Universität Bonn

Department of Economics

Prof. Dr. Alois Kneip

Kneip_Alois
© Private

Prof. Dr. Alois Kneip

2.008

Adenauerallee 24-26

53113 Bonn

Office Hours

By Agreement. Please write an e-mail to make an appointment.

Teaching

    Current lectures and seminars held by Prof. Dr. Kneip can be found on Basis


    Research Interests

    • Statistics
    • Functional Data Analysis
    • Aggregation Theory

    Curriculum Vitae


    Publications in refereed journals

    1. CAROLL, C., MULLER, H.-G. and KNEIP, A. (2020). Cross-component registration for multivariate functional data, with application to growth curves. Biometrics, to appear
    2. ARNONE, E., KNEIP, A., NOBILE, F. and SANGALLI, L.M. (2020). Some first results on the consistency of spatial regression with partial differential equation regularization. Statistica Sinica, to appear
       
    3. POß, D., LIEBL, D., KNEIP ,A., EISENBARTH, H., WAGER, T.D. and FELDMAN BARRET, L. (2020). Superconsistent estimation of points of impact in nonparametric regression with functional predictors. Journal of the Royal Statistical Society, Series B, to appear
       
    4. KNEIP, A., SIMAR, L. and WILSON, P. (2020). Inference in dynamic, nonparametric models of production: central limit theorems for Malmquist indices. Econometric Theory, to appear, doi: 10.1017/s0266466620000237
       
    5. DELAIGLE, A., HALL, P., HUANG, W. and KNEIP, A. (2020). Estimating the covariance of fragmented and other related types of functional data. Journal of the American Statistical Association, to appear, https://doi.org/10.1080/01621459.2020.1723597
       
    6. KNEIP, A. and LIEBL, D. (2020). On the optimal reconstruction of partially observed functional data. Annals of Statistics, 48, 1692-1717.
       
    7. KNEIP, A., MERZ, M. and STORJOHANN, L. (2019). Aggregation and labor supply elasticities. Journal of the European Economic Association, to appear, https://doi.org/10.1093/jeea/jvz039
       
    8. WAGNER, H. and KNEIP, A. (2019). Non-parametric registration to low-dimensional function spaces. Computational Statistics and Data Analysis, 138, 49-63.
       
    9. GRITH, M, WAGNER, H., HARDLE, W. and KNEIP, A. (2018). Functional principal component analysis for derivatives of multivariate curves. Statistica Sinica, 28, 2469-2496.
       
    10. KNEIP, A., POSS, D. and SARDA, P. (2016). Functional Linear Regression with Points of Impact. Annals of Statistics, 44, 1-30 
       
    11. KNEIP, A., SIMAR, L. and WILSON, P. (2016). Testing Hypotheses in Nonparametric Models of Production. Journal of Business & Economic Statistics, 34, 435-456
       
    12. KNEIP, A., SIMAR, L. and VAN KEILEGOM, I. (2015). Frontier estimation in the presence of measurement error with unknown variance. Journal of Econometrics, 184, 379-393
       
    13. KNEIP, A., SIMAR, L. and WILSON, P. (2015). When bias kills the variance: Central limit theorems for DEA and FDH efficiency scores. Econometric Theory, 28, 590-628
       
    14. BADA, O. and KNEIP, A. (2014). Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle. Computational Statistics and Data Analysis, 76, 95-115
       
    15. KNEIP, A., SICKLES. R.C. and SONG, W. (2012). A new panel data treatment for heterogeneity in time trends. Econometric Theory, 31, 394-422
       
    16. PALUCH, M., KNEIP. A. and HILDENBRAND, W. (2012). Individual versus Aggregate income elasticities for heterogeneous populations. Journal of Applied Econometrics, 27, 847-869
       
    17. KNEIP, A. and SICKLES, R.C. (2012). Panel data, factor models, and the Solow residual. in: Exploring Research Frontiers in Contemporary Statistics and Econometrics; van Keilegom, I. and Wilson, P. (eds.); Springer Verlag, New York, 83-114
       
    18. KNEIP, A. and SARDA, P. (2011). Factor models and variable selection in high dimensional regression analysis. Annals of Statistics, 39, 2410-2447
       
    19. KNEIP, A., SIMAR, L. and WILSON, P. (2011). A computationally efficient, consistent bootstrap for inference with non-parametric DEA estimators. Computational Economics, 38, 483-515
       
    20. CRAMBES, C., KNEIP, A. and SARDA, P. (2009). Smoothing splines estimators for functional linear regression. Annals of Statistics, 37, 35-72
       
