Simulated Effects of U. S. Withdrawal from Paris Agreement under Four Scenarios
Abstract: Under the Paris Agreement framework, many developing countries call for low-carbon technology transfers from developed countries as a critical element in the global partnership for carbon emissions abatement. Such a partnership may be disrupted as the U.S. walks away from the agreement. Based on CIECIA-TD model, this paper examines effects of the U.S. exit on global low-carbon technology transfers under various scenarios and simulates the effects on low-carbon technology transfer, climate change, countries’ emissions abatement results, and economic development. Our findings suggest that lowcarbon technology has significant emissions abatement and temperature rise mitigation effects. Low-carbon technology transfer among developed countries offers huge emissions abatement potentials, but patent protection system presents a significant barrier to further carbon emissions abatement. In this sense, the U.S. exit from the Paris Agreement will significantly impede developed countries’ carbon emissions abatement through technology transfer. With limited knowhow, R&D and learning capacity, developing countries will suffer more to cut carbon emissions under the chain effects of a more challenging technology sharing environment that may result from the U.S. exit from the Paris Agreement. As a gradualist emissions abatement approach, low-carbon technology transfer cannot reduce emissions substantially within a short time, but its climate welfare is conducive to global economic growth and of great significance to carbon governance.
Keywords: Paris Agreement, low- carbon technology transfer, carbon emissions abatement, nationally determined contributions (NDC), integrated assessment model
JEL Classification Codes: F47; D58, O11, O33, Q56
DOI:1 0.19602/j .chinaeconomist.2019.9.05
1. Introduction
The United National Framework Convention on Climate Change (UNFCCC) stipulates the principle of “common but differentiated responsibilities,” under which developed countries must provide various forms of assistance to developing countries to help them reduce carbon emissions (UNFCCC, 1992).
Low-carbon technology R&D and application are widely considered as critical means for developed countries to assist developing countries to cut carbon emissions (IPCC, 2007; Ockwell et al., 2008; Pueyo, 2013). Since the Kyoto Protocol’s effectiveness, the obligation of developed countries to provide developing countries with low-carbon technology support has been a critical part of international climate agreements. The Paris Agreement specifies mid- and short-term emissions abatement targets for various countries in the form of nationally determined contributions (NDC). In their NDC documents, many developing countries have identified access to low-carbon technology support and cooperation as a condition for emissions abatement. The international transfer of low-carbon technology has become the most critical component of global climate change response actions under the Paris Agreement.
On June 1, 2017, U.S. President Donald Trump announced that the U.S. would withdraw from the Paris Agreement on the ground that the agreement would “harm the U.S. economy.” Trump’s statement has cast a shadow on international climate protection and cooperation endeavors. With the Kyoto Protocol set to expire after 2020, this decision severely impedes global climate cooperation and sets a bad example that other countries may follow and delay emissions abatement or refuse to fulfill their emissions abatement commitments. It may also lead to the failure of the Paris Agreement. Zheng et al. (2017) believe that the U.S. exit will undermine global climate governance and climate cooperation process with multifaceted effects, dampening confidence in climate cooperation and setting a bad example for climate cooperation. Urpelainen and de Graaf (2018) contend that the U.S. withdrawal from the Paris Agreement itself will not cause much impact on global carbon emissions, but its potential political impact may jeopardize future global climate cooperation. Research on international lowcarbon technology transfer trends in the context of the U.S. withdrawal from the Paris Agreement and its impacts is of great relevance to global climate, carbon emissions abatement, and economic development, as well as global efforts on climate protection in the post-Kyoto Protocol era.
