Results 131 to 140 of about 6,156 (248)
Threshold Regression for Fixed‐T$$ T $$ Panel Data with Interactive Fixed Effects
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT This paper develops a new toolbox for estimation and inference in panel data threshold regression models with interactive fixed effects and a fixed number of time periods, T$$ T $$. The toolbox is designed to be simple, accurate, and computationally efficient.
Jan Ditzen +2 more
wiley +1 more source
Regulation &Governance, EarlyView.ABSTRACT Which candidates benefit from corruption and favoritism in public procurement? While existing studies show that politically connected firms profit from corruption risks in public procurement, we know less about whether these risks also increase the prevalence of political candidates with ties to business.
Saverio Di Giorno +2 more
wiley +1 more source
Modeling Downside Risks for China's Security Markets: Does Greenness Make Bonds a Safer Haven?
Scottish Journal of Political Economy, EarlyView.ABSTRACT Motivated by its current defective governance regime and institutional characteristics of green finance, this study models Value‐at‐Risk and Expected Shortfall of security markets for China. We extend Patton et al.'s (2019) models by introducing four exogenous risk factors including China's climate policy uncertainty (CCPU).
Xiao‐Ming Li
wiley +1 more source
Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now
Journal of Forecasting, Volume 45, Issue 6, Page 2760-2784, September 2026.ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley +1 more source
Nowcasting World Trade With Machine Learning: A Three‐Step Approach
Journal of Forecasting, Volume 45, Issue 6, Page 2954-2968, September 2026.ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn +2 more
wiley +1 more source
Proximate Climate Drivers of Beaver Pond Occupancy and Range Expansion in Arctic Alaska
Global Change Biology Communications, Volume 1, Issue 3, September 2026.To understand why beavers are colonizing the Arctic, we evaluated which climate drivers underpin beaver pond dynamics. Warm Junes, mild winters, green summers, and wet springs facilitate pond establishment. Rapid improvement in these conditions across recent decades provides mechanistic support that climate change is driving beaver colonization of the ...
Thomas W. Glass +3 more
wiley +1 more source
Journal of Dairy Science: The ability of a dairy cow to perform reliably over time is an interesting trait to include in dairy cattle breeding programs aimed at improving dairy cow resilience.
Fiona L. Guinan +3 more
doaj +1 more source
Digital Phenotyping of Physical Activity and Mortality in Cancer Survivors
MedComm – Future Medicine, Volume 5, Issue 3, September 2026.The study analyzed wrist‐worn accelerometer data from 864 cancer survivors in the NHANES dataset (left panel). We identified three key digital phenotypes and their optimal thresholds for survival benefit: MIMS Volume (> 4945), Intensity (> 24), and Variability (> 2.4) (middle panel).
Yuanyou Li +5 more
wiley +1 more source
Non‐Elliptical Dimension Reduction in Survival Regression
Stat, Volume 15, Issue 3, September 2026.ABSTRACT Sufficient dimension reduction (SDR) in survival regression aims to identify low‐dimensional structures that preserve the relationship between survival time and predictors. Classical SDR methods, such as sliced inverse regression (SIR), rely on strong assumptions such as linearity, constant variance and coverage conditions, which are often ...
Minjee Kim, Minjeong Kim, Jae Keun Yoo
wiley +1 more source