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Optimal Abatement Technology Licensing in a Dynamic Transboundary Pollution Game: Fixed Fee Versus Royalty

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Abstract

Transboundary pollution poses a major threat to environment and human health. An effective approach to addressing this problem is the adoption of long-term abatement technology; however, many developing regions are lacking in related technologies that can be acquired by licensing from developed regions. This study focuses on a differential game model of transboundary pollution between two asymmetric regions, one of which possesses advanced abatement technology that can reduce the abatement cost and licenses this technology to the other region by royalty or fixed-fee licensing. We characterize the equilibrium decisions in the regions and find that fixed-fee licensing is superior to royalty licensing from the viewpoint of both regions. The reason is that under fixed-fee licensing, the regions can gain improved incremental revenues and incur reduced environmental damage. Subsequently, we analyze the steady-state equilibrium behaviors and the effects of parameters on the licensing performance. The analysis indicates that the myopic view of the regions leads to short-term revenue maximization, resulting in an increase in total pollution stock. Moreover, a high level of abatement technology or emission tax prompts the licensee region to choose fixed-fee approach, which is beneficial both economically and environmentally for two regions.

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References

  • Arguedas, C., Cabo, F., & Martín-Herrán, G. (2017). Optimal pollution standards and non-compliance in a dynamic framework. Environmental & Resource Economics,68(3), 537–567.

    Article  Google Scholar 

  • Aronsson, T., Backlund, K., & Sahlén, L. (2010). Technology transfers and the clean development mechanism in a North-South general equilibrium model. Resource and Energy Economics,32(3), 292–309.

    Article  Google Scholar 

  • Barrett, S. (2003). Environment and statecraft: The strategy of environmental treaty-making: The strategy of environmental treaty-making. Oxford: Oxford University Press.

    Google Scholar 

  • Bayramoglu, B., & Jacques, J. F. (2015). International environmental agreements: the case of costly monetary transfers. Environmental & Resource Economics,62(4), 745–767.

    Article  Google Scholar 

  • Benchekroun, H., & Martín-Herrán, G. (2016). The impact of foresight in a transboundary pollution game. European Journal of Operational Research,251(1), 300–309.

    Article  Google Scholar 

  • Bertinelli, L., Camacho, C., & Zou, B. (2014). Carbon capture and storage and transboundary pollution: A differential game approach. European Journal of Operational Research,237(2), 721–728.

    Article  Google Scholar 

  • Bréchet, T., Hritonenko, N., & Yatsenko, Y. (2016). Domestic environmental policy and international cooperation for global commons. Resource and Energy Economics,44, 183–205.

    Article  Google Scholar 

  • Breton, M., Sbragia, L., & Zaccour, G. (2010). A dynamic model for international environmental agreements. Environmental & Resource Economics,45(1), 25–48.

    Article  Google Scholar 

  • Chang, M. C., Hu, J. L., & Tzeng, G. H. (2009). Decision making on strategic environmental technology licensing: fixed-fee versus royalty licensing methods. International Journal of Information Technology & Decision Making,8(03), 609–624.

    Article  Google Scholar 

  • Chang, R. Y., Hwang, H., & Peng, C. H. (2013). Technology licensing, R&D and welfare. Economics Letters,118(2), 396–399.

    Article  Google Scholar 

  • Chang, S., Sethi, S. P., & Wang, X. (2018). Optimal abatement and emission permit trading policies in a dynamic transboundary pollution game. Dynamic Games and Applications,8(3), 542–572.

    Article  Google Scholar 

  • De Frutos, J., & Martín-Herrán, G. (2017). Spatial effects and strategic behavior in a multiregional transboundary pollution dynamic game. Journal of Environmental Economics and Management. https://doi.org/10.1016/j.jeem.2017.08.001.

    Article  Google Scholar 

  • Dockner, E. J., Jorgensen, S., Van Long, N., & Sorger, G. (2000). Differential games in economics and management science. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Dockner, E. J., & Van Long, N. (1993). International pollution control: cooperative versus noncooperative strategies. Journal of Environmental Economics and Management,25(1), 13–29.

    Article  Google Scholar 

  • El Ouardighi, F., Kogan, K., Gnecco, G., & Sanguineti, M. (2018a). Commitment-based equilibrium environmental strategies under time-dependent absorption efficiency. Group Decision and Negotiation,27(2), 235–249.

    Article  Google Scholar 

  • El Ouardighi, F., Kogan, K., Gnecco, G., & Sanguineti, M. (2018b). Transboundary pollution control and environmental absorption efficiency management. Annals of Operations Research. https://doi.org/10.1007/s10479-018-2927-7

    Article  Google Scholar 

  • El-Sayed, A., & Rubio, S. J. (2014). Sharing R&D investments in cleaner technologies to mitigate climate change. Resource and Energy Economics,38, 168–180.

