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Will Technological Change Save the World? The Rebound Effect in International Transfers of Technology

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An Erratum to this article was published on 26 January 2017

Abstract

Technological change and its transfer to developing countries is often portrayed by policy-makers as a critical part of the solution to a resource problem such as climate change, based on the assumption that the transfer of resource-conserving technologies to developing countries will result in reduced use of natural capital by those countries. We demonstrate here, in a capital conversion based model of development, that the free transfer of resource-conserving technologies to developing countries will increase the options available to those countries, but that the way that they expend these options need not be in the direction of conserving resources. This is another example of the potential for a rebound effect to determine ultimate outcomes, here in the context of international technology transfer policy. The transfer of technologies is as likely to simply move developing countries more rapidly down the same development path as it is to alter the choices they make along that path. For this reason, the transfer of resource-conserving technologies, without incentives provided to alter development priorities, may not result in any resource-conservation at all.

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Notes

  1. We are distinguishing the term “resource-conserving” technology from the term “resource-saving” technology, which has been used to describe technologies whose net effect is to generate less resource usage. Since we are examining the question of rebound effects, we look at technologies where the net effect is not necessarily pre-determined. See Smulders and Di Maria (2012) for a clear discussion on the use of terminology regarding technologies in this area of enquiry.

  2. The literature on this question is vast. There has been a general recognition that estimates concerning climate change mitigation are sensitive to assumptions concerning the rates of technical change. The extant literature often assumes that increased technological efficiency in resource usage will in general result in reduced resource use (Dowlatabadi 1998). This result has been claimed or assumed across relatively general conditions and specifications (Fisher-Vanden 2008; Gillingham et al. 2008; Vollebergh and Kemfert 2005). This is seen as a means by which reduced resource use may be compatible with development (Jin and Zhang 2015; Bosetti et al. 2008). As a case in point, it is often assumed that the diffusion of technological change may be an essential part of the solution to the problem of climate change (Aronsson et al. 2010; Gerlagh and Kuik 2014; Grubb 2000; Hübler et al. 2012).

  3. Although the discussion is framed in terms of technology transfer, it could also be framed in terms of free technology adoption by the developing country. That is, we are assuming throughout that the policy examined here consists solely of the free transfer of a resource-conserving technology to a developing country, without other incentives or constraints for how that technology will be employed.

  4. The rebound literature primarily focuses on the question of the impacts of domestic energy policy when mediated through the responses of consumers and industries. Our paper focuses instead on the question of the impact of international policy of technology transfer when mediated through the responses of developing states. See our discussion of the specific nature of our contribution to the literature in Sect. 2 below.

  5. Our analysis is limited to the point separating out between the issues of income transfer and incentives. We do not address how these incentives might be instilled within an international transfer mechanism, but leave this to the very substantial literature on international agreements regarding the environment.

  6. We are very grateful to an anonymous referee for providing us with many of the ideas underlying this section, the role of the rebound effect, and how its application varies between domestic and international contexts.

  7. Much of the modern rebound literature originated in analyzing the OPEC impacts on oil prices in the 1970s (Saunders 2000).

  8. First, some authors examine how technological change shifts the marginal abatement cost (MAC) function within firms responsible for pollution control, and determine that the shift need not necessarily be downward (i.e. a reduction in MAC). When MAC shifts upward with technological change—a “brown technology”—there will be incentives for lower expenditures on abatement by the firms subjected to the change (Smulders and Di Maria 2012). Even if the shift in the MAC function is not ambiguously upward with the change (so that the new function perhaps intersects with the old one), the outcome for the industry will not necessarily be increased abatement expenditures (Perino and Requate 2012). So, one important point is that the responsiveness of the abatement cost to technological change is not a given, and may drive future energy use (or polluting emissions) in very different directions.

  9. A second important question regarding the rebound effect concerns the response of consumers rather than firms. When technological change results in greater energy efficiency, the consumer-oriented literature analyses the combined substitution and income effects of the policy-induced change (Binswanger 2001). The substitution effect resulting from greater energy efficiency induces consumers to economize on the resource concerned; however, the income effect may counteract at least a portion of the substitution effect. For example, the introduction of more energy-efficient appliances by reason of the policy change will represent an income improvement for consumers, some of which may then be expended on the expansion of energy use. It is the net effect of substitution and income effects that determines the extent of the rebound. Saunders (2000) termed a rebound effect of a scale sufficient to cancel out the positive substitution effects a “backfire”. There are numerous empirical papers that look at this issue of the net effect of policy change, by looking at the elasticities of demand for energy use in certain goods as their efficiency changes (Gillingham et al. 2015; Chan and Gillingham 2015).

  10. Barker et al. (2009) assesses the scale of a macroeconomic rebound effect in the context of climate policies applied to the global economy. They assess three different types of rebound effects: direct rebound effects, indirect rebound effects; economy wide rebound effects. Direct rebound effects refer to the overall increased consumption of the energy service following a reduction in the effective price of the service as a result of policy-induced technological change. Indirect rebound effects refer to the consumers’ income effect on other energy-using goods and services from the above-mentioned changed price. Economy-wide effects refer to the general equilibrium effect from the increase in energy efficiency on energy-using intermediate and final goods throughout the economy. The authors find that all of these effects exist under a range of climate policies, and estimate that the aggregate indirect and economy-wide rebound effect results in a loss of about 50% of the direct positive impact of the policies investigated (Barker et al. 2009). So, in the context of one macroeconomic model, it has been argued that the rebound effect exists at the level of international policy effects, and that its magnitude is of some consequence.

