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Safe-Haven Currency and Sequence Risk: A State-Dependent Swiss Franc Overlay for Global Portfolios
Get PDFSequence-of-returns risk (SoRR) matters because the order of returns—rather than only their long-run average—determines whether real, inflation-indexed withdrawal plans survive the early retirement years. For EUR/JPY spenders invested in globally diversified, USD-centric portfolios, SoRR is co-determined by market and FX paths in the spending currency. This paper proposes a state-dependent Swiss-franc (CHF) overlay—implemented via cash/bills or liquid FX instruments—as crisis insurance rather than generic hedging. A transparent stress score triggers and sizes the sleeve; outcomes are evaluated on sequence-sensitive metrics (e.g., CVaR(95), maximum drawdown, time-underwater, and the 5th percentile of sustainable withdrawals). Indexing and FX procedures follow MSCI and WM/Refinitiv methodology; the design is fully auditable and modular for empirical tables/figures
Dynamic Spatial Treatment Effects in Neurotransmitter Diffusion: Applications to Movement Disorders
Get PDFTraditional spatial treatment effect methods impose arbitrary boundaries between treated and control regions, obscuring how treatments spread through neural tissue. We develop a continuous functional framework deriving explicit treatment boundaries from diffusion physics, eliminating discretization artifacts while providing testable predictions. Our approach applies partial differential equations to neurotransmitter diffusion, unifying spatial scales from synaptic spillover (micrometers) to volume transmission (centimeters).
We validate using synthetic data calibrated to established neuroscience parameters across five conditions: healthy controls, dystonia, Parkinson's disease, Alzheimer's disease, and acute ischemia. Results demonstrate systematic disease-induced boundary alterations. Dystonia reduces treatment reach by 16.3\% (p 0.0001), requiring 24\% dose increases for equivalent coverage. Parkinson's shows 31.8\% reduction, ischemia 34.3\%. Spatial decay parameters evolve from 483 mm(1 hour) to 54 mm (72 hours), matching theoretical predictions.
Compared to difference-in-differences methods, our framework achieves superior fit ( = 0.92 vs. 0.76) with explicit boundary detection. Non-parametric approaches achieve higher in-sample fit ( = 0.99) but lack physical interpretability and cannot identify boundaries.
Clinical applications include: (1) data-driven determination of injection sites and stimulation parameters, (2) disease-specific dose adjustments based on tissue properties, and (3) treatment time course prediction from early measurements. These advances directly address limitations in deep brain stimulation, botulinum toxin therapy, and drug delivery planning.
Methodologically, we extend spatial causal inference from pollution dispersion and financial networks to neuroscience, demonstrating treatment boundaries emerge naturally from diffusion physics across diverse domains
Dual-Channel Technology Diffusion: Spatial Decay and Network Contagion in Supply Chain Networks
Get PDFThis paper develops a dual-channel framework for analyzing technology diffusion that integrates spatial decay mechanisms from continuous functional analysis with network contagion dynamics from spectral graph theory. Building on \citet{kikuchi2024navier} and \citet{kikuchi2024dynamical}, which establish Navier-Stokes-based approaches to spatial treatment effects and financial network fragility, we demonstrate that technology adoption spreads simultaneously through both geographic proximity and supply chain connections. Using comprehensive data on six technologies adopted by 500 firms over 2010-2023, we document three key findings. First, technology adoption exhibits strong exponential geographic decay with spatial decay rate per kilometer, implying a spatial boundary of kilometers beyond which spillovers are negligible (R-squared = 0.99). Second, supply chain connections create technology-specific networks whose algebraic connectivity () increases 300-380 percent as adoption spreads, with correlation between and adoption exceeding 0.95 across all technologies. Third, traditional difference-in-differences methods that ignore spatial and network structure exhibit 61 percent bias in estimated treatment effects. An event study around COVID-19 reveals that network fragility increased 24.5 percent post-shock, amplifying treatment effects through supply chain spillovers in a manner analogous to financial contagion documented in \citet{kikuchi2024dynamical}. Our framework provides micro-foundations for technology policy: interventions have spatial reach of 69 kilometers and network amplification factor of 10.8, requiring coordinated geographic and supply chain targeting for optimal effectiveness
Dynamic Spatial Treatment Effects as Continuous Functionals: Theory and Evidence from Healthcare Access
