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Assessing Emerging Markets through Transactional Dynamics: A New Multi-Dimensional Valuation Framework

Published: November 8, 2024 00:00

This paper introduces a novel transaction-function model for valuing emerging markets, integrating machine learning, agent-based modeling, and multi-method valuation techniques. Traditional valuation models often rely on aggregated economic indicators such…

Medical certificates and sickness absence: who stays away from work if monitoring is relaxed?

Published: November 8, 2024 00:00

Sickness insurance guarantees employees the right to take leave from work when they are sick, but is vulnerable to excessive use because monitoring of recipients’ health is difficult and costly. In terms of costs, it would be preferable to focus monitoring…

Natural Language Processing Techniques for Long Financial Document

Published: November 1, 2024 00:00

In finance, Natural Language Processing (NLP) has become both a powerful and challenging tool, as extensive unstructured documents—such as business plans, financial reports, and regulatory filings—hold essential insights for strategic decision-making. This…

Crowdfunding Success: Human Insights vs Algorithmic Textual Extraction

Published: November 1, 2024 00:00

Using a unique dataset of equity offerings from crowdfunding platforms, we explore the synergy between human insights and algorithmic analysis in evaluating campaign success through business plan assessments. Human evaluators (students) used a predefined…

Taming the Curse of Dimensionality:Quantitative Economics with Deep Learning

Published: October 29, 2024 00:00

We argue that deep learning provides a promising avenue for taming the curse of dimensionality in quantitative economics. We begin by exploring the unique challenges posed by solving dynamic equilibrium models, especially the feedback loop between…

Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call

Published: October 21, 2024 00:00

This document is a follow up to the paper by Ahmed and Pesaran (2020, AP) and reports state-level forecasts for the 2024 US presidential election. It updates the 3, 107 county level data used by AP and uses the same machine learning techniques as before to…

Predictive Power of Biological Sex and Gender Identity on Economic Behavior

Published: October 11, 2024 00:00

Behavioral differences by biological sex are still not fully understood, suggesting that studying gender differences in behavioral traits through the lenses of continuous identity might be a promising avenue to understand the remaining observed gender…

Experimental evidence that delegating to intelligent machines can increase dishonest behaviour

Published: October 4, 2024 00:00

While artificial intelligence (AI) enables significant productivity gains from delegating tasks to machines, it can also facilitate the delegation of unethical behaviour. Here, we demonstrate this risk by having human principals instruct machine agents to…

Mixed-Effects Frequency-Adjusted Borders Ordinal Forest: A Tree Ensemble Method for Ordinal Prediction with Hierarchical Data

Published: October 3, 2024 00:00

Predicting ordinal responses such as school grades or rating scale data is a common task in the social and life sciences. Currently, two major streams of methodology exist for ordinal prediction: parametric models such as the proportional odds model and…

Double machine learning and Stata application

Published: October 2, 2024 00:00

Traditional methods for estimating treatment effects generally assume strong functional forms and are only applicable when the covariates are low-dimensional data. However, using machine learning methods directly often leads to "regularization bias". The…

Doombot versus other machine-learning methods for evaluating recession risks in OECD countries

Published: September 20, 2024 00:00

An extensive literature explains recession risks using a variety of financial and business cycle variables. The problem of selecting a parsimonious set of explanatory variables, which can differ between countries and prediction horizons, is naturally…