Rutger-Jan Lange : Citation Profile

Are you Rutger-Jan Lange?

Erasmus Universiteit Rotterdam

5

H index

3

i10 index

94

Citations

RESEARCH PRODUCTION:

6

Articles

12

Papers

RESEARCH ACTIVITY:

   9 years (2015 - 2024). See details.
   Cites by year: 10
   Journals where Rutger-Jan Lange has often published
   Relations with other researchers
   Recent citing documents: 17.    Total self citations: 6 (6 %)

MORE DETAILS IN:
ABOUT THIS REPORT:

   Permalink: http://citec.repec.org/pla919
   Updated: 2024-07-05    RAS profile: 2024-02-07    
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Relations with other researchers

Works with:

Authors registered in RePEc who have co-authored more than one work in the last five years with Rutger-Jan Lange.

Is cited by:

Blazsek, Szabolcs (10)

Harvey, Andrew (9)

Ayala, Astrid (5)

Escribano, Alvaro (5)

Murray, Cameron (3)

Makieła, Kamil (3)

Fuertes, Ana-Maria (3)

Neuenkirch, Matthias (3)

González-Fernández, Marcos (2)

Schütte, Erik Christian (2)

Bhattacharjee, Arnab (2)

Cites to:

Koopman, Siem Jan (34)

Lucas, Andre (33)

Creal, Drew (17)

Harvey, Andrew (15)

Gyourko, Joseph (10)

Davis, Morris (10)

Bauwens, Luc (9)

Engle, Robert (9)

Campbell, John (8)

Rossi-Hansberg, Esteban (7)

Blasques, Francisco (7)

Main data

Where Rutger-Jan Lange has published?

Working Papers Series with more than one paper published# docs
Tinbergen Institute Discussion Papers / Tinbergen Institute8

Recent works citing Rutger-Jan Lange (2024 and 2023)

YearTitle of citing document
2023Anticipating extreme losses using score-driven shape filters. (2023). Blazsek, Szabolcs ; Alvaro, Escribano ; Szabolcs, Blazsek ; Astrid, Ayala. In: Studies in Nonlinear Dynamics & Econometrics. RePEc:bpj:sndecm:v:27:y:2023:i:4:p:449-484:n:1.

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2023Dynamic Mixture Vector Autoregressions with Score-Driven Weights. (2023). Umlandt, Dennis ; Neuenkirch, Matthias ; Gretener, Alexander Georges. In: CESifo Working Paper Series. RePEc:ces:ceswps:_10366.

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2023Modeling an early warning system for household debt risk in Korea: A simple deep learning approach. (2023). Park, Sung Y. ; Kwon, Yujin. In: Journal of Asian Economics. RePEc:eee:asieco:v:84:y:2023:i:c:s1049007822001300.

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2023Using a price floor on carbon allowances to achieve emission reductions under uncertainty. (2023). Hueng, C. ; Lemke, Robert J ; Zhang, Xinhua. In: Economic Analysis and Policy. RePEc:eee:ecanpo:v:80:y:2023:i:c:p:1096-1110.

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2023A dynamic conditional score model for the log correlation matrix. (2023). Wang, Linqi ; Hafner, Christian M. In: Journal of Econometrics. RePEc:eee:econom:v:237:y:2023:i:2:s0304407621002153.

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2023Score-driven models for realized volatility. (2023). Palumbo, Dario ; Harvey, Andrew. In: Journal of Econometrics. RePEc:eee:econom:v:237:y:2023:i:2:s0304407623001422.

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2023Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance. (2023). Umlandt, Dennis. In: Journal of Econometrics. RePEc:eee:econom:v:237:y:2023:i:2:s0304407623001641.

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2023Dynamic Tobit models. (2023). Liao, Yin ; Harvey, Andew. In: Econometrics and Statistics. RePEc:eee:ecosta:v:26:y:2023:i:c:p:72-83.