Most academic studies on low-carbon technology transfer focus on institutional factors like patents and intellectual property rights, and relevant policy measures (Shi and Lai, 2013). Based on the Porter hypothesis, Greaker and Rosendahl (2008) create a model to reveal environmental policy’s low-carbon technology spillover effects. Luo and Ye (2011) employ Logit model for an empirical analysis of lowcarbon technology transfer’s emissions abatement effect under the Clean Development Mechanism (CDM) for Chinese firms. With PV technology as an example, Lizuka (2013) discusses the role of technology transfer in the low-carbon transition of emerging economies. With the examples of electric vehicles, PV and integrated gasification combined cycle (IGCC), Rai et al. (2014) offer an analysis of how intellectual property rights system influences different types of low-carbon technology transfer to emerging economies. While studies as mentioned earlier investigate in detail the concept, types, process, and determinants of low-carbon technology transfer, they provide no estimate of carbon emissions reductions arising from technology transfer and cannot evaluate technology transfer’s effects on emissions abatement and control of temperature rise.
To evaluate low-carbon technology transfer’s emissions abatement, climate, and economic effects, we must conduct analysis and modeling of a series of technology transition processes involving innovation inputs, R&D, technology absorption and diffusion, as well as the interactions between technology progress and economic, environmental and policy factors. The multidisciplinary question of climate-economic complexities can be best examined with an integrated assessment model (IAM). While many IAMs have included technology innovation, diffusion and adoption mechanisms, drawbacks still exist (Grübler et al., 1999; Hübler et al., 2012).
Most energy technology models represented by AIM, C-GEM and EPPA use the autonomous energy efficiency improvement (AEEI) parameter to reflect the natural diffusion of low-carbon technologies (Jacoby, et al., 2006; Fujimori et al., 2012; Qi et al., 2016; Zhang et al., 2015; Morris et al., 2019). Since this mechanism only reflects the emissions abatement effect from low-carbon technology diffusion at the macro level, EPPA and C-GEM respectively create a supporting technology sector outside conventional
economic sectors and exogenous technology penetration to reflect the diffusion and use of specific technologies ( such as CCS, shale gas, bioelectrogenesis). Kypreos ( 2007) introduces endogenous technology progress in MERGE model, reduces existing R&D input through “learning by doing” and “learning by searching,” and increases the market share of low-carbon technology through market incentives. WITCH model also follows a similar method to fit the reduction of existing R&D cost resulting from technology diffusion based on experience curve (Bosetti, et al., 2009). This method may only depict the cost reduction arising from technology diffusion in the statistical sense and lacks a micromechanism. Based on REMIND model, Hübler et al. (2012) design an endogenous technology progress module, which includes such behaviors as technology innovation, imitation and R&D investment, but its diffusion mechanism determines the speed of technology imitation for various countries based on average global technology level (technology pool), which makes it hard to carry out a policy analysis on low-carbon technology transfer.
Due to the needs of model simplification, IAM based on macroeconomic model cannot express technology development and adoption process at the micro level. On the other hand, the bottomup IAM lacks endogenous technology progress mechanism due to an inadequate macroeconomic system. To address this problem, this study employs an integrated model CIECIA-TD to combine the macroeconomic model with technology transfer mechanism at the micro level. We introduce a technology diffusion mechanism based on individual imitation in a multi-country, multi-sector general equilibrium model. As the prototype of CIECIA-TD, the CIECIA model depicts economic relationships between countries/sectors under general equilibrium conditions of the global economy in a multicountry, multi-sector general equilibrium model. It can examine and evaluate the economic effects of climate change and mitigation measures (Gu and Wang, 2015; Wang, et al., 2016). Further, CIECIA-TD introduces a technology transfer and diffusion model based on individual behaviors at the micro level and achieves the micro-level mechanism of low-carbon technology diffusion with countries/sector as technology transferors.
Based on CIACIE-TD model, this paper simulates trends in global low-carbon technology transfer under different scenarios and its effects on countries’ carbon reduction and economic performance, as well as control of global surface temperature rise. It evaluates the carbon reduction effectiveness and feasibility of low-carbon technology transfer after the U.S. exit from the Paris Agreement.
2. Technology Transfer Model
After technology transfer, there is still a learning curve for the recipient to be able to use the technology. This learning curve, along with the patent system that inhibits technology diffusion, poses barriers to technology transfer (Pueyo, 2013). Based on Kennedy and Basu (2013), this paper considers that technology diffusion is inhibited by institutional barriers - IPR and patent protection system - and knowledge-investment barriers with limited knowledge reserve and investment, recipients are slow imitators and learners.
