Christian Schumacher : Citation Profile


Are you Christian Schumacher?

Deutsche Bundesbank

14

H index

16

i10 index

994

Citations

RESEARCH PRODUCTION:

18

Articles

25

Papers

RESEARCH ACTIVITY:

   19 years (2000 - 2019). See details.
   Cites by year: 52
   Journals where Christian Schumacher has often published
   Relations with other researchers
   Recent citing documents: 89.    Total self citations: 21 (2.07 %)

MORE DETAILS IN:
ABOUT THIS REPORT:

   Permalink: http://citec.repec.org/psc237
   Updated: 2021-10-09    RAS profile: 2019-05-10    
   Missing citations? Add them    Incorrect content? Let us know

Relations with other researchers


Works with:

Kaufmann, Sylvia (2)

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

Is cited by:

Marcellino, Massimiliano (54)

Wohlrabe, Klaus (36)

Foroni, Claudia (31)

Rua, António (30)

Ferrara, Laurent (29)

Siliverstovs, Boriss (25)

Scheufele, Rolf (24)

Lehmann, Robert (23)

Guérin, Pierre (23)

Kholodilin, Konstantin (19)

Heinisch, Katja (18)

Cites to:

Marcellino, Massimiliano (84)

Reichlin, Lucrezia (71)

Ng, Serena (50)

Giannone, Domenico (47)

Forni, Mario (46)

Lippi, Marco (43)

Watson, Mark (43)

Boivin, Jean (33)

Hallin, Marc (32)

Stock, James (27)

Bai, Jushan (24)

Main data


Where Christian Schumacher has published?


Journals with more than one article published# docs
International Journal of Forecasting4
Journal of Forecasting2
Journal of Applied Econometrics2
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik)2

Working Papers Series with more than one paper published# docs
Discussion Paper Series 1: Economic Studies / Deutsche Bundesbank8
Economics Working Papers / European University Institute3
Discussion Papers / Deutsche Bundesbank3
Discussion Paper Series / Hamburg Institute of International Economics2
HWWA Discussion Papers / Hamburg Institute of International Economics (HWWA)2

Recent works citing Christian Schumacher (2021 and 2020)


YearTitle of citing document
2021Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data. (2021). Montes, Erik Christian ; Rapach, David E ; Borup, Daniel. In: CREATES Research Papers. RePEc:aah:create:2021-02.

Full description at Econpapers || Download paper

2020Un modello statistico per il monitoraggio delle entrate tributarie (MoME). (2020). Giannone, Giacomo ; Faedda, Francesca ; Delia, Enrico. In: Working Papers. RePEc:ahg:wpaper:wp2020-5.

Full description at Econpapers || Download paper

2020Impact of manufacturing PMI on stock market index: A study on Turkey. (2020). Ozturk, Ozcan ; Osman, Asfia Binte ; Yanik, Ramazan. In: Journal of Administrative and Business Studies. RePEc:apb:jabsss:2020:p:104-108.

Full description at Econpapers || Download paper

2020Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction. (2019). Mogliani, Matteo. In: Papers. RePEc:arx:papers:1903.08025.

Full description at Econpapers || Download paper

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

Full description at Econpapers || Download paper

2021Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM). (2021). Hopp, Daniel. In: Papers. RePEc:arx:papers:2106.08901.

Full description at Econpapers || Download paper

2021Sparse Temporal Disaggregation. (2021). Gibberd, Alex ; Eckley, Idris ; Mosley, Luke . In: Papers. RePEc:arx:papers:2108.05783.

Full description at Econpapers || Download paper

2021Implicit Copulas: An Overview. (2021). Smith, Michael Stanley. In: Papers. RePEc:arx:papers:2109.04718.

Full description at Econpapers || Download paper

2021Macroeconomic forecasting with LSTM and mixed frequency time series data. (2021). Kamolthip, Sarun. In: Papers. RePEc:arx:papers:2109.13777.

Full description at Econpapers || Download paper

2020Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas. (2020). Cardenas-Cardenas, Julian Alonso ; Gonzalez, Eliana R ; Caicedo-Garcia, Edgar. In: Borradores de Economia. RePEc:bdr:borrec:1109.

Full description at Econpapers || Download paper

2021Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches. (2021). Rojas-Martinez, Carlos D ; Martinez-Cortes, Nicolas ; Galeano-Ramirez, Franky Juliano. In: Borradores de Economia. RePEc:bdr:borrec:1168.

