Conference Agenda

This paper develops an integrated optimal control framework to address the dual challenges of rapid decarbonization and social equity in the context of a Just Transition. We construct a dynamic two-sector labor market model that captures the decline of the coal industry and the expansion of the green economy. By introducing a dedicated state variable, \( U_1^{tr}(t) \), to track coal-sector workers undergoing retraining, the model explicitly accounts for the delays and costs associated with labor market transitions. Policy interventions are represented by three control variables: \( u_{12} \) for retraining, \( u_{13} \) for job-matching support, and \( u_{22} \) for green-sector vacancy creation. The objective is to minimize a cost functional that penalizes unemployment—placing greater weight on coal-sector unemployment—and the direct costs of policy implementation. Using a Hamiltonian formulation, we derive the necessary optimality conditions and provide explicit characterizations of the time-dependent optimal policies. Numerical simulations, conducted with a forward–backward iterative scheme in Julia, illustrate the dynamic interplay between unemployment, employment, and sectoral transitions, and highlight key phase transitions in policy interventions over time. Our results offer actionable insights for policymakers aiming to balance the imperatives of climate change mitigation with the socio-economic needs of workers in declining industries.