|
|
|
|
| LEADER |
01000caa a22002652c 4500 |
| 001 |
NLM342288822 |
| 003 |
DE-627 |
| 005 |
20250303113552.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231226s2020 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1080/02664763.2019.1652253
|2 doi
|
| 028 |
5 |
2 |
|a pubmed25n1140.xml
|
| 035 |
|
|
|a (DE-627)NLM342288822
|
| 035 |
|
|
|a (NLM)35707494
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Behrens, Christoph
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Do German economic research institutes publish efficient growth and inflation forecasts? A Bayesian analysis
|
| 264 |
|
1 |
|c 2020
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Revised 16.07.2022
|
| 500 |
|
|
|a published: Electronic-eCollection
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a © 2019 Informa UK Limited, trading as Taylor & Francis Group.
|
| 520 |
|
|
|a We use Bayesian additive regression trees to reexamine the efficiency of growth and inflation forecasts for Germany. To this end, we use forecasts of four leading German economic research institutes for the sample period from 1970 to 2016. We reject the strong form of forecast efficiency and find evidence against the weak form of forecast efficiency for longer-term growth and longer-term inflation forecasts. We cannot reject weak efficiency of short-term growth and inflation forecasts and of forecasts disaggregated at the institute level. We find that Bayesian additive regression trees perform significantly better than a standard linear efficiency-regression model in terms of forecast accuracy
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Bayesian modeling
|
| 650 |
|
4 |
|a C53
|
| 650 |
|
4 |
|a E31
|
| 650 |
|
4 |
|a E32
|
| 650 |
|
4 |
|a E37
|
| 650 |
|
4 |
|a Forecast efficiency
|
| 650 |
|
4 |
|a regression trees
|
| 700 |
1 |
|
|a Pierdzioch, Christian
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Risse, Marian
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t Journal of applied statistics
|d 1991
|g 47(2020), 4 vom: 09., Seite 698-723
|w (DE-627)NLM098188178
|x 0266-4763
|7 nnas
|
| 773 |
1 |
8 |
|g volume:47
|g year:2020
|g number:4
|g day:09
|g pages:698-723
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1080/02664763.2019.1652253
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 47
|j 2020
|e 4
|b 09
|h 698-723
|