Full description at Econpapers || Download paper

2020Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data. (2020). Paredes, Joan ; Asimakopoulos, Stylianos ; Warmedinger, Thomas. In: Scandinavian Journal of Economics. RePEc:bla:scandj:v:122:y:2020:i:1:p:369-390.

Full description at Econpapers || Download paper

2020News media vs. FRED-MD for macroeconomic forecasting. (2020). Thorsrud, Leif ; Larsen, Vegard ; Ellingsen, Jon. In: Working Paper. RePEc:bno:worpap:2020_14.

Full description at Econpapers || Download paper

2020Nowcasting Norwegian household consumption with debit card transaction data. (2020). Torstensen, Kjersti Nss ; Paulsen, Kenneth Sterhagen ; Granziera, Eleonora ; Fastb, Tuva Marie ; Aastveit, Knut Are. In: Working Paper. RePEc:bno:worpap:2020_17.

Full description at Econpapers || Download paper

2020News media vs. FRED-MD for macroeconomic forecasting. (2020). Thorsrud, Leif ; Larsen, Vegard ; Ellingsen, Jon. In: Working Papers. RePEc:bny:wpaper:0091.

Full description at Econpapers || Download paper

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.

Full description at Econpapers || Download paper

2020Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters. (2020). Reif, Magnus ; Heinrich, Markus. In: CESifo Working Paper Series. RePEc:ces:ceswps:_8054.

Full description at Econpapers || Download paper

2020The Forecasting Power of the ifo Business Survey. (2020). Lehmann, Robert. In: CESifo Working Paper Series. RePEc:ces:ceswps:_8291.

Full description at Econpapers || Download paper

2020News Media vs. FRED-MD for Macroeconomic Forecasting. (2020). Thorsrud, Leif ; Larsen, Vegard ; Ellingsen, Jon. In: CESifo Working Paper Series. RePEc:ces:ceswps:_8639.

Full description at Econpapers || Download paper

2020A Comparison of Monthly Global Indicators for Forecasting Growth. (2020). Guérin, Pierre ; Baumeister, Christiane. In: CESifo Working Paper Series. RePEc:ces:ceswps:_8656.

Full description at Econpapers || Download paper

2020Macroeconomics, Nonlinearities, and the Business Cycle. (2020). Reif, Magnus. In: ifo Beiträge zur Wirtschaftsforschung. RePEc:ces:ifobei:87.

Full description at Econpapers || Download paper

2020ifo Handbuch der Konjunkturumfragen. (2020). Wohlrabe, Klaus ; Sauer, Stefan. In: ifo Beiträge zur Wirtschaftsforschung. RePEc:ces:ifobei:88.

Full description at Econpapers || Download paper

2020ifoCAST: Der neue Prognosestandard des ifo Instituts. (2020). Wollmershäuser, Timo ; Lehmann, Robert ; Wollmershauser, Timo ; Reif, Magnus. In: ifo Schnelldienst. RePEc:ces:ifosdt:v:73:y:2020:i:11:p:31-39.

Full description at Econpapers || Download paper

2020ifo Konjunkturprognose Winter 2020: Das Coronavirus schlägt zurück – erneuter Shutdown bremst Konjunktur ein zweites Mal aus. (2020). Link, Sebastian ; Lehmann, Robert ; Göttert, Marcell ; Grimme, Christian ; Gottert, Marcell ; Sandqvist, Pauliina ; Wollmershauser, Timo ; Reif, Magnus ; Rathje, Ann-Christin ; Mohrle, Sascha ; Menkhoff, Manuel ; Sauer, Stefan ; Wolf, Anna ; Lautenbacher, Stefan ; Stockli, Marc. In: ifo Schnelldienst. RePEc:ces:ifosdt:v:73:y:2020:i:sonderausgabe:p:03-61.

Full description at Econpapers || Download 2020

Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis. (2020). Stevanovic, Dalibor ; Marcellino, Massimiliano ; Foroni, Claudia. In: CIRANO Working Papers. RePEc:cir:cirwor:2020s-32.

Full description at Econpapers || Download paper

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.

Full description at Econpapers || Download paper

2020Forecasting the Covid-19 recession and recovery: lessons from the financial crisis. (2020). Stevanovic, Dalibor ; Marcellino, Massimiliano ; Foroni, Claudia. In: Working Paper Series. RePEc:ecb:ecbwps:20202468.

