IDEAS home Printed from https://ideas.repec.org/f/pka324.html
   My authors  Follow this author

Christian Jonathan Kascha

Personal Details

First Name:Christian
Middle Name:Jonathan
Last Name:Kascha
Suffix:
RePEc Short-ID:pka324
http://www.christiankascha.com

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
  2. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
  3. Christian Kascha & Carsten Trenkler, 2011. "Cointegrated VARMA models and forecasting US interest rates," ECON - Working Papers 033, Department of Economics - University of Zurich.
  4. Christian Kascha & Carsten Trenkler, 2009. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Working Paper 2009/12, Norges Bank.
  5. Christian Kascha & Karel Mertens, 2008. "Business cycle analysis and VARMA models," Working Paper 2008/05, Norges Bank.
  6. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
  7. Christian Kascha, 2007. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Economics Working Papers ECO2007/12, European University Institute.

Articles

  1. Christian Kascha & Carsten Trenkler, 2015. "Simple Identification and Specification of Cointegrated Varma Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 675-702, June.
  2. Kascha, Christian & Trenkler, Carsten, 2011. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1008-1017, February.
  3. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
  4. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.

    Cited by:

    1. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.

  2. Christian Kascha & Carsten Trenkler, 2011. "Cointegrated VARMA models and forecasting US interest rates," ECON - Working Papers 033, Department of Economics - University of Zurich.

    Cited by:

    1. Athanasopouolos, George & Poskitt, Don & Vahid, Farshid & Yao, Wenying, 2014. "Forecasting with EC-VARMA models," Working Papers 2014-07, University of Tasmania, Tasmanian School of Business and Economics, revised 22 Feb 2014.

  3. Christian Kascha & Carsten Trenkler, 2009. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Working Paper 2009/12, Norges Bank.

    Cited by:

    1. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.

  4. Christian Kascha & Karel Mertens, 2008. "Business cycle analysis and VARMA models," Working Paper 2008/05, Norges Bank.

    Cited by:

    1. Yao, Wenying & Kam, Timothy & Vahid, Farshid, 2017. "On weak identification in structural VARMA models," Economics Letters, Elsevier, vol. 156(C), pages 1-6.
    2. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    3. D.S. Poskitt & Wenying Yao, 2012. "VAR Modeling and Business Cycle Analysis: A Taxonomy of Errors," Monash Econometrics and Business Statistics Working Papers 11/12, Monash University, Department of Econometrics and Business Statistics.
    4. Yao, Wenying & Kam, Timothy & Vahid, Farshid, 2014. "VAR(MA), what is it good for? more bad news for reduced-form estimation and inference," Working Papers 2014-14, University of Tasmania, Tasmanian School of Business and Economics.
    5. Canova, F. & Ferroni, F. & Matthes, C., 2013. "Choosing the variables to estimate singular DSGE models," Working papers 461, Banque de France.
    6. Christopher J. Gust & Robert J. Vigfusson, 2009. "The power of long-run structural VARs," International Finance Discussion Papers 978, Board of Governors of the Federal Reserve System (U.S.).
    7. Amélie Charles & Olivier Darné & Fabien Tripier, 2010. "Are Unit Root Tests Useful in the Debate over the (Non)Stationarity of Hours Worked?," Working Papers hal-00527122, HAL.
    8. Mertens, Elmar, 2012. "Are spectral estimators useful for long-run restrictions in SVARs?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1831-1844.
    9. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
    10. Alfredo García‐Hiernaux, 2011. "Forecasting linear dynamical systems using subspace methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(5), pages 462-468, September.
    11. Jean-Marie Dufour & Tarek Jouini, 2011. "Asymptotic Distributions for Some Quasi-Efficient Estimators in Echelon VARMA Models," CIRANO Working Papers 2011s-25, CIRANO.
    12. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    13. Christian Kascha & Carsten Trenkler, 2011. "Cointegrated VARMA models and forecasting US interest rates," ECON - Working Papers 033, Department of Economics - University of Zurich.

  5. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.

    Cited by:

