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An integrated ecological macroeconomic model Karl Seeley * Hartwick College March 6, 2013 Abstract Standard macroeconomics minimizes or omits the role of resources in the economy. I argue that this omission rests on: a confusion between “land” and “resources”; an overly abstract view of technol- ogy that mischaracterizes the relationship between technology and resources; and a tendency to look at the stocks of resources a country has or the flow it produces within its borders, rather than the flow of resources it uses in its economy. I then propose a new theoretical ap- proach for integrating resources into the production function in a way that is both realistic and tractable. The key ideas are: evolving com- plementarity of labor and resources; supply curves of currently avail- able resources shaped through the interaction of harvest or extraction with innovation and investment; and outcomes being determined by the interplay of resource supply, labor supply, and labor productiv- ity, with resource use playing an important role in labor productivity. I compare the implications of this model with those of a standard non-resource approach, including the effects on output, employment, and wages of a short- or long-term reduction in resource availability. The paper also applies the new model to questions about the role of resources in the history of economic development. * Thanks to Charles A.S. Hall for valuable feedback on an early version of this work and to participants at the Second International Meeting of Biophysical Economics at SUNY ESF in Syracuse, NY. 1

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An integrated ecological macroeconomic model

Karl Seeley∗

Hartwick College

March 6, 2013


Standard macroeconomics minimizes or omits the role of resourcesin the economy. I argue that this omission rests on: a confusionbetween “land” and “resources”; an overly abstract view of technol-ogy that mischaracterizes the relationship between technology andresources; and a tendency to look at the stocks of resources a countryhas or the flow it produces within its borders, rather than the flow ofresources it uses in its economy. I then propose a new theoretical ap-proach for integrating resources into the production function in a waythat is both realistic and tractable. The key ideas are: evolving com-plementarity of labor and resources; supply curves of currently avail-able resources shaped through the interaction of harvest or extractionwith innovation and investment; and outcomes being determined bythe interplay of resource supply, labor supply, and labor productiv-ity, with resource use playing an important role in labor productivity.I compare the implications of this model with those of a standardnon-resource approach, including the effects on output, employment,and wages of a short- or long-term reduction in resource availability.The paper also applies the new model to questions about the role ofresources in the history of economic development.

∗Thanks to Charles A.S. Hall for valuable feedback on an early version of this work andto participants at the Second International Meeting of Biophysical Economics at SUNYESF in Syracuse, NY.


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1 Introduction

Complaints about macroeconomics are nothing new, even from within thefield, and particularly since the financial meltdown of 2008. Perhaps thebest known of these is Paul Krugman’s [49] widely publicized complaint in theNew York Times Magazine, while Steve Keen’s [46] critique in the Australianjournal Economic Analysis and Policy may be representative of professionalcritiques with a much smaller audience. Krugman is arguing against thecutting-edge mainstream macro that has left behind some of the tools fromafter World War II that Krugman still finds useful; Keen is making a case forthe inadequacy of the IS-LM structure that Krugman more or less accepts.

Herman Daly provided a vivid statement of an even deeper critique ofmacroeconomics in talking about the emphasis on the circular flow modelwithout consideration of what it is that makes the circular flow . . . flow:

It is as if the preanalytic vision that biologists had of animalsrecognized only the circulatory system and abstracted completelyfrom the digestive tract. . . . The dependence of the animal on itsenvironment would not be evident. It would appear as a perpetualmotion machine. [12, p. 256]

There is a small minority of economists for whom the fundamental roleof resources in economics is self-evident. The simplest statement of thisview would be that rich countries are rich because they use lots of resources.The answer from the mainstream is that rich countries use lots of resourcesbecause, being rich, they can afford them.

The model in this papers arises from the sense that both those positionsare true. Its starting point is roughly what Gordon [30] refers to as “1978-eramacro,” in contrast to the “modern macroeconomics” developed since then—not because that’s necessarily a better representation of the economy thanare, say, various “heterodox” alternatives, but because it’s the workhorseof collegiate textbooks for intermediate macroeconomics. My hope is thatbuilding ecology into this particular modeling approach—grafting the main-stream synthesis onto an ecological rootstock—makes it more accessible toother economists and more likely to gain acceptance. It also results in amodel that is conceptually tractable for instruction at the intermediate un-dergraduate level.1

1Section 8 will discuss briefly how a similar approach may be combined with othermacroeconomic perspectives.


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My core aim here is to improve the performance of Gordon’s “1978-eramacro” with respect to the understanding of the role of resources in theeconomy. The resulting model has additional attractive features:

• It clarifies the relationships among resource availability, potential re-source availability, investment, technology, labor productivity, labordemand, and output.

• As mentioned, the model is conceptually tractable for instruction atthe intermediate undergraduate level.

• It provides theoretical insight into consequences of different kinds ofinnovation and investment or various scenarios of changing resourceavailability.

• At the user’s discretion, it allows much or little room in the long termfor resources to be replaced by capital, technology, or labor.

• It illustrates the historical role of resources in economic growth andprosperity.

• It can generate empirically realistic short- and long-run responses toresource shocks without resorting to sticky prices, though there’s noimpediment to incorporating sticky prices if an analyst considers suchan approach to be warranted.

Section 2 reviews the key elements in the existing literature pairing macroe-conomics with resources. Section 3 lays out a bare-bones neoclassical synthe-sis, with business cycles as demand-driven deviations around a long-run trendresulting from supply factors. (This may be skimmed by many readers—itis simply there to establish the notation that will be modified later for theresource-inclusive model, and for comparison with that model.) Section 4makes the case for including resources in macroeconomic analysis, in part bycritiquing the reasons for their omission from the mainstream approach. Sec-tion 5 is the core of the paper, beginning with the manner in which resourcesare incorporated, then revisiting the basic model from section 3, first in itslong-run implications, then in the effect on the tools of short-run analysis.Section 6 clarifies points of divergence and similarity in the policy advice thatfollows from this model compared to a more standard one, while section 7applies the new approach to some of the literature on the role of resources in


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economic history. Section 8 looks at additional potential applications of themodel, and section 9 wraps up.

2 Literature

21 years ago Herman Daly laid out four principles for macroeconomic policythat acknowledges the environment [11]. First, limit human scale (through-put) to a level within carrying capacity. Second, technological progressshould be efficiency-increasing rather than throughput-increasing. Third, re-newable resources should be exploited on a sustained-yield basis, not drivento extinction. And fourth, nonrenewable resources should be exploited at arate equal to creation of renewable substitutes.

Ten years later, Jonathan Harris in [39] restated traditional macroeco-nomic goals, and emphasized the importance of an ecological perspective inmeeting them. He first lists economic stabilization which, as he observes, isoften mistakenly considered to be the only appropriate task for macroeco-nomic policy. The next two are distributional equity and broad social goals(such as income security and universal health care). The last is providinga stable basis for economic development, in which he is careful to rephrase“growth” as “development.”

While Daly and Harris are both clear on the economic importance of re-sources and ecological considerations, their focus is more on policy objectivesthan on analytical tools for clarifying the role of resources. But the inclusionof the environment in our understanding of the economy has a long history. Inthe writings of the classical economists, “land” is one of the three fundamen-tal factors of production, along with labor and capital; Thomas Malthus even(unintentionally) gave his name to the idea that resource limits are a bindingconstraint on prosperity—at least, prosperity for the unwashed masses. Themarginal revolution of the late 19th century dropped land from the anal-ysis and focused on labor and capital. Ever since, questions of resources,pollution, and ecosystems have been sub-disciplines, sideshows, and questsreminiscent of Ahab’s pursuit of the great white whale. (A good overview ofthis history is provided in [35, Ch. 4].)

The jump in oil prices following the Arab-Israeli War of 1973 seems tohave caused a spike in interest in resource questions, and among the earlyfruits were some work in which a conventional growth model has been tweakedto include a nonrenewable resource. For example, Koopmans [47], Stiglitz [71]


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and Hartwick [41] are all trying to define the optimal path for the extractionand use of a nonrenewable resource. They all depend on what Toman [72, p.31] refers to as “the simple capital-resource substitution story in the naturalresource depletion models of the 1970’s.”

A different tack looked at sustainability in the context of standard modelsof growth or trade, often with endogenous growth, but replacing the optimalexhaustion of a nonrenewable resource with the optimal or feasible transitionto a sustainable level of using a renewable resource. (In some, the renewable“resource” is the environment’s capacity to absorb wastes or recover fromdamage, but that doesn’t change the basic math.) Examples include Smul-ders and Gradus [67], Ulph and Ulph [73], and diMaria and Smulders [25].They also tend to portray environmental protection as a cost that limitsgrowth, because the ability to harvest resources or use the environment as asink is portrayed as an input in the production function.

These works, like the ones mentioned earlier on exhaustible resources, areeither normative or in the nature of “possibility theorems.” They define anoutcome or path that is optimal or possible, in terms of a highly simplifiedspecification of resources and/or pollution. A large part of the effort tomeasure the sustainability of economic growth comes under the umbrella ofthe environmental Kuznets curve, or EKC. This extensive literature startswith Grossman and Krueger [33], who make the claim that, at least forsome pollutants, environmental impact first increases with increasing wealth,then reaches a turning point and starts to decrease with further increases inwealth. The research since then suggests an EKC effect as a pollutant’simpacts are more localized and as substitutes are available at moderate cost.For instance, CO2 shows at best a weak EKC effect, which is consistent withboth the global impact of CO2 and the difficulty of substituting away fromenergy use. The entire line of EKC research is questioned by Stern [70], whoclaims that the econometrics behind EKC estimates are not robust.

A different line of work focuses not on a specific question such as sus-tainability or the optimal path of nonrenewables extraction, but aims ratherto restore resources to their former place at the core of economics, bringingthem in from the intellectual ghetto. Part of this impetus came from ecol-ogy, as exemplified by Howard Odum in [58], a book that analyzed energyflow in ecosystems, whether human or non-human. About the same time,the economist Nicholas Georgescu-Roegen [27] emphasized the importanceof sources of low entropy for the economic process. The two strains werebrought together in [34] (the first author, Charles A.S. Hall, had been a


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graduate student of Odum’s). The logical endpoint (for now) is the por-trayal of an economy as being like an ecosystem, not merely in its necessaryobedience to the 1st and 2nd Laws of thermodynamics, but in its structure,organization, and ways of developing ([4, 64]).

Documentation of the kind of relationship between resources and theeconomy described in [34] can be found in Cleveland and Hall [10], or Brownet al. [8], or Ayres et al. [2], or by combining data on “ecological footprints”from the Global Footprint Network [28] with GDP per capita or with abroader measure of well-being such as the Human Development Index fromthe United Nations Development Programme. In a slightly different direc-tion, there are extensive computer-based simulations of an economy withresources integrated and playing a major role, such as Meadows et al. [54] orIdenberg and Wilting [43]. Simulations grounded more in Hall et al.’s visionof the economy in [34] can be found in Hall et al. [36].

Within the discipline of economic history, there is a considerable literaturearguing over the role natural resources in growth, both historically in the riseto dominance of the world’s rich countries and currently in the developingworld. For instance, Pomeranz [61] portrays a pre-modern world in whichChina is ahead of Europe, with Europe able to catch up and then far surpassChina because of the resource windfall represented by its colonial control ofthe transatlantic world. In response, [45] and [19] relegate resources to atbest a secondary role in this process. Mokyr in [55] and Wood in [74] takea similar position more generally, with non-resource factors being the keydeterminants of economic history and development.

