Thomas Götz : Citation Profile

Are you Thomas Götz?

Deutsche Bundesbank

5

H index

4

i10 index

66

Citations

RESEARCH PRODUCTION:

6

Articles

11

Papers

RESEARCH ACTIVITY:

   7 years (2012 - 2019). See details.
   Cites by year: 9
   Journals where Thomas Götz has often published
   Relations with other researchers
   Recent citing documents: 16.    Total self citations: 14 (17.5 %)

MORE DETAILS IN:
ABOUT THIS REPORT:

   Permalink: http://citec.repec.org/pgt4
   Updated: 2021-04-17    RAS profile: 2021-03-05    
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Relations with other researchers

Works with:

Hecq, Alain (4)

Knetsch, Thomas (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 (11)

Miller, J. (8)

del Barrio Castro, Tomás (5)

Barnett, William (4)

Ferrara, Laurent (4)

Leiva-Leon, Danilo (4)

Simoni, Anna (4)

Havranek, Tomas (3)

Marçal, Emerson (3)

Rossi, Eduardo (3)

Bonham, Carl (3)

Cites to:

Hecq, Alain (19)

Marcellino, Massimiliano (19)

Santa-Clara, Pedro (12)

Silvestrini, Andrea (12)

Croushore, Dean (12)

Valkanov, Rossen (12)

Urbain, Jean-Pierre (11)

Galvão, Ana (9)

Clements, Michael (9)

Reichlin, Lucrezia (9)

Schumacher, Christian (9)

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 (2021 and 2020)

YearTitle of citing document
2020When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. (2020). Ferrara, Laurent ; Simoni, Anna. In: Papers. RePEc:arx:papers:2007.00273.

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2020Time-Varying Parameters as Ridge Regressions. (2020). Coulombe, Philippe Goulet. In: Papers. RePEc:arx:papers:2009.00401.

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2020Dimension Reduction for High Dimensional Vector Autoregressive Models. (2020). Hecq, Alain ; Cubadda, Gianluca. In: Papers. RePEc:arx:papers:2009.03361.

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2021Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions. (2021). Hecq, Alain ; Wilms, Ines ; Ternes, Marie. In: Papers. RePEc:arx:papers:2102.11780.

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2020Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?. (2020). Cristea, R G. In: Cambridge Working Papers in Economics. RePEc:cam:camdae:20108.

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2020When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage. (2020). Ferrara, Laurent ; Simoni, Anna. In: EconomiX Working Papers. RePEc:drm:wpaper:2020-11.

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2020Structural analysis with mixed-frequency data: A model of US capital flows. (2020). Rossi, Eduardo ; Missale, Alessandro ; Bastianin, Andrea ; Bacchiocchi, Emanuele. In: Economic Modelling. RePEc:eee:ecmode:v:89:y:2020:i:c:p:427-443.

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2020Computationally efficient inference in large Bayesian mixed frequency VARs. (2020). Poon, Aubrey ; Koop, Gary ; Gefang, Deborah. In: Economics Letters. RePEc:eee:ecolet:v:191:y:2020:i:c:s0165176520301014.

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2020Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality. (2020). Motegi, Kaiji ; Hill, Jonathan B ; Ghysels, Eric. In: Journal of Econometrics. RePEc:eee:econom:v:218:y:2020:i:2:p:633-654.

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2021Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit. (2021). Voia, Marcel ; Saunders, Charles J ; Kichian, Maral ; Khalaf, Lynda. In: Journal of Econometrics. RePEc:eee:econom:v:220:y:2021:i:2:p:589-605.

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2020Google trends and the predictability of precious metals. (2020). Salisu, Afees ; Ogbonna, Ahamuefula ; Adewuyi, Adeolu. In: Resources Policy. RePEc:eee:jrpoli:v:65:y:2020:i:c:s0301420719307408.

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2020Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data. (2020). Mazzarella, Gianluca ; Geraci, Andrea ; Colagrossi, Marco ; Capema, Giulio. In: Working Papers. RePEc:jrs:wpaper:202004.

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2020Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs. (2020). Poon, Aubrey ; Gefang, Deborah ; Koop, Gary. In: Economic Statistics Centre of Excellence (ESCoE) Discussion Papers. RePEc:nsr:escoed:escoe-dp-2020-07.

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2021Forecasting tourist arrivals: Google Trends meets mixed-frequency data. (2021). Havranek, Tomas ; Zeynalov, Ayaz. In: Tourism Economics. RePEc:sae:toueco:v:27:y:2021:i:1:p:129-148.

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2020Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial. (2020). Gunay, Mahmut. In: Working Papers. RePEc:tcb:wpaper:2002.

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2020Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach.. (2020). Heinrich, Markus. In: EconStor Preprints. RePEc:zbw:esprep:219312.

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Works by Thomas Götz:

YearTitleTypeCited
2019Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes In: Journal of Time Series Analysis.
[Full Text][Citation analysis]		article0
2018Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes.(2018) In: MPRA Paper.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 0		paper
2014Nowcasting causality in mixed frequency vector autoregressive models In: Economics Letters.
[Full Text][Citation analysis]		article10
2013Nowcasting causality in mixed frequency vector autoregressive models.(2013) In: Research Memorandum.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 10		paper
2016Testing for Granger causality in large mixed-frequency VARs In: Journal of Econometrics.
[Full Text][Citation analysis]		article10
2014Testing for Granger causality in large mixed-frequency VARs.(2014) In: Research Memorandum.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 10		paper
2015Testing for Granger Causality in Large Mixed-Frequency VARs.(2015) In: Research Memorandum.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 10		paper
2015Testing for Granger causality in large mixed-frequency VARs.(2015) In: Discussion Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 10		paper
2016Combining forecasts from successive data vintages: An application to U.S. growth In: International Journal of Forecasting.
[Full Text][Citation analysis]		article4
2019Google data in bridge equation models for German GDP In: International Journal of Forecasting.
[Full Text][Citation analysis]		article9
2017Google data in bridge equation models for German GDP.(2017) In: Discussion Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 9		paper
2013Testing for common cycles in non-stationary VARs with varied frecquency data In: Research Memorandum.
[Full Text][Citation analysis]		paper10
2014Combining distributions of real-time forecasts: An application to U.S. growth In: Research Memorandum.
[Full Text][Citation analysis]		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.
[Full Text][Citation analysis]		paper17
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: 17		article
2018Large mixed-frequency VARs with a parsimonious time-varying parameter structure In: Discussion Papers.
[Full Text][Citation analysis]		paper5

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