Abstract: I study the effectiveness of subsidies as an alternative to carbon taxes to reduce carbon emissions in a quantitative climate-economy model. An energy firm uses brown and green energy inputs to produce energy. A firm-household then combines energy with capital and labor to produce final goods. The short-run elasticity between energy and other inputs is low. However, higher energy prices encourage higher energy efficiency, leading to a higher elasticity in the long run. The key weakness of green energy subsidies, as an alternative to carbon taxes, is that they cannot promote energy efficiency. Thus, in the baseline model, relying solely on optimal green subsidies results in a modest 1.0% decrease in emissions by the end of the century compared to the business-as-usual scenario. However, if the government can subsidize green energy usage and energy-efficient technological change simultaneously, the optimal subsidies could be nearly as effective in reducing emissions as the first-best brown energy taxes. Under this approach, 90% of the emission reductions and 88% of the welfare gains achievable through optimal carbon taxes can be realized.

Abstract: I study a two-region (North and South), two-sector (agriculture and non-agriculture)  Integrated Assessment Model (IAM). The household’s utility is Stone-Geary utility with subsistence food consumption. Because the South and agriculture are more exposed and to satisfy the subsistence requirement for food, climate change raises the relative price of agriculture, resulting in a large loss to the South and a smaller loss in the North. I compare my model-based loss calculations with the commonly used “enumerative method,” which is calculated using pre-climate change prices. I find that the South’s climate-driven utility loss is 39% greater than that of the enumerative approach, while the North’s loss is 85% lower. Optimal climate policy and policies under an uncooperative Nash equilibrium are also studied.

Abstract: Financially constrained governments, particularly in emerging and developing economies, tend to face a fiscal trade-off between adapting to climate change impacts and pursuing broader development goals. This trade-off is especially relevant in the agriculture sector, where investing in adaptation is critical to ensure food security amidst climate change. International trade can help alleviate this challenge and reduce adaptation investment needs by offsetting agricultural production shortages. However, in the presence of trade fragmentation, the adaptive role of trade diminishes, exacerbating food insecurity and increasing investment needs for adaptation. In this paper, we present a model to guide policymakers in deciding on the cost-efficient balance between investing in adaptation in the agricultural sector versus in broader development under financing and trade constraints. We apply the model to Ghana, Egypt, and Brazil, to examine the adaptation-development trade-off and highlight factors that would potentially lower adaptation investment needs. These factors include trade openness, higher agricultural productivity and efficiency of adaptation spending, and reduced labor market distortions. The key takeaways from the model applications suggest that (i) promoting trade openness and accessing concessional finance for adaptation help tackle climate challenges and ensure food security in lower-income countries; and (ii) domestic structural reforms are necessary to facilitate adaptation investments and reduce investment needs, by improving labor market flexibility, adaptation efficiency, and agriculture productivity.

Abstract: We study Gaussian Process Regressions (GPR) in providing global solutions to non-linear dynamic structural models. GPR is relatively easy to implement, can handle a large number of state variables, and approximates the high-dimensional, irregularly spaced value and policy functions with precision and efficiency. We address various practical challenges practitioners may face during GPR implementation, such as overfitting, sample selection, and handling of highly non-linear functions. We demonstrate our approach with applications to the economics of climate change and sovereign default.