Full description at Econpapers || Download paper

2020Forecasting the Consumer Confidence Index with tree-based MIDAS regressions. (2020). Qiu, Yue. In: Economic Modelling. RePEc:eee:ecmode:v:91:y:2020:i:c:p:247-256.

Full description at Econpapers || Download paper

2020Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models. (2020). Seong, Byeongchan . In: Economic Modelling. RePEc:eee:ecmode:v:91:y:2020:i:c:p:463-468.

Full description at Econpapers || Download paper

2020Mixed data sampling expectile regression with applications to measuring financial risk. (2020). Yu, Keming ; Jiang, Cuixia ; Chen, LU ; Xu, Qifa. In: Economic Modelling. RePEc:eee:ecmode:v:91:y:2020:i:c:p:469-486.

Full description at Econpapers || Download paper

2021Forecasting tourism with targeted predictors in a data-rich environment. (2021). Rua, Antonio ; Gouveia, Carlos Melo ; Loureno, Nuno. In: Economic Modelling. RePEc:eee:ecmode:v:96:y:2021:i:c:p:445-454.

Full description at Econpapers || Download paper

2020Incorporating overnight and intraday returns into multivariate GARCH volatility models. (2020). Wu, Jianbin ; Dhaene, Geert. In: Journal of Econometrics. RePEc:eee:econom:v:217:y:2020:i:2:p:471-495.

Full description at Econpapers || Download paper

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.

Full description at Econpapers || Download paper

2021On factor models with random missing: EM estimation, inference, and cross validation. (2021). Su, Liangjun ; Jin, Sainan ; Miao, KE. In: Journal of Econometrics. RePEc:eee:econom:v:222:y:2021:i:1:p:745-777.

Full description at Econpapers || Download paper

2021Bayesian MIDAS penalized regressions: Estimation, selection, and prediction. (2021). Mogliani, Matteo ; Simoni, Anna. In: Journal of Econometrics. RePEc:eee:econom:v:222:y:2021:i:1:p:833-860.

Full description at Econpapers || Download paper

2021Spatially varying sparsity in dynamic regression models. (2021). Hu, Guanyu. In: Econometrics and Statistics. RePEc:eee:ecosta:v:17:y:2021:i:c:p:23-34.

Full description at Econpapers || Download paper

2021Predicting default of listed companies in mainland China via U-MIDAS Logit model with group lasso penalty. (2021). Xiong, Wei ; Jiang, Cuixia ; Liu, Yezheng ; Xu, Qifa. In: Finance Research Letters. RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319309183.

Full description at Econpapers || Download paper

2020The role of an aligned investor sentiment index in predicting bond risk premia of the U.S. (2020). GUPTA, RANGAN ; Epni, Ouzhan ; Wohar, Mark E ; Guney, Ethem I. In: Journal of Financial Markets. RePEc:eee:finmar:v:51:y:2020:i:c:s1386418120300100.

Full description at Econpapers || Download paper

2020High-frequency credit spread information and macroeconomic forecast revision. (2020). Ka, Kook ; Ioannidis, Christos ; Deschamps, Bruno. In: International Journal of Forecasting. RePEc:eee:intfor:v:36:y:2020:i:2:p:358-372.

Full description at Econpapers || Download paper

2020Quantile forecasting with mixed-frequency data. (2020). Lima, Luiz ; Godeiro, Lucas ; Meng, Fanning. In: International Journal of Forecasting. RePEc:eee:intfor:v:36:y:2020:i:3:p:1149-1162.

Full description at Econpapers || Download paper

2020Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model. (2020). Wolters, Maik ; Reif, Magnus ; Heinrich, Markus ; Carstensen, Kai. In: International Journal of Forecasting. RePEc:eee:intfor:v:36:y:2020:i:3:p:829-850.

Full description at Econpapers || Download paper

2020A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth. (2020). Cheung, Calista ; Chernis, Tony ; Velasco, Gabriella. In: International Journal of Forecasting. RePEc:eee:intfor:v:36:y:2020:i:3:p:851-872.

Full description at Econpapers || Download paper

2021A comparison of monthly global indicators for forecasting growth. (2021). Guérin, Pierre ; Guerin, Pierre ; Baumeister, Christiane. In: International Journal of Forecasting. RePEc:eee:intfor:v:37:y:2021:i:3:p:1276-1295.