In the model, CIECIA introduces the concepts of knowledge capital and technology progress and employs random logarithm as a shock to process technology development (Buonanno, et al., 2003; Lorentz and Savona, 2008; Gong, et al., 2013). Technology progress is reflected in a falling demand for intermediate inputs for the production of each unit of product. It denotes low-carbon technology in a broad sense (Gu and Wang, 2018). On such a basis, CIECIA-TD improves an Agent-based innovation diffusion and technology spillover model (Yao, 2009; Wang, et al., 2014) by linking its technology transfer process with CIECIA model’s technology progress module. In the technology diffusion model, technology transfer is divided into three stages: technology search, selection, and imitation. Each group of technology levels in a particular sector of a country is regarded as
an independent technology ( ak, j,i,t is the sector’s intermediate demand coefficient). In technology transfer process, inter-sectoral technology transfer is depicted by R&D acceleration s and transfer threshold W. R&D acceleration reflects technology learner’s ability to absorb advanced technology and denotes the knowledge-investment barrier to technology transfer. Technology transfer threshold indicates the degree to which patented technologies are shared and represents the institutional barrier to technology transfer.
2.1 Technology Search
In the technology search stage, a sector of a country looks for a group of low-carbon technology transfer sources on a global scale. The criteria are divided into two parts: technology level and economic development level. Each sector may only introduce technology from the same sector of other countries/ blocs. If a sector boasts the highest level of technology in the world, it may only act as a technology provider.
In equation (1), is the set of feasible sources of technology transfer that can be searched by sector i of country j in period t. K is a feasible source technology; Wj, k is technology transfer threshold; cj, i,t is unit production cost (i.e. level of process technology); xj, i,t is per capita value-added, which denotes the imitator’s economic development criteria in selecting technology provider.
2.2 Technology Selection
After identifying a group of feasible technology transfer sources, the imitator needs to select one source to learn from. Based on technology catch-up and inertia effects, CIECIA-TD depicts the attraction between a sector of a country and the feasible technology sources in the form of spatial interaction force (Wang, et al., 2014).
Technology catch-up is manifested in the catch-up effect arising from technology gaps (Yao, 2009). The model is the same with Wang, et al. (2001), who believe that technology gaps are the primary impetus for technology diffusion, while the effect of economic gaps cannot be neglected. This paper specifies the technology gap between sector i of country j and sector i of country k as the ratio between their unit costs. Economic gap is the ratio between their per capita value-added. Taken into account the technology selection effect of technology transfer threshold Wj, k , we have:
In equation (2), is the intensity of technology catch-up between sector i of country j and sector i of country k; is intensity parameter; is intensity change factor.
0
After a country receives a technology transfer from another country, it may become reliant on such cooperation. is specified as the number of technology transfers between sector i of country j and sector i of country k that occurred before period t. Then, the intensity of technology reliance is:
In equation (3), v is intensity parameter, and is intensity change factor. Technology attraction intensity can be expressed as:
In terms of technology gaps and inclinations for cooperation, inter-sectoral technology attraction intensity provides decision-making probability basis for various sectors in selecting technology sources to learn from.
2.3 Technology Learning
After determining the technology sources, the imitator will acquire an R&D acceleration within the transfer threshold range, which enables it to complete this part of R&D work at an accelerated speed. Outside the transfer threshold, however, the imitator must independently carry out its R&D activities under the restriction of patent protection system. Therefore, CIECIA’s technology shock equation can be rewritten as:
In equation (5), country is the technology provider selected by sector i of country j, and is the size of intermediate coefficient for the target technology. After the sector reduces the intermediate coefficient to at s speed, it must independently conduct remaining R& D from
3. Scenario Simulation
To reflect the effects of low-carbon technology transfer on climate protection, emissions abatement and economy, our baseline scenario for comparing simulation results is free from the technology transfer mechanism. The U.S. exit from the Paris Agreement may shake global climate protection and cooperation to their foundation. Meanwhile, anti-globalization and trade protectionism is on the rise globally, particularly in major developed countries. These trends cause uncertainties to international technology cooperation and aid. This paper designs four scenarios to examine how the U.S. exit from the Paris Agreement affects low-carbon technology transfer, emissions abatement and the economy. Under Scenario 1, this paper specifies R&D acceleration and technology transfer values as 2 and 0.2 respectively, which represent technology diffusion and transfer between individual economies under normal conditions. Such specification is intended to reveal the trend of international low- carbon technology transfer under normal conditions.