    21. BENKO, M., HÄRDLE, W. and KNEIP, A. (2009). Common functional principal components. Annals of Statistics, 37, 1-34
       
    22. KNEIP, A., SIMAR, L. and WILSON,P. (2008). Asymptotics and consistent bootstraps for DEA estimators in nonparametric frontier models. Econometric Theory, 24, 1663-1697
       
    23. KNEIP, A. and RAMSAY, J. (2008). Combining registration and fitting for functional models. Journal of the American Statistical Association, 103, 1155-1165
       
    24. CARDOT, H., CRAMBES, Ch., KNEIP. A and P. SARDA (2007). Smoothing Splines Estimators in Functional Linear Regression with Errors-in-Variables. Computational Statistics & Data Analysis, 51, 4832-4848.
       
    25. HILDENBRAND, W. and KNEIP, A. (2005). Aggregate behavior and microdata. Games and Economic Behavior, 50, 3-27
       
    26. HILDENBRAND, W. and KNEIP, A. (2005). On behavioral heterogeneity. Economic Theory, 25, 155-169
       
    27. KNEIP, A., SICKLES, R.C. and SONG, W. (2004). Functional data analysis and mixed effect models. in: COMPSTAT 2004 - Proceedings in Computational Statistics ; ed. Antoch, J., Springer Verlag, New York, 315-326
       
    28. GIJBELS, I., HALL, P. and KNEIP, A. (2004). Interval and band estimation for curves with jumps. Journal of Applied Probability, 41A, 65-79
       
    29. KNEIP, A. and UTIKAL, K. (2001). Inference for density families using functional principal component analysis. Journal of the American Statistical Association, 96, 519-532 (with discussion)
       
    30. KNEIP, A. and UTIKAL, K. (2001). Rejoinder to the discussion of ''Inference for density families using functional principal component analysis''. Journal of the American Statistical Association, 96, 540-542
       
    31. KNEIP, A. and UTIKAL, K. (2001). Time trends in the joint distribution of income and age. in: Economic Essays, A Festschrift for Werner HILDENBRAND; ed. Debreu, G., Neuefeind, W., and Trockel, W. , Springer Verlag, New York, Heidelberg, 253-274
       
    32. KNEIP, A., Li, X., MACGIBBON, B. and RAMSAY, J.O. (2000). Curve registration by local regression. Canadian Journal of Statistics, 28, 19-30
       
    33. HILDENBRAND, W., KNEIP, A. and UTIKAL, K. (1999). Une analyse non paramétrique des distributions du revenu et des caractéristiques des ménages. Revue de Statistique Appliquée, 47, 39-56
       
    34. HÄRDLE, W. and KNEIP, A. (1999). Testing a regression model when we have smooth alternatives in mind. Scandinavian Journal of Statistics, 26, 221-238
       
    35. GIJBELS, I., HALL, P. and KNEIP, A. (1999). On the estimation of jump points in smooth curves. Annals of the Institute of Statistical Mathematics, 51, 231-251
       
    36. KNEIP, A. (1999). Behavioral heterogeneity and structural properties of aggregate demand. Journal of Mathematical Economics, 31, 49-79
       
    37. HILDENBRAND, W. and KNEIP, A. (1999). Demand aggregation under structural stability. Journal of Mathematical Economics, 31, 81-109
       
    38. KNEIP, A. (1999). Comment on ''Robust functional data analysis'' by Locantore, N, Marron, J.S., Simpson, D.G, Triploi, N., Zhang, J.T. and Cohen, K.L. Test, 8, 50-54
       
    39. KNEIP, A., PARK, B.U. and SIMAR, L. (1998). A note on the convergence of nonparametric DEA estimators for production efficiency scores. Econometric Theory, 14, 783-793
       
    40. KNEIP, A. (1998). Comment on ''Smoothing Spline Models for the Analysis of Nested and Crossed Samples of Curves'' by Brumback, B. and Rice, J. Journal of the American Statistical Association, 93, 984-986
       
    41. ENGEL, J. and KNEIP, A. (1996). Comment on ''Flexible smoothing with B-splines and penalties'' by Eilers, P.H.C, and Brian, D.M. Statistical Science, 11, 109-110
       
    42. KNEIP, A. and ENGEL, J. (1996). A remedy for kernel regression under random design. Statistics, 28, 201-225
       
    43. ENGEL, J. and KNEIP, A. (1996). Recent approaches to estimating Engel curves. Journal of Economics, 63, 187-212
       
    44. KNEIP, A. and SIMAR, L. (1996). A general framework for frontier estimation with panel data. Journal of Productivity Analysis, 7, 187-212
       
    45. KNEIP, A. (1995). Discussion of ''Econometrics of Information and Efficiency'' by Jati K. Sengupta. Journal of Economics, 61, 336-337
       