Full description at Econpapers || Download paper

2021Mixed-frequency approaches to nowcasting GDP: An application to Japan. (2021). Kido, Yosuke ; Hirakata, Naohisa ; Otaka, Kazuki ; Chikamatsu, Kyosuke. In: Japan and the World Economy. RePEc:eee:japwor:v:57:y:2021:i:c:s0922142521000049.

Full description at Econpapers || Download paper

2021Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model. (2021). Liu, Yezheng ; Xu, Qifa ; Jiang, Cuixia. In: International Review of Economics & Finance. RePEc:eee:reveco:v:75:y:2021:i:c:p:386-398.

Full description at Econpapers || Download paper

2021Back to the Present: Learning about the Euro Area through a Now-casting Model. (2021). Modugno, Michele ; Giannone, Domenico ; Cascaldi-Garcia, Danilo ; Revil, Thiago. In: International Finance Discussion Papers. RePEc:fip:fedgif:1313.

Full description at Econpapers || Download paper

2020Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data. (2020). Nie, Jun ; Yang, Shu-Kuei X ; Lyu, Yifei. In: Research Working Paper. RePEc:fip:fedkrw:88691.

Full description at Econpapers || Download paper

2020Forecasting Low Frequency Macroeconomic Events with High Frequency Data. (2020). Owyang, Michael ; Galvão, Ana ; Galvo, Ana B. In: Working Papers. RePEc:fip:fedlwp:88704.

Full description at Econpapers || Download paper

2020Tracking U.S. Real GDP Growth During the Pandemic. (2020). Shin, Minchul ; Arias, Jonas E. In: Economic Insights. RePEc:fip:fedpei:88740.

Full description at Econpapers || Download paper

2020Identification Through Sparsity in Factor Models. (2020). Freyaldenhoven, Simon. In: Working Papers. RePEc:fip:fedpwp:88229.

Full description at Econpapers || Download paper

2021New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and The Past? §. (2021). Siliverstovs, Boriss. In: Econometrics. RePEc:gam:jecnmx:v:9:y:2021:i:1:p:11-:d:511974.

Full description at Econpapers || Download paper

2021On the Predictability of China Macro Indicator with Carbon Emissions Trading. (2021). Hamori, Shigeyuki ; Tian, Shuairu ; Sun, LI ; Xie, Shan ; Gao, Xiang ; Chen, Qian. In: Energies. RePEc:gam:jeners:v:14:y:2021:i:5:p:1271-:d:505740.

Full description at Econpapers || Download paper

2021The Economy and Policy Incorporated Computing System for Social Energy and Power Consumption Analysis. (2021). Yan, Jing ; Hu, Chenxi ; Gao, Tianlu ; Yuan, Hongxia ; Wang, Xiaohui ; Zhang, Jun ; Zhao, Hang. In: Sustainability. RePEc:gam:jsusta:v:13:y:2021:i:18:p:10473-:d:639800.

Full description at Econpapers || Download paper

2021Another look into the factor model black box: factors interpretation and structural (in)stability. (2019). Doz, Catherine ; Despois, Thomas. In: PSE Working Papers. RePEc:hal:psewpa:halshs-02235543.

Full description at Econpapers || Download paper

2021Another look into the factor model black box: factor interpretation and structural (in)stability. (2020). Doz, Catherine ; Despois, Thomas. In: Working Papers. RePEc:hal:wpaper:halshs-02235543.

Full description at Econpapers || Download paper

2020Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother. (2020). Solberger, Martin ; Spnberg, Erik. In: Computational Economics. RePEc:kap:compec:v:55:y:2020:i:3:d:10.1007_s10614-019-09912-z.

Full description at Econpapers || Download paper

2021Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors. (2021). Yazgan, Ege ; Soybilgen, Bari. In: Computational Economics. RePEc:kap:compec:v:57:y:2021:i:1:d:10.1007_s10614-020-10083-5.

Full description at Econpapers || Download paper

2020Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic. (2020). Demircan, Hamza ; Cakmakli, Cem . In: Koç University-TUSIAD Economic Research Forum Working Papers. RePEc:koc:wpaper:2016.

