[HTML][HTML] Environmental-social-governance concept bibliometric analysis and systematic literature review: Do investors becoming more environmentally conscious?
E Steblianskaia, M Vasiev, A Denisov… - Environmental and …, 2023 - Elsevier
It is indispensable to understand where the development of the Environmental-Social-
Governance (further-ESG) concept is moving. People need to know where to develop in the …
Governance (further-ESG) concept is moving. People need to know where to develop in the …
Forecasting UK inflation bottom up
A Joseph, G Potjagailo, C Chakraborty… - International Journal of …, 2024 - Elsevier
We forecast CPI inflation indicators in the United Kingdom using a large set of monthly
disaggregated CPI item series covering a sample period of twenty years, and employing a …
disaggregated CPI item series covering a sample period of twenty years, and employing a …
The anatomy of out-of-sample forecasting accuracy
We develop metrics based on Shapley values for interpreting time-series forecasting
models, including “black-box” models from machine learning. Our metrics are model …
models, including “black-box” models from machine learning. Our metrics are model …
A neural phillips curve and a deep output gap
P Goulet Coulombe - Available at SSRN 4018079, 2022 - papers.ssrn.com
Many problems plague the estimation of Phillips curves. Among them is the hurdle that the
two key components, inflation expectations and the output gap, are both unobserved …
two key components, inflation expectations and the output gap, are both unobserved …
Enhanced bayesian neural networks for macroeconomics and finance
We develop Bayesian neural networks (BNNs) that permit to model generic nonlinearities
and time variation for (possibly large sets of) macroeconomic and financial variables. From a …
and time variation for (possibly large sets of) macroeconomic and financial variables. From a …
Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany
GW Beck, K Carstensen, JO Menz, R Schnorrenberger… - 2024 - papers.ssrn.com
We study how millions of granular and weekly household scanner data combined with
machine learning can help to improve the real-time nowcast of German inflation. Our …
machine learning can help to improve the real-time nowcast of German inflation. Our …
Forecasting inflation rates be extreme gradient boosting with the genetic algorithm
One of the most important objectives of monetary institutions is to maintain price stability in
countries or regions. Hyperinflation and deflation have adverse influences on economic …
countries or regions. Hyperinflation and deflation have adverse influences on economic …
From reactive to proactive volatility modeling with hemisphere neural networks
P Goulet Coulombe, M Frenette, K Klieber - Available at SSRN, 2023 - papers.ssrn.com
We reinvigorate maximum likelihood estimation (MLE) for macroeconomic density
forecasting through a novel neural network architecture with dedicated mean and variance …
forecasting through a novel neural network architecture with dedicated mean and variance …
A neural Phillips curve and a deep output gap
PG Coulombe - arXiv preprint arXiv:2202.04146, 2022 - arxiv.org
Many problems plague the estimation of Phillips curves. Among them is the hurdle that the
two key components, inflation expectations and the output gap, are both unobserved …
two key components, inflation expectations and the output gap, are both unobserved …
[HTML][HTML] Investor attention and consumer price index inflation rate: Evidence from the United States
P Zhu, Q Zhou, Y Zhang - Humanities and Social Sciences …, 2024 - nature.com
Explaining and forecasting inflation are important and challenging tasks because inflation is
one focus of macroeconomics. This paper introduces novel investor attention to the field of …
one focus of macroeconomics. This paper introduces novel investor attention to the field of …