    Article  Google Scholar 

  • Fan, C., Jun, B. H., & Wolfstetter, E. G. (2018). Optimal licensing of technology in the face of (asymmetric) competition. International Journal of Industrial Organization,60, 32–53.

    Article  Google Scholar 

  • Fanokoa, P. S., Telahigue, I., & Zaccour, G. (2011). Buying cooperation in an asymmetric environmental differential game. Journal of Economic Dynamics and Control,35(6), 935–946.

    Article  Google Scholar 

  • Ferreira, F., & Bode, O. R. (2012, August). Per-unit royalty and fixed-fee licensing in a differentiated Stackelberg model. In 2012 IEEE 4th International conference on nonlinear science and complexity (NSC), IEEE (pp. 99–102).

  • Hattori, K. (2017). Optimal combination of innovation and environmental policies under technology licensing. Economic Modelling,64, 601–609.

    Article  Google Scholar 

  • Heywood, J. S., Li, J., & Ye, G. (2014). Per unit vs. ad valorem royalties under asymmetric information. International Journal of Industrial Organization,37, 38–46.

    Article  Google Scholar 

  • Hoel, M., & de Zeeuw, A. (2010). Can a focus on breakthrough technologies improve the performance of international environmental agreements? Environmental & Resource Economics,47(3), 395–406.

    Article  Google Scholar 

  • Hong, F. (2014). Technology transfer with transboundary pollution: a signalling approach. Canadian Journal of Economics/Revue canadienne d’économique,47(3), 953–980.

    Article  Google Scholar 

  • Huang, X., He, P., & Zhang, W. (2016). A cooperative differential game of transboundary industrial pollution between two regions. Journal of Cleaner Production,120, 43–52.

    Article  Google Scholar 

  • Jørgensen, S., Martín-Herrán, G., & Zaccour, G. (2010). Dynamic games in the economics and management of pollution. Environmental Modeling and Assessment,15(6), 433–467.

    Article  Google Scholar 

  • Jørgensen, S., & Zaccour, G. (2001). Time consistent side payments in a dynamic game of downstream pollution. Journal of Economic Dynamics and Control,25(12), 1973–1987.

    Article  Google Scholar 

  • Kaitala, V., Pohjola, M., & Tahvonen, O. (1992). Transboundary air pollution and soil acidification: A dynamic analysis of an acid rain game between Finland and the USSR. Environmental & Resource Economics,2(2), 161–181.

    Google Scholar 

  • Kamien, M. I., Oren, S. S., & Tauman, Y. (1992). Optimal licensing of cost-reducing innovation. Journal of Mathematical Economics,21(5), 483–508.

    Article  Google Scholar 

  • Kamien, M. I., & Tauman, Y. (1986). Fees versus royalties and the private value of a patent. The Quarterly Journal of Economics,101(3), 471–491.

    Article  Google Scholar 

  • Kamien, M. I., & Tauman, Y. (2002). Patent licensing: the inside story. The Manchester School, 70(1), 7–15.

    Article  Google Scholar 

  • Kim, S. L., & Lee, S. H. (2016). The licensing of eco-technology under emission taxation: Fixed fee vs. auction. International Review of Economics & Finance,45, 343–357.

    Article  Google Scholar 

  • Kossioris, G., Plexousakis, M., Xepapadeas, A., de Zeeuw, A., & Mäler, K. G. (2008). Feedback Nash equilibria for non-linear differential games in pollution control. Journal of Economic Dynamics and Control,32(4), 1312–1331.

    Article  Google Scholar 

  • Li, S. (2014). A differential game of transboundary industrial pollution with emission permits trading. Journal of Optimization Theory and Applications,163(2), 642–659.

    Article  Google Scholar 

  • Long, N. V. (1992). Pollution control: A differential game approach. Annals of Operations Research,37(1), 283–296.

    Article  Google Scholar 

  • Mukherjee, A., & Tsai, Y. (2013). Technology licensing under optimal tax policy. Journal of Economics,108(3), 231–247.

    Article  Google Scholar 

  • Sen, D. (2005). Fee versus royalty reconsidered. Games and Economic Behavior,53(1), 141–147.

    Article  Google Scholar 

  • Takarada, Y. (2005). Transboundary pollution and the welfare effects of technology transfer. Journal of Economics,85(3), 251–275.

    Article  Google Scholar 

  • Wang, X. H. (1998). Fee versus royalty licensing in a Cournot duopoly model. Economics Letters,60(1), 55–62.