In addition to the connection between resources and long-run growth,there has been considerable focus on business cycles and resources, specifi-cally the role of oil prices as possible drivers of economic fluctuations. JamesHamilton has made seminal contributions to this literature, starting with [37]and continuing with many more works through at least [38]. A common ap-proach in his work and others following him is some sort of vector autoregres-sion model or error-correction method, with an indicator of the business cycleas the dependent variable and a measure of the oil price on the right. Earlyefforts simply looked at changes in GDP and changes in inflation-adjustedoil prices, but the quest for more robust estimation led to allowing asymmet-rical effects of price hikes vs. declines, and then increasingly subtle ways ofincorporating the oil price, such as only looking at levels that were new highscompared to the previous three years.

This literature often doesn’t specify a production function; the theoretical


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motivation for including oil prices is verbal and rests on some combination ofoil’s role in production, the effect of high energy prices on disposable income,stickiness in labor allocation that has been necessitated by the uneven effectof oil prices on different sectors, and possibly counterproductive responsesfrom policy-makers. Some, however, do have an explicit production in whichcase it is characteristic that resources and labor are substitutes, as in [6] (andin contrast to the current paper, as will be explained in section 5.2).

In [52] and [14], sectoral impacts are the main “transmission belt” fromhigher oil prices to lower output. In [63], the reliance is on imperfect compe-tition and the resulting markups. Rasmussen and Roitman in [62] implicitlyemphasize the demand-side effect, in which a growing global economy pushesup the price of oil, rather than a supply effect, in which inadequate growthin oil supply pushes up the price, in turn slowing economic growth. And [9]focuses on the role of the efficiency wage.

Within this literature, Daniel [13] is notable for treating the quantity ofresource use as a component of what is usually lumped together as “technol-ogy,” as with the Solow residual, but there doesn’t seem to be be a theoreticalbasis for the determination of the quantity of resources used. Even closer tomy work is Moroney [56], who econometrically relates resource use to laborproductivity, though as with Daniel [13], there isn’t a model that explainshow the economy chooses the quantity of resources to use. Gordon [31] in-cludes resources as a type of supply shock in the context of a Phillips-curveanalysis, one of many possible scenarios that can cause an upward shift in thetradeoff between unemployment and inflation. This will turn out to resembleone implication of my work (see section 5.5), though Gordon reaches it by adifferent route.

There are some existing models in which resources and labor are allowedto be complements rather than substitutes, examples being Aghion et al. [1]and Natal [57]. But these have significant differences from the model in thispaper, as will be discussed in relevant places later in the paper.

Hall and Klitgaard’s recent textbook [35] is a thoroughgoing resource-based treatment of the economy, adapting the approach of [34] to the macroclassroom. But Hall and Klitgaards want (with some justification) to replacestandard macroeconomics, as opposed to my program of improving standardmacro by the inclusion of some basic ecological realism. In contrast, thethread started by Heyes [42] bears a stronger resemblance to the present work,to the extent that it aims explicitly at bringing resources into conventionaltextbook macroeconomics. The theoretical approach, however, is markedly


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different.Heyes added an environmental constraint to the existing goods-market

and money-market equilibrium lines of the standard IS-LM model, produc-ing an IS-LM-EE framework. The model looks at a “generic” pollutant andconsiders the pollution intensity of production. Three features of Heyes’construction are important here. First, pollution intensity and capital areassumed to be substitutes. Since a lower interest rate allows the creation ofmore capital, it also enables a higher level of output without exceeding theenvironment’s regenerative capacity. This shows up as a downward-slopingEE curve added to the standard IS and LM curves plotted in r − Y space.Second, there is no automatic adjustment process to keep society on the EEcurve; rather, policy makers must be cognizant of the new curve and its mean-ing and must adjust their combined fiscal and monetary policies accordingly.Third, a more diminished environment regenerates more slowly (in this case,the regeneration rate is a linear function of the state of the environment).A promising feature of the model is that a diminishment of the environmentreduces regenerative capacity and thus moves the EE curve left, resulting ina more stringent constraint for maintaining environmental equilibrium. In-stitutional and regulatory factors can reduce the intensity of environmentalinputs in production, shifting EE to the right. Nonrenewable resources arenot included. Pushing back the other way, a short-term equilibrium to theright of EE thus shifts the next period’s EE curve to the left, and has theintuitively sensible result that “short-run economic development beyond theecological carrying capacity reduces the long-run sustainable development ofthe economy.” [42, p. 7]

Lawn ( [51]) extends Heyes’ framework by adding a parameter to capturespillover of environmental effects and a parameter of technological progresswhich makes it easier to substitute capital for environmental inputs. Toconvert the Heyes framework into practical policy, Lawn introduces the ideaof permits for a limited amount of throughput, along with liability bondsagainst the possibility that economic activity will have environmental impactsnot sufficiently accounted for by the throughput limitation.

Sim ( [65]) takes this structure further, citing evidence that environmen-tal damage does in fact impede growth, as environmentally provoked sicknessreduces worker productivity; Sim argues that this represents a plausible au-tomatic equilibrating mechanism. He modifies the Heyes/Lawn structure byadding an output gap, but instead of the conventional measure comparingobserved output to potential output indicated by long-run equilibrium, this


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output gap compares observed output with the level that is environmentallysustainable. In addition to the losses of productivity due to environmen-tal harm, there is assumed to be an increase in regulation in response to“excess” output. These (semi-)automatic adjustment mechanisms are incor-porated into the equation of the IS curve, ensuring that the economy will beat the intersection of all three curves (IS, LM, EE), even without the pol-icy makers having and using the extensive information necessary to achieveenvironmental equilibrium in Heyes’ and Lawn’s versions.

While the work of Heyes, Lawn, and Sim is interesting, it implicitlyequates macroeconomics with the IS-LM framework and thus with a short-term, demand-side approach (analogous to how [39] observed that economicstabilization is often taken to be the only legitimate goal of macroeconomicpolicy). The crucial dynamics of resource availability and use over the longterm are neglected, and even within the terms of the models, the representa-tion of resources and the adjustment mechanisms around them are not veryconvincing. The model that follows aims to capture some key aspects ofresource availability—far less than are reflected in the complexity of some-thing like [54] or [43], but with greater realism than in work such as [47]or [67]—and incorporate them into a model that will feel familiar to a broadselection of macroeconomics instructors.

But first I summarize the model I’m modifying, both to establish a com-mon baseline and to make clear the notation before I start changing it.

3 The standard approach

The standard neoclassical approach to macroeconomics combines a long-runmodel based on supply factors, with deviations around the long-run trend,driven by forces of demand. Gordon deals handily with the inadequaciesof “modern macro” in handling the relationship between financial meltdownand the real economy.

3.1 The long-run, full-employment model

The long-run model is built around a production function, where aggregateoutput Y is a function of capital, K, labor, N , and some technological param-eter, A. The most common way of combining these factors is a Cobb-Douglasfunction, such as


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Y = Kα(AN)β. (1)

The production function yields a marginal product of labor (MPN), whichin turn is the basis for labor demand, Nd, which is a function of the real wage,w.

Demographics and people’s leisure/labor preferences determine labor sup-ply, N s, which is also as a function of the real wage.

Equilibrium in the labor market is defined as the wage w∗ such that

Nd(w∗) = N s(w∗), (2)

leading to equilibrium labor input N∗, as shown in Figure 1.(Figure 1 here)Using that quantity of labor in the production function yields potential

output Y ∗:

Y ∗ = Y (N∗). (3)

The equilibrium level of employment in a sense tells us the natural rate ofunemployment, u∗, which is also related to the concept of the non-inflation-accelerating rate of unemployment (NAIRU).

Potential output grows along with capital, technology, and the labor sup-ply. Output per worker y∗ grows along with capital and technology.

3.2 The short-run

The long-run or full-employment equilibrium determined above can be thoughtof as “potential output,” the amount the economy “should” produce when allmarkets have had time to clear. This level of output serves as a kind of “an-chor” for the short-run analytical tools, which are used to explain deviationsfrom potential output over the course of the business cycle. We’ll look atthree workhorses of standard business-cycle modeling: the IS-LM framework;aggregate supply and aggregate demand; and the Phillips curve.

The IS curve represents all the combinations of output Y and the realinterest rate r for which the output market is in equilibrium. Higher outputrequires higher expenditure in order for equilibrium to be maintained, whichin turn implies a lower real interest rate. The slope is thus determined in partby the interest-rate elasticities of investment demand and any exchange-rate


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effects passing through to gross exports; the tax rate also affects the slope.Lateral shifts come from changes in autonomous consumption, autonomousinvestment, changes in gross exports not related to the exchange rate, andchanges in government expenditure.

The LM curve traces the combinations of Y and r for which money sup-ply and liquidity demand are in equilibrium, where liquidity demand is afunction of the nominal interest rate i and expected inflation πe, or of thereal interest rate expressed as r = i + πe. There’s generally a positive rela-tionship between Y and r, with different slopes depicting a range of possiblemonetary regimes.2

Planned expenditure, or aggregate demand, is determined by the inter-section of the IS and LM curves, and it can deviate from potential outputbecause of changes in any of the components of either curve. Figure 2a showsa pair of IS and LM curves in levels of output, but quarter by quarter, poten-tial output is shifting to the right, so one of the curves could be increasing,but not by enough to keep up with growth in potential output. Thus it issometimes more useful to show the IS nd LM curves in terms of percentageof potential output. In such a representation, as in figure 2b, an economywith stable growth would have relatively static IS and LM curves.

(Figure 2 here)The IS-LM framework feeds into the model of aggregate supply and ag-

gregate demand. Output is plotted on the horizontal axis against either theprice level or inflation on the vertical axis. Aggregate demand, or AD, isthe planned expenditure level indicated by equilibrium in the IS-LM model.This slopes down like a well-behaved demand curve; when you’re represent-ing AD in terms of the price level, this is because higher prices reduce thereal quantity of money, shifting the LM curve to the left and bringing thelevel of planned expenditure down with it; if you’re treating AS-AD in termsof inflation, then the negative slope of the AD curve is grounded in the ideathat the monetary authority will respond to inflation with a more restrictivepolicy, again shifting the LM curve to the left. Figure 3 illustrates a basicAS-AD structure, in this case with inflation on the vertical axis.

(Figure 3 here)There are two different types of stories that can be told to explain the

upward-sloping aggregate supply curve. The first type goes from higher prices

2See, for instance, Brad DeLong’s classification at [18], including one that slopes downrather than up.


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or higher inflation to greater output. It relies either on sticky wages, or elseon flexible wages but with workers who incorrectly perceive higher nominalwages as higher real wages. In either case, a higher price level or an increasein inflation results in a lower real wage, thus higher employment and higheroutput.