Get PDFI develop a continuous functional framework for spatial treatment effects grounded in Navier-Stokes partial differential equations. Rather than discrete treatment parameters, the framework characterizes treatment intensity as continuous functions over space-time, enabling rigorous analysis of boundary evolution, spatial gradients, and cumulative exposure. Empirical validation using 32,520 U.S. ZIP codes demonstrates exponential spatial decay for healthcare access ( per km, ) with detectable boundaries at 37.1 km. The framework successfully diagnoses when scope conditions hold: positive decay parameters validate diffusion assumptions near hospitals, while negative parameters correctly signal urban confounding effects. Heterogeneity analysis reveals 2-13 stronger distance effects for elderly populations and substantial education gradients. Model selection strongly favors logarithmic decay over exponential (), representing a middle ground between exponential and power-law decay. Applications span environmental economics, banking, and healthcare policy. The continuous functional framework provides predictive capability (), parameter sensitivity (), and diagnostic tests unavailable in traditional difference-in-differences approaches
Multibrand price dispersion
Get PDFWe study a market in which firms each might supply a number of variants, or "brands", of fundamentally the same product. Consumers differ in the sets of brands they consider, and firms compete using (multi-dimensional) mixed pricing strategies. We show when firms apply uniform pricing across their brands, and when they use segmented pricing so that one "discount" brand is priced below another "premium" brand. We study the case of symmetric brands in particular, and discuss the impact of a firm introducing a new brand, of imposing a requirement to set uniform prices across brands, and of mergers between firms
An Analysis of Gender-based Pricing: Personal Care Products on Amazon India
Get PDFThe goal of this study is to understand the pricing disparities of personal care products between women and men in India. While initially, we had hoped to research pads, tampons, and other menstrual products, there exists no male equivalent for comparison. Hence, we hope the analysis of our three chosen personal care products—deodorant, perfume, and razors—may reveal differences in gender-based pricing, providing a framework for future research on menstrual product costs. We collected 1,659 unique product URLs from Amazon India by including all search results across these three personal care products in women’s and men’s categories, counting repeat entries marketed to both genders. After identifying unisex entries and removing outliers, resulting in a total of 1,583 unique entries accounted for in our data, we compared the means to understand pricing differences. Contrary to expectations, the mean price of all three women’s product categories was lower than its respective men’s counterpart, with the percent increase in the average price for men as compared to women varying from 7.71%, 28.27%, 58.84%, for deodorant, perfume, and razors respectively
The determinants of forest area in Brazil: Ethanol production, exports of crops and livestock, and asymmetric impact of temperature change
Get PDFThis paper evaluates the long-run impact of fuel ethanol production, exports of crops and livestock, and the asymmetric impact of temperature change on the forest area in Brazil. We use the non-linear autoregressive distributed lag model and annual data between 1990 and 2022. An increase in ethanol production or in exports of crops and livestock importantly reduces the forest area in Brazil, in the long-run. We demonstrate that while positive temperature change does reduce forest area in the long-run, falling temperatures do not guarantee the regeneration of lost forests. A temperature change increase of 1°C leads in the long term to a significant and very worrying reduction in the forest area of Brazil, of almost 9.8%. Some policy recommendations are drawn: i) To reduce GHG emissions, Brazil should encourage R&D and innovation in energy efficiency and renewable energy (e.g., solar, wave), especially in second-generation or third-generation biofuels production, through appropriate competitive credits and subsidies; ii) Brazil should encourage agricultural research to increase agricultural yields and the use of aeroponics for vegetable culture or smart agriculture, because this will lead to less pressure on agricultural lands and therefore on deforestation; iii) A strategy to preserve or even to recover the Brazilian Amazon forest should be established combined with a strategy for developing green tourism
When Ranks Fail: New Evidence on Intergenerational Educational Mobility