  11. We return more to the question of the appropriate conceptualization of pathways of development below, but suffice it to say here that we are focusing on how countries with given preferences allocate growth between the objectives of environmentally-supplied goods and services and other goods and services, and how this alters across development.

  12. In this setting, environmental goods may end up declining (despite increased income) as the result of a conversion process in which the developing society moves away from reliance on primarily natural capital and toward a more mixed portfolio of natural/physical capital (Stokey 1998).

  13. López and Yoon (2014) use a more general model incorporating the scale-composition-technique effects to confirm the findings of Stokey (1998) that the EKC is a potential consumption path for developing countries, depending primarily on the elasticity of marginal utility with regard to consumption as the critical parameter determining the existence of an EKC (i.e. a path that ultimately turns toward higher environmental quality).

  14. Our contribution is to demonstrate that the free transfer of technologies operates very much in the same way as a transfer of income or wealth (see e.g. Munasinghe 1999). Although voluminous, it would seem fair to say that the EKC literature broadly concludes that the EKC can be tunneled through rather than traversed, to the extent that the subject countries elect to engage in enhanced regulation, i.e. implement policies to alter their balance of flows of goods and services (Dasgupta et al. 2002). As detailed below, we concur with this conclusion in the context of technology transfer, and demonstrate that changes in relative conversion rates need not provide much more in the way of incentives to alter flows of goods and services, than does a direct transfer of wealth or income.

  15. The difference between a simple income transfer and a technology transfer lies in the change in the “conversion rate” that technology implies (as will be defined in the next section). A contribution of this paper is to demonstrate the limited difference that such changes in conversion rates make relative to income transfers under certain conditions.

  16. We think of the flow of goods and services from N as being of the nature of health benefits, and so a relatively concrete but distinctive set of goods and services from those flowing from k, but we model the problem as being a direct flow from the natural capital base for purposes of simplifying the exposition. For similar modelling, see e.g. Bovenberg and Smulders (1996) and Fullerton and Kim (2008).

  17. We acknowledge that including N as a second input could make the production function more general, as an anonymous reviewer correctly pointed out. In such a case, the outcome would depend on the degree of substitutability between the two inputs. In case of high substitutability between k and N, the social planner may decrease natural capital while increasing the stock of physical capital and get more consumption (although she faces a trade-off between c and N). By contrast, in case of low substitutability, the social planner is likely to pursue a more balanced path. In either case, a decrease in \(\phi \) is likely to strengthen our results by inducing an increase in physical capital accumulation and consumption as well as a decrease in natural capital (albeit at a higher level). The outcomes will be similar to what we already have, the only difference being the pace and magnitude at which physical capital accumulation, consumption growth and depletion of natural capital take place.

  18. With some abuse of notations, we will liberally drop the time argument of our time-variant variables when there is no risk of confusion.

  19. As suggested by an anonymous reviewer, one could use a more general specification such as a CES function to feature a non-separable utility function (implying a positive cross-derivative \(U_{cN}>0\)). However, for ease and simplicity of exposition and clarity of the results, we have opted for a utility function that is separable in its arguments so that \(U_{cN}=0\). We follow closely Stokey (1998) who relies on a similar separability assumption.

  20. To fix the meaning of \(\phi \): consider it to be represented by the amount of N consumed in the production of a unit of GDP. It also represents the rate of capital conversion because the loss of a unit of natural capital represents the reduction in the flow of natural-capital services (e.g. a reduction in health preserving services on account of an increase in pollution that results from the reduction of natural capital stocks). That is, increased k is used to generate increased consumption goods f(k), and \(\phi \) is the rate at which N is reduced in the face of increased production f(k) and so implicitly declines with increased capital k. In this manner, increased physical capital stocks (and production) draw down on natural capital stocks (and their services); equivalently, the natural capital is being converted into physical capital at the exchange rate (or resource intensity) \(\phi \).

  21. Equivalently, the technological conversion coefficient may be termed the pollution or emission intensity rate of production. We focus on capital conversion (and resource intensity) because the object of our enquiry is to assess how this development path is altered by changes in technology, and our focus is on developing countries as we define them below.

  22. We view this as an explication of the development process as capital conversion, as described by Stokey (1998).

  23. The choice of such a broadly defined environmental remedial function enables us to show even with non-conventional mitigation technologies, the possibility of a rebound effect may exist on a macro level, highlighting the possible limits of relying solely on technology improvement such as reduced resource intensity to alter the priorities of developing countries towards maintaining the natural capital stock. We thank an anonymous reviewer for highlighting the possibly unconventional characteristic of the environmental protection technology.

  24. Note that beyond \(\overline{m},\) it would make more sense to reduce output than to invest in management.

  25. The modeling of the dynamics of natural capital is the environmental quality version of the pollution stock model presented by Xepapadeas (2005, 1239).

  26. We thank an anonymous reviewer for insightful comments that helped improve the proof of this proposition.

  27. We can see that the steady state \(\left( k^{\infty },N^{\infty },c^{\infty },m^{\infty }\right) \) exists in this problem. Indeed, solving the system of Eqs. (9) and (12) yields implicitly \(k^{\infty }\) and \(m^{\infty }\). It is then straightforward to obtain \(c^{\infty }\) from Eq. (11), and subsequently \(N^{\infty }\) from Eq. (10).