The second type of explanation for the upward slope of the AS curveworks in the other direction, from higher planned expenditure to a combi-nation of higher output and higher prices or inflation. In this story, changescaptured in the IS-LM model cause households and firms to spend more.The economy generally responds to this expenditure with a less than one-for-one increase in output, whether because firms don’t think that increasedoutput is worth the risk, or because they can’t increase output as much asexpenditure. Whatever the reason, an increase in expenditure that isn’t fullymatched by an increase in output will lead to an increase in inflation or theprice level. To the extent that there is at least some increase in output,this in turn gets partially respent (the basis of the Keynesian multiplier) andthis expenditure in turn leads possibly to a further expansion of output, andso on. The fully Keynesian AS curve is horizontal (output can change butprices are sticky), while the “classical” curve is vertical (prices are flexiblebut output is determined on the input side). In the “real world” of the 1978-era model, the AS curve is neither perfectly flat nor perfectly vertical buthas some sort of slope, steeper or flatter depending on circumstances.

The final piece of the short-run model to discuss here is the Phillips curve.This is graphed with unemployment on the horizontal axis and inflationon the vertical. A Phillips curve is “anchored” on a point defined by the“natural” rate of unemployment u∗ and the expected level of inflation πe.Although it slopes down to the right, it is in effect an aggregate supply curve:a move to the right implies higher unemployment and thus lower output.

(Figure 4 here)The Phillips curve can be combined with a curve showing the monetary

policy reaction function (MPRF), and although it slopes up to the right, it isessentially an aggregate demand curve. It captures the idea that the mone-tary authority will react to higher inflation by restricting the money supply,resulting in higher unemployment. A central bank that reacts strongly tohints of inflation will produce a relatively flat MPRF, while a more “toler-ant” bank will produce a steep one. Figure 4 shows both an MPRF and aPhillips curve with its anchor points of expected inflation and natural unem-ployment.


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Since the Phillips curve has those two anchors, changes in either of themwill move the curve. Prolonged experience of inflation will raise expecta-tions, as can policies thought likely to eventually generate higher inflation(this second effect is more true the more one accepts the idea of “ratio-nal expectations”). Meanwhile, structural changes in the labor market mayraise u∗. Increases in πe and/or u∗ are in effect negative supply shocks thatwill shift the curve up and/or to the right, creating a less favorable set oftrade-offs for the economy. The Phillips curve framework can also be usedto represent different ways in which expectations are formed, with the curvemoving instantaneously under rational expectations, slowly under adaptiveexpectations and (at least for a while) not at all under static expectations.

All three of these short-run tools—IS-LM; AS-AD; PC-MPRF—are cen-tered around either potential output Y ∗ or natural unemployment u∗. To-gether, they provide a way of modeling deviations from those levels alongwith changes in the interest rate and the price level or inflation.

4 Why resources are neglected

As discussed in section 2, there is extensive evidence that resources play a keyrole in the creation of wealth and thus in the economy. Yet the recognitionof that role is a distinctly minority view. There are at least three types ofreasons for the mainstream neglect of resources’ importance:

• A focus on land specifically rather than resources in general.

• An excessively abstract view of technology and capital that mischarac-terizes the relationship between them and resources.

• A confusion between the availability of resources with a country andthe quantity of resources actually used by that country’s economy.

All three are present in a representative textbook, worth quoting at somelength [50, p. 380]:

Other things equal, countries that are abundant in valuable natu-ral resources, such as highly fertile land or rich mineral deposits,have higher real GDP per capita than less fortunate countries.. . . But other things are often not equal. In the modern world,


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natural resources are a much less important determinant of pro-ductivity than human or physical capital for the great majorityof countries. For example, some nations with very high real GDPper capita, such as Japan, have very few natural resources. Someresource-rich nations, such as Nigeria (which has sizable oil de-posits), are very poor.

Historically, natural resources played a much more prominent rolein determining productivity. In the nineteenth century, the coun-tries with the highest real GDP per capita were those abundant inrich farmland and mineral deposits: the United States, Canada,Argentina, and Australia. As a consequence, natural resourcesfigured prominently in the development of economic thought. Ina famous book published in 1798, An Essay on the Principle ofPopulation, the English economist Thomas Malthus made thefixed quantity of land in the world the basis of a pessimisticprediction about future productivity. As population grew, hepointed out, the amount of land per worker would decline. Andthis, other things equal, would cause productivity to fall. Hisview, in fact, was that improvements in technology or increasesin physical capital would lead only to temporary improvementsin productivity because they would always be offset by the pres-sure of rising population and more workers on the supply of land.In the long run, he concluded, the great majority of people werecondemned to living on the edge of starvation. Only then woulddeath rates be high enough and birth rates low enough to preventrapid population growth from outstripping productivity growth.

It hasn’t turned out that way, although many historians believethat Malthus’s prediction of falling or stagnant productivity wasvalid for much of human history. Population pressure proba-bly did prevent large productivity increases until the eighteenthcentury. But in the time since Malthus wrote his book, any neg-ative effects on productivity from population growth have beenfar outweighed by other, positive factors—advances in technol-ogy, increases in human and physical capital, and the opening upof enormous amounts of cultivatable land in the New World.

Note what’s here in Krugman and Wells’ explanation of how we escapedfrom the Malthusian trap, and also what’s missing. Resources are present,


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but only in the form of “enormous amounts of cultivable land in the NewWorld.” Of energy or fossil fuels, not a word.

The focus on “land” rather than “resources” has deep roots, reachingdown at least to the benchmark work on growth accounting by Denison.In [24, p. 52] there is interesting information about the poor match-up atthe quarterly level between productivity downturns and the oil shocks of 1973and 1979. But given the nature of how productivity is measured, long-runtrends may be more reliable indicators than quarterly fluctuations. Furtheron, [24, p. 54] relies on the small share of costs devoted to energy andfocuses on energy per unit output, rather than energy per worker. But bothof these pieces of evidence are merely arguments for not measuring the effectof resources. In his actual growth accounting he is using “land” to mean quiteliterally “land,” as can be seen from Tables 7-1 through 7-4 and 8-1 through8-4 ( [24, p. 107-114]) where the input of “land” to the economy is unchangedover the period 1930-1982, a period during which use of petroleum went up by413%, coal by 12%, and overall energy use by 209%. The same treatment ofland is repeated in several other of Denison’s works, i.e., [20], [21], [22], [23].

We can see the confusion between using resources and having them withinyour borders in Denison in [20, p. 185]. He extends “land” by consideringdifferent types, including what he refers to as “mineral lands.” “Productsmeasured were bituminous coal, lignite, anthracite, peat, natural gas, crudepetroleum, iron ore, copper, uranium, zinc, lead, gold, silver, china clays,lime phosphate rock, salt, sulphur, pyrites, and potassium salts. But theseare measured in value, not in volume, and more importantly, the data aremarshalled for an “approximate comparison of minerals production (emphasisadded), not use.

The same confusion is evident in Wood [74, p. 201-202], in more barbedlanguage than Krugman and Wells employed:

Whether countries or people are rich or poor does not usuallydepend fundamentally on natural resources. Economics is helpfulin seeing through this illusion. . . . Some economists have taken aclear and correct line on this illusion, particularly in recent workon the role of institutions in development. But other economistshave persuaded themselves by various sorts of theoretical andempirical analysis that countries are poor because they have toomany natural resources and (though mercifully not usually in thesame article) that people are poor because they have too few


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natural resources.

Wood’s pretended astonishment is easily cleared up if we apply the “have-vs.-use” distinction. Having lots of resources may or may not be good for youreconomy, in part depending on the institutional factors that Wood rightlyalludes to. As illustrated in the earlier passage from Krugman and Wells withthe comparison of Japan and Nigeria, it’s easy to find resource-rich countriesthat are poor, and resource-poor countries that are rich. But if dysfunctionalinstitutions do keep you from turning resource abundance into economicprosperity, you’ll find that it is, in a sense, because those bad institutionskeep you from using the resources you have. Because whether you look attotal energy from the International Energy Agency, or at ecological footprintsfrom the Global Footprint Network, the relationship between resource useand GDP is exceptionally strong. Not only does a regression of GDP onresource use produce an astonishingly high adjusted r-squared. It’s also truethat there are no countries that are very poor yet use more-than-averagequantities of resources, and there are no countries that are very rich anduse less-than-average quantities of resources. The link between resource useand GDP is astonishing. It’s only possible to miss it if you’re looking at acountry’s resource endowment or extraction and harvest rather than its ownuse.

Turning to the nature of innovation, we see that Krugman and Wells list“advances in technology” (along with resources in the form of land) as one ofthe reasons for avoiding the Malthusian dynamic. Mokyr in [55, p. 324] putsit more pointedly, explicitly raising the technological side above the additionof resources: “It is Europe’s intellectual development rather than its coalor its colonial ghost acreage that answers Pomeranz’s query of why Chinesescience and technology—which did not ‘stagnate’—‘did not revolutionize theChinese economy.’ ”

The task, then, is to build resources into a macroeconomic model in a waythat focuses on using rather than having, that looks at resources broadlyrather than merely at land, and that gets right the relationships amonginnovation, investment, potential resources, and available resources.

5 Resources in the production function

This section is the core of the paper. I start by giving the key characteristicsof resource supply that I want the model to capture. I then incorporate


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that into the long-run model from section 3.1, then look at how technologypaths can be characterized and how different paths interact with constrainedresource supply. Finally, I look at the way the resource perspective changesthe behavior and implications of the short-run model.

5.1 Characterization of resource supply

As discussed earlier in the paper, there are numerous models that includeresources in the production function in some fashion, but there are two keyinnovations in the present work:

1. Defining the role of resources in terms of a resource-intensity of labor—that is, a quantity of resources that gets used along with a quantity oflabor.

2. A theoretical structure for determining the quantity of resource use.

Turning to the first issue, let the resource intensity be ρ; then the quantityof resources used in the economy is R = ρN . If we denote the resource priceas PR, and the effect of resource use on labor productivity as ϕ, then wecan in principle write resource intensity as a function of resource price andeffect on productivity: ρ = ρ(PR, ϕ). This function can be defined so asto allow some short-term substitutability between labor and resources, butas Spencer et al. [69, p. 20] observe, “In the short-term, [the elasticity ofsubstitution between labour and energy] may be restricted by the lock-in ofenergy intensive capital stock; in the longer-term, as the capital stock evolves,the elasticity of substitution may increase.” In the extreme, we can simplifyby saying that, though the resource-intensity of labor can evolve over thelong run, in the short-run it is fixed, so that for a given economy it can beexpressed as a function of time, ρ = ρ(t), with the understanding that itevolves slowly in response to changes in capital and technology.3

The second major change is to incorporate a resource supply curve Rs,analogous to the labor supply curve N s. Where the labor supply is deter-mined by demographics and preferences, resource supply is shaped by invest-ment and technology in combination with either biology or geology. Capital

3Natal [57] uses an estimate of oil-labor substitutability of 0.33, but that’s based onothers’ estimates of oil price-elasicity. That doesn’t necessarily justify a transfer to short-term substitutability between labor and resources in general, since one way to respondto a higher oil price is to replace some of your oil with other resources, rather than withlabor.


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can increase the harvest or capture of renewable resources, as when boatsincrease the amount of fish that can be caught in a year, forestry equipmentincreases the number of trees that can be cut in a year, and photovoltaicarrays and wind turbines increase the amount of solar or wind energy thatcan be captured in a year. A similar dynamic plays out with technology,where fish-finders, more powerful tree-harvesting machines, and better PVtechnology or wind-turbine blades can similarly increase harvest or capture,once those technologies are embodied in capital.

The same thing happens with exhaustibles: all else being equal, more coalmines or oil wells will increase the amount of fossil fuel available in a givenyear, and new technologies for reaching deep under the ocean or releasingfuel from “tight” formations will similarly increase supplies.

But with many renewables we have to account for biology, and with allexhaustible resources we have to take geology into consideration. More boatswill increase our fish catch from a given stock of fish, but the increased harvestwill also diminish next year’s stock. Analogously, more oil wells mean moreavailable oil from a given stock of oil not yet extracted, but more extractionthis year leaves less in place to be extracted in the future.

Thus we can characterize resource supply in the following terms:

1. At a given time (in a given year), there’s some maximum amount of aresource that can be made available to the economy, determined by theinteraction of either geology or biology with the installed capital forextraction, capture, or harvest and the level of technology embodied inthat capital.

2. Some of the resource will likely be available at relatively low cost, withprices rising ever faster as the quantity approaches the currently feasiblemaximum. This point and the previous one are summarized in figure 5.(Figure 5 here)

3. All else being equal, investment in capital for extraction, capture, orharvest will move the resource supply curve to the right. The same istrue of technological innovations.

4. Harvest of a biological resource tends to move the supply curve to theleft, with large harvests moving it strongly to the left. If the resourceis left alone for a time, the resource supply should in principle recoverand move back to the right.


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5. Extraction of a nonrenewable resource moves the supply curve to theleft. Being exhaustible and incapable of the regeneration that char-acterizes a biological resource, the supply curve of a nonrenewable re-source will not move back to the right on its own, but only in responseto new investment, technological innovation, or discovery.

6. At some point, the supply curve of a particular exhaustible resource(e.g., oil) must move left, regardless of any innovations or investments,or else it is not actually an exhaustible resource.

7. The supply of exhaustible resources can be moved rightward by inno-vations that reveal previously ignored materials to be valuable non-renewable resources; this happened when petroleum was added to coalas a fossil fuel, and when uranium was added to fossil fuels as a sourceof energy. Yet we are on a finite planet, and so it seems reasonablethat there will come a time when there simply are no new types of non-renewable resources to discover. And perhaps well before that happens,we will reach a point where there are no new economically viable typesof non-renewable resources to discover. Which suggests that at somepoint the aggregate exhaustible resource supply curve must also moveleftward.

The actual evolution of resource supply curves is thus a complicated inter-play among capital, technology, and the history of harvest or extraction,summarized in figure 6.

(Figure 6 here)To better understand the role of resources in the macroeconomy, it is

important to note some stylized facts about the difference between renewableand nonrenewable sources. While renewable resources are, by definition,unlimited over time, their rate of flow is constrained. The quantity of solarenergy hitting the Earth in a year dwarfs the quantity of energy used byhumans, so it might seem that, in principle, this flow constraint shouldn’tbe a big deal. But harvesting or capturing solar-derived energy requiresphysical capital, and various pieces of evidence suggest that the combinationof capital costs and flow constraints has historically made renewable resourcesupply curves more difficult to move to the right than has been the case withexhaustible resources during the Industrial Revolution. Pomeranz ( [60, p.19]observes that prices of wood and fodder “generally rose throughout the earlymodern period.” In contrast, petroleum prices exhibited a strong downward


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trend from 1864 to 1970 (see [7]) and Barnett and Morse [3] document asimilar trend for a broader range of resources. And as Figure 7 illustrates,there’s a strong tendency for wealthier countries to have a larger share oftheir ecological footprint be from nonrenewable resources. (A weighted-least-squares regression of renewable share on log GDP per capita and capacity ofbiologically productive land area per capita produces an adjusted r-squaredof 0.607 and the coefficient on log(GDP) is -0.144 with a t-statistic of -15.0.4)These observations suggest that nonrenewable energy sources tend to havelower capital costs per unit of energy made available, and that expanding theflow of fossil sources is easier than expanding the flow of renewables—whilesupplies last . . . .

(Figure 7 here)This vision of resource supply is unusual, even in macroeconomic models

that do incorporate resources. For example, Natal [57] describes oil prices assubject to shocks in an AR(1) process with ρ0 = 0.95, but the shocks them-selves appear to be strictly exogenous. There is no co-evolution of supplyand demand shaping prices over time, with plausibly exogenous shocks suchas the 1973 oil embargo laid on top of that structure.

Aghion et al. [1] implicitly assume, but do not address, the realism of hav-ing “clean” (i.e., non-fossil) resources replace fossil resources at the scale atwhich we currently use fossil fuels. In fact, it does not appear that provisionof the “clean” resource is subject to any sort of environmental constraint:“The two inputs, Yc and Yd [the “clean” and “dirty” inputs to production,respectively], are produced using labor and a continuum of sector-specificmachines (intermediates), and the production of Yd may also use a naturalexhaustible resource.” [1, p. 5] And the extraction cost of the nonrenew-able resource is specified as a non-increasing function of the remaining stock,thus omitting any role for discovery, investment, and innovation as describedhere. Lastly, their user cost is in some cases determined by an application ofthe Hotelling rule, whereas the model in this paper leaves the Hotelling ruleaside; it is an important insight and an elegant construct, but when lookingat the economy as a whole it seems to be of limited applicability.

4The footprint data are from [28] and the GDP data are from the UNDP’s WorldDevelopment Report.


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5.2 Revised long run

We’re now ready to revise the production function, incorporating the resourcesupply curve and the role of resources in production. Resources can be in-cluded in the production function in an obvious way, as an additional itemin the Cobb-Douglas production function (note that the “technology” pa-rameter A has been changed to A, for reasons that will be explained furtheron):

Y = Kα(AN)δRγ . (4)

But since R = ρN , we can rewrite equation 4 as

Y = Kα(AN)δ(ρN)γ. (5)

As in the conventional model, labor demand Nd is derived from themarginal product of labor, but output is no longer a function of K andA, but is instead a function of K, A, and ρ, so labor demand is a functionof those same arguments. As before, increased K or A both lead to highermarginal product of labor, but now an increase in ρ has the same effect—technology and capital that allow a single worker to control a greater flow ofresources have the effect of making that worker more productive.

This change from (A) to (A and ρ) reflects the historical reality of tech-nological change, because while some innovation has been in the form of anabstract, almost Platonic, learning how to do things “better,” a large por-tion has been learning how to make use of more resources than before. Fromthe harnessing of fire and the domestication of animals through the develop-ment of nuclear power, much of our getting cleverer has been getting clevererspecifically at applying more exosomatic energy, so as to make the most ofour tightly limited supplies of endosomatic energy. (See the discussion inHall and Klitgaard [35].)

Equilibrium is no longer a matter merely of labor demand and laborsupply, since hiring a unit of labor now also means buying the resources thatlabor must have it its disposal in order to realize the productivity promisedby the labor demand curve. This cost depends on ρ which, by assumption,is fixed in the short run, but also on PR, which depends on the quantityactually bought. Fortunately, we have the resource supply curve Rs, and soany given quantity of labor Ni can be converted into a quantity of resources


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Ri = ρNi, and the resource curve will then turn that resource quantity Ri

into a resource price PRi .

Now a quantity of labor Ni combines with the labor supply curve to tellus a wage wi that has to be paid in order to obtain Ni. And that sameNi combines with ρ and the resource supply curve to tell us the quantity ofresources that must be bought per worker (ρ) and the price at which thoseresources can be bought (PR

i ). In other words, we know the marginal wagecost of employing another unit of labor (wi), and the marginal resource costof buying the resources needed to make that labor productive (ρPR

i ).We can add this new information about resource costs into the labor-

supply diagram. The labor supply curve N s translates any quantity of laborNi into wi, the marginal wage implied by Ni. And if you go above that pointby the amount ρPR

i , you have the full marginal cost of employing anotherunit of labor. If you choose many different values of Ni, this series of pointswi + ρPR

i traces out a second curve, lying above the original N s, separatedby the space ρPR

i . We can think of this curve as the “resource-augmentedlabor supply curve,” denoted (N + R)s. As we move to the right, to higherlevels of N and thus higher levels of R, the resource price should increase,causing the space between N s and (N +R)s to increase, though if resourcesare abundant, PR will stay low and the space between the two curves mightnot change appreciably.

We can now determine equilibrium in this modified long-run model. As inthe conventional model, the labor demand curve reflects the marginal productof labor, but the new resource-augmented labor supply curve reflects the fullmarginal cost of employing another unit of labor, including the cost of theaccompanying resources. So equilibrium is determined by the intersection oflabor demand with resource-augmented labor supply (N + R)s, rather thanwith the simple labor supply N s. This intersection determines both N∗ andw∗ + ρ(PR)

∗, and the height of N s at N∗ determines w∗. This is illustratedin Figure 8.5

(Figure 8 here)

5This approach is reminiscent of Natal’s statement that “Changes in oil prices act as adistortionary tax on labor income and amplify the monetary policy trade-off,” [57, p. 4]except that the comparison to a “distortionary” tax is unfortunate. Energy costs aren’t adistortion of an otherwise “natural” economic outcome. They’re real costs, just as real aslabor, and economic agents develop and choose capital that commits them to those costsbecause they expect the benefits to justify the decision.


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5.3 Technology paths

In the standard model, technology is captured by the single variable A, whilein the resource-inclusive model, technology has been split into two compo-nents, A and ρ. The term ρ is the resource-intensity of labor, but thatintensity is shaped by the technology embodied in the capital being used.Increases in A and ρ both increase what labor can accomplish, but with verydifferent implications for resources. The factor ρ does its job specifically byincreasing the amount of resources used, whereas A has its effect withoutdirectly increasing the use of any other factor of production. In other words,A is the efficiency with which all inputs are turned into output, somethinglike total factor productivity.

In the conventional model growth in output per worker comes from in-creased capital and improved technology. In the resource-inclusive model, in-creased labor productivity arises from a more complicated interaction amongA, ρ, and resource supply. In general, technological change will involve si-multaneous changes in A and ρ. Any combination of changes that increasesAδργ will increase labor productivity and thus move labor demand to theright. But changes in A have no effect on the resource-augmented laborsupply curve—(N +R)s—whereas changes in ρ do have such effects.

For a given resource supply curve, a change in ρ also changes ρPR, thespace between simple labor supply N s and resource-augmented labor supply(N +R)s. Obviously the direct effect of an increase in ρ is to increase ρPR.But in addition, a higher ρ means that each labor quantity Ni corresponds toa larger resource quantity Ri = ρNi, and thus to a higher resource price PR

i .So this indirect effect further opens up the space between N s and (N + R)s

A decrease in ρ has the opposite direct and indirect effects.Figure 9 illustrates two different technological paths, one involving an

increase in A alone, from A0 to A1a, the other entailing a smaller increasefrom A0 to A1b along with an increase in ρ from ρ0 to ρ1, such that ρ0 ·A1a =ρ1 ·A1b. This equality implies that both technological paths involve the sameshift in labor demand, from Nd

0 to Nd1 . But the resulting equilibria are not

the same.We start with labor demand Nd

0 and resource-augmented labor supply(N + R)s0, and have employment N0, wage w0, and full marginal cost ofemployment w0+ ρ0P

R0 . In the case of a large increase in A with no increase

in ρ,6 (N + R)s will remain at (N + R)s0, with the resulting wage wA, full

6And assuming for simplicity no change in resource supply Rs


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marginal cost of employment wA+ρ0PRA , and employment level NA. When ρ

does increase from ρ0 to ρ1, the resource-augmented labor supply curve willinstead move to (N + R)sρ, with lower wage wρ, higher full marginal cost ofemployment wρ + ρ1P

Rρ , and lower employment level Nρ.

(Figure 9 here)This has implications for useful growth strategies. If Rs is fixed, then

increased labor productivity from higher values of ρ must eventually becomeself-defeating. Since the resource supply curve asymptotically approaches afinite value, continual increases in ρ must eventually bring about a situationwith an extremely high PR; the equilibrium employment level will then beconstrained by the limited availability of the resources required by the highρ. As figure 9 suggests, when resources are not abundant, it may well bepossible in principle for a resource-intensive increase in labor productivity(i.e., an increase in ρ) to result in a decrease in wages and employmentrather than an increase. Of course, it seems unlikely that even semi -rationalagents would pursue such a path in that type of situation.

On the other hand, if Rs moves continually to the right along with theoverall growth of the economy, then higher labor productivity through higherρ is not self-defeating. The required quantity of R continually increases, butthe increased supply of it allows the price to stay low or even fall. The(N + R)s curve stays close to the N s curve, and the resource situation hasno pronounced effect on production.

Still, growth through increased ρ has this potential roadblock, and evenif resources are cheap, they’re not free. Given those realities, why wouldan economy pursue a high-ρ strategy rather than a path of high A? Beforeoffering a speculative answer to that question, let’s consider what has actuallyhappened. Early in the Industrial Revolution, energy use grew faster thanthe economy (see [60, p. 17]), but more recent behavior has been different.Energy use in the U.S. increased from 0.96 quadrillion Btus in 1825 to 75.68quadrillion Btus in 1973. Meanwhile, from 1820 to 1973 population grewfrom 9.6 million to 211.9 million, and real GDP grew from an estimated 12.5billion dolalrs to a level of 3,536.6 million.7 The share of the population

7GDP figures are from Angus Maddison, Contours of the World Economy, 12030 AD,via http://en.wikipedia.org/wiki/List of regions by past GDP (PPP), and are in1990 international dollars. Energy use is from Tables E.1 and 1.3 from Annual energyreview, October 2011, produced by the Energy Information Administration of the U.S.Department of Energy. Population before 1900 is from p. 25 of Historical statistics of theUnited States 1789-1945: a supplement to the Statistical Abstract of the United States, pub-


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in the labor force wasn’t constant over that period, but it didn’t go up byenough to alter the conclusion that energy use has risen faster than not onlypopulation but also than the labor force—in other words, ρ has increasedover that span. At the same time, the increase in energy use per capita wasless than the increase in GDP per capita, which means that A must also haveincreased.

Looking at the period since 1949 when the data are more reliable (seefigure 10), we can see a relatively smooth trend of increasing ρ through 1973,decreasing ρ from there until 1986, then relatively stable resource intensityof labor through this last decade. The first period, when ρ was rising, cor-responded with a period of 3.2% annualized growth growth in labor produc-tivity; during the second period, when ρ fell, productivity growth averaged1.5%; and the final period has seen a productivity growth rate of 2.0%. Whilethere are obviously other factors at work in productivity growth, the dataare consistent with a relatively constant growth of A, with the differing ratesof productivity growth being driven by the changing behavior of ρ.

(Figure 10 here)So the U.S. experience suggests that technological progress has generally

been characterized by increases in both A and ρ. There was a dramaticreversal in ρ, corresponding to a period of historically high energy prices—atthe time, the highest that had been seen in a century. Even this temperingof the growth of ρ hasn’t undone the vast majority of the increase over thecourse of the Industrial Revolution. An examination of CO2 emissions datafor various countries suggests similar experience in them as well.

So it seems broadly true that economies grow by increasing both A andρ, rather than the seemingly “efficient” path of increasing A alone, or evendecreasing ρ and compensating with a still larger increase of A. This raisesthe question of why economies seem to follow this path. The simplest expla-nation is that increases in A are harder to come by than increases in ρ. Itwould follow that, during times when it’s relatively easy to increase resourcesupplies, innovations that increase ρ will tend to have an edge over thosethat focus only on increasing A.

lished by the Census Bureau, available at http://www2.census.gov/prod2/statcomp/

documents/HistoricalStatisticsoftheUnitedStates1789-1945.pdf. Populationfrom 1900 to 1973 is from “Historical National Population Estimates: July 1, 1900to July 1, 1999,” http://www.census.gov/popest/data/national/totals/pre-1980/

tables/popclockest.txt. Population for 2003 is from “Vintage 2009: National tables” athttp://www.census.gov/popest/data/historical/2000s/vintage 2009/index.html.


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In the terms of this model, the more a technological path reduces ρ, the“greener” it is. And the more it combines that with an overcompensatingincrease in A, the more it can be described as a path of “green growth”. It’san unresolved empirical matter whether a green growth path can exist on awidespread scale and over an extended period of time. However, in light of thestrong historical relationship between economic growth and increased energyuse, such as is documented by [8], there is cause for skepticism about theprospects for long-term continued “dematerialization” of the global economy.

Note the difference from the treatment of technology by Aghion et al. [1].Instead of dividing technology into something like total factor productivityand resource intensity of labor, that model distinguishes between Ac,t andAd,t, the efficacy with which the economy uses labor and capital (and, in thecase of the “dirty” input, exhaustible resources) to produce the two inputsto production. The fundamental limit, then, on producing the “clean” inputis merely past innovative effort directed at such production. The authorsare confident that sufficient effort of this type going forward will allow us tocontinue our past growth experience with no more than a transitional periodof slower growth—and they argue that the transition will be shorter andshallower the sooner we shift our effort to clean technology.

5.4 Response to resource constraints

We’ve discussed what happens over the course of historically “normal” growth,withA, ρ, andRs all increasing, but the resource-inclusive model really comesinto its own when you consider a contraction of the resource supply, a sit-uation where the resource constraint on the economy becomes significantlymore binding.

For any given quantity of N and value of ρ, this means that PR will begreater than when resources are abundant; the resource supply curve mayeven have its asymptote within the range to which N could possibly drive it.If we denote the original resource-augmented labor supply curve as (N+R)s1,this implies that the new curve (N +R)s2 must lie above (N +R)s1 and maywell approach its asymptote well to the left of where (N + R)s1 does so. Asillustrated in Figure 11, this should have the effect, all else being equal, ofdriving down the level of employment and the real wage, while increasing theresource-inclusive cost of employing people.

Remember from section 3.2 that long-run equilibrium in the labor marketindicates “full employment,” which in turn points to potential output. So if


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full employment has been reduced by a leftward shift of resource supply, thena tightened resource constraint leads to a lower level of potential output, alower real wage, and a higher natural rate of unemployment. These effectsare at the core of the implications that the resource-inclusive approach hasfor understanding the short-run behavior of the economy. (Note the commentin [63, p. 550]: “The observed effects of oil shocks are even more puzzlingwhen the effects on real wages are considered as well. In standard growthmodels, the predicted contraction of the supply of output is greater the lessreal wages fall in response to the shock, and is greatest if real wages actuallyincrease (perhaps because the product wage rises relative to the consumptionwage).” The emphasis on the efficiency wage in [9] suggests a similar story.In other words, the output decline in these models is coming in large partfrom a flavor of “sticky wages,” or even “perverse” wages, that go up in theface of adversity. In contrast, with the model in this paper, resource supplyconstraints lead directly both to lower output and to lower wages.)

(Figure 11 here)

5.5 The short run in the resource-inclusive model

The short-run tools discussed in section 3.2 are all anchored around either po-tential output or the natural rate of unemployment and the level of expectedinflation. Since declining resource availability reduces potential output andincreases the natural rate of unemployment (as explained in section 5.4, itwill also have effects in the short run, with implications both for how policyshould be carried and for the efficacy of any policy responses that are actuallyadopted.

In the IS-LM framework, the goal of good policy in the mainstream con-ception is to keep actual output close to potential output. If the output gapis negative (actual output below potential), policy makers in principle wantto move either the IS curve or the LM curve to the right, unless they judgethat autonomous forces in the economy are about to do one of those thingson their own.

But the usual calculations of potential output don’t take into accountresource availability and so are unaffected by resource shortages. In the af-termath of the recent (current) energy price spike, the U.S. economy hasexperienced continued elevated unemployment, and the Bureau of EconomicAnalysis has revised downwards its estimate of Y ∗—including a small retroac-tive revision. The Congressional Budget Office now says that Y ∗ in 2008:Q3


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was 13,461.6, whereas in 2008 it was telling us that potential GDP for thatsame quarter was 13,568.4, so it has carried out a retroactive revision of -0.8%. But much larger revisions have been carried out following the financialmeltdown. In 2007, CBO projected that potential GDP in 2012:Q1 wouldbe 15,100.6, but when we got to 2012:Q1, it said that potential output forthat period was only 14,270.3, a revision of -5.5%8. But the reason givenfor this is hysterisis, the phenomenon by which extended absence from theworkplace makes someone less likely to get a new job for a long time, aneffect that wouldn’t kick in until around 2009. In contrast, the implicationof the resource-inclusive model would be that Y ∗ had been falling (and u∗

had been rising) already in the mid-2000s, and was particularly high in 2007and 2008 ahead of the bursting of the bubble.

This downward revision of potential output would solve something of apuzzle that otherwise exists. The growth of the mid-2000s and the collapseof 2008 had all the signs of a credit bubble expanding and then bursting(see, e.g., [32]). The essence of a credit bubble is that loans are made thatcannot be justified based on a realistic assessment of overall (future) abilityto produce output. Translating this into terms of potential output, a creditbubble should be marked by actual output rising significantly above potentialduring the bubble expansion, then falling back to potential, or below it ifcredit or autonomous expenditure has overreacted to the bursting of thebubble. But that’s not what we see based on current methods of estimatingpotential GDP. Using the CBO’s estimates from 2007, the output gap beforethe current recession peaked in 2006:Q1 at 0.6% of potential GDP, and evenwith the most recent revisions, from the beginning of 2012, the peak of theoutput gap was only 1.6%. By way of comparison, the far less damagingtech bubble of the late 1990s raised the output gap to 4.1% according tothe 2007 estimate of potential GDP, or 3.5% based on the 2012 estimate.Figure 12 illustrates these changes, with the estimates of potential GDPmade in 2007:Q1, 2008:Q3, and 2012:Q1.

(Figure 12 here)The implication for policy in the IS-LM framework is that, if you overesti-

mate potential GDP, you’ll be aiming at the wrong target. This is illustratedin figure 13a, where Y ∗

C is potential output as estimated in a conventionalmodel, while Y ∗

R is the potential output as calculated in the resource-inclusive

8Vintage potential GDP estimates are downloaded from http://alfred.stlouisfed.



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model. Under these circumstances, actual output YA looks just about rightcompared to Y ∗

C , but if we think potential output is better represented by Y ∗R,

we’re getting a signal that the economy is probably, in standard terminol-ogy, “overheating.” It’s harder to say whether the revisions have adequatelyaccounted for the return of oil prices to levels that, while not matching thehighs of 2008, are nonetheless four to five times the average for the 100 yearsfrom 1873 to 1973.

(Figure 13a here)This problem is recognized by Kozicki [48] and Gavin [26] but, as can be

seen in figure 12, the revisions to potential output have been most pronouncedin the aftermath of the financial crisis, as a result of continued observationsof low output and high unemployment, rather than preceding the crisis andincorporating a recognition of the role of resources in economic output.

While figure 13a shows how a bubble can be perceived as perfect macroe-conomic management, figure 13b illustrates a post-bubble situation, whereagain resource constraints are binding. Potential output level Y ∗

C1 shows po-tential output as originally estimated, while Y ∗

C2 is the conventional estimate,now revised down because of an observed pattern of low output and highunemployment. Y ∗

R is potential output according to the resource-inclusivemodel, which could in principle be higher or lower than Y ∗

C2, depending onhow serious the resource constraint was and how large had been the revisionin the conventional approach; as shown here, Y ∗

R < Y ∗C2. Of course, the IS and

LM curves will be affected by the bursting of the bubble. Diminished expec-tations may push down autonomous consumption and investment, shiftingthe IS curve to the left; the same factors may increase demand for liquidity,pushing the LM curve to the left as well. So the economy may very well bein the general area of potential output, but if policy-makers are working withthe wrong conception of potential output, they would think it was seriouslyunder-performing.9

In the AS-AD model, the resource constraint shifts the AS curve to theleft from ASC to ASR and causes it to bend upward sooner (see figure 14; thehigh resource prices may also shift AD leftward from AD1 to AD2, throughsome combination of damage to the financial system and reduced willingnessto spend on non-resource purchases). Efforts to move the AD curve to the

9There is some similarity here to Natal’s criticism of welfare-based optimal policies onthe grounds that “they rely on unobservables such as the efficient level of output or variousshadow prices.“ [57, p. 5, emphasis added]


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right and thus increase expenditure will have a harder time than before ac-tually eliciting output, for a combination of reasons: the resources neededfor increased output are harder to come by, and to the extent that economicagents are aware of and spooked by the resource constraint, they will be re-luctant to take the risk of ramping up. If policymakers have an overestimateof Y ∗, they will be tempted to adopt stimulative policies,10 and then will besurprised at how little of the stimulus was converted into increased outputand how much of it ended up as higher inflation.

(Figure 14 here)The Phillips curve mainly extends our understanding in terms of expecta-

tions. The tightened resource constraint reflected in Figure 11 will, in itself,increase the natural rate of unemployment u∗, and thus shift the Phillipscurve to the right, in the direction of less desirable inflation-unemploymenttradeoffs. But there is also the possibility that people will react to the higherresource prices by stepping up their expectations of inflation, thus shiftingthe Phillips curve up as well, further into undesirable territory. Figure 15shows this, with the natural rate of unemployment rising from u∗

C to u∗R and

expected inflation rising from πeC to πe

R. The Phillips curve thus moves fromPCC to PCR, and even without a drop in demand (that is, a rightward shiftin the MPRF), unemployment will rise from u1 to u2. (Inflation will rise aswell, but these levels are omitted in figure 15 so as to avoid clutter.) Thisoutcome is reminiscent of the effect identified by [31], who includes changesin oil prices as being among the supply shocks that can move the Phillipscurve toward either more or less favorable employment-inflation tradeoffs,with the difference that he doesn’t tie this to a role of resources in produc-tion. Rather, the supply-shock effect is explained through the combinationof many markets having sticky prices while oil is traded in auction marketsthat clear with flexible prices.

(Figure 15 here)

6 Policy continuity and divergence

In some respects, the resource-inclusive macro model proposed in this paperprovide significantly different policy guidance than does the conventionalneoclassical synthesis. But if you consider the matter from a slightly more

10Or not, depending on the political environment . . .


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abstract perspective, the guidance is actually quite similar, while the detailsof that guidance have changed.

Regarding the long run, the standard model says growth comes from bet-ter technology and increased (physical and human) capital—in other words,larger values of K and A. The resource-inclusive model says that growthcomes from increases in K, A, and ρ, together with increases in resource sup-ply Rs, and that when Rs can’t be expanded, it count be counter-productiveto increase ρ.

These differences are unintentionally highlighted by Solow in [68], whocautions against equating conservation with sustainability. He makes thecommon assumptions that capital can substitute for resources and that con-servation implies diminished output in the present. It then follows that ifconservation means less consumption in the present, there might be somepoint to it, but if the reduced output means less investment, then it is coun-terproductive, by leading to less capital in the future, when in fact morewill be needed if our descendants are to live at least as well as us, evenwith limited resources. Further, Solow expects the future to be significantlyricher than the present, just as our wealth dwarfs that of our grandparents,so that diminishing present consumption for the supposed benefit of futuregenerations becomes a questionable choice.

All of this follows in a straightforward manner from the standard modelwhere Y = Kα(AN)β and resources are included only on an ad hoc basis. Butin the revised model, different investments can have very different effects, andthe only allow growth with shrinking resources if they lead to declining valuesof ρ combined with significant increases in A. As discussed in section 5.3, apath with those characteristics may not actually exist, and if that’s true, thenfuture prosperity will be far more dependent on resource supplies than wouldbe suggested by standard models. In that case, the best thing we can do forthe future is conservation, in order to bequeath a larger Rs than otherwise,as well as encouraging investment and innovation aimed at reducing ρ asmuch as is reasonably possible.

So on the surface, the resource-inclusive model points in a very differentdirection from the conventional one. Yet if we take a slightly more abstractlook, the lesson of both models is that, in the long run, demand-side man-agement is irrelevant—good policy aims at encouraging favorable conditionsof future production. All that changes in going from the conventional modelto one with resources is what constitutes favorable conditions for future pro-duction.


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With the short-term tools there’s a clear difference between the models inthat the resource-inclusive one tells you to be more cautious about stimulativepolicy, because potential output may be lower (natural unemployment maybe higher) than you estimate based on the conventional model. So there canbe cases where a conventional analysis would tell you to adopt stimulativepolicies while the resource model says no. But again, at a more abstract level,the advice is the same: try to keep the economy close to potential output.The only difference is in where potential output is thought to be.

As mentioned in section 5.3, Aghion et al. [1] prescribe a policy of movingthe economy away from “dirty” inputs toward “clean” ones and argue that,after a period of slower growth than usual, the economy will return to thegrowth path to which we’ve grown accustomed. If we combine the observa-tions of sections 5.4 and 5.5 and the possibility that conservation is mean-ingful, despite Solow’s warning above, we get similar advice in one regard.That is, the model suggests that when we face binding resource constraints,we should accept lower GDP in the near term than would be possible, inorder to improve our future prospects. But the model here provides a wayof understanding why “improved future prospects” might mean “less loss ofGDP than otherwise,” rather than, “GDP growth as rapid as we’re used to.”

7 Resources and economic history

One of the basic issues in economic history is how and why the IndustrialRevolution came about, and why it happened first in Europe, leading to theglobal dominance of Europe and the “neo-Europes” populated largely by self-governing European settlers. As discussed briefly in section 2, one positionemphasizes the role of resources, e.g., [61], who portrays a pre-modern worldin which China is ahead of Europe, with Europe able to catch up and thenfar surpass China because of the resource windfall represented by its colonialcontrol of the transatlantic world. Several reviewers dispute the importancethat Pomeranz attributes to resources, for example Deng [19], who pointsout that China came into a serious resource windfall with the acquisition ofManchuria, but that it didn’t do as good a job exploiting resources as Europedid. At the same time, Deng undercuts his argument by citing an earlierresearcher “who recognized the importance of the unprecedented endowmentgains from the New World.” [19, p. F492] If Europe’s endowment gains were“unprecedented,” couldn’t that uniqueness have contributed to the difference


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in outcomes between Europe and China?Jones’s response to Pomeranz (see [45]) is more adamant in his down-

playing of the role of resources, for instance:

In this account both cores were coming under ecological stress be-cause preindustrial techniques of land use were damaging and in-capable of much further intensification. Then, suddenly, Europehappened upon fresh resources. Pomeranz admits that Europehad not actually banged up against limits, but endlessly impliesthat Europeans would have been unable to transcend them oncethey were reached. This tends to disarm anyone who dissentsfrom his pessimism about European land-use practices. [45, p.856]

Overall, Jones in [45] makes an excellent case that resource availabilitywas not a sufficient condition for growth, but he’s much less convincing in hisdismissal of their role as a necessary condition. He writes, “Once new energyand raw-material windfalls could be exploited, Europeans would have beenfoolish to forego them. But this does not mean that they had reached the endof their own ecological road.” [45, p. 857]. True, it doesn’t mean that in 1800they were already faced with tightly binding resource constraints. But couldthey have gotten to where they were by 1900 without those outside supplies?It’s plausible that they never reached the end of their own ecological roadbecause they found for themselves a turn-off before reaching that end.

Jones continues: “And supposing Europe had depended on external re-sources for which there were no substitutes, its advantage lay in buildingcumulative means for exploiting them. How anomalous that Europeans,portrayed as too uncreative to tackle resource scarcities, so quickly foundthe technology and organization to work deep coalmines and suck food, fiberand timber out of the New World.” [45, p. 858]. But note how they tackledresource scarcities: not by developing on the small resource base availableto them, but by figuring out how to obtain more resources, whether fromthe ground beneath their feet or the conquered and settled lands across theocean. It’s not exactly a demonstration of how resources were not crucial toEuropean development.

The growth in European energy use from coal during the 19th century wasstupendous, leading to levels that dwarfed what had been used previouslyfrom other sources, and far outstripping what was available from water power.


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This undercuts another claim Jones makes: “We do not know, by the way,what might have been possible on the basis of water power; there is room fora Fogelian counter-factual exercise here.” [45, p. 858]

But consider the example of Japan. If Jones’s counterfactual were plau-sible, then we might expect Japan of all places to have followed it. Itsendowment in the resources of the industrial age is almost zero, and so ifanyone were to have an incentive to develop through technology alone, theywould be it. Yet they instead followed in Europe’s footsteps, developing onthe basis of resources it didn’t have at home. Why did it invest so much inmilitary control of resources and ultimately roll the dice on a military strat-egy built on an irreconcilable internal contradiction? Did it do that out ofan uncreative following of Europe and America’s lead? Or did it take thatpath because those resources, in per capita quantities that Europe couldn’thave mustered at home, are necessary to what we think of as development?

The nature of a Fogelian counter-factual is that you’re comparing theactual economy to what you imagine might have happened in the absenceof some development of interest. So in some sense anything goes. But ifsomeone wants to claim that a many-fold increase in energy use was of noparticular economic importance, the burden of proof should really be onthem.

While Jones in [45] seems determined to minimize the role of resourcesin Europe’s takeoff, elsewhere (in [44], speaking of the Discoveries and theprocess of bringing most of the rest of the world under Europe’s control) heoffers evidence for their importance, and in fact provides the key for thinkingabout their role.

An unparalleled share of the earth’s biological resources was ac-quired for this one culture, on a scale that was unprecedentedand is unrepeatable. . . .

