Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Ian Crawford, Carl-Emil Pless · 2026 · arXiv
We study the associations between everyday economic decision-making quality and people's emotional states. Using high-frequency, highly disaggregated consumer "scanner" data, we show that the cost of poor decision-making is substantial, on average equal to around half of day-to-day consumption budgets. While material circumstances help explain decision-making quality, how people feel about those circumstances is equally important. Contrary to evidence that stress and worry impair performance in settings where distraction is costly, we find these same feelings are associated with improved decis
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Valentina Macchiati, Piero Mazzarisi, Diego Garlaschelli · 2024 · arXiv
Networks of financial exposures are the key propagators of risk and distress among banks, but their empirical structure is not publicly available because of confidentiality. This limitation has triggered the development of methods of network reconstruction from partial, aggregate information. Unfortunately, even the best methods available fail in replicating the number of directed cycles, which on the other hand play a crucial role in determining graph spectra and hence the degree of network stability and systemic risk. Here we address this challenge by exploiting the hypothesis that the stati
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Damien Ackerer, Natasa Tagasovska, Thibault Vatter · 2019 · arXiv
We present a neural network (NN) approach to fit and predict implied volatility surfaces (IVSs). Atypically to standard NN applications, financial industry practitioners use such models equally to replicate market prices and to value other financial instruments. In other words, low training losses are as important as generalization capabilities. Importantly, IVS models need to generate realistic arbitrage-free option prices, meaning that no portfolio can lead to risk-free profits. We propose an approach guaranteeing the absence of arbitrage opportunities by penalizing the loss using soft const
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Yuan Gao, Dokyun Lee, Gordon Burtch et al. · 2024 · arXiv
Recent studies suggest large language models (LLMs) can exhibit human-like reasoning, aligning with human behavior in economic experiments, surveys, and political discourse. This has led many to propose that LLMs can be used as surrogates or simulations for humans in social science research. However, LLMs differ fundamentally from humans, relying on probabilistic patterns, absent the embodied experiences or survival objectives that shape human cognition. We assess the reasoning depth of LLMs using the 11-20 money request game. Nearly all advanced approaches fail to replicate human behavior dis
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Marco Caliendo, Nico Pestel, Rebecca Olthaus · 2023 · arXiv
We study the long-term effects of the 2015 German minimum wage introduction and its subsequent increases on regional employment. Using data from two waves of the Structure of Earnings Survey allows us to estimate models that account for changes in the minimum wage bite over time. While the introduction mainly affected the labour market in East Germany, the raises are also increasingly affecting low-wage regions in West Germany, such that around one third of regions have changed their (binary) treatment status over time. We apply different specifications and extensions of the classic difference
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Francis X. Diebold, Maximilian Goebel, Philippe Goulet Coulombe · 2022 · arXiv
We use "glide charts" (plots of sequences of root mean squared forecast errors as the target date is approached) to evaluate and compare fixed-target forecasts of Arctic sea ice. We first use them to evaluate the simple feature-engineered linear regression (FELR) forecasts of Diebold and Goebel (2021), and to compare FELR forecasts to naive pure-trend benchmark forecasts. Then we introduce a much more sophisticated feature-engineered machine learning (FEML) model, and we use glide charts to evaluate FEML forecasts and compare them to a FELR benchmark. Our substantive results include the freque
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Claudiu Tiberiu Albulescu, Daniel Goyeau · 2016 · arXiv
Inside the EU, the commercial integration of the CEE countries has gained remarkable momentum before the crisis appearance, but it has slightly slowed down afterwards. Consequently, the interest in identifying the factors supporting the commercial integration process is high. Recent findings in the new trade theory suggest that FDI influence the trade intensity but the studies approaching this relationship for the CEE countries present mixed evidence, and investigate the commercial integration of CEE countries with the old EU members. Against this background, the purpose of this paper is to as