  28. This is seen most clearly if the production function is specified; for example, if \(f(k)=Ak^{\alpha }\), then this condition becomes \(\Psi ^{\prime }(m)<\phi /\left( 1-\alpha \right) \).

  29. In this case, the assumed non-homothetic preferences characterized by \(\eta >\sigma \) lead to a bias in favour of private consumption goods c because c increases at a faster rate than N.

  30. Note that we established in Eq. (10), that in the steady state, the optimal provision of natural capital is given by \({\displaystyle \frac{U_{N}}{U_{c}}\frac{1}{\rho }=\frac{1}{\Psi ^{\prime }\left( m^{\infty }\right) }}\). In other words, the social planner’s discounted marginal rate of substitution of natural capital for consumption goods is equal to the marginal cost of providing N, i.e., \({\displaystyle \frac{1}{\Psi ^{\prime }\left( m^{\infty }\right) }}\). This relationship is equivalent to the optimal provision of a public good by the social planner assuming that the population of the country is normalized and equal to 1.

  31. The important point here is to distinguish between the effects of technological and institutional endowments. We do so by restricting technological change to those changes that alter the rate of conversion between capital stocks, while restricting institutional change to those changes that alter the rate at which foregone consumption is able to translate directly into increased natural capital stocks. Obviously, the two concepts are closely related in that they both represent alternate methods for enhancing natural capital stocks, at a given level of physical capital, and we separate out between them simply to indicate that we believe that there are two distinct techiques for doing so. For example, a technological change could represent a new form of physical capital that produces the desired output with reduced natural capital input (e.g. a more fuel efficient automobile), whereas an institutional change could represent an expenditure of national income on management to reduce inefficient usage of natural capital (e.g. a tax on air pollution that internalises an externality and thus causes a firm to reduce its production to a more efficient level).

  32. The increase in N through the income effect is bound to be moderate because of the non-homotheticity of the preferences where \(\eta >\sigma \).

  33. One of the principal points of the Stokey analysis of the EKC is that expenditures on management are endogenous to the country’s preferences concerning natural and standard consumption.

  34. That is, for a developing country that has currently a pollution intensity of 0.546, what would be the effect of adopting a foreign technology that enables it to benefit from a technology improvement of 30 years \((\phi =0.390)\), or 60 years \((\phi =0.290)\).

  35. The optimal control problem for the simulation was solved using GPOPS-II (Patterson and Rao 2014). We thank Antony Millner for sharing code and tricks.

  36. See the discussion about the rebound effect in Sect. 3.3 (p. 14).

  37. This is due in part to the fact that physical capital accumulation increases while natural capital stock decreases with reduced \(\sigma \).

  38. This places our paper at odds with the “tunneling through” camp of the EKC debate. Our findings indicate that countries will use transfers of technology to move more rapidly (and further) along the same path, rather than to alter that path or jump forward along it. If there is a silver lining to our findings, it is that the rapid movement along the EKC path might reach a point much further along the same path in a shorter amount of time, meaning that the country concerned might target a very different portfolio of capital at a much earlier point in time. However, the passage along the same path to get there implies substantial levels of resource use—at earlier points in time—than would have occurred in the absence of the transfer.

  39. We have elected to model it as disembodied technical change that decreases the polluting effect of physical capital.

  40. Note that since \(\dot{\lambda }<0\), inequality (20) suggests that the LHS has a steeper slope than the RHS. This is confirmed by the fact the fact that \(\lambda \) is decreasing and convex \(\ddot{\lambda }=\underbrace{\left( \underbrace{\delta +\rho -f^{\prime }\left( k\right) }_{<0}\right) \underbrace{\dot{\lambda }}_{<0}}_{>0}+\underbrace{\dot{\mu }f^{\prime }\left( k\right) }_{>0}\underbrace{-\underbrace{\left( \lambda -\mu \phi \right) }_{>0 \text{ since } \lambda -\mu>0}\underbrace{f^{\prime \prime }\left( k\right) }_{<0}}_{>0}>0\).

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Correspondence to Mare Sarr.

Additional information

We are grateful to two anonymous referees for their insightful comments. We benefited immensely from these. We also thank Jean-Pierre Amigues, Lucas Bretschger, Antony Millner, Cees Withagen, members of the CostAssess and Sinergia team, and the audience at the 2015 conference on “Economics of innovation, diffusion, growth and the environment” in London for useful comments and discussions. Adeola Oyenubi provided excellent research assistance. We gratefully acknowledge financial support from the Swiss National Science Foundation (SNSF) and the South African National Research Foundation (NRF) through the Swiss-South Africa Joint Research Programme (SSAJRP). Mare Sarr thanks the South African Department of Science and Technology and Economic Research Southern Africa for additional financial support. All errors are our own.

An erratum to this article is available at http://dx.doi.org/10.1007/s10640-017-0116-9.

