Estimating deterministic trends with an integrated or stationary noise component

Perron, Pierre; Yabu, Tomoyoshi

doi:10.1016/j.jeconom.2009.03.011

Cited by 123 publications

(187 citation statements)

References 26 publications

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“…That is, without individual e¤ects, the t-ratio based on the FGLS, can be used for inference using the standard normal distribution. Hence, in this case, one does not have to consider the "super-e¢ cient" type estimator by Perron and Yabu (2009) which is designed to bridge the gap between I(0) and I(1). 10 …”

Section: Case 1: Without Individual E¤ectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…While Baltagi et al (2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on test of hypotheses in this setting. One important finding is that unlike the time series case, one does not necessarily need to rely on the "super-efficient" type AR estimator by Perron and Yabu (2009) to make inference in panel data.In fact, we show that the simple t-ratio always converges to the standard normal distribution regardless of whether the disturbances and/or the regressor are stationary.Key Words: Panel Data, OLS, Fixed-Effects, First-Difference, GLS, t-ratio. …”

mentioning

confidence: 99%

“…This paper is a follow up paper which is concerned with test of hypotheses using these standard panel data estimators. One important …nding, is that unlike the time series setting, one does not necessarily need to rely on the "super-e¢ cient"type AR estimator by Perron and Yabu (2009) to make inference in panel data. In fact, we show that the simple t-ratio based on the FGLS estimator of Baltagi and Li (1991), will always converge to the standard normal distribution regardless of whether the disturbances and/or the regressor are stationary or not.…”

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confidence: 99%

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Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

Baltagi

Kao

2011

AStA Adv Stat Anal

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This paper considers the problem of hypotheses testing in a simple panel data regression model with random individual effects and serially correlated disturbances. Following Baltagi, Kao and Liu (2008), we allow for the possibility of non-stationarity in the regressor and/or the disturbance term. While Baltagi et al. (2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on test of hypotheses in this setting. One important finding is that unlike the time series case, one does not necessarily need to rely on the "super-efficient" type AR estimator by Perron and Yabu (2009) to make inference in panel data.In fact, we show that the simple t-ratio always converges to the standard normal distribution regardless of whether the disturbances and/or the regressor are stationary.Key Words: Panel Data, OLS, Fixed-Effects, First-Difference, GLS, t-ratio.

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Section: Case 1: Without Individual E¤ectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

Baltagi

Kao

2011

AStA Adv Stat Anal

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“…In this situation, a theory is constructed for the class of regressors that satisfy the so-called Grenander's condition. However, while these regressors may be sufficiently general in empirical work or in the theoretical analysis of deterministically trending models, such as in Vogelsang (1998) and Perron and Yabu (2009), theoretical studies of asymptotic efficiency without this condition have rarely been seen.…”

Section: Introductionmentioning

confidence: 99%

Asymptotic efficiency of the OLS estimator with singular limiting sample moment matrices

Uematsu

2016

Statistics & Probability Letters

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This paper presents a time series model that has an asymptotically efficient ordinary least squares (OLS) estimator, irrespective of the singularity of its limiting sample moment matrices. In the literature on stationary time series analysis, Grenander and Rosenblatt's (1957) (G-R) classical result is used to judge the asymptotic efficiency of regression coefficients on deterministic regressors satisfying Grenander's condition. Without this condition, however, it is not obvious that the model is efficient. In this paper, we introduce such a model by proving the efficiency of the model with a slowly varying (SV) regressor under

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Economic growth in China and its impact on international commodity prices

Ghoshray

Pundit²

2020

Int. J Fin Econ

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Since the turn of the century, China has experienced economic growth that has called for rapid industrialisation, infrastructure growth and urbanisation, making China highly dependent on primary commodities. The resource intensive growth path followed by a slowdown in recent years has raised the question to what extent her demand for commodities can affect international commodity prices. To this end, recent studies have analysed the link between economic growth or slowdown on commodity prices using linear multivariate models. However, a problem is that commodity prices are known to be highly variable and characterised by multiple structural changes. With such characteristics of the data, it is likely to be the case one may obtain mis‐specified inferences from a linear multivariate framework. Accordingly, we make use of novel Flexible Fourier Form (FFF) econometric procedures to account for multiple breaks in the economic variables, which have better power and size properties over the standard linear models. We find that the persistence of economic variables employed in this study and their causal link are better approximated by such nonlinear FFF procedures. Our results show that there is evidence of short run predictability between selected commodity prices and economic growth in China. Further, the responses of different commodity prices to shocks in economic growth are quite profound especially for those cases where we find causal links with economic growth in China. While we find a significant impact of economic growth of China on commodity prices, the response varies for different commodities.

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Estimating deterministic trends with an integrated or stationary noise component

Cited by 123 publications

References 26 publications

Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

Asymptotic efficiency of the OLS estimator with singular limiting sample moment matrices

Economic growth in China and its impact on international commodity prices

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