    Article  Google Scholar 

  • Wu, C. H. (2018). Price competition and technology licensing in a dynamic duopoly. European Journal of Operational Research,267(2), 570–584.

    Article  Google Scholar 

  • Xia, H., Fan, T., & Chang, X. (2019). Emission Reduction Technology Licensing and Diffusion Under Command-and-Control Regulation. Environmental & Resource Economics,72(2), 477–500.

    Article  Google Scholar 

  • Yan, Q., & Yang, L. (2018). Optimal licensing in a differentiated Bertrand market under uncertain R&D outcomes and technology spillover. Economic Modelling,68, 117–126.

    Article  Google Scholar 

  • Ye, G., & Zhao, J. (2016). Environmental regulation in a mixed economy. Environmental & Resource Economics,65(1), 273–295.

    Article  Google Scholar 

  • Yeung, D. W. K., & Petrosyan, L. A. (2008). A cooperative stochastic differential game of transboundary industrial pollution. Automatica,44(6), 1532–1544.

    Article  Google Scholar 

  • Zavaleta, A. (2016). Climate Change and Breakthrough Technologies: The Role of Markets. Environmental & Resource Economics,64(4), 597–617.

    Article  Google Scholar 

  • Zhang, Q., Jiang, X., Tong, D., Davis, S. J., Zhao, H., Geng, G., et al. (2017). Transboundary health impacts of transported global air pollution and international trade. Nature,543(7647), 705–709.

    Article  Google Scholar 

Download references

Acknowledgements

This paper was funded by Soft Science Research Project of Sichuan (2018ZR0333), the National Natural Science Foundation of China (71571149).

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Appendices

Appendix 1 for Proposition 1

The first-order conditions of \( E_{iN}^{*} \), \( E_{jN}^{*} \), \( \alpha_{iN}^{*} \) and \( \alpha_{jN}^{*} \) are as follows:

$$ E_{iN}^{*} (t) = A - \tau + V_{iN}^{\prime } (p),\;\alpha_{iN}^{*} (t) = \frac{{\tau - V_{iN}^{\prime } (p)}}{{(c - \varepsilon )[A - \tau + V_{iN}^{\prime } (p)]}} $$
(A1)
$$ E_{jN}^{*} (t) = \theta A - \tau + V_{jN}^{\prime } (p),\;\alpha_{jN}^{*} (t) = \frac{{\tau - V_{jN}^{\prime } (p)}}{{c[\theta A - \tau + V_{jN}^{\prime } (p)]}} $$
(A2)

Substituting (A1) and (A2) into (5a) and (5b), we then obtain the simplified HJB equations:

$$ \begin{aligned} \lambda V_{iN} (p) & = \frac{1}{2}[A - \tau + V_{iN}^{\prime } (p)]^{2} + \frac{{[\tau - V_{iN}^{\prime } (p)]^{2} }}{2(c - \varepsilon )} \\ &\quad+\, V_{iN}^{\prime } (p)\left[\theta A - \tau + V_{jN}^{\prime } (p) - \,\frac{{\tau - V_{jN}^{\prime } (p)}}{c}\right] - Dp(t) - \delta V_{iN}^{\prime } (p)p(t) \\ \end{aligned} $$
(A3)
$$ \begin{aligned} \lambda V_{jN} (p) & = \frac{1}{2}[\theta A - \tau + V_{jN}^{\prime } (p)]^{2} + \frac{{[\tau - V_{jN}^{\prime } (p)]^{2} }}{2c} \\ &\quad+\, V_{jN}^{\prime } (p)\left[A - \tau + V_{iN}^{\prime } (p) - \,\frac{{\tau - V_{iN}^{\prime } (p)}}{c - \varepsilon }\right] - \beta Dp(t) - \delta V_{jN}^{\prime } (p)p(t) \\ \end{aligned} $$
(A4)

For \( m = i,j \), we guess the form the value functions \( V_{mN} (p) \) to be linear in p, that is,

$$ V_{iN} (p) = k_{iN} + f_{iN} p,\quad V_{jN} (p) = k_{jN} + f_{jN} p $$
(A5)

where \( f_{iN} \), \( k_{iN} \), \( f_{jN} \) and \( k_{jN} \) are constant coefficients. Then, we obtain these constant coefficients to verify that our guess is correct, that means the exact expressions of the value functions are linear. Differentiating Eq. (A5) with respect to p, we obtain \( V_{iN}^{\prime } (p) = f_{iN} \), \( V_{jN}^{\prime } (p) = f_{jN} \) which when substituted into (A3) and (A4) gives

