Using natural resource shocks to study economic behavior

Overview and summary of past literature

In 1995, Will Carrington published an intriguing study about how the construction of the Trans-Alaskan Pipeline System (TAPS) from 1974 to 1977 affected Alaska's economy. Alaska at the time was a very small state, with a population of about 400,000 people. To put that in perspective, this would only be the seventh largest county in today's Chicago metropolitan area. Yet, TAPS was the largest privately financed construction project ever attempted. Simply put, Alaska did not have the necessary workforce to complete such a project. In his study, Carrington documents the remarkable flexibility of the Alaskan low-skilled labor market to find the necessary skilled and unskilled workers to complete such a massive project.

Other researchers have explored how similar resource shocks affect local economies for the low skilled, or examine the long-term consequence of resource endowments on economies [1], [2], [3], [4]. These studies also find remarkable flexibility within local economies to accommodate the large demand shocks associated with natural resource shocks. While these results are certainly interesting, economists recognize that such shocks could further help understand how a wide range of other economic activity is affected.

In October 1973, OPEC's oil embargo of the US, and other countries perceived to have supported Israel in the Yom Kippur War, induced a massive increase in coal prices. While for most of the world's economies this dramatic increase in energy prices was traumatic, areas with coal and oil boomed. Figure 1 shows the real price of coal during this period; there clearly was a sharp price increase in line with the oil embargo. At least through the mid-1980s, the pattern of relative TPI in Pike County, Kentucky, as shown in the Illustration, is indistinguishable from the real price of coal: demand for labor increased and earnings followed.

A study from 2002 uses this sizable shock to examine the impact of local labor market conditions for low-skilled men on the take up of two US disability programs: the Social Security Disability Insurance program (SSDI) (which is a social insurance program) and Supplemental Security Income (SSI) (which is a means-tested program for people who do not qualify or only partially qualify for SSDI) [4]. The authors focus on four Appalachian states—Kentucky, Ohio, Pennsylvania, and West Virginia—which represented some of the poorest areas in the US at that time. Despite coal being particularly dangerous work, the authors find that disability payments actually declined substantially during the coal boom and increased during the coal bust. They find that a 10% increase in local labor market earnings decreased SSDI payments by about 3.5%. Similarly, a 10% increase in local labor market earnings reduced SSI payments within a county by about 6.4%. Thus, local labor market conditions appear to be a very important determinant of disability recipiency.

Natural resource shocks afford opportunities to study a wide range of outcomes

Because of the magnitude of these shocks, it is not surprising that researchers have used them to examine a wide variety of economic behaviors, including fertility [5], public assistance use and marriage rates [6], voting behavior [7], the local provision of public goods [8], health care use [9], and education [10], [11], [12].

Are findings from specific events generalizable across time and location?

While it is clear that a wide range of topics have been analyzed, it is perhaps not so clear whether these findings are generalizable to other periods of time and areas of the world. Toward this end, a couple of studies address the serious issue known as “Dutch disease.” Growth and trade economists have long-posited that having an abundance of natural resources can crowd out development in other industries. Cross-country studies have found that countries with large endowments have fewer exports of non-natural resource products, and growth has been lower for countries with large endowments of natural resources. Recent work has examined how oil and energy resources affect the development of areas with such endowments [2], [3].

One study looks at several US states (Colorado, New Mexico, Kansas, Oklahoma, Texas, Missouri, Arkansas, Louisiana, Tennessee, Mississippi, and Florida), comparing their development as of 1890 and then comparing outcomes from 1940 to 1990 [2]. The author finds that having an endowment of oil facilitated development. As the author states, “in 1940, about 50 years after oil was first discovered, its effects were large and beneficial. By the middle of the twentieth century, the development of the oil sector increased education and per capita income in oil-abundant counties without increasing local income inequality. Oil abundance also increased the employment share of the extraction sector mostly at the expense of agriculture and it had little impact on the employment share of manufacturing. But while oil abundance did not change the employment share of manufacturing, it did affect overall manufacturing employment density, increasing it by at least 50%” [2], p. 52. In other words, the study finds that the existence of oil facilitated economic growth and development in the endowed areas.