Appendix

Appendix

1.1 Proof Proposition 1

The Hamiltonian of this problem \(\mathcal {H}=U(c,N)+\lambda \left[ f(k)-c-m\right] +\mu \left[ \Psi (m)\right. \left. -\,\phi f(k)\right] \) yields the following first order conditions:

$$\begin{aligned}&U_{c}=\lambda \end{aligned}$$
(13)
$$\begin{aligned}&-\lambda +\mu \Psi ^{\prime }(m)\le 0\;\quad \text{ with } \text{ equality } \text{ if } m>0\nonumber \\&m = {\left\{ \begin{array}{ll} 0 &{} \text{ if } \lambda \ge \mu \\ m^{*}=\Psi ^{\prime -1}\left( \lambda /\mu \right) >0 &{} \text{ if } \lambda =\mu \Psi ^{\prime }(m) \end{array}\right. } \end{aligned}$$
(14)
$$\begin{aligned}&\frac{\dot{\lambda }}{\lambda }={\left\{ \begin{array}{ll} {\displaystyle \rho -\left( 1-\frac{\mu }{\lambda }\phi \right) f^{\prime }(k)} &{} \text{ if } \lambda \ge \mu \\ {\displaystyle \rho -\left( 1-\frac{\phi }{\Psi ^{\prime }(m)}\right) f^{\prime }(k)} &{} \text{ if } \lambda =\mu \Psi ^{\prime }(m) \end{array}\right. } \end{aligned}$$
(15)
$$\begin{aligned}&\frac{\dot{\mu }}{\mu }={\left\{ \begin{array}{ll} {\displaystyle \rho -\frac{U_{N}\left( c,N\right) }{\mu }} &{} \text{ if } \lambda \ge \mu \\ {\displaystyle \rho -\frac{U_{N}\left( c,N\right) }{U_{c}}\Psi ^{\prime }(m)} &{} \text{ if } \lambda =\mu \Psi ^{\prime }(m) \end{array}\right. } \end{aligned}$$
(16)

The dynamics of consumption and environmental management obtain following time differentiation of (13) and \(\lambda =\mu \Psi ^{\prime }(m)\) for \(m>0\):

$$\begin{aligned}&{\displaystyle \frac{\dot{c}}{c}={\left\{ \begin{array}{ll} \frac{1}{\sigma }{\displaystyle \left[ \left( 1-\frac{\mu }{\lambda }\phi \right) f^{\prime }(k)-\rho \right] } &{} \text{ if } \lambda \ge \mu \\ \frac{1}{\sigma }{\displaystyle \left[ \left( 1-\frac{\phi }{\Psi ^{\prime }(m)}\right) f^{\prime }(k)-\rho \right] } &{} \text{ if } \lambda =\mu \Psi ^{\prime }(m) \end{array}\right. }} \end{aligned}$$
(17)
$$\begin{aligned}&\dot{m}={\left\{ \begin{array}{ll} 0 &{} \text{ if } \lambda \ge \mu \\ {\displaystyle \frac{\Psi ^{\prime }(m)}{\Psi ^{\prime \prime }(m)}\left\{ \frac{U_{N}}{U_{c}}\Psi ^{\prime }(m)-\sigma \frac{\dot{c}}{c}-\rho \right\} } &{} \text{ if } \lambda =\mu \Psi ^{\prime }(m) \end{array}\right. } \end{aligned}$$
(18)

Part (a) Consider a developing country that is initially endowed with low physical capital stock \(k_{0}\) and large natural capital stock \(N_{0}\). So long as the shadow value of physical capital is high relative to the shadow value of natural capital so that \(\lambda \ge \mu \), the social planner will optimally choose not to manage the environment and set \(m^{*}=0\). To see that there is an optimal time at which environmental management is undertaken, we resort to the same argument as Stokey (1998). Since \(\lambda \) is decreasing while \(\mu \) is increasing , so that the ratio \(\lambda /\mu \) declines monotonically, there exists a finite time period \(\tilde{t}\) (i.e. \(\tilde{t}<\infty \)) that satisfies \(\lambda (\tilde{t})=\mu (\tilde{t})\) (with \(\dot{\lambda }(\tilde{t})<0\) and \(\dot{\mu }(\tilde{t})>0\)) so that for \(t<\tilde{t}\), \(\lambda (t)\ge \mu (t)\) and therefore \(m\left( t\right) =0\).

Now for \(t\le \tilde{t}\), \(\dot{\lambda }(t)<0\) if and only if \({\displaystyle f^{\prime }\left( k\left( t\right) \right) >\frac{\rho }{1-{\displaystyle \frac{\mu \left( t\right) }{\lambda \left( t\right) }}\phi }}\) i.e. \(\displaystyle k\left( t\right) <f^{\prime -1}\left( \frac{\rho }{1-{\displaystyle \frac{\mu \left( t\right) }{\lambda \left( t\right) }}\phi }\right) \). In particular for \(t=0\), we have \({\displaystyle k_{0}<f^{\prime -1}\left( \frac{\rho }{1-{\displaystyle \frac{\mu _{0}}{\lambda _{0}}}\phi }\right) }\). In addition, from (16), for \(t\le \tilde{t}\), \(\dot{\mu }>0\) if and only if \(U_{N}<\rho \mu \le \rho \lambda =\rho U_{c}\) or equivalently \({\displaystyle \frac{U_{c}}{U_{N}}>\frac{1}{\rho }}\) , i.e. if the marginal rate of N for c is large enough. In other words if N is large enough. In particular for \(t=0\), we have \({\displaystyle \frac{U_{c}\left( c_{0},N_{0}\right) }{U_{N}\left( c_{0},N_{0}\right) }>\frac{1}{\rho }}\).

