Understanding the distributional effects of climate policy is crucial for designing measures that are politically feasible. These effects are closely linked to the increase in fossil prices caused by climate policy, which in turn depends strongly on the induced technological advances and the availability and scalability of fossil-free technologies. To date, however, most numerical studies treat energy substitution and technological progress as exogenous. This chapter adds to the literature by numerically quantifying the equity and efficiency effects of climate policy when energy substitution and technological progress are endogenous as opposed to their exogenous counterparts. To represent the macroeconomic framework of climate policy, I employ the dynamic, multi-sectoral CGE model CITE, which features endogenous growth driven by specialization gains in production, heterogeneous households with a labor-leisure choice and an endogenous elasticity of substitution that flexibly interacts with the relative share of clean energy in the economy. Using data for the Swiss economy, I find that—although beneficial to the economy as a whole—a lump-sum redistributed carbon tax disproportionately favors high-income households when energy substitution and technological change evolve dynamically over time.

We construct an overlapping generations model for the global South in which the choice between dirty and clean technology hinges on the economy’s capital stock, susceptible to climate-induced depreciation. The process of capital accumulation contributes to environmental emissions, yet its intensity can be mitigated through a shift to cleaner production. The tipping point of technological transition is endogenously determined, leading to a diverse range of potential long-term outcomes shaped by capital endowment, pollution intensity, climate vulnerability, and clean factor productivity. Our analysis reveals the possibility of the economy converging into a “carbon trap”, characterized by a sustained equilibrium marked by elevated pollution and diminished income, despite the feasibility of pursuing green growth. Additionally, we present optimal policy measures and simulations that highlight the temporal disparities between the socially optimal timing for transitioning to green technology and the timing dictated by market forces. Finally, to account for the high upfront costs of starting clean production, we extend the model by including a non-convexity in the production structure of the clean technology.

There is widespread concern that climate policy is moving too slowly and that decarbonization is coming too late for effective climate protection. We analyze three different empirically relevant effects that emerge endogenously during decarbonization and amplify current policies: growing substitutability of dirty with clean energy inputs, learning and scale effects in renewable energies, and efficiency improvements in the application of energy. We employ the CITE simulation model, a dynamic computable general equilibrium (CGE) model with endogenous growth, to represent the macroeconomic framework of climate policy, calibrate the impacts, and obtain quantitative results. We use data for the Swiss economy and find that all three effects significantly accelerate decarbonization and markely reduce the costs of climate policy, with increasing energy substitutability having the strongest impact. Targeted policies such as subsidies to clean energy and R&D may amplify these effects and thereby speed up the transition towards a carbon-free economy.

Solving major sustainability problems such as climate change and the loss of biodiversity requires overcoming a fundamental dilemma: on the one hand, central decisions on the realignment of the economy and society should be quick and far-reaching, on the other hand, actual decision-makers are strongly oriented towards established structures, which entail great inertia and path dependencies. As a result, expectations and reality are often still far apart in sustainability policy. Tipping processes can play a decisive role in closing this gap and generally describe a non-linear and self-sustaining dynamic which can be triggered when a critical threshold (a tipping point) is crossed. The targeted promotion of crossing important thresholds can thus become a successful strategy for sustainability policy. In this paper, we highlight the importance and limitations of tipping dynamics in promoting sustainability. We develop an integrative formal approach to illustrate the characteristics of tipping dynamics in nature, technology, politics, society and the economy, and deepen the discussion using two case studies from economic history. Finally, we discuss implications for research, policy and institutions.