Pilar Poncela : Citation Profile


Are you Pilar Poncela?

Universidad Autónoma de Madrid

12

H index

14

i10 index

406

Citations

RESEARCH PRODUCTION:

37

Articles

27

Papers

1

Chapters

RESEARCH ACTIVITY:

   27 years (1996 - 2023). See details.
   Cites by year: 15
   Journals where Pilar Poncela has often published
   Relations with other researchers
   Recent citing documents: 33.    Total self citations: 23 (5.36 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/ppo612
   Updated: 2024-01-16    RAS profile: 2022-03-22    
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Relations with other researchers


Works with:

Ruiz, Esther (3)

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

Is cited by:

Leiva-Leon, Danilo (12)

Sierra, Lya (10)

Camacho, Maximo (9)

Reif, Magnus (9)

Corona, Francisco (9)

Wolters, Maik (9)

Carstensen, Kai (9)

Martinez-Martin, Jaime (8)

Perez Quiros, Gabriel (7)

Ferrara, Laurent (6)

Ruiz, Esther (6)

Cites to:

Reichlin, Lucrezia (104)

Giannone, Domenico (76)

Watson, Mark (48)

Forni, Mario (44)

Lippi, Marco (40)

Bai, Jushan (37)

Ng, Serena (35)

Hallin, Marc (33)

Perez Quiros, Gabriel (27)

Camacho, Maximo (21)

Diebold, Francis (21)

Main data


Where Pilar Poncela has published?


Journals with more than one article published# docs
International Journal of Forecasting9
Empirical Economics3
Applied Economics2
Journal of Applied Econometrics2
Revista CEPAL2
Statistics & Probability Letters2

Working Papers Series with more than one paper published# docs
DES - Working Papers. Statistics and Econometrics. WS / Universidad Carlos III de Madrid. Departamento de Estadística14
Working Papers / Banco de Espaa4
CEPR Discussion Papers / C.E.P.R. Discussion Papers3

Recent works citing Pilar Poncela (2024 and 2023)


YearTitle of citing document
2023Deep Dynamic Factor Models. (2020). Ricco, Giovanni ; Izzo, Cosimo ; Andreini, Paolo. In: Papers. RePEc:arx:papers:2007.11887.

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2023Global combinations of expert forecasts. (2022). Vasnev, Andrey L ; Thompson, Ryan ; Qian, Yilin. In: Papers. RePEc:arx:papers:2207.07318.

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2023Network log-ARCH models for forecasting stock market volatility. (2023). Otto, Philipp ; Mattera, Raffaele. In: Papers. RePEc:arx:papers:2303.11064.

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2023sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings. (2023). Gibberd, Alex ; Chan, Tak-Shing ; Mosley, Luke. In: Papers. RePEc:arx:papers:2303.14125.

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2023Inference on common trends in functional time series. (2023). Seo, Won-Ki ; Nielsen, Morten Orregaard ; Seong, Dakyung. In: Papers. RePEc:arx:papers:2312.00590.

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2023Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts. (2023). Caporale, Guglielmo Maria ; Anderl, Christina. In: Manchester School. RePEc:bla:manchs:v:91:y:2023:i:3:p:171-232.

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2023How to Deal With Missing Observations in Surveys of Professional Forecasters. (2023). Burgi, Constantin. In: CESifo Working Paper Series. RePEc:ces:ceswps:_10203.

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2023Economic activity and C02 emissions in Spain. (2023). Ortega, Esther Ruiz ; Poncela, Maria Pilar ; de Juan, Aranzazu. In: DES - Working Papers. Statistics and Econometrics. WS. RePEc:cte:wsrepe:37975.

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2023Dynamic Factor Models: a Genealogy. (2023). Hallin, Marc ; Barigozzi, Matteo. In: Working Papers ECARES. RePEc:eca:wpaper:2013/364359.

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2023A deep dive into the capital channel of risk sharing in the euro area. (2023). Born, Alexandra ; Fuentes, Natalia Martin ; Lambert, Claudia ; Kastelein, Wieger ; Bremus, Franziska. In: Working Paper Series. RePEc:ecb:ecbwps:20232864.

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2023Pass-through Effects of Oil Prices on LATAM Emerging Stocks before and during COVID-19: An Evidence from a Wavelet -VAR Analysis. (2023). Ahmed, Gouher ; Sisodia, Gyanendra Singh ; Rafiuddin, Aqila ; Tellez, Jesus Cuauhtemoc ; Paramaiah, CH. In: International Journal of Energy Economics and Policy. RePEc:eco:journ2:2023-01-56.

