Breaking the panels: An application to the GDP per capita Lluís Carrion-i-Silvestre, Josep; Del Barrio-Castro, Tomás; López-Bazo, Enrique
Econometrics journal/The econometrics journal online,
01/2005, Volume:
8, Issue:
2
Journal Article
Peer reviewed
Open access
This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different specifications are considered depending on ...the structural breaks affecting the individual effects and/or the time trend. The model is flexible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have a standard normal limit distribution with a good finite sample performance. It is applied to typical panel data of real per capita GDP in a set of OECD countries.
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This article explores the possibility of cointegration existing between processes integrated at different frequencies. Using the demodulator operator, we show that such cointegration can exist and ...explore its form using both complex‐ and real‐valued representations. A straightforward approach to test for the presence of cointegration between processes integrated at different frequencies is proposed, with a Monte Carlo study and an application showing that the testing approach works well.
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This paper investigates the presence of deterministic seasonal features within a mixed frequency vector autoregressive model. A strategy based on Wald tests is proposed.
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We investigate the implications that temporally aggregating, either by average sampling or systematic (skip) sampling, a seasonal process has on the integration properties of the resulting series at ...both the zero and seasonal frequencies. Our results extend the existing literature in three ways. First, they demonstrate the implications of temporal aggregation for a general seasonally integrated process with S seasons. Second, rather than only considering the aggregation of seasonal processes with exact unit roots at some or all of the zero and seasonal frequencies, we consider the case where these roots are local‐to‐unity such that the original series is near‐integrated at some or all of the zero and seasonal frequencies. These results show, among other things, that systematic sampling, although not average sampling, can impact on the non‐seasonal unit root properties of the data; for example, even where an exact zero frequency unit root holds in the original data it need not necessarily hold in the systematically sampled data. Moreover, the systematically sampled data could be near‐integrated at the zero frequency even where the original data is not. Third, the implications of aggregation on the deterministic kernel of the series are explored.‐142
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SEMI-PARAMETRIC SEASONAL UNIT ROOT TESTS del Barrio Castro, Tomás; Rodrigues, Paulo M.M.; Robert Taylor, A.M.
Econometric theory,
04/2018, Volume:
34, Issue:
2
Journal Article
Peer reviewed
Open access
We extend the ${\cal M}$ class of unit root tests introduced by Stock (1999, Cointegration, Causality and Forecasting. A Festschrift in Honour of Clive W.J. Granger. Oxford University Press), Perron ...and Ng (1996, Review of Economic Studies 63, 435–463) and Ng and Perron (2001, Econometrica 69, 1519–1554) to the seasonal case, thereby developing semi-parametric alternatives to the regression-based augmented seasonal unit root tests of Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238). The success of this class of unit root tests to deliver good finite sample size control even in the most problematic (near-cancellation) case where the shocks contain a strong negative moving average component is shown to carry over to the seasonal case as is the superior size/power trade-off offered by these tests relative to other available tests.
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Del Barrio-Castro T. and García-Quevedo J. (2005) Effects of university research on the geography of innovation, Regional Studies 39 , 1217-1229. Applied studies on the relationship between geography ...and technological innovation for the USA, Germany, France and Italy have shown the positive effects that academic research exerts on the innovative output of firms at a spatial level. The purpose of this paper is to look for new evidence on the possible effects of university research for the case of Spanish regions. Within the framework of a Griliches-Jaffe knowledge production function, and using panel data and count models, the relationship between innovative inputs and patents is explored. The results show that university research exerts a positive influence on the regional distribution of private innovation of high-technological content.
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In this paper, we analyse the impact of persistent cycles on the well‐known semi‐parametric unit root tests of Phillips and Perron (1988, Biometrika, Vol. 75, pp. 335–346). It is shown, both ...analytically and through Monte Carlo simulations, that the presence of complex (near) unit roots can severely bias the size properties of these tests. Given the popularity of these tests with applied researchers and their routine presence in most econometric software packages, the results presented in this paper suggest that practitioners should treat the outcomes of these tests with some caution when applied to data which display a strong cyclical component.
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In this paper we extend the large-sample results provided for the augmented Dickey–Fuller test by Said and Dickey (1984, Biometrika 71, 599–607) and Chang and Park (2002, Econometric Reviews 21, ...431–447) to the case of the augmented seasonal unit root tests of Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238), inter alia. Our analysis is performed under the same conditions on the innovations as in Chang and Park (2002), thereby allowing for general linear processes driven by (possibly conditionally heteroskedastic) martingale difference innovations. We show that the limiting null distributions of the t-statistics for unit roots at the zero and Nyquist frequencies and joint F-type statistics are pivotal, whereas those of the t-statistics at the harmonic seasonal frequencies depend on nuisance parameters that derive from the lag parameters characterizing the linear process. Moreover, the rates on the lag truncation required for these results to hold are shown to coincide with the corresponding rates given in Chang and Park (2002); in particular, an o(T1/2) rate is shown to be sufficient.
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In this paper we investigate the impact of persistent (nonstationary or near nonstationary) cycles on the asymptotic and finite-sample properties of standard unit root tests. Results are presented ...for the augmented Dickey–Fuller (ADF) normalized bias and t-ratio-based tests (Dickey and Fuller, 1979, Journal of the American Statistical Association 745, 427–431; Said and Dickey, 1984; Biometrika 71, 599–607). the variance ratio unit root test of Breitung (2002, Journal of Econometrics 108, 343–363), and the M class of unit-root tests introduced by Stock (1999, in Engle and White (eds.), A Festschrift in Honour of Clive W.J. Granger) and Perron and Ng (1996, Review of Economic Studies 63, 435–463). We show that although the ADF statistics remain asymptotically pivotal (provided the test regression is properly augmented) in the presence of persistent cycles, this is not the case for the other statistics considered and show numerically that the size properties of the tests based on these statistics are too unreliable to be used in practice. We also show that the t-ratios associated with lags of the dependent variable of order greater than two in the ADF regression are asymptotically normally distributed. This is an important result as it implies that extant sequential methods (see Hall, 1994, Journal of Business & Economic Statistics 17, 461–470; Ng and Perron, 1995, Journal of the American Statistical Association 90, 268–281) used to determine the order of augmentation in the ADF regression remain valid in the presence of persistent cycles.
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This paper analyzes two key issues for the empirical implementation of parametric seasonal unit root tests, namely generalized least squares (GLS) versus ordinary least squares (OLS) detrending and ...the selection of the lag augmentation polynomial. Through an extensive Monte Carlo analysis, the performance of a battery of lag selection techniques is analyzed, including a new extension of modified information criteria for the seasonal unit root context. All procedures are applied for both OLS and GLS detrending for a range of data generating processes, also including an examination of hybrid OLS-GLS detrending in conjunction with (seasonal) modified AIC lag selection. An application to quarterly U.S. industrial production indices illustrates the practical implications of choices made.
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