes unitary elasticity of substitution and neutrality of technological change, among other things. It is the marginal product of labor, not the average product measured by output per unit of labor input, which tends to parallel the real wage rate under competition. But under the conditions described, the index of the marginal product of labor is identical with the index of the average product of labor, Y/L, as can easily be shown. If the relationship between national output, labor input, and tangible capital input is as specified in the logarithmic-linear production function, and if competition prevails, the conditions hold. The index of national output per unit of labor input tends to equal the index of real wages per weighted manhour–that is, the index of real wages per hour of fixed (and average) quality.

The index of productivity usually employed in discussions of wages is national output per (unweighted) manhour, however. But national output per manhour is output per manhour of changing quality. It is Y/N, not Y/L: Y/N = (Y/L)(L/N). Under the conditions specified, then, this index of productivity tends to equal the index of average hourly earnings of labor of changing quality, not fixed quality. Given the same conditions, when the quality of labor improves, the index of productivity generally used (Y/N) will tend to rise more rapidly than an index of average hourly earnings of labor of fixed quality.

Statistical evidence

Whether the specified conditions do hold is an empirical question not yet satisfactorily answered by direct tests of the elasticity of substitution, neutrality of change in technology and product-mix, or even competition. A test of a sort is provided for all the conditions combined, however, by historical information on the fraction of national output received as real labor income. The share of national product going to hired workers in the form of wages and salaries (including “fringe” benefits) has generally risen, but the share of national product going to entrepreneurial income (which includes property as well as labor income) has generally fallen. It is difficult to determine the net result, and there is some tendency to overstate its stability–a change from 70 per cent to 80 per cent may appear rather modest. On the whole, however, the fraction going to labor in various countries seems to have fluctuated around a substantially horizontal trend prior to World War i and a somewhat higher but still horizontal trend afterward. [SeeIncome distribution, article onfunctional share.]

In terms of a comparison of long-term changes in productivity and real hourly earnings of production workers in manufacturing industries, available for the United States for 1889–1960, the conditions meet the test moderately well. The real hourly earnings rose at the annual rate of 2.3 per cent. Real national product per unit of labor input rose at the rate of 1.9 per cent per annum, and real private domestic product per unit of labor input rose at the average annual rate of 2.0 per cent. Because the manufacturing earnings are in some degree affected by improvements in labor quality, it is well to compare them also with the corresponding rise in output per manhour: 2.2 per cent per annum in the national economy, 2.4 per cent in the private domestic economy. Larger differences are revealed by comparisons over periods that, although shorter, are long enough to reveal a trend rather than a cyclical or an erratic fluctuation. For example, real hourly earnings in manufacturing in the United States rose less rapidly than national output per manhour in seven such periods between 1889 and 1960, more rapidly in six, and at the same rate in only two. And the absolute difference between the annual rates of change in real wages and in national output per manhour in all 15 periods averaged about 40 per cent of the average annual rate of change in output per manhour.

If it is the real hourly income of an occupation of relatively fixed labor quality that is of concern, the appropriate productivity index is Y/L, not Y/N, as we have seen. The difference is not negligible, to judge from the figures just cited. If the wage rate of every occupation were to parallel national output per manhour and if workers benefited not only from these increases but also from the increases in their labor income resulting from training and subsequent upgrading, the share of national product going to labor would rise rather than remain constant; and it would rise at an average annual rate equal to the difference in rates of growth between Y/L and Y/N.

It should also be stressed that Y/L is not the appropriate productivity index for every occupation of fixed labor quality but only for those close to the occupation of average quality. It is plausible that the higher the quality of labor in a particular occupation, the more rapid has been its growth in numbers employed. If this is so and if the conditions mentioned hold for each class of labor, the appropriate productivity index cannot be the same for every occupation. This conclusion also follows if the human capital resulting from education and other investments is thought of as homogeneous.

On either basis, the appropriate index for unskilled labor would be best approximated by Y/N; for occupations of average labor quality, it would be Y/L; and it would be something less than Y/L for occupations of high labor quality. This amounts, of course, to saying that the rate of return to investments in education and the like, and therefore the average hourly earnings of skilled workers, would be expected to decline in relation to the earnings of unskilled labor, when the number of skilled workers increased more than the number of unskilled. Whether or not the rate of return declined absolutely would depend on the other determinants of earnings–the rate of increase in efficiency and the relative growth of tangible capital.

When separate categories of labor are distinguished, however, the assumption of neutrality must be questioned. If, for example, technological change has not been neutral but rather has tended to diminish the demand for unskilled labor significantly, the logarithmic-linear production function no longer summarizes fairly the determinants of the wages of unskilled labor, and expectations based on this function are no longer valid. Other qualifications, already mentioned, also need to be remembered: no fully adequate measure of L is yet available; and the quality of the labor force in most occupations in a progressive economy is improved over time, if only by the increase in literacy.

Wage policy

The questions raised indicate some of the difficulties in the way of using a relatively simple productivity index as a summary even of the major factors affecting the trend of wages. The difficulties are greater when a productivity index is used as a general guidepost to short-term change in wages in an “incomes” policy–or, as it is sometimes put, as a guide to how wages would change in a competitive industry in a noninflationary economy. Some of these difficulties should be mentioned.

