peer reviewed article


Craig S. Marxsen   is an Associate Professor of Economics, Department of Economics, University of Nebraska at Kearney.

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Stagnant Wages

Since 1973, real average hourly earnings have declined more than one-seventh. Even adding fringe benefits still results in remarkably stagnant real hourly compensation that was only slightly higher in the mid 1990s than it was in the early 1970s. [Burtless, 4] What a contrast this is to the period between the Civil War and 1973, when real earnings doubled about every 36 years! Real hourly compensation increased by more than 2.5 percent per year from 1959 to 1973 in the nonfarm business sector of America. [Michel et. al, 38] Had that rate persisted through the 36-year period ending in 1995, it would have increased by over 150 percent over this period!

Biases in the Consumer Price Index possibly exaggerate the apparent post-1973 decline in real wages. However, if hourly compensation in the non farm business sector is deflated using the sector's output price deflator (from the GDP Implicit Price Deflator series reported by the Commerce Department), then real hourly compensation approximately followed productivity growth from 1960 through the early 1990s. [Bosworth and Perry, 318 - 319] Productivity growth (non farm business output per worker hour) since 1973 has averaged less than 1 percent per year, down dramatically from its 2.5 percent annual average from 1960 to 1973 and from 1948 to 1960. [Oliner and Wascher, 19). For the first 70 years of the 20th century, even including the 1930s, productivity grew at an average rate of 2.25 percent per year, and it never averaged less than 1.5 percent per year for a single decade. [Oliner and Wascher, 18]

Several explanations for this stagnation have been advanced .

1. Price Index Bias

Recently, controversy about biases in the Consumer Price Index has cast doubt on the reliability of all sorts of inflation adjusted measures of economic performance. However, biases in measuring prices cannot explain the relative slowing seen when comparing pre- and post-1973 real earnings or productivity growth. Real wages have clearly stagnated relative to the earlier period, regardless of how the price index bias controversy resolves itself.

Michael J. Boskin headed a special committee appointed by the United States Senate for the purpose of studying the Consumer Price Index (CPI). Boskin's team reports that the CPI overestimates the rate of increase in the cost of living by about 1.1 percentage points per year. [Boskin, et. al., 3] The bias allegedly comes from the substitution bias inherent in Laspeyres indexes, the failure to adequately account for quality change and new products, and the failure to adequately account for changes in retail outlets (Goods are introduced on main street and then later are sold mostly at discount stores at reduced prices.). The Bureau of Labor Statistics (BLS) has generally acknowledged the substitution bias but challenged claims concerning the overall bias, that the BLS argues might actually be in the opposite direction if it exists at all. [Abraham, et. al., 31-33]

A recent paper by William Nordhaus attempts to verify the CPI bias found by the Boskin Committee. Nordhaus compares University of Michigan Survey Research Center questionnaire responses with CPI-deflated median income growth each year. [Nordhaus, 65-67] The median consumer reported being financially worse or better off in a pattern which indicated that a 1 percent to 1.5 percent decline in real income was neutral. Nordhaus inferred that the CPI seems indeed biased as claimed by Boskin, et. al. However, subsequently, Alan Krueger and Aaron Siskind [1998] have found fault with Nordhaus' method, repaired its defect, and used the procedure to show that the CPI is without bias.

Dean Baker [1996] observed that the BLS has been improving its methodology over the past decades. He argues the CPI biases due to quality changes, new goods, and retail outlets have gotten smaller than they were prior to 1983; the CPI overstated inflation by perhaps twice as much from 1950 to 1983 as after 1983. Baker uses the bias assumptions of the Boskin Committee to project today's poverty line back to the 1960s and 1950s. Median family income would have been right about at the poverty line in 1960 and somewhere between 65 percent and 95 percent of the 1994 poverty level in 1953. [Baker, 31]. Baker does not seem to regard such a conclusion as plausible.

