Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.

A multicenter study to validate the reproducibility of MSI testing with a panel of 5 quasimonomorphic mononucleotide repeats.

Microsatellite instability (MSI) testing in clinics is becoming increasingly widespread; therefore, there is an urgent need for methodology standardization and the availability of quality control. This study is aimed to assess the interlaboratory reproducibility of MSI testing in archive samples by using a panel of 5 recently introduced, mononucleotide repeats (MNR). The quality control involved 8 European institutions. