Template-type: ReDif-Paper 1.0
Author-Name: Beutner, Eric
Author-workplace-name: QE Math. Economics & Game Theory, RS: GSBE ETBC
Author-Name: Heinemann, Alexander
Author-workplace-name: QE Econometrics, RS: GSBE EFME
Author-Name: Smeekes, Stephan
Author-workplace-name: QE Econometrics, RS: GSBE EFME
Title: A Justification of Conditional Confidence Intervals
Abstract: To quantify uncertainty around point estimates of conditional objects such as conditional means or variances, parameter uncertainty has to be taken into account. Attempts to incorporate parameter uncertainty are typically based on the unrealistic assumption of observing two independent processes, where one is used for parameter estimation, and the other for conditioning upon. Such unrealistic foundation raises the question whether these intervals are theoretically justified in a realistic setting. This paper presents an asymptotic justification for this type of intervals that does not require such an unrealistic assumption, but relies on a sample-split approach instead. By showing that our sample-split intervals coincide asymptotically with the standard intervals, we provide a novel, and realistic, justification for confidence intervals of conditional objects. The analysis is carried out for a general class of Markov chains nesting various time series models.
Classification-JEL: c53,c22,c32,g17
Series: GSBE Research Memoranda
Creation-Date: 20171010
Number: 023
File-URL: https://cris.maastrichtuniversity.nl/ws/files/16594611/RM17023.pdf
File-Format: application/pdf
File-Size: 586512
Handle: Repec:unm:umagsb:2017023
DOI: 10.26481/umagsb.2017023