Part (b) For \(t\le \tilde{t}\), it is straightforward to see that \(\dot{N}=-\phi f\left( k\right) <0\) and \(\dot{m}=0\). By definition of \(\tilde{t}\), when \(t\le \tilde{t}\), \(\dot{\lambda }<0\) and \(\dot{\mu }>0\). By the dynamics of c (Eq. 17), \(\dot{c}>0\) if and only if \(\dot{\lambda }<0\). This in turn implies that \(\dot{k}=f(k)-c>0\).

Part (c) Part (a) implies that the developing country will use management \(m\left( t\right) >0\) for \(t>\tilde{t}\). In the transition phase towards \(\tilde{t}\), we know that \(\lambda \ge \mu \Psi ^{\prime }(m)\), which implies that \({\displaystyle 1-\frac{\mu }{\lambda }\phi \ge 1-\frac{\phi }{\Psi ^{\prime }(m)}}\). In addition, since \(f^{\prime }\left( k\left( t\le \tilde{t}\right) \right)>f^{\prime }\left( k\left( t>\tilde{t}\right) \right) \), it follows that:

$$\begin{aligned} {\displaystyle \frac{1}{\sigma }\left[ \left( 1-\frac{\mu }{\lambda }\phi \right) f^{\prime }\left( k\left( t\le \tilde{t}\right) \right) -\rho \right] }> & {} \frac{1}{\sigma }\left[ \left( 1-\frac{\phi }{\Psi ^{\prime }(m)}\right) f^{\prime }\left( k\left( t>\tilde{t}\right) \right) -\rho \right] \nonumber \\ \frac{\dot{c}\left( t\le \tilde{t}\right) }{c\left( t\le \tilde{t}\right) }> & {} {\displaystyle \frac{\dot{c}\left( t>\tilde{t}\right) }{c\left( t>\tilde{t}\right) }} \end{aligned}$$
(19)

That is, consumption growth slows down beyond the optimal date \(\tilde{t}\). In addition, multiplying (19) by \(-\sigma \) yields:

$$\begin{aligned} {\displaystyle \rho -\left( 1-\frac{\mu }{\lambda }\phi \right) f^{\prime }\left( k\left( t\le \tilde{t}\right) \right) }< & {} \rho -\left( 1-\frac{\phi }{\Psi ^{\prime }(m)}\right) f^{\prime }\left( k\left( t>\tilde{t}\right) \right) \nonumber \\ \frac{\dot{\lambda }\left( t\le \tilde{t}\right) }{\lambda \left( t\le \tilde{t}\right) }< & {} {\displaystyle \frac{\dot{\lambda }\left( t>\tilde{t}\right) }{\lambda \left( t>\tilde{t}\right) }} \end{aligned}$$
(20)

Inequality (20) suggests that the shadow value of physical capital decelerates at a slower rate beyond \(\tilde{t}\). It must be the case that the growth in the stock of physical capital slows down relative to the earlier phase before \(\tilde{t}\).Footnote 40

In addition, since for \(t>\tilde{t}\), \(\dot{N}=\Psi (m)-\phi f(k)\), the depletion of natural capital decelerates due to the investment in environmental management. Note that for sufficiently small \(\phi <\Psi \left( m\right) /f\left( k\right) \), \(\dot{N}>0\), i.e. the natural capital is regenerated.

Part (d) We established earlier that at \(\tilde{t}\), \(\lambda (\tilde{t})=\mu (\tilde{t})\). This is implies that:

$$\begin{aligned}&\displaystyle \int _{\tilde{t}}^{\infty }\dot{\lambda }(s)ds = \int _{\tilde{t}}^{\infty }\dot{\mu }(s)ds\nonumber \\&\displaystyle \int _{\tilde{t}}^{\infty }\left[ \left( \rho -f^{\prime }\left( k\left( s\right) \right) \right) \lambda (s)+\phi \mu (s)f^{\prime }\left( k\left( s\right) \right) \right] ds = \int _{\tilde{t}}^{\infty }\left[ \rho \mu (s)-U_{N}\left( c\left( s\right) ,N\left( s\right) \right) \right] ds\nonumber \\&\displaystyle \int _{\tilde{t}}^{\infty }\left[ \left( \rho -f^{\prime }\left( k\left( s\right) \right) \right) \lambda (s)+\phi \mu (s)f^{\prime }\left( k\left( s\right) \right) \right] -\left[ \rho \mu (s)-U_{N}\left( c\left( s\right) ,N\left( s\right) \right) \right] ds = 0\nonumber \\ \end{aligned}$$
(21)

Consider \({\displaystyle J(\beta )=\int _{a}^{b}h(x,\beta )\,\mathrm {d}x}\), Leibniz rule states that \(\displaystyle \frac{\mathrm {d}J}{\mathrm {d}\beta }=\int _{a}^{b}h_{\beta }(x,\beta )\,\mathrm {d}x+h(b,\beta )\frac{\mathrm {d}b}{\mathrm {d}\beta }-h(a,\beta )\frac{\mathrm {d}a}{\mathrm {d}\beta }\). Applying Leibniz rule to Eq. (21), we obtain:

$$\begin{aligned}&\displaystyle \left. {\left\{ \begin{array}{ll} \int _{\tilde{t}}^{\infty }\mu (s)f^{\prime }\left( k\left( s\right) \right) ds\\ -\left[ \underbrace{\left( \rho -f^{\prime }\left( k\left( \tilde{t}\right) \right) \right) \lambda (\tilde{t})+\phi \mu (\tilde{t})f^{\prime }\left( k\left( \tilde{t}\right) \right) }_{\dot{\lambda }\left( \tilde{t}\right) }-\underbrace{\left( \rho \mu (\tilde{t})-U_{N}\left( c\left( \tilde{t}\right) ,N\left( \tilde{t}\right) \right) \right) }_{\dot{\mu }\left( \tilde{t}\right) }\right] {\displaystyle \frac{d\tilde{t}}{d\phi }} \end{array}\right. }\right\} = 0 \nonumber \\\end{aligned}$$
(22)
$$\begin{aligned}&\displaystyle {\displaystyle \frac{d\tilde{t}}{d\phi }} = \frac{{\displaystyle \int _{\tilde{t}}^{\infty }\mu (s)f^{\prime }\left( k\left( s\right) \right) ds}}{\dot{\lambda }\left( \tilde{t}\right) -{\displaystyle \dot{\mu }\left( \tilde{t}\right) }}<0 \end{aligned}$$
(23)

This is true because \(\dot{\lambda }\left( \tilde{t}\right) <0\) and \(\dot{\mu }\left( \tilde{t}\right) >0\) by Part (a) of this proof (see above). \(\square \)

1.2 Proof Proposition 2

The system of Eqs. (912) that defines the steady state after total differentiation can be written in matrix form as:

figure a

where the matrix is denoted \(\Xi \); \({\displaystyle a_{1}\equiv \frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) ^{2}}\phi }f^{\prime }\left( k\right) <0\); \({\displaystyle a_{2}\equiv \left( 1-\frac{\phi }{\Psi ^{\prime }\left( m\right) }\right) }f^{\prime \prime }\left( k\right) <0\); \(a_{3}\equiv -\rho U_{cc}>0\); \(a_{4}\equiv U_{N}\Psi ^{\prime \prime }\left( m\right) <0\); \(a_{5}\equiv U_{NN}\Psi ^{\prime }\left( m\right) <0\).

Define \(\Xi =\left( \begin{array}{cccc} 0 &{} a_{1} &{} a_{2} &{} 0\\ a_{3} &{} a_{4} &{} 0 &{} a_{5}\\ -1 &{} -1 &{} f^{\prime }\left( k\right) &{} 0\\ 0 &{} \Psi ^{\prime }\left( m\right) &{} -\phi f^{\prime }\left( k\right) &{} 0 \end{array}\right) \); \(M_{c}=\left( \begin{array}{cccc} \frac{f^{\prime }\left( k\right) }{\Psi ^{\prime }\left( m\right) } &{} a_{1} &{} a_{2} &{} 0\\ 0 &{} a_{4} &{} 0 &{} a_{5}\\ 0 &{} -1 &{} f^{\prime }\left( k\right) &{} 0\\ f\left( k\right) &{} \Psi ^{\prime }\left( m\right) &{} -\phi f^{\prime }\left( k\right) &{} 0 \end{array}\right) \);

\(M_{m}=\left( \begin{array}{cccc} 0 &{} \frac{f^{\prime }\left( k\right) }{\Psi ^{\prime }\left( m\right) } &{} a_{2} &{} 0\\ a_{3} &{} 0 &{} 0 &{} a_{5}\\ -1 &{} 0 &{} f^{\prime }\left( k\right) &{} 0\\ 0 &{} f\left( k\right) &{} -\phi f^{\prime }\left( k\right) &{} 0 \end{array}\right) \); \(M_{k}=\left( \begin{array}{cccc} 0 &{} a_{1} &{} \frac{f^{\prime }\left( k\right) }{\Psi ^{\prime }\left( m\right) } &{} 0\\ a_{3} &{} a_{4} &{} 0 &{} a_{5}\\ -1 &{} -1 &{} 0 &{} 0\\ 0 &{} \Psi ^{\prime }\left( m\right) &{} f\left( k\right) &{} 0 \end{array}\right) \)

\(M_{N}=\left( \begin{array}{cccc} 0 &{} a_{1} &{} a_{2} &{} \frac{f^{\prime }\left( k\right) }{\Psi ^{\prime }\left( m\right) }\\ a_{3} &{} a_{4} &{} 0 &{} 0\\ -1 &{} -1 &{} f^{\prime }\left( k\right) &{} 0\\ 0 &{} \Psi ^{\prime }\left( m\right) &{} -\phi f^{\prime }\left( k\right) &{} f\left( k\right) \end{array}\right) \)

Using Cramer’s rule, we can derive the comparative statics:

$$\begin{aligned} \frac{dc^{\infty }}{d\phi }=\frac{\det M_{c}}{\det \Xi };\;\;\;\;\frac{dm^{\infty }}{d\phi }=\frac{\det M_{m}}{\det \Xi };\;\;\;\;\frac{dk^{\infty }}{d\phi }=\frac{\det M_{k}}{\det \Xi };\;\;\;\;\frac{dN^{\infty }}{d\phi }=\frac{\det M_{N}}{\det \Xi } \end{aligned}$$

The determinant of \(\Xi \) is negative and given by:

$$\begin{aligned} \det \Xi =-a_{5}\left[ a_{1}\phi f^{\prime }\left( k\right) +a_{2}\Psi ^{\prime }\left( m\right) \right] <0 \end{aligned}$$

The direction of the four effects is therefore given by the sign of the determinants \(\det M_{c}\), \(\det M_{m}\), \(\det M_{k}\) and \(\det M_{N}\).