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2023Private health insurance consumption and public health-care provision in OECD countries: Impact of culture, finance, and the pandemic. (2023). Ho, Nhut Quang ; Chao, Chi-Chur ; Trinh, Cong Tam. In: The North American Journal of Economics and Finance. RePEc:eee:ecofin:v:64:y:2023:i:c:s106294082200184x.

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2023Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models. (2023). Ruiz, Esther ; Poncela, Pilar ; Fresoli, Diego. In: Economics Letters. RePEc:eee:ecolet:v:230:y:2023:i:c:s0165176523002719.

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2023High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research. (2023). Anderson, Brian ; Deistler, Manfred ; Lippi, Marco. In: Econometrics and Statistics. RePEc:eee:ecosta:v:26:y:2023:i:c:p:3-16.

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2023Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach. (2023). Urom, Christian ; Benkraiem, Ramzi ; Masood, Amna ; Raza, Syed Ali. In: Energy Economics. RePEc:eee:eneeco:v:120:y:2023:i:c:s0140988323000890.

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2023Risk sharing and the adoption of the Euro. (2023). Picco, Anna Rogantini ; Ferrari, Alessandro. In: Journal of International Economics. RePEc:eee:inecon:v:141:y:2023:i:c:s0022199623000132.

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2023Weekly economic activity: Measurement and informational content. (2023). Guggia, Valentino ; Glocker, Christian ; Wegmuller, Philipp. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:1:p:228-243.

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2023Estimation of a dynamic multi-level factor model with possible long-range dependence. (2023). Rodriguez-Caballero, Vladimir C ; Ergemen, Yunus Emre. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:1:p:405-430.

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2023What do the AI methods tell us about predicting price volatility of key natural resources: Evidence from hyperparameter tuning. (2023). Chavriya, Shubham ; Parihar, Jaya Singh ; Rao, Amar ; Srivastava, Mrinalini ; Singh, Surendar. In: Resources Policy. RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722006924.

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2023Risk-sharing and consumption-smoothing patterns in the US and the Euro Area: A comprehensive comparison. (2023). Thirion, Gilles ; Dimperio, Paolo ; Alcidi, Cinzia. In: Structural Change and Economic Dynamics. RePEc:eee:streco:v:64:y:2023:i:c:p:58-69.

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2023Short-Term Wind Power Prediction Based on a Hybrid Markov-Based PSO-BP Neural Network. (2023). Tian, Rong ; Zhao, Qigen ; Wang, Chia-Hung. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:11:p:4282-:d:1154052.

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2023Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP). (2023). Khoukhi, Lyes ; Mellal, Idir ; Oukaira, Aziz ; Said, Dhaou ; Khabbouchi, Imed. In: Energies. RePEc:gam:jeners:v:16:y:2023:i:5:p:2179-:d:1078891.

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2023.

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2023.

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2023Combining SEM, fsQCA and BNs to Explore E-Bike Riders’ Helmet Wearing Intentions under the Impact of Mandatory Policies: An Empirical Study in Zhenjiang. (2023). Jiang, Chengxi ; Jing, Peng ; Wang, Bichen. In: Sustainability. RePEc:gam:jsusta:v:15:y:2023:i:24:p:16704-:d:1297140.

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2023Effects of global energy and price fluctuations on Turkeys inflation: new evidence. (2023). Ozahin, Erife ; Ozmen, Brahim. In: Economic Change and Restructuring. RePEc:kap:ecopln:v:56:y:2023:i:4:d:10.1007_s10644-023-09530-8.

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2023Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008. (2023). Kim, Hyun Hak ; Swanson, Norman R. In: Empirical Economics. RePEc:spr:empeco:v:64:y:2023:i:3:d:10.1007_s00181-022-02289-3.

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2023Nowcasting Japan’s GDP. (2023). Tachi, Yuta ; Hayashi, Fumio. In: Empirical Economics. RePEc:spr:empeco:v:64:y:2023:i:4:d:10.1007_s00181-022-02301-w.

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2023Does climate change affect economic data?. (2023). Choi, IN. In: Empirical Economics. RePEc:spr:empeco:v:64:y:2023:i:6:d:10.1007_s00181-023-02363-4.

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2023Forecasting GDP with many predictors in a small open economy: forecast or information pooling?. (2023). Han, Daniel ; Fei, Yijie ; Chow, Hwee Kwan. In: Empirical Economics. RePEc:spr:empeco:v:65:y:2023:i:2:d:10.1007_s00181-022-02356-9.