Full description at Econpapers || Download paper

2020Asymmetric Responses of Economic Growth to Daily Oil Price Changes: New Global Evidence from Mixed-data Sampling Approach. (2020). Basel, Awartani ; Osama, Sweidan ; Aktham, Maghyereh . In: Review of Economics. RePEc:lus:reveco:v:71:y:2020:i:2:p:81-99:n:1.

Full description at Econpapers || Download paper

2020A Comparison of Monthly Global Indicators for Forecasting Growth. (2020). Guérin, Pierre ; Baumeister, Christiane. In: NBER Working Papers. RePEc:nbr:nberwo:28014.

Full description at Econpapers || Download paper

2021Marketing response and temporal aggregation. (2021). Franses, Philip Hans. In: Journal of Marketing Analytics. RePEc:pal:jmarka:v:9:y:2021:i:2:d:10.1057_s41270-020-00102-7.

Full description at Econpapers || Download paper

2020A bivariate prediction approach for adapting the health care system response to the spread of COVID-19. (2020). Verzillo, Stefano ; Paruolo, Paolo ; Lovaglio, Pietro Giorgio ; Berta, Paolo. In: PLOS ONE. RePEc:plo:pone00:0240150.

Full description at Econpapers || Download paper

2020Structural modeling and forecasting using a cluster of dynamic factor models. (2020). Glocker, Christian ; Kaniovski, Serguei. In: MPRA Paper. RePEc:pra:mprapa:101874.

Full description at Econpapers || Download paper

2020The Role of Investor Sentiment in Forecasting Housing Returns in China: A Machine Learning Approach. (2020). GUPTA, RANGAN ; Onay, Yigit ; Cepni, Oguzhan. In: Working Papers. RePEc:pre:wpaper:202055.

Full description at Econpapers || Download paper

2020Forecasting tourism with targeted predictors in a data-rich environment. (2020). Loureno, Nuno ; Gouveia, Carlos Melo ; Rua, Antonio. In: Working Papers. RePEc:ptu:wpaper:w202005.

Full description at Econpapers || Download paper

2020Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach. (2020). Wichitaksorn, Nuttanan. In: PIER Discussion Papers. RePEc:pui:dpaper:146.

Full description at Econpapers || Download paper

2020.

Full description at Econpapers || Download paper

2021.

Full description at Econpapers || Download paper

2021Nowcasting South African GDP using a suite of statistical models. (2021). Steenkamp, Daan ; Botha, Byron ; van Jaarsveld, Rossouw ; Olds, Tim ; Reid, Geordie . In: Working Papers. RePEc:rbz:wpaper:11001.

Full description at Econpapers || Download paper

2020Comparison of macroeconomic indicators nowcasting methods: Russian GDP case. (2020). Stankevich, Ivan. In: Applied Econometrics. RePEc:ris:apltrx:0402.

Full description at Econpapers || Download paper

2021On the applicability of dynamic factor models for forecasting real GDP growth in Armenia. (2021). Poghosyan, Karen. In: Applied Econometrics. RePEc:ris:apltrx:0411.

Full description at Econpapers || Download paper

2021.

Full description at Econpapers || Download paper

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.

Full description at Econpapers || Download paper

2020Business cycle dating and forecasting with real-time Swiss GDP data. (2020). Glocker, Christian ; Wegmueller, Philipp. In: Empirical Economics. RePEc:spr:empeco:v:58:y:2020:i:1:d:10.1007_s00181-019-01666-9.

Full description at Econpapers || Download paper

2020Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts. (2020). Siliverstovs, Boriss. In: Empirical Economics. RePEc:spr:empeco:v:58:y:2020:i:1:d:10.1007_s00181-019-01704-6.

Full description at Econpapers || Download paper

2020Forecasting models for the Chinese macroeconomy: the simpler the better?. (2020). Ponomareva, Natalia ; Zhang, Qin ; Heaton, Chris . In: Empirical Economics. RePEc:spr:empeco:v:58:y:2020:i:1:d:10.1007_s00181-019-01788-0.

Full description at Econpapers || Download paper

2020Nowcasting East German GDP growth: a MIDAS approach. (2020). Holtemöller, Oliver ; Holtemoller, Oliver ; Heinisch, Katja ; Claudio, Joo C. In: Empirical Economics. RePEc:spr:empeco:v:58:y:2020:i:1:d:10.1007_s00181-019-01810-5.

