The yield curve is widely regarded as a powerful descriptor of the economy and market expectations. A common approach to its statistical representation relies on a small number of factors summarizing the curve, which can then be used to forecast real economic activity. We argue that optimal...

The paper derives and proves results of Gaussian maximum likelihood estimation of constant unknowns (coefficients, covariances) and time-varying unknowns (factors, disturbances) of static and dynamic factor models and, thereby, extends the statistics and econometrics literatures on estimation...

In this article, we examine the dynamic interdependencies among components of Japan's consumer price index (CPI) using a two-lag time-varying loading factor (TLTVLF) model. Whereas previous studies have typically decomposed CPI series into long-term trends, seasonal patterns, and cyclical...

One of the most important priorities of the most recent research work regarding the professional appraisal (PA) process is to understand different aspects of the social workers' satisfaction with this particular type of professional evaluation. In this sense, this study addresses the imperative...

This study examined the factor structure of Green, Grey, and Red EU securities using extended asset pricing models built on the Fama–French and Carhart frameworks. The findings show improved return predictability and consistently negative risk-adjusted alpha across categories post-Global...

This paper develops an econometric framework for identifying latent factors that provide real-time estimates of supply and demand conditions shaping goods- and services-related price pressures in the U.S. economy. The factors are estimated using category-specific personal consumption...

Stock return prediction has been in the spotlight because it involves numerous factors. Improving the accuracy of stock return prediction and quantifying the impact of individual factors on forecasting remain challenging tasks. Motivated by these challenges, we propose a novel forecasting method...

This paper develops new identification results for multidimensional continuous measurement-error models where all observed measurements are contaminated by potentially correlated errors and none provides an injective mapping of the latent distribution. Using third-order cross-moments, the paper...

This article aims to provide new and robust evidence of the effect of air pollution on migration at the level of 70 European cities in the period 2004-2019. We use factor and regression analysis and panel data conducted from Eurobarometer, Eurostat, national statistical offices, and the European...

This paper proposes a nonparametric estimator of the spot volatility matrix with high-frequency data. Our newly proposed Positive Definite Fourier (PDF) estimator produces symmetric positive semi-definite estimates and is consistent with a suitable choice of the localizing kernel. The PDF...

Background: Truck drivers are a vital workforce sustaining Thailand's freight transport, particularly in Northeastern Thailand (Isan), a major logistics hub connecting with Laos, Vietnam, and Cambodia via Highway No. 2 and the AEC network. However, these drivers face disproportionately high...

This study integrates the Logistics Performance Index (LPI), Worldwide Governance Indicators (WGI), and Human Development Index (HDI) through Multiple Factor Analysis (MFA) and hierarchical clustering to create a comprehensive perspective on global development. By clustering countries based on...

The purpose of this study was to investigate the relative importance of determinants that should be considered first in order for container terminals to realize carbon neutrality and become an eco-friendly port. Three upper determinants and 12 lower determinants were derived through the...

This paper explores the hypothesis that the returns of asset classes can be predicted using common, systematic risk factors represented by the level, slope, and curvature of the US interest rate term structure. These are extracted using the Nelson-Siegel model, which effectively captures the...

This study develops and validates an innovation management framework based on the integration of dynamic capabilities and multidimensional innovation process factors. A mixed-methods approach was employed, combining a quantitative survey of 267 respondents from the Porto Digital ecosystem with...

Purpose This study aims to explore the asymmetric effects of macroeconomic factors on the profitability of large-cap companies in an emerging country like Colombia, using the Morgan Stanley Capital International (MSCI) Colombia index as the basis. Design/methodology/approach We employ a...

Background: Team viability, understood as the ability to adapt and collaborate effectively over time, is a key concept in organizational literature. In Peru, where changes are constant, culturally adapted tools are needed for its measurement. Objective: To translate and validate a team viability...

We propose a new rank-based test for the number of common primitive shocks, q, in large panel data. After estimating a VAR(1) model on r static factors extracted by principal component analysis, we estimate the number of common primitive shocks by testing the rank of the VAR residuals'...

This study examines the impact of agile practices on supply chain performance measurements in manufacturing firms. Following COVID-19, there have been operational and logistics disruptions in manufacturing firms and supply chains worldwide. We study the link between supply chain performance and...

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel data. The model exploits both serial and cross-sectional information in the data and can easily cope with time-variation in conditional means and variances, as well as with either...

In this paper, we propose a component-based dynamic factor model for nowcasting GDP growth. We combine ideas from "bottom-up" approaches, which utilize the national income accounting identity through modelling and predicting sub-components of GDP, with a dynamic factor (DF) model, which is...