Skip to main navigation
Skip to search
Skip to main content
Maastricht University Home
Support & FAQ
Link opens in a new tab
Search content at Maastricht University
Home
Researchers
Publications
Activities
Press/Media
Prizes
Organisations
Dataset/Software
Projects
Forecasting using sparse cointegration
Ines Wilms
*
, Christophe Croux
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
Academic
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Forecasting using sparse cointegration'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Cointegration
100%
Cointegrating Vector
100%
Prediction Accuracy
66%
High-dimensional Setting
66%
Long-term Equilibrium Relationship
66%
Johansen's Method
66%
Growth Forecasting
66%
Sparse Estimators
66%
Cointegration Model
66%
Interest Rates
33%
Some Element
33%
Estimation Accuracy
33%
Sparse Estimation
33%
Sparse Methods
33%
Consumption Growth
33%
Cointegration Analysis
33%
INIS
vectors
100%
forecasting
100%
accuracy
66%
equilibrium
66%
growth
66%
comparative evaluations
33%
gain
33%
interest rate
33%
lead method
33%
Economics, Econometrics and Finance
Time Series
100%
Interest Rate
33%