Scenario 1: Assumes that the U.S. did not withdraw from the Paris Agreement, which reflects international low-carbon technology transfer under normal conditions;
Scenario 2: The U.S. starts to cease its technology transfer relations with other countries/blocs; Scenario 3: Based on Scenario 2, Japan, the EU and other developed countries will raise technology transfer threshold with other developed countries and other countries/blocs to 0.5 as of 2020;
Scenario 4: Based on Scenario 2, technology transfer threshold between all countries/blocs will be raised to 0.5 as of 2020; specifically, the technology transfer threshold of developed countries such as Japan and the EU with other countries/blocs will be raised to 1.
R&D accelerations in the four scenarios are all the same with Scenario 1, and Scenario 2 only considers the U.S. exit from the Paris Agreement and termination of low-carbon technology transfer with other countries, while Scenarios 3 and 4 also take into account the adverse chain effects that the U.S. exit may cause to countries’ participation in global cooperation for emissions abatement. As a result of the U.S. exit, countries may change their attitudes toward low-carbon technology aid, thus raising IPR and patent protection barriers. Due to the limit of length, we cannot list CIECIA’s baseline scenario simulation results. Please refer to Gu and Wang (2015) for details.
Table 1 shows the pre-industrial global surface temperature rises by 2100 under the four scenarios. Under Scenario 1, global surface temperature will increase by about 2.8°C over the pre-industrial level. This increase is way above the 2°C and 1.5°C targets set by the Paris Agreement, but is still significantly below 3.25°C under the baseline scenario. The implication is that international low-carbon technology transfers have great emissions abatement potentials. As the U.S. withdraws from the Paris Agreement and ceases to provide technology support to other countries/blocs, the rise of global surface temperature by 2100 under Scenario 2 is 0.05°C higher than Scenario 1. Moreover, the chain effects of institutional barriers raised by countries against technology transfer may cause global surface temperature rise to reach 2.94°C and about 3.06°C under Scenarios 3 and 4. Obviously, the U.S. withdrawal from the Paris Agreement may cause tremendous shocks to the control of rising temperature through low-carbon technology transfer.
Table 2 shows changes in the number of international low-carbon technology transfers under the four scenarios. Under Scenario 1, low-carbon technology transfer primarily occurs between developed countries and from developed to developing countries. Notably, technology transfer between developed countries is also rather frequent, which coincides with Kennedy and Basu’s (2013) findings. Since developed countries boast stronger R&D capabilities and higher technology levels than developing countries, they have a shorter learning curve in absorbing technology transfers from other countries. As developed countries become reluctant to transfer their technology after the U.S. exit, there will be a sharp reduction in the number of global low-carbon technology transfers, particularly those between developed countries, in our simulation process. Under Scenario 4, the number of global low-carbon technology transfers is less than a third that of Scenario 1, and only 40% are from developed countries. This result directly affects countries’ carbon emissions abatement volumes.
Prior to the Bonn climate change conference in November 2017, 190 countries/regions submitted 165 intended nationally determined contributions (INDCs) to the UNFCCC. Currently, 177 countries/ regions have converted INDCs into their first NDC documents. Countries have adopted varied forms
of mid- and short-term INDC/NDC emissions abatement targets, which include carbon emissions and intensity reductions. Base years include 1990, 2005 and the baseline scenario period, and target years range from 2025 to 2035. We define the INDC targets of countries yet to officially submit NDCs, including Russia, as their NDC targets and set 2030 as the NDC target year for other developed countries and high-, medium- and low-development countries. The method of emissions abatement is unified to be the abatement of carbon emissions. Please refer to Table 3 for the emissions abatement targets of countries/blocs.