$$\begin{aligned} \lambda (k_{iN} + f_{iN} p) &= \frac{1}{2}[A - \tau + f_{iN} ]^{2} + \frac{{[\tau - f_{iN} ]^{2} }}{2(c - \varepsilon )}\\ & \quad + f_{iN} \left[ {\theta A - \tau + f_{jN} - \frac{{\tau - f_{jN} }}{c}} \right] - Dp(t) - \delta f_{iN} p(t)\end{aligned} $$
(A6)
$$\begin{aligned} \lambda (k_{jN} + f_{jN} p) &= \frac{1}{2}[\theta A - \tau + f_{jN} ]^{2} + \frac{{[\tau - f_{jN} ]^{2} }}{2c}\\ & \quad + f_{jN} \left[ {A - \tau + f_{iN} - \frac{{\tau - f_{iN} }}{c - \varepsilon }} \right] - \beta Dp(t) - \delta f_{jN} p(t)\end{aligned} $$
(A7)

Then, we can derive \( f_{iN} \), \( k_{iN} \), \( f_{jN} \), \( k_{jN} \) from (A6) and (A7), as follows:

$$ f_{iN} = \frac{ - D}{\lambda + \delta },\quad f_{jN} = \frac{ - \beta D}{\lambda + \delta } $$
(A8)
$$\begin{aligned} k_{iN} &= \frac{1}{2\lambda }\left( {A - \tau - \frac{D}{\lambda + \delta }} \right)^{2} + \frac{{[\tau (\lambda + \delta ) + D]^{2} }}{{2\lambda (\lambda + \delta )^{2} (c - \varepsilon )}}\\ & \quad - \frac{D}{\lambda (\lambda + \delta )}\left[ {\theta A - \tau - \frac{\beta D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + \beta D}{c(\lambda + \delta )}} \right]\end{aligned} $$
(A9)
$$\begin{aligned} k_{jN} &= \frac{1}{2\lambda }\left( {\theta A - \tau - \frac{\beta D}{\lambda + \delta }} \right)^{2} + \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2c\lambda (\lambda + \delta )^{2} }}\\ & \quad - \frac{\beta D}{\lambda (\lambda + \delta )}\left[ {A - \tau - \frac{D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + D}{(c - \varepsilon )(\lambda + \delta )}} \right]\end{aligned} $$
(A10)

Substituting (A8), (A9), and (A10) into \( V_{mN}^{\prime } (p) \) and from (A1) and (A2), we can determine the Markov-perfect Nash equilibrium outputs, optimal proportions of pollutants that the regions choose to abate, and net revenues.

Appendix 2 for Corollary 1

The steady-state equilibrium decisions of \( E_{iN}^{**} \), \( E_{jN}^{**} \) and \( \alpha_{iN}^{**} \), \( \alpha_{jN}^{**} \) are the same as those in (6a) and (6b) in Scenario N. The steady state \( V_{iN}^{**} \), \( V_{jN}^{**} \) can be obtained by inserting \( p_{N}^{**} \) into (6c) and (6d). Thus,

$$ \begin{aligned} V_{iN}^{**} (p) & = - \frac{D}{\lambda + \delta }p_{N}^{**} + \frac{1}{2\lambda }\left( {A - \tau - \frac{D}{\lambda + \delta }} \right)^{2} + \frac{{[\tau (\lambda + \delta ) + D]^{2} }}{{2\lambda (\lambda + \delta )^{2} (c - \varepsilon )}}\\ &\qquad - \frac{D}{\lambda (\lambda + \delta )}\left[ {\theta A - \tau - \frac{\beta D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + \beta D}{c(\lambda + \delta )}} \right] \\ V_{jN}^{**} (p) & = - \frac{\beta D}{\lambda + \delta }p_{N}^{**} + \frac{1}{2\lambda }\left( {\theta A - \tau - \frac{\beta D}{\lambda + \delta }} \right)^{2} + \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2c\lambda (\lambda + \delta )^{2} }}\\ & \qquad - \frac{\beta D}{\lambda (\lambda + \delta )}\left[ {A - \tau - \frac{D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + D}{(c - \varepsilon )(\lambda + \delta )}} \right] \\ \end{aligned} $$