Part (a) we have:

$$\begin{aligned} \det M_{c}= & {} \frac{a_{5}\left[ -\left( \Psi ^{\prime }\left( m\right) -\phi \right) f^{\prime }\left( k\right) ^{2}+\left( a_{2}+a_{1}f^{\prime }\left( k\right) \right) f\left( k\right) \Psi ^{\prime }\left( m\right) \right] }{\Psi ^{\prime }\left( m\right) }>0\\ \det M_{k}= & {} a_{5}\left[ a_{1}f(k)-f^{\prime }(k)\right] >0 \end{aligned}$$

It follows that \(dc^{\infty }/d\phi<0;\;\;\text{ and } \;\;dk^{\infty }/d\phi <0\).

Part (b) & (c)

$$\begin{aligned} \det M_{m}= & {} -a_{5}\left[ \frac{\phi f^{\prime }\left( k\right) ^{2}}{\Psi ^{\prime }\left( m\right) }+a_{2}f(k)\right] \end{aligned}$$

As a result, \({{\mathrm{sgn}}}\left( \det M_{m}\right) {=}{{\mathrm{sgn}}}\left( {\displaystyle \Delta }\right) \) where \(\displaystyle \Delta {\equiv }\frac{\phi f^{\prime }\left( k\right) ^{2}}{\Psi ^{\prime }\left( m\right) }+ a_{2}f(k){=}\bigg [\phi +\left( \Psi ^{\prime }\left( m\right) -\phi \right) \frac{f\left( k\right) f^{\prime \prime }\left( k\right) }{f^{\prime }\left( k\right) ^{2}}\bigg ]\frac{f^{\prime }\left( k\right) ^{2}}{\Psi ^{\prime }\left( m\right) }\).

\(\Delta <0\) if and only if \({\displaystyle \Psi ^{\prime }\left( m\right) >\left( 1-\frac{f^{\prime }\left( k\right) ^{2}}{f\left( k\right) f^{\prime \prime }\left( k\right) }\right) \phi }\). Then \(\det M_{m}<0\) and consequently we always have \(dm^{\infty }/d\phi >0\).

\(\Delta >0\) if and only if \({\displaystyle \Psi ^{\prime }\left( m\right) <\left( 1-\frac{f^{\prime }\left( k\right) ^{2}}{f\left( k\right) f^{\prime \prime }\left( k\right) }\right) \phi }\). Then \(\det M_{m}>0\) and consequently we always have \(dm^{\infty }/d\phi <0\).

In addition, we have:

$$\begin{aligned} \det M_{N}= & {} -\underbrace{\frac{f^{\prime }\left( k\right) ^{2}}{\Psi ^{\prime }\left( m\right) }\rho U_{cc}\Gamma }_{>0}+\underbrace{\Psi ^{\prime \prime }\left( m\right) U_{N}}_{<0}\underbrace{\Delta }_{\lessgtr 0} \end{aligned}$$

where \({\displaystyle \Gamma \equiv \left[ 1-\frac{f\left( k\right) f^{\prime \prime }\left( k\right) }{f^{\prime }\left( k\right) ^{2}}\right] \left( \Psi ^{\prime }\left( m\right) -\phi \right) -\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }\phi f\left( k\right) }>0\).

If \(\Delta <0\) then \(\det M_{N}>0\) and consequently we always have \(dN^{\infty }/d\phi <0\).

If \(\Delta >0\) then the sign of \(\det M_{N}>0\) if and only if:

$$\begin{aligned} -\rho U_{cc}> & {} -\Psi ^{\prime \prime }\left( m\right) U_{N}\frac{\Psi ^{\prime }\left( m\right) }{f^{\prime }\left( k\right) ^{2}}\frac{\Delta }{\Gamma } \end{aligned}$$
(24)

Now \(\text{ det }M_{c}\) and \(\text{ det }M_{m}\) can be written as a function of \(\Gamma \) and \(\Delta \) respectively so that \(\text{ det }M_{c}=-U_{NN}f^{\prime }\left( k\right) ^{2}\Gamma \) and \(\text{ det }M_{m}=-U_{NN}\Psi ^{\prime }\left( m\right) \Delta \). As a result, the necessary and sufficient condition (24) can be written:

$$\begin{aligned} -\rho U_{cc}> & {} -\Psi ^{\prime \prime }\left( m\right) U_{N}\frac{\text{ det }M_{m}}{\text{ det }M_{c}} \end{aligned}$$

This is equivalent to

$$\begin{aligned} -\frac{U_{cc}}{U_{c}}> & {} -\Psi ^{\prime \prime }\left( m\right) \frac{U_{N}}{U_{c}}\frac{1}{\rho }\frac{dm^{\infty }/d\phi }{dc^{\infty }/d\phi } \end{aligned}$$

By Eq. (10), we established that \({\displaystyle \frac{U_{N}}{U_{c}}\frac{1}{\rho }=\frac{1}{\Psi ^{\prime }\left( m^{\infty }\right) }}\), i.e., the discounted marginal rate of substitution between natural capital (as a public good) and consumption goods is equal to the marginal cost of providing N. This implies that:

$$\begin{aligned} -\frac{U_{cc}}{U_{c}}> & {} -\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m^{\infty }\right) }\frac{dm^{\infty }/d\phi }{dc^{\infty }/d\phi } \end{aligned}$$