Jack Triplett addresses the research issues that the price index bias raises in measuring earnings stagnation after 1973. Comparing the period 1959-1973 with the 1973-1995 period, Triplett observes a marked slowdown in the growth of (1) output per hour (2.9 percent dec;omes to 1.0 percent per year); (2) real hourly compensation (2.4 percent declines to 0.3 percent); and 3) real per capita consumption (per capita real personal consumption expenditure declines of  from 3.0 percent annual growth to 1.7 percent). [Triplett, 10] Triplett emphasizes that personal consumption expenditure data is deflated using the new Fisher ideal Chain Weighted Index method, thereby giving results which are essentially free of the substitution bias. The other sources of CPI bias, he shows, cannot explain a significant amount of the consumption growth slowdown after 1973. [Triplett, 22.] The sources of price index bias were no less present in the estimates for real wage, productivity, and real personal consumption growth prior to 1973. Although the exact rates of increase may be suspect, the abrupt slowdown cannot be explained away by biases in the price indexes. Therefore, the existence of a relative post 1973 stagnation appears to be indisputable.

Similarly, John B. Carlson and Mark E. Schweitzer [1998, 2] conclude that new methods of compiling the CPI reduce its bias by more than two-thirds of a percentage point. The Bureau of Labor Statistics has made these methodological changes in response to the Boskin Committee report. However, these same modifications, when applied to the GDP deflator, result in less than one-quarter of a percentage point change in labor productivity growth. The CPI bias sources were simply present to a lesser extent in the GDP deflator index. Moreover, as Carlson and Schweitzer also observe, there is no reason to think that price index bias was any less present in the numbers prior to recent years.

2. Foreign Trade

The productivity connection provides strong evidence against globalization of labor markets being the root cause of American wage stagnation. The popular vision pictures American workers sinking in an expanding competition with masses of low wage workers in developing countries. Freedom is blamed for their plight -- freedom to trade. A flood of labor intensive imports allegedly reduces demand for labor and, therefore, wages in America. Meanwhile, a frenzy abroad for machine-made exports propels rising returns for America's owners of capital. So, according to the famous Stolper- Samuelson theorem, although America as a whole gains from trade, labor must lose more due to the convergence of wages toward developing country levels than labor gains from participating in America's net gains from trade. But productivity is real output divided by labor hours. The existence of gains from trade means trade tends to increase productivity. By keeping up with productivity, American earnings have given labor a full share of the gains from trade with no apparent loss due to wage convergence (or factor price equalization).

In fact, the applicability of the Stolper-Samuelson theorem to America's foreign trade appeared dubious as far back as when the Leontief Paradox emerged in the 1950s. Subsequently, America was found to be a net exporter of labor intensive goods in one factor content study after another. Recent evidence shows that trade since 1973 has not resulted in declining prices for traded labor intensive goods relative to other traded goods. [Lawrence and Slaughter, 165] Neither has trade increased the return to capital relative to labor. [Lawrence and Slaughter, 170]

Increasing wage inequality has been a closely related topic in foreign trade studies. It appears that trade can't even explain why the real earnings of non-college graduates in America's labor force have fallen relative to college graduates' real earnings. Most factor content analysis studies (with the exception of one by Adrian Wood) find that trade cannot account for more than 10 percent to 20 percent of the post 1973 decline in the demand for unskilled labor underlying the rise in American wage differentials. [Freeman, 25] Likewise, price effect studies find that changes in import prices and changes in the prices of all of America's various manufacturing products cannot account for a significant part of America's widening wage inequality. [Freeman, 28] These findings were incisively summarized by Richard B. Freeman in 1995.

