Compnet Training Program
CompNet Training Program Structure The course is made for autonomous online learning. It is structured in three modules : Beginners, Intermediate and Advanced. Each of them…
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10th Vintage
The CompNet 10th Vintage Dataset 10th Vintage dataset is now available! The CompNet dataset provides a comprehensive set of micro-aggregated indicators, specifically designed to…
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Forecasting Natural Gas Prices in Real Time
Christiane Baumeister, Florian Huber, Thomas K. Lee, Francesco Ravazzolo
NBER Working Paper,
No. 33156,
2024
Abstract
This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.
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1st CompNet Data User Conference
1st CompNet Data User Conference Since it is well established among researchers of productivity and competitiveness that macro data cannot answer all questions emerging in today's…
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6th vintage
6th Vintage CompNet Dataset CompNet has created a competitiveness indicator dataset including a number of European countries. The dataset is unique in terms of its coverage and…
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8th Round [DL FILTER]
8th Round Welcome to the CompNet dataset. In this page, you can navigate through the many files that compose the dataset and choose which one you need for your analysis. Below,…
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Transformation tables for administrative borders in Germany
Transformation tables for administrative borders in Germany The state has the ability to change the original spatial structure of its administrative regions. The stated goal of…
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Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
June Cao, Zhanzhong Gu, Iftekhar Hasan
Journal of International Accounting Research,
Vol. 22 (3),
2023
Abstract
This study explores the evolution of accounting research by utilizing an unsupervised machine learning approach. We aim to identify the latent topics of accounting from the 1980s up to 2018, the dynamics and emerging topics of accounting research, and the economic reasons behind those changes. First, based on 23,220 articles from 46 accounting journals, we identify 55 topics using the latent Dirichlet allocation model. To illustrate the connection between topics, we use HistCite to generate a citation map along a timeline. The citation clusters demonstrate the “tribalism” phenomenon in accounting research. We then implement the dynamic topic model to reveal the dynamics of topics to show changes in accounting research. The emerging research trends are identified from the topic analytics. We further explore the economic reasons and in-depth insights into the topic evolution, indicating the economic development embeddedness nature of accounting research.
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EVA-KULT
EVA-KULT Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany The project aims at expanding the Centre for Evidence-based Policy Advice at the Halle…
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Anniversary 2017
Anniversary 2017 25 years IWH. Highlights and turning points. A quarter of a century ago, our employees started to work for IWH. What has happened from then until now? Content 25…
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