Table 3 reveals changes in carbon emissions and intensity in NDC target years for countries under the four scenarios. China and India can achieve their NDC carbon intensity reduction targets under Scenario 1, and their carbon intensity will reduce by 72% and 55% respectively over 2005. China’s carbon emissions will peak in 2030, which meets its commitments under the China-U.S. Joint Statement on Climate Change and China’s Nationally Determined Contribution (NDC). Under Scenario 1, Japan’s carbon emissions will reduce by 39.76% by 2030 over 2005, which also achieves its NDC target.
Under the adverse impact of the U.S. exit from the Paris Agreement, countries’ emissions abatement ratios in NDC target years decline with rising technology transfer threshold. For developing countries, in particular, high- and medium-development countries will reduce their emissions by less than 3% in target years, which fall far short of their commitments. From Scenario 2 to Scenario 4, although China’s carbon intensity reduces by over 65% by 2030 in all scenarios, its carbon peak occurs after 2030 and cannot meet its commitments under the China-U.S. Joint Statement on Climate Change and China’s Nationally Determined Contribution (NDC).
As Figure 1 shows, under Scenario 1, India’s cumulative carbon emissions abatement ratio can reach around 50%, while those of China, medium-development and high-development countries are also above 20%. The implication is that international low-carbon technology transfer has a significant emissions abatement effect for developing countries. For the United States as the most critical technology source, its carbon emissions are affected little by technology transfer, while the carbon emissions of Japan and the European Union may also reduce by 15% under the Scenario 1. The implication is that frequent technology exchanges between developed countries are highly effective for their long-term emissions abatements. In future international carbon emissions abatement cooperation, technology transfer and aid should not be that from developed to developing countries. Technology sharing within developed countries may also vastly help reduce their carbon emissions.
With rising technology transfer threshold, countries will see a significant reduction in their
cumulative carbon emissions abatement ratios over the baseline scenario. After the U.S. exit from the Paris Agreement, developed countries will suffer an even greater impact on their carbon emissions reductions through low- carbon technology transfer. Under Scenario 2, Japan’s carbon emissions abatement ratio falls by 12 percentage points over Scenario 3, and those of the European Union and other advanced economies will also reduce by above five percentage points - a huge decline considering their limited emissions abatement ratios. Under Scenarios 3 and 4, carbon emissions abatement ratios are almost identical. For developing countries, the collapse of the Paris Agreement framework that may follow the U.S. exit and the further tightening of patent protection system by other countries may deal a more significant blow to their emissions abatement efforts. Under Scenario 2, India’s carbon emissions abatement ratio will reduce by less than two percentage points over Scenario 1, but under Scenario 4, its carbon emissions abatement ratio drops by more than 10 percentage points over Scenario 1. Since technology gaps are small between advanced economies, if their technology transfer threshold rises to 0.5, there is almost no feasible technology transfer source, so that further raising technology transfer threshold above 0.5 has a minimal effect on their carbon emissions. In comparison, developing countries are technologically less advanced with longer learning curves when they import technology from developed countries. When the U.S. walks away from the Paris Agreement, developing countries are still able to find replacement technology resources. Their carbon emissions will steadily increase with rising technology transfer threshold, but their emissions abatement ratio will not decline significantly.
Notably, although cumulative emissions abatement ratios of high-, medium- and low-development countries may reach 20% under Scenario 1, their carbon emissions abatement ratios in NDC years are less than 10%. The implication is that the emissions abatement potentials of low-carbon technology transfer take time to unleash, but technology transfer and learning take time. In other words, significant
emissions abatements are unlikely to achieve in the short term.
Figure 2 shows Keynes-Ramsey cumulative utility of countries during 2016-2100 under the four scenarios compared with the baseline scenario. The Keynes-Ramsey utility reflects changes in the economic prowess of countries throughout the simulation process in the form of intertemporal discount accumulation, and its expression is as follows:
In equation (6), UAj( T ) is the cumulative utility of country j by period T; is consumption; is population; is discount rate; is consumer time preference.