First, the trend of national productivity is intended to serve as a guide to the rate of increase in wages from one year to the next, or over the brief period (two or three years) of a wage agreement, and not to the trend rate of increase in wages. There is little ground for supposing that these would parallel one another even in a competitive, noninflationary economy. During the expansion phase of a business cycle, for example, the average real wage–in competitive and noncompetitive industries alike–usually rises more rapidly than its trend rate or than the trend rate of increase in productivity. During the contraction phase of a business cycle, the average real wage usually rises less rapidly than these trend rates. To apply the general wage guide only to less than fully competitive industries–letting wages in competitive industries move freely–would mean imposing on the former “competitive criteria” that are competitive only in a very special, if not peculiar, sense. If the application were successful, wages in the industries affected would move differently from wages in the industries that remained free to respond to cyclical as well as other changes in supply and demand.

Second, the reason for choosing national output per manhour (or per unit of labor input) even when the wage in a sector of the economy is under consideration is not because the efficiency and the capital per worker of the sector have no effect, or should have no effect, on the sector’s wage. They do influence the sector’s wage, even though they cannot be counted as a major factor in the long run. They belong among the “qualifications” that must always be attached to any short list of factors affecting wages in order to explain, or justify, a discrepancy between changes in the wages of a sector and changes in national output per manhour.

Third, and related to the second point, changes in technology, in tangible capital per worker, in the quality of labor, and even in the cost of living take time to work out their effects in the economy and make their impact on wages. This is true even in a competitive economy and even with such allowance as needs to be made for the influence of expectations on the lags. No industry, nor the economy as a whole, is ever in full equilibrium either in the present or in the base period with which the present is compared.

Fourth, with government–and the taxes government levies, the transfers it makes, and the services it renders–economically so much more important now than in earlier periods, changes in the structure and level of taxes and of government expenditures also significantly affect the relation between wages and national output per manhour, at least in the long run. In addition, the difficulties of measuring wages and productivity are aggravated. This explains the custom in the United States of using indexes for the “private economy” to represent national productivity, but the problem is not fully solved by these indexes.

Finally, changes in the terms of foreign trade may properly be treated as one of the “qualifications” in the few countries in which foreign trade is of relatively minor importance. As a general rule, however, it is better to define productivity to take account of these changes, for it is national output, not domestic output, that is distributed in the form of real wages and other real income.

To overcome some of the difficulties posed by the limitations of a general guidepost, recourse may be had to a rule providing for modifications or exceptions. It is seldom clear, however, when an exception is justified or–perhaps more to the point–when an exception is not justified. And there are problems in determining the permissible degree of deviation from the general guidepost.

There are other troublesome points that arise when it is asked whether productivity can provide an adequate guidepost for wages. It should be evident by now, however, that many assumptions are involved in applying national output per manhour in wage negotiation and determination and that they do not hold fully in every period and in every situation.

Productivity and employment

Productivity indexes are frequently used, along with other information, to estimate labor and other resource requirements. For example, future levels of national employment and unemployment have been calculated by (1) estimating the future output implied by certain assumed levels and conditions of demand, (2) extrapolating the past rate of increase in output per manhour, (3) dividing the output by the output per manhour to estimate manhour employment, (4) determining the expected number of persons employed by assuming some level of hours per person, and (5) subtracting the expected employment from the expected labor force to estimate unemployment. If the unemployment so estimated seems likely to be excessive, a policy may be proposed to avoid it–by speeding up the increase in demand, or slowing down the increase in productivity, or reducing hours below what they would otherwise be. Similar calculations have been made of national requirements of land, other tangible capital, water, and power, and of these and other requirements of particular industries. Of the questions raised by these procedures, the two discussed here are put in terms of labor requirements only.

The first question concerns the adequacy of the productivity projections. As has been indicated, output per manhour may be viewed as determined by efficiency in the use of resources as a whole, the scarcity of labor relative to tangible capital (or total input), and the quality of labor. The direction of change of these factors can usually be foreseen with some confidence. As a rule, efficiency and labor quality may be expected to rise, and manhours relative to tangible capital may be expected to decline. However, seldom is enough known about their expected rates of change to make possible a quantitative projection of labor productivity. What is usually done, therefore, is to assume a continuation of past trends and other patterns of change in productivity. The crucial point is whether these are sufficiently stable to yield reliable projections.

To estimate future labor requirements, it is usually necessary to take account of cyclical fluctuations. As we have seen, labor productivity generally rises much more rapidly during business expansions than during contractions. The rate of increase in national output per manhour in the United States between 1889 and 1960 averaged 3.4 per cent per annum during years of expansion in output and –0.6 per cent per annum during years of contraction in output. However, there was a good deal of variation around these averages, only part of which can be explained by differences in the degree of rise in output. Use of the average cyclical pattern of labor productivity, or of the average relation of change in productivity to change in output, will help to improve the projection but can hardly eliminate all uncertainty.

Even in making long-term projections of output per manhour, cyclical fluctuations must be kept in mind. The calculation may be seriously marred if the business-cycle phase at the beginning of the period used to determine the past trend is different from the phase at the end. Also, the business-cycle phase of the year from which the projection starts must be taken into account. The more important question for long-term projections, however, concerns the past trend. Can it be adequately expressed by a constant rate of growth, or must allowance be made for acceleration or retardation of the rate of growth or for less regular changes in trend rates?

At one time it was supposed that output per manhour tended to rise at a declining rate as an industry or economy grew. It does appear to be true of individual industries during their early careers. (This must be judged from the prices of their products, for information on the output per manhour of young industries is usually lacking; but there is good evidence that the two are significantly–and negatively–correlated.) However, any systematic tendency toward retardation seems to disappear once the first period of development has passed.