Full description at Econpapers || Download paper

2020The role of temporal dependence in factor selection and forecasting oil prices. (2020). Mjelde, James W ; Pourahmadi, Mohsen ; Binder, Kyle E. In: Empirical Economics. RePEc:spr:empeco:v:58:y:2020:i:3:d:10.1007_s00181-018-1574-9.

Full description at Econpapers || Download paper

2021Horizon confidence sets. (2021). Gutknecht, Daniel ; Fosten, Jack. In: Empirical Economics. RePEc:spr:empeco:v:61:y:2021:i:2:d:10.1007_s00181-020-01891-7.

Full description at Econpapers || Download paper

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

Full description at Econpapers || Download paper

2020Modelling and forecasting GDP using factor model: An empirical study from Bosnia and Herzegovina. (2020). Adem, Abdi ; Emina, Resi ; Ademir, Abdi. In: Croatian Review of Economic, Business and Social Statistics. RePEc:vrs:crebss:v:6:y:2020:i:1:p:10-26:n:2.

Full description at Econpapers || Download paper

2020Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models. (2020). Adnan, Rovanin ; Adem, Abdi ; Emina, Resi ; Ademir, Abdi. In: South East European Journal of Economics and Business. RePEc:vrs:seejeb:v:15:y:2020:i:2:p:1-14:n:1.

Full description at Econpapers || Download paper

2020Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations. (2020). Swanson, Norman ; Yang, Xiye ; Xiong, Weiqi. In: Journal of Applied Econometrics. RePEc:wly:japmet:v:35:y:2020:i:5:p:587-613.

Full description at Econpapers || Download paper

2021Forecasting Baden?Württembergs GDP growth: MIDAS regressions versus dynamic mixed?frequency factor models. (2021). Schweikert, Karsten ; Kuck, Konstantin. In: Journal of Forecasting. RePEc:wly:jforec:v:40:y:2021:i:5:p:861-882.

Full description at Econpapers || Download paper

2021Dynamics of globalization effect in India. (2021). Kumar, Nand ; Gupta, Shikha. In: Managerial and Decision Economics. RePEc:wly:mgtdec:v:42:y:2021:i:6:p:1394-1406.

Full description at Econpapers || Download paper

2020Forecasting Low Frequency Macroeconomic Events with High Frequency Data. (2020). Koop, Gary ; Mitchell, James ; McIntyre, Stuart ; Poon, Aubrey. In: EMF Research Papers. RePEc:wrk:wrkemf:38.

Full description at Econpapers || Download paper

2020Nowcasting Finnish GDP growth using financial variables: a MIDAS approach. (2020). Lindblad, Annika ; Laine, Olli-Matti. In: BoF Economics Review. RePEc:zbw:bofecr:42020.

Full description at Econpapers || Download paper

2021Precision-based sampling with missing observations: A factor model application. (2021). Hauber, Philipp ; Schumacher, Christian. In: Discussion Papers. RePEc:zbw:bubdps:112021.

Full description at Econpapers || Download paper

2020Forecasting industrial production in Germany: The predictive power of leading indicators. (2020). Schlosser, Alexander. In: Ruhr Economic Papers. RePEc:zbw:rwirep:838.

Full description at Econpapers || Download paper

Works by Christian Schumacher:


