Panel unit root tests in the presence of cross-sectional dependence: finite sample performance and an application

This paper examines the finite sample properties of three testing regimes for the null hypothesis of a panel unit root against stationary alternatives in the presence of cross-sectional correlation. The regimes of Bai and Ng (2004), Moon and Perron (2004) and Pesaran (2007) are assessed in the presence of multiple factors and also other non-standard situations. The behaviour of some information criteria used to determine the number of factors in a panel is examined and new information criteria with improved properties in small-N panels proposed. An application to the efficient markets hypothesis is also provided. The null hypothesis of a panel random walk is not rejected by any of the tests, supporting the efficient markets hypothesis in the financial services sector of the Australian Stock Exchange.

Beyond Panel Unit Root Tests: Using Multiple Testing to Determine the Non Stationarity Properties of Individual Series in a Panel

Most panel unit root tests are designed to test the joint null hypothesis of a unit root for each individual series in a panel. After a rejection, it will often be of interest to identify which series can be deemed to be stationary and which series can be deemed nonstationary. Researchers will sometimes carry out this classification on the basis of n individual (univariate) unit root tests based on some ad hoc significance level. In this paper, we demonstrate how to use the false discovery rate (FDR) in evaluating I(1)=I(0) classifications based on individual unit root tests when the size of the cross section (n) and time series (T) dimensions are large. We report results from a simulation experiment and illustrate the methods on two data sets.

Sostenibilidad fiscal: una aproximación con datos panel para 8 países Latinoaméricanos

Este documento examina la hipótesis de sostenibilidad fiscal para 8 países de Latinoamérica. A partir de un modelo de datos panel, se determina si los ingresos y gasto primario de los Gobiernos entre 1960 - 2009 están cointegrados, es decir, si son sostenibles a largo plazo. Para esto, se utilizaron pruebas de raíz unitaria y cointegración de segunda generación con datos panel macroeconómicos, lo que permite tener en cuenta la dependencia cruzada entre los países, así como los posibles quiebres estructurales en la relación que estén determinados de manera endógena; en particular, se usan la prueba de estacionariedad de Hadri y Rao (2008) y la prueba de cointegración de Westerlund (2006). Como resultado del análisis se encontró evidencia empírica de que en el período bajo estudio el déficit primario en los 8 países latinoamericanos es sostenible pero en sentido débil.

Testing for unit roots in bounded time series

Many key economic and financial series are bounded either by construction or through policy controls. Conventional unit root tests are potentially unreliable in the presence of bounds, since they tend to over-reject the null hypothesis of a unit root, even asymptotically. So far, very little work has been undertaken to develop unit root tests which can be applied to bounded time series. In this paper we address this gap in the literature by proposing unit root tests which are valid in the presence of bounds. We present new augmented Dickey–Fuller type tests as well as new versions of the modified ‘M’ tests developed by Ng and Perron [Ng, S., Perron, P., 2001. LAG length selection and the construction of unit root tests with good size and power. Econometrica 69, 1519–1554] and demonstrate how these tests, combined with a simulation-based method to retrieve the relevant critical values, make it possible to control size asymptotically. A Monte Carlo study suggests that the proposed tests perform well in finite samples. Moreover, the tests outperform the Phillips–Perron type tests originally proposed in Cavaliere [Cavaliere, G., 2005. Limited time series with a unit root. Econometric Theory 21, 907–945]. An illustrative application to U.S. interest rate data is provided

Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

Testing for Seasonal Unit Roots when Residuals Contain Serial Correlations under HEGY Test Framework

This paper introduces a corrected test statistic for testing seasonal unit roots when residuals contain serial correlations, based on the HEGY test proposed by Hylleberg,Engle, Granger and Yoo (1990). The serial correlations in the residuals of test regressionare accommodated by making corrections to the commonly used HEGY t statistics. Theasymptotic distributions of the corrected t statistics are free from nuisance parameters.The size and power properties of the corrected statistics for quarterly and montly data are investigated. Based on our simulations, the corrected statistics for monthly data havemore power compared with the commonly used HEGY test statistics, but they also have size distortions when there are strong negative seasonal correlations in the residuals.

Unit roots and the welfare gains of cycle smoothing

li consumption is log-Normal and is decomposed into a linear deterministic trend and a stationary cycle, a surprising result in business-cycle research is that the welfare gains of eliminating uncertainty are relatively small. A possible problem with such calculations is the dichotomy between the trend and the cyclical components of consumption. In this paper, we abandon this dichotomy in two ways. First, we decompose consumption into a deterministic trend, a stochastic trend, and a stationary cyclical component, calculating the welfare gains of cycle smoothing. Calculations are carried forward only after a careful discussion of the limitations of macroeconomic policy. Second, still under the stochastic-trend model, we incorporate a variable slope for consumption depending negatively on the overall volatility in the economy. Results are obtained for a variety of preference parameterizations, parameter values, and different macroeconomic-policy goals. They show that, once the dichotomy in the decomposition in consumption is abandoned, the welfare gains of cycle smoothing may be substantial, especially due to the volatility effect.

Using a panel structure to discuss the Feldstein-Horioka puzzle in developing countries

The purpose of this paper is to test the implications of current account solvency for the savinginvestment correlation in developing countries. Since solvency is a long-run phenomenon, and given that the power of the standard unit root and cointegration tests is low, we exploit the panel structure of the sample of 29 developing countries. We find evidence that saving and investment are cointegrated and that the current account is stationary. Therefore, the Feldstein-Horioka correlations are not a puzzle in the sense they reflect the intertemporal budget constraint. The same results are obtained for different subsamples (Africa, Asia, and Latin America) and for different periods of time (1960-74 and 1975-96). We, then, suggest that an error correction model should distinguish between the long-run correlation, which reflects the solvency condition, and the short-run correlation, which could measure capital mobility.

Testing for a Unit Root in Panels with Dynamic Factors

This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asymptotic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.

Panel Cointegration of Chinese A and B Shares

This paper uses panel unit root and cointegration methods to test the stationarity of the premium on domestic investors’ A shares over foreign investors’ B shares and cointegration between the A and B share prices on the Chinese stock exchanges. We find that the A share price premium is nonstationary until 2001, when the A and B share markets were partially merged, and that the A and B share prices are cointegrated in the panel.Cointegration is more likely to be found for firms in the service sector and for firms that issued B shares recently.

CO2 Emissions, GDP and trade : a panel cointegration approach

This paper examines the relationships among per capita CO2 emissions, per capita GDP and international trade based on panel data sets spanning the period 1960-2008: one for 150 countries and the others for sub-samples comprising OECD and Non-OECD economies. We apply panel unit root and cointegration tests, and estimate a panel error correction model. The results from the error correction model suggest that there are long-term relationships between the variables for the whole sample and for Non-OECD countries. Finally, Granger causality tests show that there is bi-directional short-term causality between per capita GDP and international trade for the whole sample and between per capita GDP and CO2 emissions for OECD countries