As for trends in national output per manhour, no evidence has been found of a tendency for rates of increase to decline systematically with the passage of time. Indeed, speculation has veered in the other direction, and it is now more often asserted that national output per manhour has been accelerating, at least in recent years. But it is not clear whether the current high rates of growth, mentioned earlier, represent acceleration or simply a higher plateau. The rates may rise to still higher levels; or they may continue at present levels; or they may return to earlier levels, as they have often done. Even apart from cyclical fluctuations, then, and even assuming a continuation of past levels of rates of growth, trend extrapolations will be sensitive to the choice of the past period that provides the estimate of the future trend. Allowance must be made for rather wide margins of error.

Our second question concerns the nature of the connection between labor productivity and employment. During periods of persistent unemployment, for example, some of the blame for unemployment is often put on mechanization, automation, and the other sources of increase of output per manhour, especially in industries in which output per manhour is rising rapidly. It is often implied that the more rapid the increase in an industry’s output per manhour, the less rapid is the increase in the manhours of employment offered by it. It is true that the direct effect of a rise in an industry’s output per manhour is to depress its employment. But there are also indirect effects. An exceptionally rapid rise in the output per manhour of an industry has usually caused the price of its product to rise much less, or fall much more, than prices generally; as has been mentioned, there is a fair degree of negative correlation between trends in output per manhour and trends in selling prices. In turn, the relative price decline has served to stimulate the industry’s production and thus, indirectly, to maintain or even stimulate a rise in the employment it offers. Indeed, long-term rates of growth of output per manhour in the industries for which British and U.S. data are available–largely the commodity-producing industries–are positively, not inversely, correlated with employment and with output.

Other factors enter, of course. The elasticity of demand in response to changes in price varies considerably among industries. The elasticity of demand in response to changes in real national income–which is largely the result of changes in national efficiency–also varies among industries. High income elasticities of demand may help to explain the growth of employment in the service industries despite an apparent lag in output per manhour and a rise in selling prices relative to the commodity-producing industries. For industries generally, at this stage of knowledge it seems safe to say only that especially high rates of growth in output per manhour are not necessarily accompanied by absolute or even relative declines in the employment offered. More must be learned about this, as about other aspects of productivity.

Solomon Fabricant

[See also Agriculture, article on Productivity and technology; Production; Wages, article onTheory.]


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views updated May 17 2018


Productivity is a measure of output, and the most common use of productivity measures is in gauging economic performance at the national level. Statistics on productivity are collected routinely by the U.S. Bureau of Labor Statistics (BLS) and their publication every quarter usually brings coverage in the business press. BLS measures "labor productivity" based on dollar output per hour of labor; the agency also publishes a more complex measure known as "multifactor productivity" which takes other inputs into account. Productivity is also measured at the level of the enterprise in output of physical product by a worker. When the worker's pay is directly based on number of pieces produced, that type of work is known as "piece-work": pay is tied to the item ("collars sewn," for instance, rather than time spent).


In economic theory (echoed in popular opinion), labor compensation is determined by productivity. In theory a person can only earn a fixed amount by labor because the labor must be compensated by the sale of the product made, and all things being equal, competition will keep the prices competitive. This translates to an essentially stagnant economy unless, in some way, the cost of the production process can be lowered. One way to lower costs is to increase output while keeping the input the same. Thus if a worker can increase his or her production from 8 items an hour to 12 items an hour while still being paid $9 an hour, the labor costs of the items will decrease from $1.125 an item to $0.75 an item. (Economics has been called the "dreary science" because it delights in such thingsbut to go on ) The converse of such an improvement in productivity is that the price of the item could be held steady and the laborer could be paid more. In this instance the worker's pay could be increased to $13.50 an hour ($1.125 times 12, not times 8). For this reason, it is a fundamental assumption of economics that wages in a genuinely free market can only increase if productivity increases.

Productivity can only increase if 1) the worker's skills increase, 2) the worker's effort increases, 3) the quality of the material processed increases, 4) the worker's tooling is better, and 5) the work-process itself is improved by better arrangements of workers, work-flow, etc. Increases in skill require time and experience, increased effort requires incentives, and the remaining factors are produced by improvements in technology.

Wages, of course, can also increase as a consequence of social force. Thus workers can unionize and impose their will. Higher costs are then imposed on the public. Similarly, government can enforce a wage level with similar consequence, the minimum wage being an example. These situations, of course, no longer represent a genuine "free market"which, to be sure, has never existed and never shall.

Throughout the period of modern industrial history, productivity has been rising steadily as a consequence of all of the factors enumerated above, namely education in general and the invention and deployment of technology which itself is based on knowledge and energy. Arguably modern civilization rests on the discovery of fossil fuels and their exploitation which have enabled humanity to have leisure to learn and power to burn.


Labor Productivity

Government data on productivity are calculated by measuring and/or estimating the output of different sectors of the economy in dollars and the hours worked. The output divided by the hours produces the base of a productivity measure. But because the economy has its ups and downs as well as its seasonal swings, BLS does not publish the raw numbers but, instead, produces an index number. At present the base year of this index is 1992. This means that the values measured in that year are taken as 100. Other years are expressed as deviations from 1992. In 2000, for instance, manufacturing output per hour was 138.3, meaning that it had improved 38.3 percent over 1992. Productivity data are seasonally adjusted and adjusted dollar values are used to eliminate the influence of inflation.

