Zobrazeno 1 - 6
of 6
pro vyhledávání: '"David de Antonio Liedo"'
Publikováno v:
Journal of Business Cycle Research. 14:1-46
This paper analyses the contribution of survey data, in particular various sentiment indicators, to nowcasts of quarterly euro area GDP. It uses a genuine real-time dataset that is constructed from original press releases in order to transform the ac
Autor:
David de Antonio Liedo
This paper proposes a method that takes into account the calendar of European and Belgian intraquarterly data releases to automatically update GDP growth expectations or nowcasts in realtime. The role of surveys is well known in the nowcasting litera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80c3b31960eff4162c0eec9b7adf72bf
https://www.nbb.be/doc/oc/repec/reswpp/wp256en.pdf
https://www.nbb.be/doc/oc/repec/reswpp/wp256en.pdf
Publikováno v:
SSRN Electronic Journal.
This article presents the first open source IT solution for nowcasting and reading news with dynamic factor models. As illustrated in our workhorse example, the software allows us to extend the limits of currently established practices. The nowcastin
Publikováno v:
International Journal of Computational Economics and Econometrics. 7:5
This paper analyses the nowcasting performance of hyper-parameterised dynamic regression models with a large number of variables in log levels, and compares it with state-of-the-art methods for nowcasting. We deal with the 'curse of dimensionality' b
Publikováno v:
SSRN Electronic Journal.
The sharp decline in economic activity registered in Spain over 2008 and 2009 has no precedents in recent history. After ten prosperous years with an average GDP growth of 3.7%, the current recession places non-judgemental forecasting models under st
Autor:
David de Antonio Liedo
Publikováno v:
SSRN Electronic Journal.
This paper proposes the use of dynamic factor models as an alternative to the VAR-based tools for the empirical validation of dynamic stochastic general equilibrium (DSGE) theories. Along the lines of Giannone et al. (2006), we use the state-space pa