In the aforementioned equations, \( p_{N}^{**} \) is given in Eq. (6e). We can subsequently derive

$$ \begin{aligned} & \frac{{\partial E_{iN}^{**} (t)}}{\partial \tau } = - 1 < 0,\quad \frac{{\partial E_{jN}^{**} (t)}}{\partial \tau } = - 1 < 0 \\ & \frac{{\partial \alpha_{iN}^{**} (t)}}{\partial \tau } = \frac{{A(\lambda + \delta )^{2} }}{{(c - \varepsilon )[(A - \tau )(\lambda + \delta ) - D]^{2} }} > 0,\\ & \frac{{\partial \alpha_{jN}^{**} (t)}}{\partial \tau } = \frac{{\theta A(\lambda + \delta )^{2} }}{{c[(\theta A - \tau )(\lambda + \delta ) - \beta D]^{2} }} > 0 \\ & \frac{{\partial \alpha_{iN}^{**} (t)}}{\partial \varepsilon } = \frac{\tau (\lambda + \delta ) + D}{{(c - \varepsilon )^{2} (\lambda + \delta )(A - \tau - \frac{D}{\lambda + \delta })}} > 0 \\ & \frac{{\partial s_{iN}^{**} }}{\partial \lambda } = - \frac{D}{{(c - \varepsilon )(\lambda + \delta )^{2} }} < 0,\quad \frac{{\partial s_{jN}^{**} }}{\partial \lambda } = - \frac{\beta D}{{c(\lambda + \delta )^{2} }} < 0 \\ & \frac{{\partial V_{iN}^{**} }}{\partial p} = - \frac{D}{\lambda + \delta } < 0,\quad \frac{{\partial V_{jN}^{**} }}{\partial p} = - \frac{\beta D}{\lambda + \delta } < 0 \\ \end{aligned} $$

Then, we can obtain the conclusions of Corollary 1.

Appendix 3 for Proposition 2

The first-order conditions of \( E_{iR}^{*} \), \( E_{jR}^{*} \), \( \alpha_{iR}^{*} \), and \( \alpha_{jR}^{*} \) are calculated as follows:

$$ E_{iR}^{*} (t) = A - \tau + V_{iR}^{\prime } (p),\quad \alpha_{iR}^{*} (t) = \frac{{\tau - V_{iR}^{\prime } (p)}}{{(c - \varepsilon )[A - \tau + V_{iR}^{\prime } (p)]}} $$
(A11)
$$ E_{jR}^{*} (t) = \theta A - \tau + V_{jR}^{\prime } (p),\quad \alpha_{jR}^{*} (t) = \frac{{\tau - \omega - V_{jR}^{\prime } (p)}}{{(c - \varepsilon )[\theta A - \tau + V_{jR}^{\prime } (p)]}} $$
(A12)

By substituting (A11) and (A12) into (8a) and (8b), we have

$$\begin{aligned} \lambda V_{iR} (p) &= \frac{1}{2}[A - \tau + V_{iR}^{\prime } (p)]^{2} + \frac{{[\tau - V_{iR}^{\prime } (p)]^{2} }}{2(c - \varepsilon )}\\ & \quad + V_{iR}^{\prime } (p)\left[ {\theta A - \tau + V_{jR}^{\prime } (p) - \frac{{\tau - V_{jR}^{\prime } (p) - \omega }}{c - \varepsilon }} \right] \\ & \quad- Dp(t) - \delta V_{iR}^{\prime } (p)p(t)\end{aligned} $$
(A13)
$$\begin{aligned} \lambda V_{jR} (p) &= \frac{1}{2}[\theta A - \tau + V_{jR}^{\prime } (p)]^{2} + \frac{{[V_{jR}^{\prime } (p) - \tau + \omega ]^{2} }}{2(c - \varepsilon )}\\ & \quad + V_{jR}^{\prime } (p)\left[A - \tau + V_{iR}^{\prime } (p) - \frac{{\tau - V_{iR}^{\prime } (p)}}{c - \varepsilon }\right] \\ & \quad- \beta Dp(t) - \delta V_{jR}^{\prime } (p)p(t)\end{aligned} $$
(A14)

From (A13) and (A14), we conjecture that the structures of (A13) and (A14) can be regarded as linear value functions:

$$ V_{iR} (p) = k_{iR} + f_{iR} p,\quad V_{jR} (p) = k_{jR} + f_{jR} p $$
(A15)

We then obtain \( V_{iR}^{\prime } (p) = f_{iR} \), \( V_{jR}^{\prime } (p) = f_{jR} \) and substitute \( V_{iR}^{\prime } (p),V_{jR}^{\prime } (p) \) into (A13) and (A14):

$$\begin{aligned} \lambda (k_{iR} + f_{iR} p) &= \frac{1}{2}[A - \tau + f_{iR} ]^{2} + \frac{{[\tau - f_{iR} ]^{2} }}{2(c - \varepsilon )} + f_{iR} \left[\theta A - \tau + f_{jR} - \frac{{\tau - f_{jR} - \omega }}{c - \varepsilon }\right]\\ & \qquad + \frac{{\omega [\tau - f_{jR} - \omega ]}}{c - \varepsilon } - Dp(t) - \delta f_{iR} p(t)\end{aligned} $$
(A16)
$$\begin{aligned} \lambda (k_{jR} + f_{jR} p) &= \frac{1}{2}[\theta A - \tau + f_{jR} ]^{2} + \frac{{[f_{jR} - \tau + \omega ]^{2} }}{2(c - \varepsilon )}\\ & \quad + f_{jR} \left[A - \tau + f_{iR} - \frac{{\tau - f_{iR} }}{c - \varepsilon }\right] - \beta Dp(t) - \delta f_{jR} p(t)\end{aligned} $$
(A17)