The two major categories used are Manufacturing and Business as a whole. The most precise are data for manufacturing because, in that sector, the U.S. Census Bureau collects hourly compensation data separately from other employment data. In both categories, productivity is up substantially over against 1992 and in recent years as well. Manufacturing productivity (output per hour) stood at 138.3 in 2000 and at 171.2 in 2005, having increased 23.8 points since 2000. In Business as a whole, the productivity index in 2000 was 120.3; it increased to 136.7 by 2005, increasing 13.6 points.

The significantly higher growth rate in manufacturing productivity reflects the fact that tooling acts as a "multiplier" of human labor. Much more machinery is used in manufacturing than in any other sector. High output per hour is also experienced in highly automated activities like utilities and where large sums of money are transferred as in wholesale trade and in the financial sectors.

Based on data derived from the 1997 Economic Census, cited in Social Trends & Indicators USA, it took 4.4 people to produce $1 million in output in manufacturing, 5.7 people to produce $1 million in retail, 9 people to produce that volume in professional, scientific, and technical services, and 15.3 people to produce $1 million in health care. To produce the same dollar figure as output, the finance and insurance sector only needed 2.7 people, utilities 1.7 persons, and wholesale trade 1.4.

Multifactor Productivity (MP)

Labor productivity, of course, is a very rough measure because it only incorporates sales or revenues on the one hand and hours worked on the other. It is thus used as a stand-in, a kind of abbreviation, for more complex and very difficult calculations that take other and often intangible factors into account. One attempt to do so is the effort to measure multifactor productivity.

The BLS, in its press release on this subject, provides the following comment: "Multifactor productivity is designed to measure the joint influences of economic growth on technological change, efficiency improvements, returns to scale, reallocation of resources, and other factors, allowing for the effects of capital and labor. Multifactor productivity, therefore, differs from labor productivity (output per hour worked) measures that are published quarterly by BLS since it includes information on capital services and other data that are not available on a quarterly basis."

The MP index separately measures labor and capital inputs and then combines them based on the relative importance of each in a given sector to create a "composite" input. It similarly measures outputs per hour and outputs per unit of capital employed and also combines these. The index is then computed from the two composites.

The MP index is available back to 1987, has a base year of 2000 (index at 100), and is available to 2004. The index has increased 7.7 percent between 2000 and 2004. Multifactor productivity thus produces a more sobering picture of productivity by reflecting the role of capital which, indirectly, reflects the importance and costs of technology.

The data streams required to calculate MP are difficult to get and the index therefore difficult to replicate. Cause-and-effect relationships can only be inferred indirectly. For these reasons, MP is used primarily in academic analyses.


Labor productivity and compensation grow in tandem but not in precise coordination. In times of economic slow-down, inventories tend to be high but over time is cut and early layoffs take place. In times of up-turn, employers are slow to hire new labor until growth is well established. The overall growth rate of compensation lags that of productivity, in part explained by the "multi-factor" influence of technology which, ultimately, accounts for productivity.

This lag has been pronounced in the early years of the 21st century. In the 1992 to 2000 period, productivity increased just 4 points more than compensation based on the indices. But in the 2000 to 2005 period, productivity increased 9.1 points over compensation. A possible explanation of this divergence may be globalization. If functions heretofore counted into hours worked are off-shored, but output continues to be counted, fewer hours will be divided into dollars. Productivity will be going up precisely because the hours are expended overseas and have become invisible.


The small business, by its very definition ("small") will lack the scale effects often needed to justify high levels of automation. Similarly, unavoidable overhead functions will have less production to absorb their costs. Technological means of increasing productivity are, of course, also available to small businessand deployed by the alert business owner. This applies to rather esoteric areas as well as the more usual. The continued expansion in information technology (IT) and related specialties, for instance, such as computer-aided design and manufacturing (CAD/CAM), is bringing IT more and more within the "affordable range" of small business, as illustrated in several places throughout this volume. Small business, however, also has unique opportunities to achieve productivity through flexibility and creativity. It is very common in small businesses to have highly skilled and cross-trained employees who do "everything." Communications and decision-making are easier and often swifter. Small businesses tend to be innovators, not least in the novel use or invention of technology. Many of these traits are indirectly captured in multifactor productivity statistics even though they escape the simple calculation of sales divided by hours worked.


Magee, Monique, ed. Social Trends & Indicators USA: Work & Leisure. Thomson Gale, 2003

Parry, Thomas, and Phil Lacy. "Promoting Productivity and Workforce Effectiveness." Financial Executive. November 2000.

U.S. Bureau of Labor Statistics. "Multifactor Productivity Trends, 2003 and 2004." Press Release. 23 March 2006.

U.S. Bureau of Labor Statistics. "Productivity and Costs." Press Release. 7 March 2006.

                                                 Darnay, ECDI


views updated May 18 2018


Productivity is the result or the sum of all effort that it takes to deliver a product or service. Productivity is frequently referred to as output and, to some degree, can be measured. The output generated by a person, organization, or other entity is measured in terms of (the number of) units or items produced and services performed within a specified time frame. Thus, productivity is the economic value of goods and services. It becomes the value or result of the price of a product or service minus all costs (supplies, materials, human labor, etc., which frequently are monetary) that go into the effort.


