Messy data missing observations, outliers, and mixed-frequency data
Often applied econometricians are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes econometric results are very fragile to the inclusion or omission of just a few ob...
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Other Authors: | |
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Format: | Electronic |
Language: | English |
Published: |
Bingley, U.K. :
Emerald,
1999.
|
Series: | Advances in econometrics ;
v. 13. |
Subjects: | |
ISBN: | 9781849508230 (electronic bk.) : |
Physical Description: | 1 online resource (xii, 305 p.). |
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245 | 0 | 0 | |a Messy data |h [electronic resource] : |b missing observations, outliers, and mixed-frequency data / |c edited by R. Carter Hill. |
260 | |a Bingley, U.K. : |b Emerald, |c 1999. | ||
300 | |a 1 online resource (xii, 305 p.). | ||
490 | 1 | |a Advances in econometrics, |x 0731-9053 ; |v v. 13 | |
505 | 0 | |a Testing for random individual and time effects using unbalanced panel data / Qi Li -- Messy time series : a unified approach / Jeremy Penzer -- Simulation of multinomial probit probabilities and imputation of missing data / Steven Stern -- Temporal disaggregation, missing observations, outliers, and forecasting : a unifying non-model-based procedure / Massimiliano Marcellino -- Testing for unit roots in economic time series with missing observations / David E.A. Giles -- A statistical approach for disaggregating mixed-frequency economic / Zhao-Guo Chen -- Influential data diagnostics for transition data / Larry W. Taylor -- The effects of different types of outliers on unit root tests / G.S. Maddala -- An extended yule-walker method for estimating a vector autoregressive model with mixed-frequencey data / Peter A. Zadrozny -- Missing data from infrequency of purchase : Bayesian estimation of a linear expenditure system / Ma. Rebecca Valenzuela -- Introduction / Carter Hill. | |
520 | |a Often applied econometricians are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes econometric results are very fragile to the inclusion or omission of just a few observations in the sample. Papers in this volume discuss new econometric techniques for addressing these problems. | ||
588 | 0 | |a Print version record | |
650 | 7 | |a Science |x History. |2 bisacsh | |
650 | 7 | |a Business & Economics |x Econometrics. |2 bisacsh | |
650 | 7 | |a Econometrics. |2 bicssc | |
650 | 0 | |a Econometrics. | |
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655 | 9 | |a electronic books |2 eczenas | |
700 | 1 | |a Hill, R. Carter. | |
776 | 1 | |z 9780762303038 | |
830 | 0 | |a Advances in econometrics ; |v v. 13. | |
856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://doi.org/10.1108/S0731-9053(1999)13 |y Full text |