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2023The D-model for GDP nowcasting. (2023). Degiannakis, Stavros. In: Swiss Journal of Economics and Statistics. RePEc:spr:sjecst:v:159:y:2023:i:1:d:10.1186_s41937-023-00109-8.

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2023Performance Improvement of LSTM-based Deep Learning Model for Streamflow Forecasting Using Kalman Filtering. (2023). Taheri, Somayeh ; Nia, Alireza Moghaddam ; Asadi, Ali ; Moradi, Saba ; Ostadkalayeh, Fatemeh Bakhshi. In: Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA). RePEc:spr:waterr:v:37:y:2023:i:8:d:10.1007_s11269-023-03492-2.

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2023Fiscal targets. A guide to forecasters?. (2023). Pérez, Javier ; Perez Quiros, Gabriel ; Paredes, Joan. In: Journal of Applied Econometrics. RePEc:wly:japmet:v:38:y:2023:i:4:p:472-492.

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Works by Pilar Poncela:


YearTitleTypeCited
2023Understanding fluctuations through Multivariate Circulant Singular Spectrum Analysis In: Papers.
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paper0
2010Green shoots in the euro area. A real time measure In: Working Papers.
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paper9
2012Extracting non-linear signals from several economic indicators In: Working Papers.
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paper33
2012Extracting nonlinear signals from several economic indicators.(2012) In: CEPR Discussion Papers.
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This paper has nother version. Agregated cites: 33
paper
2015Extracting Nonlinear Signals from Several Economic Indicators.(2015) In: Journal of Applied Econometrics.
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This paper has nother version. Agregated cites: 33
article
2012Markov-switching dynamic factor models in real time In: Working Papers.
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paper48
2012Markov-switching dynamic factor models in real time.(2012) In: CEPR Discussion Papers.
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This paper has nother version. Agregated cites: 48
paper
2018Markov-switching dynamic factor models in real time.(2018) In: International Journal of Forecasting.
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This paper has nother version. Agregated cites: 48
article
2013Short-term forecasting for empirical economists. A survey of the recently proposed algorithms In: Working Papers.
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paper24
2013Short-term Forecasting for Empirical Economists: A Survey of the Recently Proposed Algorithms.(2013) In: Foundations and Trends(R) in Econometrics.
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This paper has nother version. Agregated cites: 24
article
1998Measuring Intervention Effects on Multiple Time Series Subjected to Linear Restrictions: A Banking Example. In: Journal of Business & Economic Statistics.
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article0
1997Measuring intervention effects on multiplie time series subjected to linear restrictions: A Banking Example.(1997) In: DES - Working Papers. Statistics and Econometrics. WS.
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This paper has nother version. Agregated cites: 0
paper
2012Green Shoots and Double Dips in the Euro Area. A Real Time Measure In: CEPR Discussion Papers.
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paper23
2014Green shoots and double dips in the euro area: A real time measure.(2014) In: International Journal of Forecasting.
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This paper has nother version. Agregated cites: 23
article
1996Pooling information and forecasting with dynamic factor analysis In: DES - Working Papers. Statistics and Econometrics. WS.
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paper0
2017Estimating non-stationary common factors : Implications for risk sharing In: DES - Working Papers. Statistics and Econometrics. WS.
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paper8
2020Estimating Non-stationary Common Factors: Implications for Risk Sharing.(2020) In: Computational Economics.
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This paper has nother version. Agregated cites: 8
article
2020Factor extraction using Kalman filter and smoothing: this is not just another survey In: DES - Working Papers. Statistics and Econometrics. WS.
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paper12
2021Factor extraction using Kalman filter and smoothing: This is not just another survey.(2021) In: International Journal of Forecasting.
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This paper has nother version. Agregated cites: 12
article
2021Dynamic factor models: does the specification matter? In: DES - Working Papers. Statistics and Econometrics. WS.
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paper0
1997Data graduation based on statistical time series methods In: DES - Working Papers. Statistics and Econometrics. WS.
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paper3
2001Data graduation based on statistical time series methods.(2001) In: Statistics & Probability Letters.
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This paper has nother version. Agregated cites: 3
article
1997Eigenstructure of nonstationary factor models In: DES - Working Papers. Statistics and Econometrics. WS.
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paper1
2000Forecasting with nostationary dynamic factor models In: DES - Working Papers. Statistics and Econometrics. WS.
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paper28
2004Forecasting with nonstationary dynamic factor models.(2004) In: Journal of Econometrics.
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This paper has nother version. Agregated cites: 28
article
2002Forecasting monthly us consumer price indexes through a disaggregated I(2) analysis In: DES - Working Papers. Statistics and Econometrics. WS.
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paper6
2012Sparse partial least squares in time series for macroeconomic forecasting In: DES - Working Papers. Statistics and Econometrics. WS.
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paper12
2015Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting.(2015) In: Journal of Applied Econometrics.
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article