    46. GASSER, T. and KNEIP, A. (1995). Searching for structure in curve samples. Journal of the American Statistical Association, 90, 1179-1188
       
    47. KNEIP, A. and ENGEL, J. (1995). Model estimation in nonlinear regression under shape invariance. Annals of Statistics, 23, 551-570
       
    48. ENGEL, J. and KNEIP, A. (1995). Model estimation in nonlinear regression. in: Statistical Modelling, Proceedings of the 10th International Workshop on Statistical Modelling; ed. Seeber G.U.H., Francis B.J., Hatzinger R., Steckel-Berger G. , Springer Verlag, New York, Heidelberg
       
    49. KNEIP, A. (1994). Nonparametric estimation of common regressors for similar curve data. Annals of Statistics, 22, 1386-1428
       
    50. KNEIP, A. (1994). Ordered linear smoothers. Annals of Statistics, 22, 835-866
       
    51. GASSER, T., KNEIP, A., ZIEGLER, P., MOLINARI, L., PRADER, A. and LARGO, R. (1994). Development and outcome of indices of obesity in normal children. Annals of Human Biology, 21, 275-286
       
    52. HILDENBRAND, W. and KNEIP, A. (1993). Family expenditure data, heteroscedasticity and the law of demand. Richerche Economiche, 47, 137-165
       
    53. GASSER, T., ZIEGLER, P., KNEIP, A., PRADER, A., MOLINARI, L. and LARGO, R. (1993). The dynamics of growth of weight, circumferences and skinfolds in distance, velocity and acceleration Annals of Human Biology, 20, 239-259
       
    54. HERRMANN, E., GASSER, T. and KNEIP, A. (1992). Choice of bandwidth for kernel regression when residuals are correlated. Biometrika, 79, 783-796
       
    55. KNEIP, A. and GASSER, T. (1992). Statistical tools to analyze data representing a sample of curves. Annals of Statistics, 20, 1266-1305
       
    56. GASSER, T., KNEIP, A. and KÖLER, W. (1991). A flexible and fast method for automatic smoothing. Journal of the American Statistical Association, 86, 643--652
       
    57. GASSER, T., KNEIP, A., ZIEGLER, P., LARGO, R. and PRADER, A. (1991). The dynamics of growth of width in distance, velocity and acceleration. Annals of Human Biology, 18, 449--461
       
    58. GASSER, T., KNEIP, A., BINDING, A., PRADER, A. and MOLINARI, L. (1991). The dynamics of linear growth in distance, velocity and acceleration. Annals of Human Biology, 18, 187--205
       
    59. GASSER, T., KNEIP, A., ZIEGLER, P., LARGO, R. and PRADER, A. (1990). A method for determining the dynamics and intensity of average growth. Annals of Human Biology, 17, 459--474
       
    60. KNEIP, A. and PFEIFFER-KURDA, M. (1990). Anmerkungen zu ''Gauquelins Planetenhypothese: Stein des Anstoßes oder Prüfstein der Vernunft'' von Suitbert Ertel. Psychologische Rundschau, 23, 235--237
       
    61. GASSER, T. and KNEIP, A. (1990). Analysis of samples of curves. in: Non-parametric functional estimation and related topics. ed. G.G. Roussas, NATO ASI Series, Kluwer Academic Publishers
       
    62. GASSER, T. and KNEIP, A. (1989). Discussion of ''Linear smoothers and additive models'' by A. Buja, T. Hastie, R. Tibshirani. Annals of Statistics, 17, 532--535
       
    63. GASSER, T., KNEIP, A., BINDING, A., LARGO, R. and MOLINARI, L. (1989). Flexible methods for nonparametric fitting of individual and sample growth curves. in: Anxology 88, ed. J.M. Tanner, Smith-Gordon, London
       
    64. KNEIP, A. and GASSER, T. (1988). Convergence and consistency results for self modeling nonlinear regression. Annals of Statistics, 11, 82--112
       
    65. GASSER, T., KÖHLER, W., MÜLLER, H.G., KNEIP, A., LARGO, R. and MOLINARI, L. (1984). Velocity and Acceleration of height growth using kernel estimation. Annals of Human Biology, 11, 397--411
       
    66. HÄRDLE, W. and KNEIP, A. (1983). DACAPO: Ein Programm-Paket zur graphischen Verarbeitung von Daten und Funktionen. Angewandte Informatik, 7, Depot
       
    67. GASSER, T., KNEIP, A. and VERLEGER, R. (1982). Modification of the EEG time constant by digital filtering. Psychophysiology, 19, 237--240
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