Get PDFMany recent studies on intergenerational educational mobility adopted the rank-rank model popularized by the work of Chetty et al. (2014, QJE) on income mobility, under the assumption that the approach remains valid for discrete variables. However, conversion of discrete data such as years of schooling into percentile ranks fails to make the empirical rank distribution uniform, unlike continuous variables such as income. Thus, the estimates of relative educational mobility from rank-rank regressions are not margin-free, and capture a fundamentally different concept of mobility compared to the rank-rank slope in income mobility analysis. Taking advantage of recent advances on discrete copulas, we introduce a margin-free measure of relative educational mobility, Yule’s coefficient, which is the analogue of the rank-rank slope in income mobility. Yule’s coefficient was proposed by Geenens (2020) as a summary measure of the margin-free dependence structure between two discrete variables such as children’s and parents’ schooling. The margin-free dependence structure is estimated by an iterative matrix re-scaling procedure applied to the joint probability mass function of the bivariate discrete distribution. We report estimates of Yule’s coefficient for 6 countries: the USA, Bangladesh, India, Indonesia, Chile, and Mexico. The evidence suggests that, in many cases, the rank-rank slope estimates for schooling overestimate the margin-free relative educational mobility (positional mobility). For example, the estimates for the USA (PSID data) are: rank-rank slope=0.441 and Yule’s coefficient=0.534. The extent of overestimation in the national estimates varies considerably across countries: 3.09%−48.31%. The cross-country rankings and evolution of educational mobility across cohorts are substantially different when we use the margin-free Yule’s coefficient instead of the rank-based measures
Advancing Audit Practices through Technology: A Comprehensive Review of Continuous Auditing
Get PDFContinuous auditing has emerged as a transformative practice within the accounting and auditing professions, driven by rapid technological advancements and the growing demand for real-time financial assurance. Traditional audit practices rely on manual work, increasing the risk of human error and repetitive tasks. But Continuous auditing is powered by transformative tools like robotic process automation which eliminates these barriers by automating routine processes, reducing errors, and freeing employees from repetitive work. This paper examines the evolution of continuous auditing, its integration with advanced technologies such as artificial intelligence, robotic process automation, blockchain, and data analytics, and the broader implications for auditors, organizations, and academic institutions. Such advanced technology works together in continuous auditing to enhance accuracy, automate processes, and ensure data accuracy. Synergy in these advanced technologies enhanced audit efficiency. Through a comprehensive review of scholarly literature, the study underscores how continuous auditing facilitates real-time monitoring, improves audit quality, and reduces risks associated with traditional audit methods. Nevertheless, its adoption presents several challenges, including the management of information overload, the preservation of auditor independence, and the resolution of skill deficiencies among professionals. The 2024 BDO Audit Innovation Survey found that more than two-thirds (69%) of finance leaders said establishing data governance and internal data management is a barrier to a smooth audit experience. According to a 2019 ISACA survey, nearly two-thirds of organizations say the tech skills gap is impacting IT audits. The paper concludes by stressing the critical need to align auditing practices, professional training, and technological innovation to get the maximum benefits of continuous auditing in a digitally driven business environment
The Global Minimum Tax, Investment Incentives and Asymmetric Tax Competition
Get PDFThis paper investigates the OECD's global minimum tax (GMT) in a formal model of tax competition between asymmetric countries. We consider both profit shifting and real responses of multinational enterprises, and highlight the role of the substance-based income exclusion (SBIE) in investment incentives and tax rate setting. The GMT reduces the true tax rate differential and benefits the large country, while the revenue effect is generally ambiguous for the small country. In the short run where tax rates are fixed, the GMT reduces the small country's revenue if profit shifting costs are low and increases it otherwise. In the long run where countries adjust tax rates, the GMT reshapes the tax game and the competition pattern. We reveal that the minimum rate binds the small country only if it is low. With the rise of the GMT rate, countries will set tax rates below the minimum to boost capital investments and collect top-up taxes. Simulations show that a moderate GMT rate can raise both countries' revenues and the large country's welfare in the long run. However, it may reduce the small country's welfare if the welfare weight of private income is high