The Discoveries were the first positive economic shock, or stimu-lant in Leibenstein’s (1957) terminology, of a magnitude capableof promoting system-wide growth.

The ‘general advantages which, considered as a great country,Europe has derived’, to use Adam Smith’s (1884:243) conceptu-alization, were staggering. The average area of land available percapita in western Europe in 1500 had been 24 acres, and the Dis-coveries raised this to 148 acres per capita a six-fold gain. Full


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utilization of the resource potential was deferred, partly by theseductions of precious metal. But even in the preindustrial pe-riod the ’fall-out’ of raw materials and the capital investment andtechnology generated to exploit them was a boost to the devel-opment impulses already being released by the growth of tradewithin Europe’s borders. Commodities came in that could neverhave been produced at home at anything less than an infinite cost.A range of climates was effectively coupled to Europe’s own. [44,p. 82]

This perspective helps explain the data presented by deLong ( [17]), whomarvels at the change in growth rates, from 0.01% per year from 8000 B.C.E.to the beginning of the common era; 0.02% annual growth from then until1500 C.E., 0.09% from 1500 to 1800, 0.89% during the 19th century, and2% from 1900 to 2007. His description of the escape from the MalthusianEra (before 1500) is that it was: selective at first; involved a demographictransition; and resulted from invention and innovation. Similarly at [16] heshows a “Malthusian” relationship between English population and wagesfrom the 1250s to the 1640s, with population and wages transiting up anddown a negatively sloped line of inverse relationship; after the 1640s, the datapoints move off that line, first with higher wages unaccompanied by lowerpopulation, then with increasing population without falling wages, and finallyduring the 19th century wages and population rising together.

DeLong observes, “Something happened to change the pace of innovation;Something happened to change the dynamics of population growth.” Not allof his commenters overlook the possibility that the observed relationshipsmight have something to do with stagnant energy and resource use in theearlier period, turning to rapidly growing resource use in the latter. Particu-larly in the case of the acceleration of global growth, the periodization withresources is remarkably tight. The early modern period (1500-1800) coin-cides with when the Discoveries put the resources of much of the world atthe disposal of one particular segment of the world’s population, enabling itto invent and invest in the technologies that would allow it to grow, and even-tually to spread those to other parts of the world. The 19th century alignswith the age of oil and a bigger increase in the use of resources, while the20th century is the age of oil, bringing a still bigger increase in resource use.This is all consistent with Jones’s statement cited above, that “The Discov-eries were the first positive economic shock, or stimulant . . . of a magnitude


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capable of promoting system-wide growth.”This passage also helps in the reinterpretation of the focus on technology

found in Mokyr [55], for whom resource play something of an “also ran” role:“Intellectual factors never operate alone; institutional change was equallynecessary. The importance of property rights, incentives, factor markets,natural resources, law and order, market integration, and many other eco-nomic elements is not in question. But without an understanding of thechanges in attitudes and beliefs of the key players in the growth of usefulknowledge, the technological elements will remain inside a black box.” [55,p. 327].

Resource availability can offer a potential answer to an issue that Mokyrleaves vague:

Pre-1750 economic growth created the economic surpluses thatmade it possible for a considerable number of people to moveto urban areas and nonagricultural occupations, including bybecoming full-time intellectuals. Yet despite the stimuli of theGreat Discoveries and the technical advances of the fifteenth cen-tury, Renaissance Europe did not generate anything like moderngrowth. Many highly commercial societies of the past, for onereason or another, failed to switch from trade-based growth totechnology-based growth. Even the great Dutch prosperity of theseventeenth century dissipated and petered out in the end. [55,p. 339] (emphasis added)

Growth episodes before the Industrial Revolution of the 18th century werelargely based on renewable resources.11 Even the windfall described by [44]above was not as powerful as the coal that would come to dominate in the 19th

century. And note that the Dutch prosperity of the seventeenth century alsopetered out as they lost control of their most readily accessible resource-richcolony in New Amsterdam.

11De Decker in [15] makes this statement more precise: while stating that a story of aprogression from renewables to fossil fuel is “basically correct,” he also observes that “Ourromantic image of the Middle Ages and Renaissance as a paradise of renewable technologiesresults largely because of our failure to distinguish between thermal and kinetic energy.”The breakthrough of the steam engine was needed for fossil fuel to be a source of kineticenergy, but it was already important as a source of heat. “Almost all of the leadingeconomies in Western Europe during the last millenium relied on a large-scale use of fossilfuels such as peat and coal.”


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Mokyr has his candidate for that “one reason or another” that the growthwave of the Industrial Revolution didn’t peter out like the earlier ones:

The short answer as to why the West is so much richer todaythan it was two centuries ago is that collectively, these societies“know” more. This does not necessarily mean that each individ-ual on average knows more than his or her great-great grandpar-ent (although that is almost certainly the case given the increasedinvestment in human capital), but that the social knowledge, de-fined as the union of all pieces of individual knowledge, has ex-panded. [55, p. 287]

There’s nothing wrong with this in itself, but it’s worth reiterating thata large piece of what we “know” is how to use resources, and a large portionof innovation has been the development of new ways to use resources, i.e.,the ρ of this paper’s model, as opposed to its A. So while the resourceswould be of little avail without the innovation, the innovation and knowl-edge themselves wouldn’t get us very far without the resources. Thus it ishard to agree with Mokyr’s next statement: “The effective deployment ofthat knowledge, scientific or otherwise, in the service of production is theprimary—if not the only—cause for the rapid growth of Western economiesin the past centuries.” [55, p. 287]

This risks degenerating into a semantic argument. If the knowledge isabout how to access and utilize resources, then is it the resources or theknowledge which is the cause of growth? Perhaps it’s best to look at knowl-edge and natural resources as two necessary conditions, rather than lookingat either one as a sufficient condition.

But they are not merely two necessary conditions, for innovation, invest-ment, and potential resource availability are tightly intertwined. If you thinkabout the motive for investment and innovation, the model in this papersuggests a possible resolution of the dispute in economic history between theproponents of resource-based explanations and those who point to innova-tion, investment, institutions, or other more “social” factors.

It’s true that resources on their own make nobody rich. The vast coal andoil reserves of North America were here for 10,000 years without providingany benefit to the Native Americans, and that uselessness continued for a fewcenturies more, although now it was the European settlers to whom they wereof no use. These resources only became useful once innovations occurred that


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showed people how to apply them, and investments were made in the capitalthat allowed people to actually extract and use them. Even the agriculturalwealth of the prairies waited on innovation and investment. The grasslandsdid support vast herds of buffalo, which the natives turned to good use. Butthe much more profitable exploitation of the fabulously rich soil beneaththe grass was only possible with the invention—and mass manufacture—ofthe steel plow to break the sod, and this commercial exploitation was greatlyabetted by the extension of the railroads—more innovation and investment—out across the land.

So investment and innovation have certainly been crucial to developmentand growth—the North American example can easily be replicated. But thesesocial factors do not act independently of potential resources. The ploughand the railroad made the soil profitable, but these investments themselveswould not have been nearly as profitable without the rich soil being there inthe first place.

A parable can help illuminate the effect of an abundant stock of resourceson innovation and investment. A small stream will never repay the invest-ment in a large waterwheel. Innovation might allow the neighbors to makebetter use of the little flow there is, but only to a point. Even if the streamis utilized to the theoretical maximum of its potential, it still won’t providevery much power. In contrast, a large river richly rewards even a small in-vestment in a run-of-river water wheel. And if you make the same innovationthat might have allowed you to squeeze a few hundred watts of extra powerout of the small stream and apply it instead on the large river, the result isthousands and thousands of watts of additional power. The same comparisonholds for the investments which implement the innovation.

And while one may argue that people dependent on such meagre resourceshave all the more motivation to innovate and invest so as to make the verybest use of what they have, it’s also true that innovations and (particularly)investments have real costs, and that if those costs are not justified by the re-sults, the innovation and investment are less likely to occur. In the extreme,“unwise” investment is self-limiting, even without a competitive market, asthe unrecouped costs are a continuing burden to those who incurred them.So it is reasonable to suppose that abundant potential resources encourageprogress by rewarding it handsomely, whereas a situation that makes it dif-ficult to convert investment into, say, useful power will tend to elicit lessinvestment and innovation rather than more.

A as power goes, so go other pieces in the chain of development. The


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essence of the automation at the core of the Industrial Revolution was achange in the role of human labor. Before, people provided both the controlof the process and the motive power to make it work, running spinningwheels with their feet, running looms with their feet and their arms. Afterautomation, humans retained their role in control of the machinery (thoughat a higher and higher level as automation progressed), but the movementof the machinery and of the material through the machinery was driven byoutside power sources, first water wheels, then steam engines. So withoutaccess to power—both the underlying resource of falling water or availablecoal, and the innovation and investment to make it a currently availablesource of power—there would be little economic benefit to automation andthus little incentive to innovate and invest in that direction.

Prairie soils, forests, rivers, coal, oil: Everywhere we turn, we find an-other variation on the same tune. Innovation and investment are neededto make resources more economically useful, but that same innovation andinvestment—on the scale that is the mark of the modern world, and particu-larly of the Industrial Revolution—happen because the potential resources arethere. Take away those potentially available resources, and Europe’s scientificrevolution would simply not have produced modern economic growth.12

8 Extensions and implications

There are three core ideas presented in this work:

1. Complementarity between labor and resource use, defined by technol-ogy and capital—evolving over time so that, in effect, new capital can

12It may be worth distinguishing one very small set of innovations from the rest, with thesmall set consisting of those that made us aware that a particular thing was a resource,while the larger set is made up of advances that improved a type of use or made itfeasible under new circumstances. Coal’s potential as a source of thermal energy hadlong been known (though its dirty qualities had also limited its demand), but it wasn’tan energy resource for the ferrous metals industry until a series of innovations in 18th-century England (see Harris [40]). Subsequent innovations made it a better resource, butdidn’t unlock a new resource. On the other hand, even as coal was becoming establishedin the iron industry, it still wasn’t a source of kinetic energy until the invention of thesteam engine. Once that breakthrough was made, further innovations brought increasedefficiency that made steam engines affordable in more uses, and they brought reductions inweight together with increases in power that made them practical first for ships and thenfor railroad locomotives (see Smil [66]). But these innovations were new applications of aknown resource (coal for kinetic energy), not innovations that made coal into a resource.


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lead to long-run substitution between labor and resources, but withonly limited substitution possible in the short run.

2. Supply curves of resources currently available, which shift right withinvestment, innovation, and discovery or conquest, but shift left withextraction or high levels of harvest.

3. Economic outcomes determined by the interaction among resource sup-ply, labor supply, and labor productivity, with that productivity beingdetermined in part by the ability of labor to apply resources.

These have been attached here to the models at the core of the neo-classical synthesis, in part to maximize the compatibility with the approachmost commonly found in textbooks, but they can be incorporated into otherperspectives as well.