We can determine \( f_{iR} \), \( k_{iR} \), \( f_{jR} \), \( k_{jR} \) from (A16) and (A17):

$$ f_{iR} = \frac{ - D}{\lambda + \delta },\quad f_{jR} = \frac{ - \beta D}{\lambda + \delta } $$
(A18)
$$\begin{aligned} k_{iR} &= \frac{1}{2\lambda }\left(A - \tau - \frac{D}{\lambda + \delta }\right)^{2} + \frac{{[\tau (\lambda + \delta ) + D]^{2} }}{{2\lambda (\lambda + \delta )^{2} (c - \varepsilon )}}\\ & \quad - \frac{D}{\lambda (\lambda + \delta )}\left[ {\theta A - \tau - \frac{\beta D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + \beta D}{c(\lambda + \delta )}} \right] + \frac{{\tau \omega (\lambda + \delta ) + \beta \omega D - \omega^{2} (\lambda + \delta )}}{\lambda (c - \varepsilon )(\lambda + \delta )}\end{aligned} $$
(A19)
$$\begin{aligned} k_{jR} &= \frac{1}{2\lambda }\left(\theta A - \tau - \frac{\beta D}{\lambda + \delta }\right)^{2} + \frac{{[ - \tau (\lambda + \delta ) - \beta D + \omega (\lambda + \delta )]^{2} }}{{2\lambda (c - \varepsilon )(\lambda + \delta )^{2} }}\\ & \quad - \frac{\beta D}{\lambda (\lambda + \delta )}\left[ {A - \tau - \frac{D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + D}{(c - \varepsilon )(\lambda + \delta )}} \right]\end{aligned} $$
(A20)

Substituting (A18), (A19), and (A20) into \( V_{mR}^{\prime } (p) \) and referring to (A11) and (A12), we obtain the equilibrium outputs, optimal proportion of pollutants that the region chooses to reduce, and net revenues.

Appendix 4 for Proposition 3

Similar to the aforementioned analysis, the first-order conditions of \( E_{iF}^{*} \), \( E_{jF}^{*} \), \( \alpha_{iF}^{*} \), and \( \alpha_{jF}^{*} \) are as follows:

$$ E_{iF}^{*} (t) = A - \tau + V_{iF}^{\prime } (p),\quad \alpha_{iF}^{*} (t) = \frac{{\tau - V_{iF}^{\prime } (p)}}{{(c - \varepsilon )[A - \tau + V_{iF}^{\prime } (p)]}} $$
(A21)
$$ E_{jF}^{*} (t) = \theta A - \tau + V_{jF}^{\prime } (p),\quad \alpha_{jF}^{*} (t) = \frac{{\tau - V_{jF}^{\prime } (p)}}{{(c - \varepsilon )[\theta A - \tau + V_{jF}^{\prime } (p)]}} $$
(A22)

Substituting (A21) and (A22) into (10a) and (10b), we obtain following HJB equations:

$$\begin{aligned} \lambda V_{iF} (p) &= \frac{1}{2}[A - \tau + V_{iF}^{\prime } (p)]^{2} + \frac{{[\tau - V_{iF}^{\prime } (p)]^{2} }}{2(c - \varepsilon )}\\ & \quad + V_{iF}^{\prime } (p)\left[ {\theta A - \tau + V_{jF}^{\prime } (p) - \frac{{\tau - V_{jF}^{\prime } (p)}}{c - \varepsilon }} \right] \\ & \quad- Dp(t) - \delta V_{iF}^{\prime } (p)p(t)\end{aligned} $$
(A23)
$$\begin{aligned} \lambda V_{jF} (p) &= \frac{1}{2}[\theta A - \tau + V_{jF}^{\prime } (p)]^{2} + \frac{{[\tau - V_{jF}^{\prime } (p)]^{2} }}{2(c - \varepsilon )}\\ & \quad + V_{jF}^{\prime } (p)\left[ {A - \tau + V_{iF}^{\prime } (p) - \frac{{\tau - V_{iF}^{\prime } (p)}}{c - \varepsilon }} \right] \\ & \quad- \beta Dp(t) - \delta V_{jF}^{\prime } (p)p(t)\end{aligned} $$
(A24)

