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Economic Policy Uncertainty (EPU) is a critical indicator in economic studies, while it can be used to forecast a recession. Under higher levels of uncertainty, firms' owners cut their investment, which leads to a longer post-recession…

Computation and Language · Computer Science 2021-05-12 Fatemeh Kaveh-Yazdy , Sajjad Zarifzadeh

Economic Policy Uncertainty (EPU) represents the uncertainty realized by the investors during economic policy alterations. EPU is a critical indicator in economic studies to predict future investments, the unemployment rate, and recessions.…

Computers and Society · Computer Science 2023-08-22 Fatemeh Kaveh-Yazdy , Sajjad Zarifzadeh

Quantification of economic uncertainty is a key concept for the prediction of macro economic variables such as gross domestic product (GDP), and it becomes particularly relevant on real-time or short-time predictions methodologies, such as…

Machine Learning · Computer Science 2022-09-13 Hairo U. Miranda Belmonte , Victor Muñiz-Sánchez , Francisco Corona

Methods and applications are inextricably linked in science, and in particular in the domain of text-as-data. In this paper, we examine one such text-as-data application, an established economic index that measures economic policy…

Computation and Language · Computer Science 2020-10-12 Katherine A. Keith , Christoph Teichmann , Brendan O'Connor , Edgar Meij

The Economic Policy Uncertainty index had gained considerable traction with both academics and policy practitioners. Here, we analyse news feed data to construct a simple, general measure of uncertainty in the United States using a highly…

Econometrics · Economics 2020-06-12 Rickard Nyman , Paul Ormerod

Extraction of financial and economic events from text has previously been done mostly using rule-based methods, with more recent works employing machine learning techniques. This work is in line with this latter approach, leveraging…

Computation and Language · Computer Science 2022-11-29 Liat Ein-Dor , Ariel Gera , Orith Toledo-Ronen , Alon Halfon , Benjamin Sznajder , Lena Dankin , Yonatan Bilu , Yoav Katz , Noam Slonim

This paper defines theoretical lower bounds of uncertainty of observations of macroeconomic variables that depend on statistical moments and correlations of random values and volumes of market trades. Any econometric assessments of…

General Economics · Economics 2024-10-08 Victor Olkhov

Supervised machine learning and predictive models have achieved an impressive standard today, enabling us to answer questions that were inconceivable a few years ago. Besides these successes, it becomes clear, that beyond pure prediction,…

Machine Learning · Statistics 2025-01-29 Cornelia Gruber , Patrick Oliver Schenk , Malte Schierholz , Frauke Kreuter , Göran Kauermann

Limited labeled data is becoming the largest bottleneck for supervised learning systems. This is especially the case for many real-world tasks where large scale annotated examples are either too expensive to acquire or unavailable due to…

Social and Information Networks · Computer Science 2020-05-28 Kai Shu , Ahmed Hassan Awadallah , Susan Dumais , Huan Liu

An increase in the novelty of news predicts negative stock market returns and negative macroeconomic outcomes over the next year. We quantify news novelty - changes in the distribution of news text - through an entropy measure, calculated…

General Finance · Quantitative Finance 2023-09-12 Paul Glasserman , Harry Mamaysky , Jimmy Qin

The macroeconomic climate influences operations with regard to, e.g., raw material prices, financing, supply chain utilization and demand quotas. In order to adapt to the economic environment, decision-makers across the public and private…

Machine Learning · Statistics 2018-03-13 Stefan Feuerriegel , Julius Gordon

Bayesian deep learning plays an important role especially for its ability evaluating epistemic uncertainty (EU). Due to computational complexity issues, approximation methods such as variational inference (VI) have been used in practice to…

Machine Learning · Statistics 2022-10-12 Futoshi Futami , Tomoharu Iwata , Naonori Ueda , Issei Sato , Masashi Sugiyama

Anticipating price developments in financial markets is a topic of continued interest in forecasting. Funneled by advancements in deep learning and natural language processing (NLP) together with the availability of vast amounts of textual…

Statistical Finance · Quantitative Finance 2023-03-21 Duygu Ider , Stefan Lessmann

Automatic fact-checking systems detect misinformation, such as fake news, by (i) selecting check-worthy sentences for fact-checking, (ii) gathering related information to the sentences, and (iii) inferring the factuality of the sentences.…

Information Retrieval · Computer Science 2019-03-21 Casper Hansen , Christian Hansen , Stephen Alstrup , Jakob Grue Simonsen , Christina Lioma

In many applications, training machine learning models involves using large amounts of human-annotated data. Obtaining precise labels for the data is expensive. Instead, training with weak supervision provides a low-cost alternative. We…

Machine Learning · Computer Science 2022-02-09 Chidubem Arachie , Bert Huang

Quantification of the political leaning of online news articles can aid in understanding the dynamics of political ideology in social groups and measures to mitigating them. However, predicting the accurate political leaning of a news…

Machine Learning · Computer Science 2023-09-13 Sadia Kamal , Jimmy Hartford , Jeremy Willis , Arunkumar Bagavathi

We develop a resource-efficient methodology for measuring economic outlook in news text that combines document embeddings with synthetic training data generated by large language models. Applied to 27 million news articles, the resulting…

General Economics · Economics 2026-02-18 Elliot Beck , Franziska Eckert , Linus Kühne , Helge Liebert , Rina Rosenblatt-Wisch

Since fake news poses a serious threat to society and individuals, numerous studies have been brought by considering text, propagation and user profiles. Due to the data collection problem, these methods based on propagation and user…

Computation and Language · Computer Science 2022-05-31 Yuhang Wang , Li Wang , Yanjie Yang , Yilin Zhang

Accurately forecasting Climate Policy Uncertainty (CPU) is essential for designing climate strategies that balance economic growth with environmental objectives. Elevated CPU levels can delay regulatory implementation, hinder investment in…

Econometrics · Economics 2026-01-21 Donia Besher , Anirban Sengupta , Tanujit Chakraborty

The Economy Watcher Survey, which is a market survey published by the Japanese government, contains \emph{assessments of current and future economic conditions} by people from various fields. Although this survey provides insights regarding…

Econometrics · Economics 2020-04-23 Masahiro Kato
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