missing observations, outliers, and mixed-frequency data Hill, R. Carter. text enk Bingley, U.K Emerald 1999 monographic eng

electronic resource

1 online resource (xii, 305 p.). 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. 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. edited by R. Carter Hill. Science History Business & Economics Econometrics Econometrics Econometrics HB139 .M47 1999 330.015195 330.43 9781849508230 (electronic bk.) : http://www.emeraldinsight.com/0731-9053/13 http://www.emeraldinsight.com/0731-9053/13 UtOrBLW 101115 20161010130639.0 bslw06309190