Following the analysis for Scenario R, we then determine that the value function of the firm is linear in p; that is,

$$ V_{iF} (p) = k_{iF} + f_{iF} p,\quad V_{jF} (p) = k_{jF} + f_{jF} p $$
(A25)

Similar to the aforementioned analysis, we can obtain \( V_{iF}^{\prime } (p) = f_{iF} \), \( V_{jF}^{\prime } (p) = f_{jF} \), substitute it into (A23) and (A24), and determine \( f_{iF} \), \( k_{iF} \), \( f_{jF} \), \( k_{jF} \), as follows:

$$ f_{iF} = \frac{ - D}{\lambda + \delta },\quad f_{jF} = \frac{ - \beta D}{\lambda + \delta } $$
(A26)
$$\begin{aligned} k_{iF} &= \frac{1}{2\lambda }(A - \tau - \frac{D}{\lambda + \delta })^{2} + \frac{{[\tau (\lambda + \delta ) + D]^{2} }}{{2\lambda (\lambda + \delta )^{2} (c - \varepsilon )}}\\ & \quad - \frac{D}{\lambda (\lambda + \delta )}\left[ {\theta A - \tau - \frac{\beta D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + \beta D}{(c - \varepsilon )(\lambda + \delta )}} \right]\end{aligned} $$
(A27)
$$\begin{aligned} k_{jF} &= \frac{1}{2\lambda }\left( {\theta A - \tau - \frac{\beta D}{\lambda + \delta }} \right)^{2} + \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2(c - \varepsilon )\lambda (\lambda + \delta )^{2} }}\\ & \quad - \frac{\beta D}{\lambda (\lambda + \delta )}\left[ {A - \tau - \frac{D}{\lambda + \delta } - \frac{\tau (\lambda + \delta ) + D}{(c - \varepsilon )(\lambda + \delta )}} \right]\end{aligned} $$
(A28)

Substituting (A26), (A27), and (A28) into \( V_{mF}^{\prime } (p) \), and referring to (A21) and (A22), we can derive the equilibrium outputs, optimal proportion of pollutants that the region chooses to reduce, and net revenues.

Appendix 5 for Proposition 4

$$ \begin{aligned} V_{jR}^{*} - V_{jN}^{*} & = \frac{{[\omega (\lambda + \delta ) - \tau (\lambda + \delta ) - \beta D]^{2} }}{{2(c - \varepsilon )(\lambda + \delta )^{2} \lambda }} - \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2c(\lambda + \delta )^{2} \lambda }} \\ & = \frac{{c[\omega (\lambda + \delta ) - \tau (\lambda + \delta ) - \beta D]^{2} - (c - \varepsilon )[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2c(c - \varepsilon )(\lambda + \delta )^{2} \lambda }} \\ \end{aligned} $$
(A29)

We determine the optimal per-unit royalty licensing fee \( \omega^{*} \) when \( V_{jR}^{*} (p) - V_{jN}^{*} (p) = 0 \). For region i, we have

$$ \begin{aligned} V_{iR}^{*} - V_{iN}^{*} & = \frac{D[(\tau - \omega )(\lambda + \delta ) + \beta D]}{{\lambda (c - \varepsilon )(\lambda + \delta )^{2} }} - \frac{D[\tau (\lambda + \delta ) + \beta D]}{{\lambda c(\lambda + \delta )^{2} }} + \frac{\omega [(\tau - \omega )(\lambda + \delta ) + \beta D]}{\lambda (c - \varepsilon )(\lambda + \delta )} \\ & = \frac{D[\varepsilon \tau (\lambda + \delta ) - c\omega (\lambda + \delta ) + \varepsilon \beta D]}{{\lambda c(c - \varepsilon )(\lambda + \delta )^{2} }} + \frac{\omega [(\tau - \omega )(\lambda + \delta ) + \beta D]}{(c - \varepsilon )(\lambda + \delta )\lambda } \\ \end{aligned} $$
(A30)

Substituting the steady-state \( \omega^{*} \) into (A30), we obtain

$$\begin{aligned} V_{iR}^{*} - V_{iN}^{*} &= \frac{{[ - c + \varepsilon + \sqrt {c(c - \varepsilon )} ]D[\tau (\lambda + \delta ) + \beta D]}}{{c\lambda (c - \varepsilon )(\lambda + \delta )^{2} }} \\ & \quad + \frac{{[c - \sqrt {c(c - \varepsilon )} ][\sqrt {c(c - \varepsilon )} ][\tau (\lambda + \delta ) + \beta D]^{2} }}{{\lambda c^{2} (c - \varepsilon )(\lambda + \delta )^{2} }}\end{aligned} $$
(A31)