    1. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    2. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    3. Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.
    4. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    5. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    6. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    7. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    8. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    9. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
    10. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
    11. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
    12. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España;Working Papers Homepage.
    13. Hilde Bjørnland & Karsten Gerdrup & Christie Smith & Anne Sofie Jore & Leif Anders Thorsrud, 2010. "Weights and pools for a Norwegian density combination," Working Paper 2010/06, Norges Bank.
    14. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, Research Program on Forecasting.
    15. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Valeriu Nalban, 2015. "Do Bayesian Vector Autoregressive models improve density forecasting accuracy? The case of the Czech Republic and Romania," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 4(1), pages 60-74, March.
    17. Jakub Ryšánek, 2010. "Combining VAR Forecast Densities Using Fast Fourier Transform," Acta Oeconomica Pragensia, University of Economics, Prague, vol. 2010(5), pages 72-88.
    18. Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    19. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
    20. Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    21. Emilio Zanetti Chini, 2017. "Generalizing Smooth Transition Autoregressions," DEM Working Papers Series 138, University of Pavia, Department of Economics and Management.
    22. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    23. Victor Lopez-Perez, 2016. "Macroeconomic Forecast Uncertainty In The Euro Area," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(1), pages 9-41, March.
    24. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
    25. Garratt, Anthony & Mitchell, James & Vahey, Shaun, 2013. "Measuring Output Gap Nowcast Uncertainty," EMF Research Papers 01, Economic Modelling and Forecasting Group.
    26. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
    27. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    28. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    29. Francesco Ravazzolo & Marco J. Lombardi, 2012. "Oil price density forecasts: Exploring the linkages with stock markets," Working Papers No 3/2012, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    30. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring Output Gap Uncertainty," Birkbeck Working Papers in Economics and Finance 0909, Birkbeck, Department of Economics, Mathematics & Statistics.
    31. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank, Research Department.
    32. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume,in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.
    33. Stephen McKnight & Alexander Mihailov & Kerry Patterson & Fabio Rumler, 2014. "The Predictive Performance of Fundamental Inflation Concepts: An Application to the Euro Area and the United States," Economics & Management Discussion Papers em-dp2014-03, Henley Business School, Reading University.
    34. Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
    35. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    36. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    37. Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank, Research Department.
    38. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," BORRADORES DE ECONOMIA 010973, BANCO DE LA REPÚBLICA.
    39. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    40. Emilio Zanetti Chini, 2803. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    41. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Paper 1134, Federal Reserve Bank of Cleveland.
    42. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    43. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2014. "Evaluating FOMC forecast ranges: an interval data approach," Empirical Economics, Springer, vol. 47(1), pages 365-388, August.
    44. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    45. Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
    46. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    47. Timo Henckel & Shaun Vahey & Liz Wakerly, 2011. "Probabilistic Interest Rate Setting With A Shadow Board: A Description Of The Pilot Project," CAMA Working Papers 2011-27, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    48. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.

  6. Christian Kascha, 2007. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Economics Working Papers ECO2007/12, European University Institute.

    Cited by:

    1. George Athanasopoulos & Donald S. Poskitt & Farshid Vahid & Wenying Yao, 2016. "Determination of Long‐run and Short‐run Dynamics in EC‐VARMA Models via Canonical Correlations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1100-1119, September.
    2. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    3. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    4. Boubacar Mainassara, Y. & Francq, C., 2011. "Estimating structural VARMA models with uncorrelated but non-independent error terms," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 496-505, March.
    5. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    6. Jean-Marie Dufour & Tarek Jouini, 2011. "Asymptotic Distributions for Some Quasi-Efficient Estimators in Echelon VARMA Models," CIRANO Working Papers 2011s-25, CIRANO.
    7. Dufour, Jean-Marie & Jouini, Tarek, 2014. "Asymptotic distributions for quasi-efficient estimators in echelon VARMA models," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 69-86.
    8. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Athanasopouolos, George & Poskitt, Don & Vahid, Farshid & Yao, Wenying, 2014. "Forecasting with EC-VARMA models," Working Papers 2014-07, University of Tasmania, Tasmanian School of Business and Economics, revised 22 Feb 2014.
    10. Escribano, Álvaro & Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Poloni, Federico & Sbrana, Giacomo, 2015. "A note on forecasting demand using the multivariate exponential smoothing framework," International Journal of Production Economics, Elsevier, vol. 162(C), pages 143-150.

Articles

  1. Christian Kascha & Carsten Trenkler, 2015. "Simple Identification and Specification of Cointegrated Varma Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 675-702, June.

    Cited by:

    1. George Athanasopoulos & Donald S. Poskitt & Farshid Vahid & Wenying Yao, 2016. "Determination of Long‐run and Short‐run Dynamics in EC‐VARMA Models via Canonical Correlations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1100-1119, September.
    2. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    3. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

  2. Kascha, Christian & Trenkler, Carsten, 2011. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1008-1017, February. See citations under working paper version above.
  3. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
    See citations under working paper version above.
  4. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (6) 2007-01-28 2007-07-07 2009-01-03 2009-08-16 2011-10-15 2017-08-13. Author is listed
  2. NEP-ETS: Econometric Time Series (6) 2007-01-28 2007-07-07 2009-01-03 2009-08-16 2011-10-15 2015-06-20. Author is listed
  3. NEP-FOR: Forecasting (4) 2007-07-07 2009-01-03 2011-10-15 2015-06-20
  4. NEP-MAC: Macroeconomics (4) 2007-01-28 2009-01-03 2015-06-20 2017-08-13
  5. NEP-CBA: Central Banking (2) 2009-01-03 2011-10-15
  6. NEP-DGE: Dynamic General Equilibrium (1) 2007-01-28
  7. NEP-MST: Market Microstructure (1) 2009-08-16
  8. NEP-ORE: Operations Research (1) 2015-06-20

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Christian Jonathan Kascha should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.