Recursive mean adjustment in time-series inferences

So, Beong Soo; Shin, Dong Wan

doi:10.1016/s0167-7152(98)00247-8

Cited by 81 publications

(65 citation statements)

References 7 publications

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“…7 Since z it( ) is deviated from past means, it can be seen as a modification of the recursive mean adjustment (RMA) method by So and Shin (1999). 8 Now, we show that z it( ) meets the above two requirements.…”

Section: Instruments Deviated From Past Meansmentioning

confidence: 85%

A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR(p) MODELS WHEN BOTHNANDTARE LARGE

Hayakawa¹

2009

Econom. Theory

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In this paper, we show that for panel AR(p) models, an instrumental variable (IV) estimator with instruments deviated from past means has the same asymptotic distribution as the infeasible optimal IV estimator when both N and T , the dimensions of the cross section and the time series, are large. If we assume that the errors are normally distributed, the asymptotic variance of the proposed IV estimator is shown to attain the lower bound when both N and T are large. A simulation study is conducted to assess the estimator.Keywords: panel AR(p) models, the optimal instruments, instruments deviated from past means.

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Section: Instruments Deviated From Past Meansmentioning

confidence: 85%

A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR(p) MODELS WHEN BOTHNANDTARE LARGE

Hayakawa¹

2009

Econom. Theory

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“…The bias correction procedure used by CMS -suggested by So and Shin (1999) and extended by Sul, Phillips and Choi (2002) to account for common effects in residuals -is only meant to assess the relative importance of the small sample and the temporal aggregation biases. In their panel of aggregate real exchange rates, CMS find the small sample bias dominates.…”

Section: Data Corrections Part 2: Formal Tests For Errors-in-mentioning

confidence: 99%

"Aggregation Bias" DOES Explain the PPP Puzzle

Imbs

Mumtaz

Ravn³

et al. 2005

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This article summarizes our views on the role of an "aggregation bias" in explaining the PPP Puzzle, in response to the several papers recently written in reaction to our initial contribution. We discuss in particular the criticisms of Imbs, Mumtaz, Ravn and Rey (2002) presented in Chen and Engel (2005). We show that their contentions are based on: (i) analytical counter-examples which are not empirically relevant; (ii) simulation results minimizing the extent of "aggregation bias"; (iii) unfounded claims on the impact of measurement errors on our results; and (iv) problematic implementation of small-sample bias corrections. We conclude, as in our original paper, that "aggregation bias" goes a long way towards explaining the PPP puzzle.

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“…Framework of Phillips et al (2004) extends the analysis of So and Shin (1999) 2 , providing a more general analysis of IV estimation in potentially nonstationary autoregressions and showing that the Cauchy estimator has an optimality property in the class of certain IV procedures.…”

Section: The Econometric Methodologymentioning

confidence: 94%

“…On the other hand, of course, the t-ratio based on the OLS estimator has a limit normal distribution only when ||<1 and its limit distribution is non-Gaussian when distribution has implications for tests of a unit root. These properties are explored in So and Shin (1999), where the Cauchy estimator was first suggested, Phillips et al (2004) proposed six nonlinear instrument generating functions summarized below. Because of singularity problem, in this article, we report the IVi3 results for our empirical study, where F(y t-1 )=y t-1 Exp(-|y t-1 |) is used for lagged level y t-1 .…”

Section: The Econometric Methodologymentioning

confidence: 99%

Using the SUR model of tourism demand for neighbouring regions in Sweden and Norway

Salman¹

2011

Advances in Econometrics - Theory and Applications

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Recursive mean adjustment in time-series inferences

Cited by 81 publications

References 7 publications

A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR(p) MODELS WHEN BOTHNANDTARE LARGE

A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR(p) MODELS WHEN BOTHNANDTARE LARGE

"Aggregation Bias" DOES Explain the PPP Puzzle

Using the SUR model of tourism demand for neighbouring regions in Sweden and Norway

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