Evidently, the polynomial \( [ - c + \varepsilon + \sqrt {c(c - \varepsilon )} ] > 0 \), \( c - \sqrt {c(c - \varepsilon )} \) when \( c > \varepsilon > 0 \); thus, \( V_{iR}^{*} - V_{iN}^{*} > 0 \). For \( \alpha_{iR}^{*} \), \( \alpha_{iN}^{*} \), \( \alpha_{jR}^{*} \), \( \alpha_{jN}^{*} \),

$$ \alpha_{iR}^{*} (t) - \alpha_{iN}^{*} (t) = \frac{\tau (\lambda + \delta ) + D}{{(c - \varepsilon )(\lambda + \delta )(A - \tau - \frac{D}{\lambda + \delta })}} - \frac{\tau (\lambda + \delta ) + D}{{(c - \varepsilon )(\lambda + \delta )(A - \tau - \frac{D}{\lambda + \delta })}} = 0 $$
(A32)
$$ \alpha_{jR}^{*} (t) - \alpha_{jN}^{*} (t) = \frac{{[\sqrt {c(c - \varepsilon )} - c + \varepsilon ][\tau (\lambda + \delta ) + \beta D]}}{{c(c - \varepsilon )(\lambda + \delta )(\theta A - \tau - \frac{\beta D}{\lambda + \delta })}} $$
(A33)

In accordance with (A33), \( \alpha_{iR}^{*} - \alpha_{iN}^{*} > 0 \) in the steady state, and \( E_{iN}^{*} = E_{iR}^{*} \), \( E_{jN}^{*} = E_{jR}^{*} \).

On the basis of (A29)–(A33), we can determine the condition of Proposition 4.

Appendix 6 for Proposition 5

The proof is similar to that of Proposition 4, which is derived from (6c), (6d) and (12c), (12d), gives as follows:

$$ \begin{aligned} V_{jF}^{*} - V_{jN}^{*} & = \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2\lambda (c - \varepsilon )(\lambda + \delta )^{2} }} - \frac{{[\tau (\lambda + \delta ) + \beta D]^{2} }}{{2\lambda c(\lambda + \delta )^{2} }} - M \\ & = \frac{{\varepsilon [\tau (\lambda + \delta ) + \beta D]^{2} }}{{2\lambda c(c - \varepsilon )(\lambda + \delta )^{2} }} - M \\ \end{aligned} $$
(A34)
$$ V_{iF}^{*} - V_{iN}^{*} = \frac{\varepsilon D[\tau (\lambda + \delta ) + \beta D]}{{\lambda c(c - \varepsilon )(\lambda + \delta )^{2} }} + M > 0 $$
(A35)

For \( V_{jF}^{*} - V_{jN}^{*} = 0 \), we can calculate the equilibrium \( M^{*} = \frac{{\varepsilon [\tau (\lambda + \delta ) + \beta D]^{2} }}{{2\lambda c(c - \varepsilon )(\lambda + \delta )^{2} }} \) in the steady state.

Similarly, referring to (6a), (6b) and (12a), (12b), we derive

$$ \begin{aligned} \alpha_{jF}^{*} - \alpha_{jN}^{*} & = \frac{\tau (\lambda + \delta ) + \beta D}{{(c - \varepsilon )(\lambda + \delta )(\theta A - \tau - \frac{\beta D}{\lambda + \delta })}} - \frac{\tau (\lambda + \delta ) + \beta D}{{c(\lambda + \delta )(\theta A - \tau - \frac{\beta D}{\lambda + \delta })}} \\ & = \frac{\varepsilon [\tau (\lambda + \delta ) + \beta D]}{{c(c - \varepsilon )(\lambda + \delta )(\theta A - \tau - \frac{\beta D}{\lambda + \delta })}} > 0 \\ \end{aligned} $$
(A36)
$$ \alpha_{iF}^{*} - \alpha_{iN}^{*} = \frac{\tau (\lambda + \delta ) + D}{{(c - \varepsilon )(\lambda + \delta )(A - \tau - \frac{D}{\lambda + \delta })}} - \frac{\tau (\lambda + \delta ) + D}{{(c - \varepsilon )(\lambda + \delta )(A - \tau - \frac{D}{\lambda + \delta })}} = 0 $$
(A37)

The total outputs of the two regions remain unchanged (\( E_{iN}^{*} = E_{iF}^{*} \), \( E_{jN}^{*} = E_{jF}^{*} \)); thus, Proposition 5 can be directly obtained from the aforementioned proofs.

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Xu, H., Tan, D. Optimal Abatement Technology Licensing in a Dynamic Transboundary Pollution Game: Fixed Fee Versus Royalty. Comput Econ 61, 905–935 (2023). https://doi.org/10.1007/s10614-019-09909-8

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