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Francisco Rodríguez · 2022 · arXiv
We revisit the results of a recent paper by Equipo Anova, who claim to find evidence of an improvement in Venezuelan imports of food and medicines associated with the adoption of U.S. financial sanctions towards Venezuela in 2017. We show that their results are consequence of data coding errors and questionable methodological choices, including the use an unreasonable functional form that implies a counterfactual of negative imports in the absence of sanctions, the omission of data accounting for four-fifths of the country's food imports at the time of sanctions and incorrect application of re
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Yuda Bi, Vince D Calhoun · 2026 · arXiv
We address the attribution problem for apparent slow collective dynamics: is the observed persistence intrinsic, or inherited from a persistent driver? For the leading eigenvalue fraction $ψ_1=λ_{\max}/N$ of S\&P 500 60-day rolling correlation matrices ($237$ stocks, 2004--2023), a VIX-coupled Ornstein--Uhlenbeck model reduces the effective relaxation time from $298$ to $61$ trading days and improves the fit over bare mean reversion by $Δ$BIC$=109$. On the decomposition sample, an informational residual of $\log(\mathrm{VIX})$ alone retains most of that gain ($Δ$BIC$=78.6$), whereas a mechanic
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Novriana Sumarti, Rafki Hidayat · 2013 · arXiv
The Financial Crisis of 2008 is a worldwide financial crisis causing a worldwide economic decline that is the most severe since the 1930s. According to the International Monetary Fund (IMF), the global financial crisis gave impact on USD 3.4 trillion losses from financial institutions around the world between 2007 and 2010. Does the crisis give impact on the returns of the U.S. movie Box Office? It will be answered by doing an analysis on the financial risk model based on Extreme Value Theory (EVT) and calculations of Value at Risk (VaR) and Expected Shortfall (ES). The values of VaR and ES fr
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Cheikh Mbaye, Frédéric Vrins · 2019 · arXiv
We address the so-called calibration problem which consists of fitting in a tractable way a given model to a specified term structure like, e.g., yield or default probability curves. Time-homogeneous jump-diffusions like Vasicek or Cox-Ingersoll-Ross (possibly coupled with compounded Poisson jumps, JCIR), are tractable processes but have limited flexibility; they fail to replicate actual market curves. The deterministic shift extension of the latter (Hull-White or JCIR++) is a simple but yet efficient solution that is widely used by both academics and practitioners. However, the shift approach
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Agnieszka Kleszcz, Krzysztof Rusek · 2022 · arXiv
Nowadays innovation is one of the main determinants of economic development. Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, technologies and firms. This paper provides new insights on the causal effects of the enlargement of the European Union (EU) by investigating the patents performance within the new EU member states (EU-13). The empirical results based on data collected from the OECD database from 1985-2017 and causal impact using a Bayesian structural time-series model (proposed by Google) point towards a conclusion tha
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Mohammad Hassan Shakil, Arne Johan Pollestad, Khine Kyaw et al. · 2025 · arXiv
With European Union initiatives mandating gender quotas on corporate boards, a key question arises: Is greater board gender diversity (BGD) associated with better emissions performance (EP)? To answer this question, we examine the influence of BGD on EP across a sample of European firms from 2016 to 2022. Using panel regressions, advanced machine learning algorithms, and explainable AI, we reveal a non-linear relationship. Specifically, EP improves with BGD up to an optimal level of approximately 35 %, beyond which further increases in BGD yield no additional improvement in EP. A minimum BGD t
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Akhmad Muhammadin, Rashila Ramli, Syamsul Ridjal et al. · 2020 · arXiv
The dynamic capability and marketing strategy are challenges to the banking sector in Indonesia. This study uses a survey method solving 39 banks in Makassar. Data collection was conducted of questionnaires. The results show that, the dynamic capability has a positive yet insignificant impact on the organizational performance, the marketing strategy has a positive and significant effect on organizational performance and, dynamic capability and marketing strategy have a positive and significant effect on the organization's performance in the banking sector in Makassar. Keywords : dynamic capabi
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