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I show that house prices can be modeled using machine learning (kNN and tree-bagging) and a small dataset composed of macro-economic factors (MEF), including an inflation metric (CPI), US treasury rates (10-yr), Gross Domestic Product…
Pre-season prediction of crop production outcomes such as grain yields and N losses can provide insights to stakeholders when making decisions. Simulation models can assist in scenario planning, but their use is limited because of data…
Despite the key role of multinational enterprises (MNEs) in both international markets and domestic economies, there is no consensus on their impact on their host economy. In particular, do MNEs stimulate new domestic firms through…
Disasters often impact supply chains, leading to cascading effects across regions. While unaffected regions may attempt to compensate, their ability is constrained by their available production capacity and logistical constraints between…
Long-term load forecasting plays a vital role for utilities and planners in terms of grid development and expansion planning. An overestimate of long-term electricity load will result in substantial wasted investment in the construction of…
As the scale of machine learning models increases, trends such as scaling laws anticipate consistent downstream improvements in predictive accuracy. However, these trends take the perspective of a single model-provider in isolation, while…
A large class of trading strategies focus on opportunities offered by the yield curve. In particular, a set of yield curve trading strategies are based on the view that the yield curve mean-reverts. Based on these strategies' positive…
What is the environmental impact of exports? Focusing on 2000-20, this paper combines customs, administrative, and census microdata to estimate employment elasticities with respect to exports. The findings show that municipalities that…
Labor displacement off-or nearshore is a performance improvement instrument that currently sparks a lot of interest in the service sector. This article proposes a model to understand the consequences of such a decision on management…
Understanding the business cycle is crucial for building economic stability, guiding business planning, and informing investment decisions. The business cycle refers to the recurring pattern of expansion and contraction in economic activity…
The North American commercial electric vehicle (EV) sector is undergoing rapid expansion, with unit sales rising from 21,120 in 2022 to 36,491 in 2023 - a 73% increase, according to the International Energy Agency. However, this…
The bulk electric power system in New England is fundamentally changing. The representation of nuclear, coal and oil generation facilities is set to dramatically fall, and natural gas, wind and solar facilities will come to fill their…
The agricultural sector is particularly susceptible to the impact of climate change. In this paper, I investigate how vulnerability to climate change affects U.S. farms' credit access, and demonstrates that such impact is unequally…
This research employs quantitative techniques interpreted through relevant economic theories to analyze a proposed U.S. "Discounted Reciprocal Tariff" structure. Statistical modeling (linear regression) quantifies the policy's consistent…
The effects of weather on agriculture in recent years have become a major global concern. Hence, the need for an effective weather risk management tool (i.e., weather derivatives) that can hedge crop yields against weather uncertainties.…
This study examines the effects of Trump-era tariffs on financial market efficiency by applying multifractal detrended fluctuation analysis to the return and absolute return time series of six major financial assets: the S\&P 500, SSEC,…
The incorporation of trees on farms can help to improve livelihoods and build resilience among small-holder farmers in developing countries. On-farm trees can help gen- erate additional income from commercial tree harvest as well as…
We present a vessel and target-specific positive mathematical programming model (PMP) for Hawaii's longline fishing fleet. Although common in agricultural economics, PMP modeling is rarely attempted in fisheries. To demonstrate the…
Transmission lines, crucial to the power grid, are subjected to diverse environmental conditions such as wind, temperature, humidity, and pollution. While these conditions represent a consistent impact on the transmission lines, certain…
Recent Machine Learning (ML) approaches have shown increased performance on benchmarks but at the cost of escalating computational demands. Hardware, algorithmic and carbon optimizations have been proposed to curb energy consumption and…