After simple calculation and re-interpretation of the expression in terms of elasticities, we obtain:

$$\begin{aligned} \sigma> & {} \varepsilon \frac{\theta _{m}}{\theta _{c}} \end{aligned}$$
(25)

where \({\displaystyle \sigma =-\frac{U_{cc}}{U_{c}}c}\) and \({\displaystyle \varepsilon =-\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }m}\) represent the elasticity of marginal utility of consumption and the elasticity of marginal product of management, respectively; \({\displaystyle \theta _{c}=\frac{dc}{d\phi }\frac{\phi }{c}}\) and \({\displaystyle \theta _{m}=\frac{dm}{d\phi }\frac{\phi }{m}}\) denote the elasticity of consumption and management with respect to \(\phi \).

Part (d) From the expressions of \(\det M_{N}\) and \(\det \Xi \), we can write:

$$\begin{aligned}&\displaystyle \frac{dN^{\infty }}{d\phi }=\frac{\det M_{N}}{\det \Xi }\\&\displaystyle \quad =\frac{{\displaystyle -\frac{f^{\prime }\left( k\right) ^{2}}{\Psi ^{\prime }\left( m\right) }}\rho U_{cc}\left\{ {\displaystyle \left[ 1-\frac{f\left( k\right) f^{\prime \prime }\left( k\right) }{f^{\prime }\left( k\right) ^{2}}\right] \left( \Psi ^{\prime }\left( m\right) -\phi \right) -\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }\phi f\left( k\right) }\right\} +\Psi ^{\prime \prime }\left( m\right) U_{N}\Delta }{{\displaystyle -U_{NN}\Psi ^{\prime }\left( m\right) \left\{ \frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }\phi ^{2}f^{\prime }\left( k\right) ^{2}+\left( 1-\frac{\phi }{\Psi ^{\prime }\left( m\right) }\right) f^{\prime \prime }\left( k\right) \Psi ^{\prime }\left( m\right) \right\} }} \end{aligned}$$

After some tedious though simple computation, we obtain:

$$\begin{aligned} \frac{dN^{\infty }}{d\phi }=\frac{{\displaystyle \rho \sigma c^{-1-\sigma }}\left\{ {\displaystyle \left[ f^{\prime }\left( k\right) ^{2}-f\left( k\right) f^{\prime \prime }\left( k\right) \right] \left( \Psi ^{\prime }\left( m\right) -\phi \right) -\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }\phi f\left( k\right) f\left( k\right) f^{\prime }\left( k\right) ^{2}}\right\} +\Psi ^{\prime \prime }\left( m\right) U_{N}\Delta }{{\displaystyle \chi \eta N^{-1-\eta }\left\{ \Psi ^{\prime \prime }\left( m\right) \phi ^{2}f^{\prime }\left( k\right) ^{2}+\left( \Psi ^{\prime }\left( m\right) -\phi \right) f^{\prime \prime }\left( k\right) \Psi ^{\prime }\left( m\right) ^{2}\right\} }} \end{aligned}$$

Now \(c^{-1-\sigma }=e^{(-1-\sigma )\ln c}\) so that for \(g\left( \sigma \right) =\sigma c^{-1-\sigma }=\sigma e^{(-1-\sigma )\ln c}\), we have \(g^{\prime }\left( \sigma \right) =c^{-1-\sigma }+\sigma (-1)\ln \left( c\right) e^{(-1-\sigma )\ln c}=c^{-1-\sigma }\left[ 1-\sigma \ln \left( c\right) \right] \),

$$\begin{aligned} \frac{\partial }{\partial \sigma }\left( \frac{dN^{\infty }}{d\phi }\right) =\rho c^{-\sigma -1}\left[ 1-\sigma \ln \left( c\right) \right] \Omega \end{aligned}$$

where \({\displaystyle \Omega \equiv \frac{{\displaystyle \left[ f^{\prime }\left( k\right) ^{2}-f\left( k\right) f^{\prime \prime }\left( k\right) \right] \left( \Psi ^{\prime }\left( m\right) -\phi \right) -\frac{\Psi ^{\prime \prime }\left( m\right) }{\Psi ^{\prime }\left( m\right) }\phi f\left( k\right) f\left( k\right) f^{\prime }\left( k\right) ^{2}}}{{\displaystyle \chi \eta N^{-1-\eta }\left[ \Psi ^{\prime \prime }\left( m\right) \phi ^{2}f^{\prime }\left( k\right) ^{2}+\left( \Psi ^{\prime }\left( m\right) -\phi \right) f^{\prime \prime }\left( k\right) \Psi ^{\prime }\left( m\right) ^{2}\right] }}}<0\) since both the numerator is positive and the denominator is negative.

$$\begin{aligned} \frac{\partial }{\partial \sigma }\left( \frac{dN^{\infty }}{d\phi }\right)<0\iff 1-\sigma \ln \left( c^{\infty }\right) >0\iff c^{\infty }<e^{1/\sigma } \end{aligned}$$

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Sarr, M., Swanson, T. Will Technological Change Save the World? The Rebound Effect in International Transfers of Technology. Environ Resource Econ 66, 577–604 (2017). https://doi.org/10.1007/s10640-016-0093-4

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