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2023Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data. (2023). Montes, Erik Christian ; Rapach, David E ; Borup, Daniel. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:3:p:1122-1144.

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2023Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model. (2023). Bhattacharjee, Arnab ; Kohns, David. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:3:p:1384-1412.

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2023An end-to-end deep learning model for solving data-driven newsvendor problem with accessibility to textual review data. (2023). Zhang, Chuan ; Tian, Yu-Xin. In: International Journal of Production Economics. RePEc:eee:proeco:v:265:y:2023:i:c:s0925527323002487.

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2023.

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2023When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage. (2022). Simoni, Anna ; Ferrara, Laurent. In: Post-Print. RePEc:hal:journl:hal-03919944.

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2023The two-component Beta-t-QVAR-M-lev: a new forecasting model. (2023). Blazsek, Szabolcs ; Cardia, Michel Ferreira ; Sheng, Hsia Hua ; Fuerst, Franz ; Arestis, Philip. In: Financial Markets and Portfolio Management. RePEc:kap:fmktpm:v:37:y:2023:i:4:d:10.1007_s11408-023-00431-4.

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2023Forecasting unemployment with Google Trends: age, gender and digital divide. (2023). Garcia-Hiernaux, Alfredo ; Mulero, Rodrigo. In: Empirical Economics. RePEc:spr:empeco:v:65:y:2023:i:2:d:10.1007_s00181-022-02347-w.

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2023Information-Theoretic Time-Varying Density Modeling. (2023). van Os, Bram. In: Tinbergen Institute Discussion Papers. RePEc:tin:wpaper:20230037.

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Works by Rutger-Jan Lange:

YearTitleTypeCited
2018Modeling the Interactions between Volatility and Returns using EGARCH?M In: Journal of Time Series Analysis.
[Full Text][Citation analysis]		article13
2015Volatility Modeling with a Generalized t-distribution In: Cambridge Working Papers in Economics.
[Full Text][Citation analysis]		paper39
2015Modeling the Interactions between Volatility and Returns In: Cambridge Working Papers in Economics.
[Full Text][Citation analysis]		paper3
2018The option value of vacant land and the optimal timing of city extensions In: CEPR Discussion Papers.
[Full Text][Citation analysis]		paper4
2018The option value of vacant land and the optimal timing of city extensions.(2018) In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]
This paper has nother version. Agregated cites: 4		paper
2020Real-Option Valuation in Multiple Dimensions Using Poisson Optional Stopping Times In: Journal of Financial and Quantitative Analysis.
[Full Text][Citation analysis]		article8
2024Bellman filtering and smoothing for state–space models In: Journal of Econometrics.
[Full Text][Citation analysis]		article0
2020Can Google search data help predict macroeconomic series? In: International Journal of Forecasting.
[Full Text][Citation analysis]		article19
0000Can Google Search Data Help Predict Macroeconomic Series?.(0000) In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]
This paper has nother version. Agregated cites: 19		paper
2024Irreversible investment under predictable growth: Why land stays vacant when housing demand is booming In: Journal of Economic Theory.
[Full Text][Citation analysis]		article0
2018Systems Innovation, Inertia and Pliability: A mathematical exploration with implications for climate change abatement In: Working Papers.
[Full Text][Citation analysis]		paper0
2016When Is Information Sufficient for Action? Search with Unreliable yet Informative Intelligence In: Operations Research.
[Full Text][Citation analysis]		article2
2016Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper5
2021Bellman filtering for state-space models In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper0
2022Interactions of time and technology as critical determinants of optimal climate change policy In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper1
2021The option value of vacant land: Dont build when demand for housing is booming In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper0
2022Robust Observation-Driven Models Using Proximal-Parameter Updates Abstract We propose an observation-driven modelling framework that permits time variation in the model’s parameters using a proximal-p In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper0
2022Dynamic Partial Correlation Models In: Tinbergen Institute Discussion Papers.
[Full Text][Citation analysis]		paper0

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