Productivity is a performance measure that indicates how effectively an organization converts its resources into its desired products or services. It is a relative measure in that it is used to compare the effectiveness of a country, organization, department, workstation, or individual to itself over time for the same operation, or to other countries, organizations, departments, workstations, or individuals. From a systems perspective, productivity indicates how well an organization transforms its inputs into outputs. In manufacturing, productivity is generally stated as a ratio of output to input. Productivity may be expressed as partial measures, multifactor measures, and total measures. Partial productivity measures are used to analyze activities in terms of a single input (e.g., units produced per worker, units produced per plant, units produced per hour, or units produced per quantity of material). Multifactor productivity measures take into account the utilization of multiple inputs (e.g., units of output per the sum of labor, capital, and energy or units of output per the sum of labor and materials). A total measure of productivity expresses the ratio of all outputs produced to all resources used.


An important point in seeking productivity improvements in a subsystem of an organization is to link the subsystem improvements to the total system productivity. Optimization of a subsystem operation that does not affect the overall productivity of the organization is a waste of resources. For example, a manufacturer might improve the productivity of its machining operations, as measured by number of units produced per dollar. But if these units cannot be sold and are warehoused, the productivity of the organization has not increased, since the goal of the manufacturer is to generate revenue through the sale of its products. Activities intended to improve productivity must be carefully selected, and the appropriate measures must be developed to ensure that the organization's efforts result in the improvement of its overall productivity.

Numerous specific components are involved in contributing to and measuring productivity. The most important of these are discussed below.

Return on Investment

Productivity is closely related to, but not dependent on, profit. It can be measured by return on investment (ROI). ROI is determined after the sale of a product or service minus the deductions for the total amount of effort (resources, etc.) put into its design, development, implementation, evaluation, and marketing. The formula for determining ROI is: Price minus Cost divided by Sales.

Productivity Measures for Individuals and Teams

An individual's productivity is measured by that person's potential to reach the highest level of productivity possible. That is, a person has certain skills that determine his or her level of capability (an engineer's skills, banker's knowledge, etc.). An individual's experiences and education usually determine his or her skill level regarding a particular job. Other factors, such as a positive environment (working with a good team, having a good boss, liking the physical surroundings in the workplace, being appreciated, etc.) and how motivated one is to do a job, also contribute to productivity. When several individuals come together to work as a team, the team's productivity or the effectiveness of the team is the sum of individual efforts toward achieving a desired goal. Several factors (motivation, expertise, working conditions, team compatibility, potential, etc.) influence the level of productivity achieved.

Productivity Gap

A productivity, or capacity, gap is the difference between what a person can do and what that person actually does. That is, every person has the ability to achieve at a certain level. If a person is not motivated and is not working up to potential, that person's productivity gap is usually quite large. The same principle applies to a work team, organization, and so on. It is desirable to estimate potential (of a person, work unit, company, etc.) to determine where productivity gaps exist (and how large they are) and find ways to close them. By looking at a person's ability in conjunction with other motivational factors, it is possible to estimate a person's (or a group's) potential to achieve desired results. When all factors operate at optimum, the productivity is said to be at its highest levelthe productivity gap has been filled or is minimized.


Productivity is directly related to how motivated a person is to perform a task or activity. Many businesses devote much time and effort to finding ways to motivate employees. Worker enhancement programs (for an individual, team, company, etc.) that are built on ways to motivate workers (toward self-motivation and long-term motivation) can optimize productivity. Organizations that are most successful in motivating workers provide a variety of programs (formal and informal avenues within and outside the organization) to meet the needs of their employees. Some organizations offer employees sports and recreational activities, fitness and leisure activities, and family-oriented programs (work or job-augmented incentives). Incentive programs may be totally separate from or incorporated into work-team meetings, seminars, and education/training programs. Such a comprehensive approach toward enhancing worker performance may capitalize on quality measures (such as value, total quality management [TQM], quality circles, innovation, etc.) and performance standards (such as profitability, efficiency, customer satisfaction, on-time delivery, etc.) and include a wide range of personal and team rewards and incentives.

Mutual Reward Theory

Mutual reward theory (MRT) is based on finding ways for all to benefit. That is, if an organization can assist an employee in reaching some of his or her goals while still meeting the company's production goals, a mutual reward has occurred. When the benefits are at an optimum for all persons involved, the greatest rewards are realized. Productivity is usually directly proportional to the degree of MRT success.

Productivity Benchmarks

Factors that enter into productivity benchmarking for an organization include overall operations, worker training, technology, continuous quality improvement, and management philosophy and strategy. Management strategy includes how and at what level decision making takes place. Usually greater productivity gains are realized when decision making is pushed to its lowest level possible and is still effective. Also, an organization's efficiency may depend just as much on borrowing and lending strategies (e.g., requiring immediate payment on goods sold while practicing delayed payments to creditors) to maximize resource availability as it does on efficient operations and a safe environment. Thus, there are many important factors included in maximizing ROI, most of which depend on making the right decisions at the right time. What is a good decision for one company may be bad or devastating for another.

Productivity Growth and Economics

Productivity growth is defined as a measure of the amount of goods and services that are produced during a specified period of time. Once a standard has been determined, the standard (benchmark or identified level of production) becomes the measure against which all future production can be compared. Since 1950, the U.S. ten-year annual growth rates have been 2.17 percent for the 1950s; 2.85 percent for the 1960s; 1.71 percent for the 1970s; 2.17 percent for the 1980s; and an estimated 1.31 percent for the 1990s. The annual growth rate is of particular interest to individuals, since the productivity growth rate is directly proportional to a person's wealth. That is, as productivity levels go up, so does an individual's buying power. In turn, the total economy benefits from the boost.