2012More is not always better : back to the Kalman filter in dynamic factor models In: DES - Working Papers. Statistics and Econometrics. WS.
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2014Selecting and combining experts from survey forecasts In: DES - Working Papers. Statistics and Econometrics. WS.
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paper1
2015Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment In: DES - Working Papers. Statistics and Econometrics. WS.
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2016Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment.(2016) In: Advances in Econometrics.
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This paper has nother version. Agregated cites: 6
chapter
2016Determining the number of factors after stationary univariate transformations In: DES - Working Papers. Statistics and Econometrics. WS.
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2017Determining the number of factors after stationary univariate transformations.(2017) In: Empirical Economics.
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This paper has nother version. Agregated cites: 5
article
2014México: la combinación de las predicciones mensuales de inflación mediante encuestas In: Revista CEPAL.
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article0
2014Mexico: Combining monthly inflation predictions from surveys In: Revista CEPAL.
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article0
2013Automatic tuning of Kalman filters by maximum likelihood methods for wind energy forecasting In: Applied Energy.
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article16
2022Seasonality in COVID-19 times In: Economics Letters.
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article1
2004Time series analysis by state space methods: J. Durbin and S.J. Koopman, Oxford Statistical Series 24, 2001, Oxford University Press, ISBN 0-19-852354-8, 254 pages, price: [UK pound]36.00 (hardback) In: International Journal of Forecasting.
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article0
2005Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models In: International Journal of Forecasting.
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article8
2005Introduction to nonlinearities, business cycles, and forecasting In: International Journal of Forecasting.
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article1
2006Forecasting traffic accidents using disaggregated data In: International Journal of Forecasting.
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article9
2011Forecast combination through dimension reduction techniques In: International Journal of Forecasting.
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article23
2011Forecast combination through dimension reduction techniques.(2011) In: International Journal of Forecasting.
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This paper has nother version. Agregated cites: 23
article
2016Choosing a dynamic common factor as a coincident index In: Statistics & Probability Letters.
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article1
2010Green Shoots? Where, when and how? In: Working Papers.
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2021Improving Wind Power Forecasts: Combination through Multivariate Dimension Reduction Techniques In: Energies.
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In: .
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2014Some New Results on the Estimation of Structural Budget Balance for Spain In: Hacienda Pública Española / Review of Public Economics.
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article5
2016Risk Sharing in Europe In: JRC Research Reports.
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2002Forecasting European GNP Data through Common Factor Models and Other Procedures. In: Journal of Forecasting.
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article6
2018New Risk Sharing Channels in OECD Countries: a Heterogeneous Panel VAR In: Working Papers.
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paper10
2020Global vs Sectoral Factors and the Impact of the Financialization in Commodity Price Changes In: Open Economies Review.
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article0
2017Automatic Signal Extraction for Stationary and Non-Stationary Time Series by Circulant SSA In: MPRA Paper.
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2019A Review of International Risk Sharing for Policy Analysis In: East Asian Economic Review.
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article8
2020A fragmented-periodogram approach for clustering big data time series In: Advances in Data Analysis and Classification.
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article3
2017Long-term links between raw materials prices, real exchange rate and relative de-industrialization in a commodity-dependent economy: empirical evidence of “Dutch disease” in Colombia In: Empirical Economics.
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article9
2017Measuring uncertainty and assessing its predictive power in the euro area In: Empirical Economics.
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article6
2017A new look at oil price pass-through into inflation: evidence from disaggregated European data In: Economia Politica: Journal of Analytical and Institutional Economics.
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2006A two factor model to combine US inflation forecasts In: Applied Economics.
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2014Common dynamics of nonenergy commodity prices and their relation to uncertainty In: Applied Economics.
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article19
2006Demand Forecast and Elasticities Estimation of Public Transport In: Journal of Transport Economics and Policy.
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article17
2007The relationship between road traffic accidents and real economic activity in spain: common cycles and health issues In: Health Economics.
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2014The Effects of Disaggregation on Forecasting Nonstationary Time Series In: Journal of Forecasting.
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article2
2020A comment on the dynamic factor model with dynamic factors In: Economics Discussion Papers.
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