The school of Modern Monetary Theory (e.g., Wray [75]) presents an in-teresting alternative to the standard textbook understanding of what moneyis and how monetary policy works to shape aggregate demand. LikewiseKeen [46] (cited in section 1) argues for a rejection of the entire IS-LM frame-work in favor of a model built around the role of money creation and debtIt would be useful to explore ways of connecting these perspectives with aresource-based view of how value is created to pay off credit and how boththe reality of and expectations about that process are affected by changes inresource supply and the technology of resource use in the economy. In Keen’sterms [46, p. 157], debt “finances the expansion of economic activity via in-novation and investment, but it can also cause asset bubbles and eventually,an economic crisis if too much of this debt is directed to Ponzi Finance.”The model in this paper has implications for readily debt actually can leadto economic expansion, and increased difficulty in achieving that expansionmay thus mean that a greater share of debt it, by default, getting funneledinto Ponzi Finance.

In a different direction, more can be done with the differences between thebehavior of renewable and non-renewable resources described in section 5.1.Aggregate resource R can be divided into exhaustible resources E and re-newable resources B.13 Then in addition to A and ρ, a stock of capital and

13The choice of B reflects that many renewable resources, such as fish or biofuels, arebased in biological systems, and this influences their behavior. Obviously things such ashydroelectricity and wind power don’t fit that description, and would could in principle


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the technology embedded in it can be said to also determine ϵ, the share ofresources that comes from exhaustible resources. Then

ρN = R = E +B = ϵρN + (1− ϵ)ρN. (6)

We can now add a detail to the description of the Industrial Revolution,which is that ϵ increased from near zero to about 0.9. For reasons discussedin section 5.1, it is often easier to expand the supply of non-renewables thanof renewables, so that a shift to a greater ϵ will enable an economy to growfaster by allowing it to use a type of resource with a more quickly increasingsupply. Adaptation to dwindling fossil-fuel stocks, or policy to reduce climateimpacts from fossil-fuel consumption, also have an additional dimension, notonly an effort to reduce ρ, but the possibility of reducing ϵ as well, so longas the resulting demand for renewables doesn’t cause unacceptable damageto ecosystems.

Changing direction again, section 5.5 lays out the logic by which thismodel cautions against stimulative monetary or fiscal policies when resourceconstraints are binding. On a superficial level, this sounds like the “struc-tural” arguments promoted by freshwater economists, saying that macroeco-nomic policy is useless in our current recession, but there are two fundamentaldifferences. First, as expounded by, e.g., Lucas [53], the freshwater positionis a rejection of the mechanisms of Keynesian economics: new spendingby the government cannot logically lead to more economic activity, becausethe $100,000 spent by the government on a bridge had to be taxed or bor-rowed away from someone, and that other person would have spent the same$100,000 on some other purpose. The model in this paper makes no suchclaim. It is fully compatible with views on the role of money and spendingin Modern Monetary Theory, the debt-based approach of Steve Keen, otherpost-Keynesian models, or the work of Keynes himself.

Second, while there is a “structural” aspect to this model, it’s a very dif-ferent one from what we find in the freshwater canon. Freshwater economistsare likely to point to high taxes, excessive regulation, and technology shocksas the causes of our current stagnation, and the policy prescription is there-fore to reduce taxes (and government expenditure), reduce regulation, getgovernment out of the way, and wait for the market to reallocate factors ofproduction and return to equilibrium, where we will once again witness a

create a third category for non-biological renewable resources, but for now I’ll limit thediscussion to only two categories.


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comfortable growth rate of around 3% per year and a “normal” unemploy-ment rate around 5%.

The model proposed here sees a different structural problem. It’s nottaxes, or regulation, or some generalized technology shock. Rather, it’s thata mismatch has developed between the technology embedded in our capitaland the resources available to make that capital profitable. Until that’s dealtwith, standard Keynesian or post-Keynesian prescriptions may well fall shortof expectations, but not for freshwater reasons. In this model, the structuralproblem could be dealt with by increasing resource supplies, but that hastwo complications. One is that it may not be possible, for reasons reviewedin section 5.1. The other is that even this model only indirectly takes intoaccount environmental damage, to the extent that it limits resource supplies(primarily biologically based renewable resources). Environmental damage isof course costly in its own right, and so if increased resource supply requireslarge increases in environmental damage, or enables the economy to extendits negative environmental impact, an increase in resource supplies may notbe desirable even if it is possible.

The other way to resolve the structural problem of resource constraintsis to reduce ρ, the resource intensity of labor. Since this is determined byevolved technology and capital, it is not a “quick fix.” It may well requiredirect investment by government, or taxation of the use of scarce resources orother regulatory measures designed to accelerate the move away from theiruse.

There is one point of commonality with the New Classical perspective,which is that wages may have to fall. In the long run, the productivity of laborrepresents an upper bound on wages, since people cannot in aggregate be paidmore than they produce. If resource costs rise, then the productivity of laborhas been effectively reduced and higher employment does, as the freshwatereconomists would have it, require lower wages. Even in the long run, wagesmay not be sustainable at current levels. When ρ is reduced, a sufficientlylarge increase inA will sustain labor productivity, but as discussed toward theend of section 5.3, such a tradeoff may not actually exist. With a sufficientlyconstrained resource, we may be better of with a low value of ρ than witha high one, even if A doesn’t fully compensate, but that doesn’t alter theimplication that future productivity—and thus future wages—will be lowerthan current wages. An economy facing resource constraints may be simplyunable to match the level of wealth that was common when resources wereavailable more cheaply. The question is how respond to that.


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In thinking about this, it is important to consider whether an economyhas a purpose, and if so, what that purpose is. If we analogize an economyto an ecosystem, then perhaps the one, just like the other, simply is. Butas human inhabitants of an economy, we are entitled to views about whatan economy should do. A useful construct in this context is the idea of the“core” economy as described in Goodwin et al. [29], the part of the economythat directly addresses human wants and needs. If resource supplies cannotor should not be greatly expanded, and if there isn’t a technologically feasiblepath to continue increasing labor productivity while reducing resource use,then the standard macroeconomic goal of continual GDP growth may verywell be out of reach. However, that does not mean that improvements inthe functioning of the “core” economy are impossible. We have left suchimprovement to happen as an assumed automatic byproduct of increasingGDP per capita. Above a basic level of economic wealth, this connectionhas long been suspect, suggesting more explicit attention to the core. IfGDP growth is now ramping down, such explicit attention becomes all themore important, so that the social response to economic degrowth doesn’tdevastate the core.

9 Conclusion

In 2009, when the security of the global financial system was still a dailyworry, Blanchard [5, p. 210] wrote that, “The state of macro is good.” Threeyears later we have U.S. headline unemployment that has been above 8% forthree-and-a-half years, long-term unemployment unmatched since the GreatDepression, the UK in a double-dip recession, parts of the Eurozone in de-pression, and the euro itself in danger of disintegrating even as it contributesto the distress in some of the Eurozone countries. Against that background,Blanchard’s pronouncement looks ever more questionable.

One could counter that macroeconomics is in good shape, that the prob-lem is with the politicians who are failing to implement the useful policies thateconomists know will work. If an epidemic were spreading and biologists rec-ommended a combination of quarantines and medication, you wouldn’t blamethe biologists for the continued spread of the disease if politicians hadn’t fol-lowed their advice. But the phrase “biologists recommended” implies a kindof consensus in that discipline that is lacking in macro.

Saltwater economists advocate increased government spending and looser


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monetary policy, and President Obama partly heeds them. Prominent fresh-water economists worry that our deficit is too large and that the FederalReserve’s actions are already too much, and the Congressional Republicans,along with many Democrats, follow their lead. A statement that “economistsrecommend x” runs the risk of being incoherent if x is to represent the fullrange of respectable opinion in the field. So on its own terms, macroeco-nomics is arguably in crisis—or should be.

And that’s without considering the environmental situation. From globalwarming to habitat destruction and accelerated rates of extinction, we’refacing a host of serious environmental problems, issues in which our economicactivity is implicated, one way or another. And yet the economic models webring to these questions are usually specialized tools meant for consideringrelatively narrow “environmental” concerns. It seems clear to some (thepresent author included), that there is a fundamental, two-way relationshipbetween the economy on the one hand, and resources and the environmenton the other. The awareness of that relationship has yet to make its wayto the heart of the discipline and day-to-day macroeconomic analyses anddecisions are made without a coherent view of how resources shape our realoptions and how our economic actions affect the environment.

The project of mending macroeconomics may need to include somethinglike a Post-Keynesian approach in order to better handle asset-market tur-bulence such as we’ve witnessed over the last several years. But the resource-inclusive approach, even in the version presented here installed underneath aconventional “1978-era” framework, already provides some improved insightinto the recent turmoil and recession. And it offers a way in which diversemodels, from New Classical to Post-Keynesian, can more meaningfully reflectthe real, physical world in which we live.

This may not be a “complete” model in the sense implied by Pollitt etal. [59], but hopefully it is a significant step forward.


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Figure 1: Labor market in conventional model


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% ofY ∗


(a) (b)

1211 13



Y1 100%90% 110%




Figure 2: (a) IS-LM framework with potential GDP of 12 trillion and actualGDP of 11.64 trillion; (b) IS-LM framework relative to potential GDP, withoutput gap of -3%


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% of Y ∗100%90% 110%




Figure 3: Standard AS-AD diagram, relative to potential output





3% 9%u∗


Phillips Curve




Figure 4: Standard Phillips Curve diagram


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Figure 5: Resource supply curve


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Figure 6: Resource supply curves over time


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5.2 6.2 7.2 8.2 9.2 10.2 11.2





s sh




l fo




log (GDP per capita)

Figure 7: Relationship between renewables share in footprint and GDP percapita. Dashed line shows relationship from OLS; solid line is from WLS,using population as weights. Both regressions include biocapacity per capita;both “fit” lines use sample average biocapacity to produce a straight line.


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w, w + ρPR


N s

(N +R)s

Ndw∗ + ρ(PR)∗



Figure 8: Labor market with resource costs


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N s

(N +R)s0(N +R)sρ





w0 + ρ0PR0



wA + ρ0PRA

wρ + ρ1PRρ

w, w + ρPR


Figure 9: Different technology paths interacting with moderately scarce re-sources


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n B

tu p





Figure 10: Energy per worker, United States, 1949-2010, million Btuper worker. Employment data from Bureau of Labor Statistics, seriesLNS12000000; Energy data from Annual Energy Review, Energy Informa-tion Administration, U.S. Department of Energy, Table 1.1 “Primary EnergyOverview,” total consumption


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w, w + ρPR


N s

(N +R)s1(N +R)s2



w2 + ρPR2



Figure 11: Labor market with abundant and scarce resources


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t g










l) in

% o

f p







Figure 12: Output gap, based on three different vintages of potential GDP.Potential GDP data downloaded from http://alfred.stlouisfed.org/

series/downloaddata?seid=GDPPOT&cid=106, June 30, 2012.


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r r


(a) (b)

Y ∗CY ∗

R11 13



Y ∗C1Y ∗

C2Y ∗R11 13




Figure 13: (a) Economy with undiagnosed “overheating” due to overestimateof potential GDP; (b) Post-bubble economy with overestimated ability torecover, due to overestimate of potential GDP


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Y ∗C


Y ∗R

11 13






Figure 14: Aggregate supply curve shifted left and steepened by worseningsupply constraint


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u1 u2

Figure 15: Phillips curve shifted up by higher expected inflation and right-ward by higher natural unemployment, both resulting from worsening supplyconstraint