Productivity Value Added

While productivity is more easily measured in manufacturing (products produced) than in services, most productivity researchers agree that people are the world's most valuable resources. Many productivity researchers suggest that education and training are the basic foundation for raising productivity levels. The acquisition of expertise through education and training, coupled with the best equipment and resources within an efficient and safe environment, can be maximized by developing employees into people who want to learn, who want to work at their potential, and who want to continuously improve. These factors are best achieved when an employee is motivated to take pride in the work he or she does. A motivated, self-starting employee is one who adds value to an organization and contributes to the overall productivity of him or herself, a work group, an organization, and the economy.

see also Quality Management ; Standard-Based Work Performance


Goodstein, Leonard, Nolan, Timothy, and Pfeiffer, J. William (1993). Applied Strategic Planning: A Comprehensive Guide. New York: McGraw-Hill.

Hammer, Michael (1996). Beyond Reengineering. New York: HarperBusiness.

Jonash, Ronald S., and Sommerlatte, Tom (1999). The Innovation Premium. Reading, MA: Perseus Books.

Langdon, Danny (2000). Aligning Performance: Improving People, Systems, and Organizations. San Francisco: Jossey-Bass/Pfeiffer.

Lewis, James P. (2000). The Project Manager's Desk Reference. New York: McGraw-Hill.

Meyer, Marc H., and Lehnerd, Alvin P. (1997). The Power of Product Platforms: Building Value and Cost Leadership. New York: Free Press.

Recardo, Ronald J., Wade, David, Mention, Charles A. III, and Jolly, Jennifer A. (1996). Teams: Who Needs Them and Why? Houston, TX: Gulf Publishing.

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Smith, Elizabeth A. (1995). The Productivity Manual (2nd ed.). Houston, TX: Gulf Publishing.

Tesoro, Ferdinand, and Tootson, Jack (2000). Implementing Global Performance Measurement Systems: A Cookbook Approach. San Francisco: Jossey-Bass.

Sharon Lund O'Neil

John W. Hansen


views updated May 23 2018


What It Means

Productivity is the ratio of output (goods created or services performed) to input (all costs of production, including workers’ wages and costs required to run business equipment). Productivity is not merely a measure of the final output from a company. For example, an automobile factory (Factory A) produces 1,000 new cars in an eight-hour workday. Another factory (Factory B) produces only 500 cars in an eight-hour day. To measure each factory’s productivity, it is necessary to compare the production of cars (the output) at each factory against workers’ wages and the cost to run the assembly line (the input) at each factory. Assume that both factories pay the same cost for using exactly the same equipment and that both factories pay their workers at the same rate. If Factory A required 50 workers to produce 1,000 cars in an eight-hour workday and Factory B required only 20 workers to produce 500 cars in an eight-hour workday, then Factory B would be more productive than Factory A, even though Factory A produced more cars than Factory B.

Productivity is difficult to measure accurately. Most companies measure productivity by weighing the total output against one aspect of the input, usually the total number of labor hours required to produce the final product. The total number of labor hours is the sum of the number of hours worked by each individual involved in the making of the product. For example, if 10 workers each worked eight hours to make a product, then the production required 80 total hours of labor.

Productivity is closely related to another economic concept called efficiency. Whereas productivity is a ratio of the amount of the output to the cost of the input, efficiency is a ration of the value of the output to the input. A business is considered to be operating at peak, or optimal, efficiency if it produces the greatest number of goods possible at the lowest possible cost.

When Did It Begin?

Finding ways to increase productivity has always been important to the long-term success of a business. Maximizing output became even more important after the Industrial Revolution because of the high costs associated with mass producing goods. Securing land and building a factory, purchasing and installing equipment, paying for fuel for equipment, and paying a labor force is expensive. Given these costs, it is crucial that a factory produce enough goods to make a profit. Thus, not long after the rise of factories came an outpouring of productivity and efficiency studies as well as numerous methods for getting the most possible output from a factory.

One of the best known of these ideas is called Fordism. Named after Henry Ford (1863–1947), the automobile entrepreneur who introduced the concept, the principle of Fordism states that in order to make workers happy (and therefore productive) it is necessary to pay them high enough wages so that they can afford to purchase the merchandise that they are producing. With a large group of his workers eager to buy his cars, Ford had a guaranteed market for his cars. This increased the demand for his cars among middle-class Americans, which in turn required his workers to be more productive to meet this demand. The strategy worked. By 1910 the Ford Motor Company had sold over 10 million Model T Fords. At the time, his employees were the highest paid factory workers in the world. In the aftermath of this success, Fordism was promoted as a model for worker management throughout the United States and Europe. These ideas now form the basis for what is called “efficiency wage” theory, which states that a worker’s productivity and efficiency is positively related to the wage he or she is paid. That is, if you pay workers more than the going wage, they will want to make sure they do not lose their job, encouraging them to work harder.

More Detailed Information

Businesses of all sizes, whether they produce thousands of cars a day or cut lawns in a suburban neighborhood, are always trying to maximize worker productivity. One of the best ways to maximize productivity is to create a working environment in which workers are likely to be working at their full potential for most of the time that they work. There are numerous theories about how to maximize worker production, and most economists agree that there is no single way that works best in all situations. Ford’s theory of paying high wages to workers is just one of those theories, and, though it worked for Ford, many economists point out that this approach is not always good for small businesses.

