Results 1 to 10 of about 262 (135)
Complexity, 2021 This work compares Autometrics with dual penalization techniques such as minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) under asymmetric error distributions such as exponential, gamma, and Frechet with varying sample sizes ...
Faridoon Khan +4 more
doaj +3 more sources
EconomiesThe literature regarding innovation drivers is usually based on variables taken from some theoretical approach and validated within a methodology. Some authors have included COVID-19 as a driver for innovations.
Carlos Santos, Maria Alberta Oliveira
exaly +4 more sources
Complexity, 2022 In order to reduce the dimensionality of parameter space and enhance out-of-sample forecasting performance, this research compares regularization techniques with Autometrics in time-series modeling.
Sara Muhammadullah +5 more
doaj +2 more sources
Complexity, 2021 This research compares factor models based on principal component analysis (PCA) and partial least squares (PLS) with Autometrics, elastic smoothly clipped absolute deviation (E-SCAD), and minimax concave penalty (MCP) under different simulated schemes ...
Faridoon Khan +5 more
doaj +2 more sources
What Drives the Agricultural Growth in Azerbaijan? Insights from Autometrics with Super Saturation
Acta Universitatis Agriculturae Et Silviculturae Mendelianae Brunensis, 2022 The development of the agricultural sector is essential for any economy, including Azerbaijan, the largest economy in the South Caucasus, as it plays an important role in food security, rural development, and environmental protection.
Fakhri Hasanov +2 more
exaly +3 more sources
Selecting a Model for Forecasting
Econometrics, 2021 We investigate forecasting in models that condition on variables for which future values are unknown. We consider the role of the significance level because it guides the binary decisions whether to include or exclude variables.
Jennifer L. Castle +2 more
exaly +3 more sources
Statistical model selection with “Big Data”
Cogent Economics and Finance, 2015 Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods.
Jurgen Doornik +2 more
exaly +2 more sources
Improving the teaching of econometrics
Cogent Economics and Finance, 2016 We recommend a major shift in the Econometrics curriculum for both graduate and undergraduate teaching. It is essential to include a range of topics that are still rarely addressed in such teaching, but are now vital for understanding and conducting ...
Yr Athro Steve Cook +2 more
exaly +2 more sources
Detecting Location Shifts during Model Selection by Step-Indicator Saturation
Econometrics, 2015 To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables.
Jennifer L. Castle +2 more
exaly +3 more sources
RisksThis study investigates the determinants of trading activity in the U.S. corporate bond market, focusing on the effects of Seasonal Affective Disorder (SAD) and macroeconomic announcements. Employing the General-to-Specific (Gets) Autometrics methodology,
James Forest, Ben Shirley Branch
exaly +3 more sources