With rising institutional barriers such as patent protection represented by technology transfer threshold, the carbon emissions of countries will significantly increase under Scenarios 1 to 4, which will lead to rising global surface temperatures, falling climate welfare and finally a reduction in their cumulative utility. Under Scenario 1, the cumulative utilities of India, medium- and high-development countries will rise by over 1.2% compared with the baseline scenario, while the cumulative utilities of developed countries like the United States and Japan will also rise by more than 0.5%. Under Scenario 4, the cumulative utilities of India, medium-development and high-development countries will rise by a smaller degree of around 0.5% compared with the baseline scenario, while the increase in developed countries’ cumulative utility drops to about 0.3%. Despite the limited carbon emissions abatement effect in the short run, low-carbon technology transfer is a cost-efficient way of emissions abatement and brings about climate welfare conducive to world economic development. It reduces the economic losses
from emissions abatement. For such reasons, low-carbon technology transfer is of pivotal significance to carbon governance.
4. Conclusions and Discussions
In this paper, we employ the capital, industrial evolution and climate change integrated assessment (CIECIA-TD) model combined with a top-down economic model and a bottom-up technology transfer and diffusion model. We use technology transfer threshold and R&D acceleration to denote the degree to which advanced technologies are shared globally (institutional barrier) and the ability of imitators to absorb advanced technology (knowledge-investment barrier). By evaluating the climate, economic and carbon emissions abatement effects of low-carbon technology transfer in the context of the U.S. exit from the Paris Agreement, we made the following findings:
(1) Low-carbon technology transfer has significant effect on carbon emissions abatement and global warming control. Under Scenario 1, the global surface temperature rise may fall from 3.25°C to 2.8°C by 2100, and the cumulative emissions abatement ratios of developing countries like India and China may also exceed 20%. The implication is that low-carbon technology transfer has tremendous emissions abatement potentials. Countries will not be able to cut their emissions in NDC target years as much as they do on a cumulative basis during the simulation period, which suggests that the emissions abatement potentials of low- carbon technology transfer take time to materialize. While significant emissions abatement cannot be achieved in the short run, low-carbon technology transfer has a considerable long-term emissions abatement effect at a small cost, and thus is of great significance to carbon governance.
(2) The U.S. exit from the Paris Agreement is detrimental to the global climate partnership, and the potential chain effect has an extremely adverse impact on the international transfer of low-carbon technology. With strong R&D capabilities and technologies, developed countries have a short learning curve for low-carbon technologies within the threshold range. In this sense, patent and IPR protection systems represented by technology transfer threshold are major barriers to their further emissions abatement. Thus, the U.S. exit will cause a huge direct impact on developed countries’ carbon emissions abatement through technology transfer.
(3) For developing countries with limited know-how and R&D capacity, they still have a rather long learning curve within the threshold range and technologically lag far behind developed countries. For this reason, the U.S. exit from the Paris Agreement has a limited effect on developing countries’ carbon emissions abatement through technology transfer. However, an overall rise in institutional barriers against the transfer of low-carbon technologies still has a significant impact on their emissions abatement. Among them, China will be unable to achieve its NDC carbon peak target set for 2030 under the scenario of the U.S. exit from the Paris Agreement.
(4) While demand for low-carbon technology transfer mainly comes from developing countries, our simulation result reveals that under normal conditions, technology transfer between developed countries is exceptionally vibrant with significant emissions abatement effects and potentials. In future international climate cooperation, technology transfer should not be confined to that from developed to developing countries, and low-carbon technology sharing between developed countries also warrants close attention.
The key aspect of the CIECIA-TD model created in this paper is a multi-country, multi-sector general equilibrium model with data from input-output tables. Although technology diffusion mechanism from a micro perspective is integrated in our design, low- carbon technologies therein are still abstracted from the macro level. This model cannot capture the R& D, transfer, and diffusion of specific carbon emissions abatement technologies. Also, this paper assumes that technology progress is gradual and thus cannot reflect the emergence and diffusion of groundbreaking or
revolutionizing emissions abatement technologies. We intend to carry out further research to address these shortcomings.
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