Consider the case of a landscaping business that makes most of its profits from cutting lawns. Each day the manager sends two teams of three workers to various clients. If the manager were to pay one team of older workers $10 per hour and the younger team $7 per hour, one might assume that the older, better-paid team would mow more lawns. This would likely be true in the beginning of the season. However, by the middle of the season, the younger team would likely be able to work as fast as the older team. Also, the younger team might work harder because they wanted to make more money. Say, for instance, that the workers on both teams socialize together in off hours and that all the workers spend about the same amount of money. Each of the workers decides that he or she must earn about $200 a week to make ends meet and to have enough money to spend recreationally. This would mean that the younger team would have to cut 29 lawns a week, but the older team would only have to cut 20 lawns (for the sake of this example, each lawn takes one hour to mow). Even though they were paid a better wage, the older team would be less productive than the younger team.

This example highlights two important aspects of productivity. The first is that when dealing with individual workers, individual motivation has a significant impact on productivity. In the above scenario, the younger group was motivated to work harder than the older group because they wanted to earn as much money by the end of the week as the older group had. The second concept is that money does not always motivate workers the way an employer would expect. Sometimes instead of raising the level of productivity, increased wages produce a “productivity gap,” or the difference between what a person is capable of producing and what he or she actually produces. In the above example, the older group was capable of mowing at least 29 lawns a week, but they mowed only 20. This productivity gap decreased the business’s profits.

Because money does not always motivate workers, employers make many other attempts to maximize workers’ productivity. For example, many employers purchase ergonomically sound equipment with the hope that these devices will make their employees more comfortable while doing their jobs. Ergonomics is a science that studies the best way to design products so that workers will maximize their output. For example, an ergonomically sound chair is comfortable and designed in a way that prevents back injury. Thus an office worker who has to spend his or her entire shift sitting down will be more productive seated in an ergonomically sound chair. This person will not need to take as many breaks to relieve tension in his or her back, nor will he or she be as likely to call into work sick because of back pain from sitting all day. This chair might cost as much as $300 more than other chairs, but it might prove to be a worthwhile expense because workers who use these chairs would generate more revenue. Businesses have taken many other measures to ensure that the work environment makes workers more productive. Scientific studies have shown the temperature at which workers are most productive. A Japanese company even saw increases in worker production when the air in the office was perfumed.

Recent Trends

Immediately after World War II, productivity in most sectors of U.S. industry increased sharply. This trend continued into the early 1970s, at which point there was a significant decline in productivity that lasted until the mid-1990s. Then in 1995 productivity in the United States increased and continued to grow through the turn of the millennium. Some economists attribute the growth in productivity to the growth of the Internet and the introduction of e-commerce (the buying and selling of goods online) in the mid-1990s. Other economists attribute the rapid growth in productivity to an influx of foreign talent into the United States. According to some reports, entrepreneurs from India and China operated 29 percent of the technology firms opened in Silicon Valley (a region of the San Francisco Bay Area) from 1995 through 1998. These leaders were making important contributions to the fastest growing industry in the United States, information technology.

Many talented immigrants joined the U.S. workforce throughout the second half of the 1990s. According to the 2000 census, more than 8 million college-educated, foreign-born people resided in the United States at the turn of the millennium. The United States was host to the largest such population in the world. The United States also is also home to more immigrants with doctorate degrees than any other country. Consistent levels of high-skill immigration are crucial to the technology industry because intelligent workers are required in the Research and Development (R&D) departments of technology firms. More intelligence means more innovation, and more innovation translates into greater productivity.


views updated May 18 2018



Productivity is a measure of output relative to input. It can be calculated in a number of different ways, and in a variety of different situations, both over time and within sets of firms, industries, countries, or other organizations.

The two principal measures are labor productivity and total factor productivity (TFP, sometimes loosely called the Solow residual). For the former, it is typical to take the ratio of output to the quantity of labor input, for example, the number of automobiles produced per production worker or the number of automobiles per hour of production worker time. For the latter, it is typical to take the ratio of output to the weighted sum of a broader set of inputs (sometimes labor and capital together; sometimes labor, capital and intermediate inputs, taken together). While labor productivity is easier to measure, TFP is often preferred as a measure of productivity since TFP growth represents output growth not accounted for by the growth of inputs, whereas labor productivity growth reflects both TFP growth and changes in the capital to labor ratio.

Although a single productivity number is of some interest, it is often better to have time-series productivity data for a particular unit or a cross-section of productivity data for a range of similar units. Furthermore, the definitions of labor productivity and total factor productivity are straightforward, but there are a large number of potential problems of measurement when it comes to defining just what is meant by output and by the various inputs. For example, in the case of the quality of inputs, should labor inputs be adjusted for the skills of workers and, if so, how? There are also a large number of problems in aggregating various outputs and inputs together. For example, in the case of TFP it is usual to weight labor and capital by their shares in value-added, which makes certain assumptions about the nature of the production function.

Empirically, the majority of work on national productivity growth has been conducted for the United States, which has presented a number of interesting features. First, there was a marked slowdown in productivity growth in the 1970s associated with the economic turbulence of that decade (oil shocks, stagflation, and so on) as well as structural changes (the rise of the service sector which historically has had slower productivity growth than manufacturing, as well as being harder to measure). Second, there has been a marked speedup (especially relative to European productivity growth rates) since 1995, associated with the spread of information and communication technologies throughout the U.S. economy, but most particularly in the financial, wholesale, and retail industries.