Another study from 2018 produces similar findings, although the focus is on a much more recent period (1969–2014) [3]. The authors consider the endowments of oil and natural gas within a county and examine how shocks to the energy sector affect both short-term and long-term effects on the local economy. Unlike earlier works [1], [2], this study finds some evidence of short-term crowding-out of employment in certain manufacturing sectors, but these sectors’ productivities or revenues did not decline. Moreover, any reduction in employment in these sectors was strictly temporary. As the authors conclude, “we find evidence against each link in the hypothesized Dutch disease chain of events. Manufacturing plants in resource-abundant counties benefit a surprising amount from local demand growth, manufacturing productivity does not decrease, and overall, there is no Natural Resource Curse: oil and gas abundance increases cumulative local wages and welfare” [3], p. 698.

Thus, there appears to be little evidence that areas with an abundance of natural resources are materially different economically from similar areas without natural resources. This is an important finding both for growth and trade economists who worry about the Dutch disease and for economists who wish to use resource shocks as instruments for changes in local labor market demand. But while the energy rich areas of, for example, Appalachia (the coal rich region of the Appalachian mountains in the eastern US) might be similar to other areas of Appalachia without energy, it is still the case that Appalachia remains a unique and peculiar place, with extremely low incomes and education levels relative to the rest of the US and other developed countries. Given the numerous studies that have used the Appalachian shock, researchers might wish to know whether the results of these studies have the desired “external validity.”

To see how well one may generalize these results, it is useful to examine two areas where the topics have been analyzed across both time and countries.

Human capital theory predicts that individuals acquire less schooling when the returns to schooling are reduced. To test this theory, the authors of a 2005 study examine the effect of the coal boom in Appalachia on high school enrollments [10]. During the 1970s, the coal boom increased the earnings of high school dropouts relative to graduates. During the 1980s, the boom subsided and the earnings of high school dropouts declined relative to graduates. The authors found that high school enrollment rates declined considerably in the 1970s and increased in the 1980s in coal producing counties relative to counties without coal. A more recent study also finds very large impacts on high school enrollment from the fracking boom in states with shale deposits during the 2000s.

In contrast, another study from 2012 explores the impact of the 1973–1981 oil boom in Alberta, Canada [11]. The authors find some evidence that the oil boom may have altered the time of education, particularly in relation to post-secondary education, but there appears to be no evidence that the oil boom affected the ultimate educational attainment of Alberta men. A 2015 study supports this finding via an examination of the later 2001–2008 oil boom [12].

The differences between US and Canadian results are summarized in Figure 2. The contrast between results is intriguing, though it must be mentioned that Alberta is a relatively wealthy province within Canada, and its schools have an excellent reputation, whereas Appalachia is a US region on the other end of both spectrums. Even so, the fact that two different shocks seem to produce consistent and contrasting outcomes in the US and Canadian settings is highly interesting.

Examining the impact of natural resource shocks on the utilization of disability insurance

A second area of research with an interesting replication is that of disability insurance take-up and local labor market conditions. A recent study from 2018 uses data from oil-producing US states between 1970 and 2011 [13] to compare findings with a previously referenced 2002 study [5]. Examining data through 2011 allows the authors of the more recent study to examine the long bust from the late 1980s to the later 1990s, and the subsequent boom beginning at the turn of the century. The authors’ focus on more recent cohorts and 11 states largely in the American West offers a very different experiment. The authors argue, “To the extent that disability benefits offer higher replacement rates to lower-earning workers […] disability take-up for the typical American worker, who more closely resembles the oil and gas workers we study, may exhibit very different responses to earnings shocks than do coal workers to shocks in their sector” [13], p. 416.

Despite these differences, the results are remarkably consistent across the two studies. The earlier study estimates that a 10% increase in earnings would reduce SSDI payments by 3.5%, while the estimate is 2.9% in the 2018 study. Again from the 2018 work, the authors note, “we find a similar relationship in a more nationally representative set of states, among more educated persons, and during a much more recent time period. This somewhat surprising result suggests that the response of disability take-up to market conditions is similar across areas and disability programs, despite different targeted populations for SSDI and SSI programs” [13], p. 442.