New articles on Quantitative Finance

[1] 2404.12477

Sustainable regional economic development and land use: a case of Russia

This paper analyzes sustainable regional economic development and land use employing a case study of Russia. The economics of land management in Russia which is shaped by both historical legacies and contemporary policies represents an interesting conundrum. Following the dissolution of the Soviet Union, Russia embarked on a thorny and complex path towards the economic reforms and transformation characterized, among all, by the privatization and decentralization of land ownership. This transition was aimed at improving agricultural productivity and fostering sustainable regional economic development but also led to new challenges such as uneven distribution of land resources, unclear property rights, and underinvestment in rural infrastructure. However, managing all of that effectively poses significant challenges and opportunities. With the help of the comprehensive bibliographic network analysis, this study sheds some light on the current state of sustainable regional economic development and land use management in Russia. Its results and outcomes might be helpful for the researchers and stakeholders alike in devising effective strategies aimed at maximizing resources for sustainable land use, particularly within their respective regional economies.

[2] 2404.12974

Quantifying seasonal hydrogen storage demands under cost and market uptake uncertainties in energy system transformation pathways

Climate neutrality paradigms put electricity systems at the core of a clean energy supply. At the same time, indirect electrification, with a potential uptake of hydrogen or derived fuel economy, plays a crucial role in decarbonising the energy supply and industrial processes. Besides energy markets coordinating the transition, climate and energy policy targets require fundamental changes and expansions in the energy transmission, import, distribution, and storage infrastructures. While existing studies identify relevant demands for hydrogen, critical decisions involve imports versus domestic fuel production and investments in new or repurposing existing pipeline and storage infrastructure. Linking the pan-European energy system planning model SCOPE SD with the multiperiod European gas market model IMAGINE, the case study analysis and its transformation pathway results indicate extensive network development of hydrogen infrastructure, including expansion beyond refurbished methane infrastructure. However, the ranges of future hydrogen storage costs and market uptake restrictions expose and quantify the uncertainty of its role in Europes transformation. The study finds that rapidly planning the construction of hydrogen storage and pipeline infrastructure is crucial to achieving the required capacity by 2050.

[3] 2404.12988

Understanding Intra-Household Educational Inequalities: Gender, Birth Order, and Ability Dynamics in Benin's Households

This paper investigates the nuanced interplay of gender, birth order, and innate ability in shaping educational disparities among children within households, employing both a reduced-form analysis and a structural model of household resource allocation. By decomposing overall disparities, I identify the contributions of gender, birth order, and innate ability differences. In the context of Benin, for households with non-educated heads and mixed-gender children, total inequality comprises 50% gender disparity, 20% birth order effect, and 30% ability gap. Conversely, in households with only sons or only daughters and non-educated heads, total inequality is predominantly driven by ability disparities 70% for daughters and 83% for sons, with lesser contributions from birth order effects. Furthermore, my analysis reveals that in households with non-educated heads, firstborn daughters surpass their younger brothers in educational attainment on the intensive margin if their innate ability exceeds their brothers' by at least 13%, a figure reduced to 8% in households with college-educated parents. Additionally, the study unveils parental preferences favoring sons' education over daughters' among non-educated parents, with a perceived 22% higher average benefit. Targeted policies aimed at reducing composite education costs prove effective in mitigating gender and birth order gaps, albeit with a modest 5% reduction in total inequality. Overall, this research underscores the complex dynamics influencing intra-household educational inequalities and suggests policy avenues to address them.

[4] 2404.12598

Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty

This paper studies continuous-time risk-sensitive reinforcement learning (RL) under the entropy-regularized, exploratory diffusion process formulation with the exponential-form objective. The risk-sensitive objective arises either as the agent's risk attitude or as a distributionally robust approach against the model uncertainty. Owing to the martingale perspective in Jia and Zhou (2023) the risk-sensitive RL problem is shown to be equivalent to ensuring the martingale property of a process involving both the value function and the q-function, augmented by an additional penalty term: the quadratic variation of the value process, capturing the variability of the value-to-go along the trajectory. This characterization allows for the straightforward adaptation of existing RL algorithms developed for non-risk-sensitive scenarios to incorporate risk sensitivity by adding the realized variance of the value process. Additionally, I highlight that the conventional policy gradient representation is inadequate for risk-sensitive problems due to the nonlinear nature of quadratic variation; however, q-learning offers a solution and extends to infinite horizon settings. Finally, I prove the convergence of the proposed algorithm for Merton's investment problem and quantify the impact of temperature parameter on the behavior of the learning procedure. I also conduct simulation experiments to demonstrate how risk-sensitive RL improves the finite-sample performance in the linear-quadratic control problem.