YearTitleTypeCited
2000Forecasting Trend Output in the Euro Area In: Discussion Paper Series.
[Full Text][Citation analysis]
paper4
2002Forecasting Trend Output in the Euro Area..(2002) In: Journal of Forecasting.
[Citation analysis]
This paper has another version. Agregated cites: 4
article
2000Forecasting trend output in the Euro area.(2000) In: HWWA Discussion Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 4
paper
2002Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? In: Discussion Paper Series.
[Full Text][Citation analysis]
paper25
2002Estimating large-scale factor models for economic activity in Germany: Do they outperform simpler models?.(2002) In: HWWA Discussion Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 25
paper
2015Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials In: Journal of the Royal Statistical Society Series A.
[Full Text][Citation analysis]
article87
2010Factor MIDAS for Nowcasting and Forecasting with Ragged?Edge Data: A Model Comparison for German GDP In: Oxford Bulletin of Economics and Statistics.
[Full Text][Citation analysis]
article120
2008Factor-MIDAS for now- and forecasting with ragged-edge data: A model comparison for German GDP In: CEPR Discussion Papers.
[Full Text][Citation analysis]
paper29
2008Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP.(2008) In: Economics Working Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 29
paper
2007Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP.(2007) In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 29
paper
2009Pooling versus model selection for nowcasting with many predictors: An application to German GDP In: CEPR Discussion Papers.
[Full Text][Citation analysis]
paper14
2009Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP.(2009) In: Economics Working Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 14
paper
2009Pooling versus model selection for nowcasting with many predictors: an application to German GDP.(2009) In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 14
paper
2009MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area In: CEPR Discussion Papers.
[Full Text][Citation analysis]
paper130
2011MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area.(2011) In: International Journal of Forecasting.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 130
article
2011MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area.(2011) In: International Journal of Forecasting.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 130
article
2009MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area.(2009) In: Economics Working Papers.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 130
paper
2012U-MIDAS: MIDAS regressions with unrestricted lag polynomials In: CEPR Discussion Papers.
[Full Text][Citation analysis]
paper37
2011U-MIDAS: MIDAS regressions with unrestricted lag polynomials.(2011) In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 37
paper
2001Trend and Cycle in the Euro-Area: A Permanent-Transitory Decomposition Using a Cointegrated VAR Model In: Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research.
[Full Text][Citation analysis]
article0
2010Factor forecasting using international targeted predictors: The case of German GDP In: Economics Letters.
[Full Text][Citation analysis]
article43
2009Factor forecasting using international targeted predictors: the case of German GDP.(2009) In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 43
paper
2019Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification In: Journal of Econometrics.
[Full Text][Citation analysis]
article4
2008Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data In: International Journal of Forecasting.
[Full Text][Citation analysis]
article142
2016A comparison of MIDAS and bridge equations In: International Journal of Forecasting.
[Full Text][Citation analysis]
article20
2008Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1 In: Working Papers.
[Full Text][Citation analysis]
paper10
2004Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? / Die Schätzung von großen Faktormodellen für die deutsche Volkswirtschaft: Übertreffen sie ei In: Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).
[Full Text][Citation analysis]
article18
2011Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP In: Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).
[Full Text][Citation analysis]
article8
2007Forecasting German GDP using alternative factor models based on large datasets In: Journal of Forecasting.
[Full Text][Citation analysis]
article118
2005Forecasting German GDP using alternative factor models based on large datasets.(2005) In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
This paper has another version. Agregated cites: 118
paper
2005Out-of-sample Performance of Leading Indicators for the German Business Cycle: Single vs. Combined Forecasts In: Journal of Business Cycle Measurement and Analysis.
[Full Text][Citation analysis]
article31
2003Are Real Interest Rates Cointegrated? Further evidence based on paneleconometric methods In: Swiss Journal of Economics and Statistics (SJES).
[Full Text][Citation analysis]
article9
2008Measuring uncertainty of the euro area NAIRU: Monte Carlo and empirical evidence for alternative confidence intervals in a state space framework In: Empirical Economics.
[Full Text][Citation analysis]
article9
2013Bayesian estimation of sparse dynamic factor models with order-independent identification In: Working Papers.
[Full Text][Citation analysis]
paper6
2013POOLING VERSUS MODEL SELECTION FOR NOWCASTING GDP WITH MANY PREDICTORS: EMPIRICAL EVIDENCE FOR SIX INDUSTRIALIZED COUNTRIES In: Journal of Applied Econometrics.
[Citation analysis]
article68
2017Identifying relevant and irrelevant variables in sparse factor models In: Journal of Applied Econometrics.
[Full Text][Citation analysis]
article8
2006Real-time forecasting of GDP based on a large factor model with monthly and quarterly data In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
paper15
2007Reconsidering the role of monetary indicators for euro area inflation from a Bayesian perspective using group inclusion probabilities In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
paper9
2009MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area In: Discussion Paper Series 1: Economic Studies.
[Full Text][Citation analysis]
paper8
2019A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing In: Discussion Papers.
[Full Text][Citation analysis]
paper0
2014MIDAS and bridge equations In: Discussion Papers.
[Full Text][Citation analysis]
paper9
2012Finding relevant variables in sparse Bayesian factor models: Economic applications and simulation results In: Discussion Papers.
[Full Text][Citation analysis]
paper8
2014MIDAS regressions with time-varying parameters: An application to corporate bond spreads and GDP in the Euro area In: VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy.
[Full Text][Citation analysis]
paper5

CitEc is a RePEc service, providing citation data for Economics since 2001. Sponsored by INOMICS. Last updated March, 2 2021. Contact: CitEc Team