Thomas Götz : Citation Profile


Are you Thomas Götz?

Deutsche Bundesbank

5

H index

1

i10 index

44

Citations

RESEARCH PRODUCTION:

5

Articles

11

Papers

RESEARCH ACTIVITY:

   6 years (2012 - 2018). See details.
   Cites by year: 7
   Journals where Thomas Götz has often published
   Relations with other researchers
   Recent citing documents: 13.    Total self citations: 14 (24.14 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pgt4
   Updated: 2019-10-15    RAS profile: 2019-05-08    
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Relations with other researchers


Works with:

Hecq, Alain (10)

Smeekes, Stephan (3)

Knetsch, Thomas (2)

Urbain, Jean-Pierre (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Thomas Götz.

Is cited by:

Hecq, Alain (8)

Miller, J. (8)

del Barrio Castro, Tomás (5)

Barnett, William (4)

Leiva-Leon, Danilo (4)

Mendonça, Diogo (3)

Merlin, Giovanni (3)

Motegi, Kaiji (3)

Fuleky, Peter (3)

Chauvet, Marcelle (3)

Marçal, Emerson (3)

Cites to:

Hecq, Alain (23)

Marcellino, Massimiliano (22)

Veredas, David (15)

Silvestrini, Andrea (15)

Valkanov, Rossen (14)

Santa-Clara, Pedro (14)

Miller, J. (13)

Urbain, Jean-Pierre (13)

Croushore, Dean (12)

Schumacher, Christian (11)

Galvão, Ana (10)

Main data


Where Thomas Götz has published?


Journals with more than one article published# docs
International Journal of Forecasting2

Working Papers Series with more than one paper published# docs
Research Memorandum / Maastricht University, Graduate School of Business and Economics (GSBE)5
Discussion Papers / Deutsche Bundesbank3
Research Memorandum / Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR)2

Recent works citing Thomas Götz (2019 and 2018)


YearTitle of citing document
2019Simulation smoothing for nowcasting with large mixed-frequency VARs. (2019). Ankargren, Sebastian ; Jon, Paulina. In: Papers. RePEc:arx:papers:1907.01075.

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2018Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data. (2018). Urtasun, Alberto ; Sanchez Fuentes, Antonio Jesus ; Pérez, Javier ; Perez, Javier J ; Gil, Maria. In: Working Papers. RePEc:bde:wpaper:1842.

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2019When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. (2019). Simoni, Anna ; Ferrara, Laurent. In: Working papers. RePEc:bfr:banfra:717.

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2019When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. (2019). Simoni, Anna ; Ferrara, Laurent. In: Working Papers. RePEc:crs:wpaper:2019-04.

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2018Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach. (2018). Motegi, Kaiji ; Sadahiro, Akira. In: The North American Journal of Economics and Finance. RePEc:eee:ecofin:v:43:y:2018:i:c:p:118-128.

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2018Simple robust tests for the specification of high-frequency predictors of a low-frequency series. (2018). Miller, J.. In: Econometrics and Statistics. RePEc:eee:ecosta:v:5:y:2018:i:c:p:45-66.

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2019Testing for news and noise in non-stationary time series subject to multiple historical revisions. (2019). Hecq, Alain ; Stamatogiannis, Michalis P. In: Journal of Macroeconomics. RePEc:eee:jmacro:v:60:y:2019:i:c:p:396-407.

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2018Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data. (2018). Havranek, Tomas ; Zeynalov, Ayaz. In: MPRA Paper. RePEc:pra:mprapa:90205.

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2019Monthly Forecasting of GDP with Mixed Frequency Multivariate Singular Spectrum Analysis. (2019). Thomakos, Dimitrios ; Silva, Emmanuel Sirimal ; Hassani, Hossein ; Rua, Antonio. In: Working Papers. RePEc:ptu:wpaper:w201913.

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2018A note on the predictive power of survey data in nowcasting euro area GDP. (2018). Kurz-Kim, Jeong-Ryeol. In: Discussion Papers. RePEc:zbw:bubdps:102018.

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2018Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations. (2018). Pinkwart, Nicolas . In: Discussion Papers. RePEc:zbw:bubdps:362018.

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2018Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data. (2018). Havranek, Tomas ; Zeynalov, Ayaz. In: EconStor Preprints. RePEc:zbw:esprep:187420.

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Works by Thomas Götz:


YearTitleTypeCited
2014Nowcasting causality in mixed frequency vector autoregressive models In: Economics Letters.
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article7
2013Nowcasting causality in mixed frequency vector autoregressive models.(2013) In: Research Memorandum.
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This paper has another version. Agregated cites: 7
paper
2016Testing for Granger causality in large mixed-frequency VARs In: Journal of Econometrics.
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article5
2014Testing for Granger causality in large mixed-frequency VARs.(2014) In: Research Memorandum.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 5
paper
2015Testing for Granger Causality in Large Mixed-Frequency VARs.(2015) In: Research Memorandum.
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This paper has another version. Agregated cites: 5
paper
2015Testing for Granger causality in large mixed-frequency VARs.(2015) In: Discussion Papers.
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This paper has another version. Agregated cites: 5
paper
2016Combining forecasts from successive data vintages: An application to U.S. growth In: International Journal of Forecasting.
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article3
2019Google data in bridge equation models for German GDP In: International Journal of Forecasting.
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article5
2017Google data in bridge equation models for German GDP.(2017) In: Discussion Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 5
paper
2018Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes In: MPRA Paper.
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paper0
2013Testing for common cycles in non-stationary VARs with varied frecquency data In: Research Memorandum.
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paper9
2014Combining distributions of real-time forecasts: An application to U.S. growth In: Research Memorandum.
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paper1
2012Real-Time Forecast Density Combinations (Forecasting US GDP Growth Using Mixed-Frequency Data).(2012) In: Research Memorandum.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 1
paper
2012Forecasting Mixed Frequency Time Series with ECM-MIDAS Models In: Research Memorandum.
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paper14
2014Forecasting Mixed‐Frequency Time Series with ECM‐MIDAS Models.(2014) In: Journal of Forecasting.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 14
article
2018Large mixed-frequency VARs with a parsimonious time-varying parameter structure In: Discussion Papers.
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paper0

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