International comparisons of productivity are particularly difficult because of problems with exchange rates and differences in industrial structure. The United States enjoys a substantial advantage in terms of output per worker over every other major economy in the world14 percent higher in 2004 than the G7 average. This is driven by a higher ratio of capital per worker, high labor utilization, and high levels of technology. The relative position of the United States is somewhat less advantageous in terms of output per worker hour. According to data from the Organization for Economic Cooperation and Development (OECD), if the United States in 2004 is taken to have a productivity level (output per hour) of 100, the Eurozone has a level of 87, with the United Kingdom at 86, Germany at 91, and France at 103. Substantially larger gaps remain with other OECD members, with Japan at 70, Czech Republic at 45, and Mexico at 29. The excellent performance of France is often seen as a result of high capital intensity and a labor market that tends to favor employment of skilled rather than unskilled workers.

Finally, the level of productivity is an important determinant of the standard of living, which is often measured by the gross domestic product (GDP) per person. However, higher productivity does not necessarily imply a higher standard of living. In addition to productivity per worker hour, GDP per person also depends on hours worked per worker and the employment rate (employment per person) and these latter two factors are affected by national and local labor market institutions. Based on data from the OECD survey of the Euro area, GDP per person in the Euro area was 30 percent lower than that of the United States in 2002, with just over two-thirds of that shortfall due to lower labor resource utilization and the other one-third due to lower labor productivity.

SEE ALSO Cambridge Capital Controversy; Economic Growth; Marginal Productivity; Physical Capital; Production Function; Savings Rate


Durlauf, S., and J. Temple. 2005. Growth Econometrics. In Handbook of Economic Growth, ed. P. Aghion and S. Durlauf, Vol. 1A, 555-663. Amsterdam: North-Holland.

Jorgenson, D., Mun S. Ho, and Kevin J. Stiroh. 2005. Information Technology and the American Growth Resurgence. Vol. 3 of Productivity. Cambridge, MA: MIT Press.

Gavin Cameron


views updated May 21 2018


Productivity is the quantitative relationship between the number of inputs employed and the number of outputs produced. For example, productivity on a farm involves the inputs (or resources) of land, labor, tractors, feed, etc., and the outputs (outcomes) of crops and livestock. An increase in productivity means that more outputs (crops and livestock) can be produced from the same or fewer inputs. For instance, crop productivity on a farm may increase because the farmer planted a new, genetically engineered crop designed to be more resistant to insects and disease. The crop is planted on the same amount of land the farmer used the year before, however, the sturdiness of the genetically engineered plant allows more of the crop to survive the growing season and be harvested, increasing the farmer's productivity.

An increase in crop yield is a single-factor productivity indicator. A single-factor productivity indicator defines itself as one factor, rather than many, contributing to increased productivity. Another single-factor productivity indicator may be output per man-hours worked. Several factors combined can also contribute to increased productivity. They are called multi-factor productivity indicators. Total farm output per unit of input is a multi-factor measure.

Productivity plays a vital role in the economy. Increased productivity in national industries can raise the standard of living and the quality of life. It can also improve production efficiency and enhance competition. Technological advances have played a large role in increasing industrial productivity in the twentieth century. However, growth through improved technology may also work against an economy, creating unemployment, as the number of workers needed to produce the same output declines. For instance, with the advent of the multi-purpose tractor in the agricultural industry many tasks previously done by manual laborers were mechanized. The laborers who could not adjust their skills to meet the changes in the industry saw their jobs disappear. Unemployment brought on by changing technology and worker inability to meet those needs is called structural unemployment.

Though productivity and growth clearly affect a nation's economy there is no single way to measure it. Inputs and outputs involve numerous variables and no method has developed to accurately capture all the factors involved.

See also: Structural Unemployment


views updated May 23 2018

productivity (production) (in ecology) The rate at which an organism, population, or community assimilates energy (gross productivity) or makes energy potentially available (as body tissue) to an animal that feeds on it (net productivity). The difference between these two rates is due to the rate at which energy is lost through excretion and respiration. Thus gross primary productivity is the rate at which plants (or other producers) assimilate light energy, and net primary productivity is the rate at which energy is incorporated as plant tissue. It is measured in kilojoules per square metre per year (kJ m–2 y–1). In terrestrial plants, much of the net productivity is not actually available to consumers, e.g. tree roots are not eaten by herbivores. See also energy flow; secondary productivity.


views updated May 18 2018

pro·duc·tiv·i·ty / ˌprōˌdəkˈtivətē; ˌprädək-; prəˌdək-/ • n. the state or quality of producing something, esp. crops: the long-term productivity of land agricultural productivity. ∎  the effectiveness of productive effort, esp. in industry, as measured in terms of the rate of output per unit of input: workers have boosted productivity by 30 percent. ∎  Ecol. the rate of production of new biomass by an individual, population, or community; the fertility or capacity of a given habitat or area: nutrient-rich waters with high productivity.


views updated Jun 08 2018

productivity The ratio of output to input. Neither element is easy to measure completely or consistently over time; they are often converted into money values. Labour input can be expressed in numbers of workers, total number of hours worked, or wage costs in a given period. Similar choices exist for other factors of production. Outputs may be measured in differing ways, some physical (such as the number of items made), some related to value (such as the sale price or value added). Different measures can produce wide variations in the resulting values for productivity. Typical examples are volume of output per human hour worked or per machine hour; or sales value per dollar labour costs or per dollar invested.


views updated Jun 08 2018

productivity See primary productivity.

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