This paper presents a systematic review of research papers on nowcasting economic
activity. The study summarizes the state‐of‐the‐art nowcasting approaches and methods …

A novel approach based on long short-term memory (LSTM) networks that can incorporate
multivariate time series data, including historical tourism volume data, search engine data …

Dynamic factor models are parsimonious representations of relationships among time series
variables. With the surge in data availability, they have proven to be indispensable in …

PM 2.5 emissions not only have serious adverse health effects, but also impede
transportation activities, especially in air and highway transport. As a result, PM 2.5 …

Over the past decades, time series analysis has experienced a proliferous increase of
applications in economics, especially in macroeconomics and finance. Today these tools …

The modern calculation of textual sentiment involves a myriad of choices as to the actual
calibration. We introduce a general sentiment engineering framework that optimizes the …

Understanding the policy effectiveness in renewable energy technology innovation is
essential to advancing the global energy transition. This paper constructs a patent quality …

Mary Renck Jalongo Olivia N. Saracho Transitions and Tools that Support Scholars’ Success
Page 1 Springer Texts in Education Writing for Publication Mary Renck Jalongo Olivia N. Saracho …

We present new results for the likelihood‐based analysis of the dynamic factor model. The
latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic …

Central banks around the globe are commonly charged with the responsibility of producing
timely predictions of the current state of the economy in the course of conducting monetary …