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Found 8 papers, 1 papers with code
Money Growth and Inflation: A Quantile Sensitivity Approach
Then, the proposed framework is exploited to examine the distributional effects of money growth on the distributions of inflation and its disaggregate measures in the United States and the Euro area.
Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications
This article proposes a novel Bayesian multivariate quantile regression to forecast the tail behavior of US macro and financial indicators, where the homoskedasticity assumption is relaxed to allow for time-varying volatility.
Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP
Timely characterizations of risks in economic and financial systems play an essential role in both economic policy and private sector decisions.
Filtering the intensity of public concern from social media count data with jumps
Count time series obtained from online social media data, such as Twitter, have drawn increasing interest among academics and market analysts over the past decade.
Time Series Analysis
Applications
Econometrics
Visualizing and comparing distributions with half-disk density strips
We propose a user-friendly graphical tool, the half-disk density strip (HDDS), for visualizing and comparing probability density functions.
Methodology Econometrics Applications
Public Concern and the Financial Markets during the COVID-19 outbreak
We measure the public concern during the outbreak of COVID-19 disease using three data sources from Google Trends (YouTube, Google News, and Google Search).
Bayesian Markov Switching Tensor Regression for Time-varying Networks
First, to avoid over-fitting we propose a parsimonious parametrization based on a low-rank decomposition of the tensor of regression coefficients.
Methodology
