body {overflow: hidden;} .js-needed-message {position: fixed; z-index: 999; width: 100%; height: 100%; background-color: rgba(0, 0, 0, 0.5); } .js-needed-message p {color: #444; width: 50%; padding: 30px; position: relative; top: 40%; left: 25%; pointer-events: auto; background-color: #fff; background-clip: padding-box; border: 1px solid rgba(0, 0, 0, 0.2); border-radius: 0.3rem; outline: 0; }

Enable JavaScript in your browser to view this website correctly.

Close panel

Home
Publications
Who we are
Big Data

High frecuency

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

125

High granularity

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

137

Geopolitic

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

149

Publications

Forecasts

EN
ES

High frecuency

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

243

High granularity

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

255

Geopolitic

Warning

/var/www/html/wp-content/themes/bbvaresearch/headerMenu.php

267

Publications

Compartir RRSS Cerrar RRSS

Published on Monday, May 23, 2016 | Updated on Tuesday, April 16, 2019

Document number 16/10

Long and short-run components in explanatory variables and different panel-data estimates

Publication Documents and files Authors

Summary

We investigate the idea that when we separate an explanatory variable into its “between” and “within” variations we could be roughly decomposing it into a structural (long-term) and a cyclical component respectively, and this could translate into different Between and Within estimates in panel data.