3. Government Regulation

The slowdown in productivity growth, it has been claimed, was to some extent caused by government regulation. Denison and Kendrick, for example, attributed between 13 percent and 16 percent of the slowdown seen in the 1970s to government regulation. [Wolff, 50] A study by Norsworthy et al. [1979] attributed 12 percent of the downturn in labor productivity to environmental regulations. Haveman and Christiansen [1981] estimated that 8 percent to 12 percent of the decline in productivity growth in manufacturing was due to federal regulations of all types. [Repetto, et. al., 48] Haveman and Christiansen estimated that regulation reduced annual labor productivity growth by .27 percentage points. [Gray,  998] Gollop and Roberts [1983] found emissions regulations had a large effect of 0.59 percentage points per year on total factor productivity growth for electric utilities. [Gray, 998] Gray [1987] found that Occupational Safety and Health Administration (OSHA) and Environmental Protection Agency (EPA) regulations accounted for more than 30 percent of the 1970s slowdown in total factor productivity growth in the average manufacturing industry. [Gray, 1005]

The most recent studies are finding a larger effect. In 1995, James Robinson at the University of California, Berkeley, reported finding that multi-factor productivity in manufacturing had by 1986 grown 11.4 percentage points less since 1974 than it would have without EPA and OSHA regulations. [Robinson, 414] Projecting these findings to 1992, a cumulative 17 percent of  the total factor productivity growth slowdown in manufacturing is explained, accounting for approximately 80 percent of the cumulative total factor productivity growth slowdown that actually occurred in manufacturing during that period of time. Robinson found OSHA regulations were unimportant; thereby  implicating the EPA as the major cause of this slowdown.

A recent study by the author [Marxsen, 1997] reached conclusions identical to Robinson's. Marxsen's study employed a simple regression of the post-1973 multi-factor productivity growth slowdown on 1991 pollution control spending as a percentage of sales for each of the 18 industries in the manufacturing sector. (These were those industries for which the Office of Technology Assessment provided data). A 17 percent manufacturing output growth shortfall by 1992 was detected. [Marxsen,  31]

Robinson's study also employed regression analysis inlooking at the total factor productivity growth from one component industry to the next among manufacturing's 455 disaggregated industries. Each sub-industry's compliance cost for EPA regulations was used to estimate that industry's productivity growth. Four different measures of multi-factor productivity were tried, and two different measures of regulatory compliance costs were used, resulting in 8 separate regression models. A regression was run for each of the models for each of the years from 1974 to 1986, and one was also run for all of the years in a pooled cross section and time series estimate for each of the 8 models. His results were robust among most of these exercises. Those industries with high compliance costs slowed much, while industries with low compliance costs (as a fraction of industry sales), experienced a very moderate slowing of total factor productivity growth.

The ripple effects throughout the economy can be seen in a general equilibrium model such as was developed by Hazilla and Kopp [1990]. In their model, EPA compliance costs were concentrated in just a few sectors. Manufacturing was directly depressed 6.33 percent by 1990. However, the financial, insurance and real estate sector, which bears virtually no direct compliance cost at all, suffered a 4.97 percent output reduction caused by higher input prices induced by direct effects in other sectors. [Hazilla and Kopp, 868 - 869] Combined direct and ripple effects resulted in output falling economy wide by 5.87 percent in response to EPA compliance costs that depressed manufacturing by 6.33 percent in Hazilla and Kopp's general equilibrium study. Such findings suggest that retarded productivity growth in sectors directly impacted by EPA regulations might induce similar retardations in the growth of output per worker hour in other sectors of the economy. The magnitude of this would greatly exceed what was actually estimated in the Hazilla and Kopp study. The author, by combining Robinson with Hazilla and Kopp, estimated that a 15.8 percent GNP shortfall has resulted from the same environmental regulatory program which caused a 17 percent manufacturing output shortfall by 1992. [Marxsen, 1998, 3]

A recent study by Richard K. Vedder of Washington University compares various measures of American productivity growth with federal regulatory costs over the period from 1960 to 1994. Estimates of three different models are reported for each of five different productivity measures. Time series regressions of these indicate that nearly half of the slowdown in long-run productivity growth from 1963 to 1993 in the private business sector can be explained by rising regulatory activity. [Vedder,. 16] Vedder concludes that, by 1993, the total annual cost of regulation approached $2 trillion. Taxation and deficit growth account for a major portion of the other half of the productivity growth slowdown, according to Vedder's regression results. [Vedder, 18]

4. Contaminated Motives

Mancur Olson [1988] emphasizes the role of special interest coalitions in bringing about a slowdown in productivity growth. His broader thesis [1982] emphasizes that nations naturally tend to eventually stagnate and decline as a result of "distributive coalitions" -- special interest groups which institute a host of restrictions. Excessive regulations get to be like barnacles growing on the hull of a ship. Olson provides a strong statistical argument for this general thesis in his 1982 book, The Rise and Decline of Nations.

In the 1970s, it at first appeared that manufacturers might be effective political adversaries of mandated pollution control equipment such as catalytic converters added to exhaust systems. Yet, such laws were little different from mandates requiring that any other kind of equipment be purchased by the public. It has been in the interest of manufacturers to encourage pollution control in general, while lobbying to rewrite the specifics of such legislation. Economic efficiency has not been their principal aim. For example, David Vogel [1997] emphasizes the quasi-protectionist effects of corporate average fuel economy standards (CAFE) and the trouble which they have caused in America's free trade negotiations with other countries. Likewise, the coal industry did not effectively resist the inefficiency of clean air legislation, but, instead, lobbied to mandate scrubbers rather than sulfur emission limits in the late 1970s. [Landy, Marc and Cass, Loren,  228] As is true of many environmental laws, the tug-of-war among interest groups greatly raised costs relative to the value of benefits from the clean air act and its amendments. [Landy, Marc and Cass, Loren, 228]

Voters largely own the existing stock of marketable assets, including equity shares and real estate. Companies, in aggregate, are not expanding the amount of outstanding shares of common stock. The enhancement of monopoly power that regulation provides existing, entrenched firms also promoted the appreciation of the market prices of their stocks. For example, "new source" air pollution control standards have been more rigorous than standards imposed on previously existing pollution sources. The large, "incumbent" corporations gained as the entry of new companies was suppressed by pollution control standards. In fact,the recent appreciation of large-capitalization corporate equities relative to small-caps must have been somewhat stimulated by such regulation. At the same time, large companies with old physical plants were discouraged from modernizing by building new plants that would have been subject to the "new source" standards.

The beneficial effects of regulation on real estate values are often sought openly. Zoning restrictions, building codes, and other construction standards and regulations are partly intended to protect the property values of existing houses and other structures. Environmental regulations also help limit the expansion of the housing stock and promote appreciation of housing prices. By interfering with timber harvesting, environmental regulation causes increases in lumber prices. Widespread home ownership creates a broad base of political support for such policies that protect property values, making the public receptive to otherwise hurtful regulatory initiatives. The individual rationally delights in otherwise inefficient laws which, nonetheless, prevent others from developing real estate nearby and spoiling the view.

Concluding Comments

A variety of studies have attempted to compare the benefits of regulations with their costs. The Office of Management and Budget prepared a Draft Report for submission to Congress on September 30, 1997, summarizing the total costs and benefits of federal regulations. The OMB drew heavily on a 1991 study published by Robert W. Hahn and John A. Hird, as well as reports from the U.S. Environmental Protection Agency and other federal sources. The OMB concluded that annual costs for environmental and social regulations were about $200 billion, while benefits were worth about $300 billion. In other words, net benefits were in the order of 1% of GDP. This estimate does not take into account the possibility that GDP is now more than 15 percent smaller annually due to the stifling effect such regulations have on productivity growth!

This article has, admittedly, presented a one-sided view of the impact of environmental regulations -- only certain costs were considered, and benefits were not considered. A full investigation of the benefits is, perhaps, more difficult than that of costs because many benefits are not so pecuniary in nature. In the last analysis,therefore, regulations could still conceivably prove to have provided net benefits to society.  It is my hope that the uncovering of hidden costs such as wage stagnation will lead to better public policy in the future.


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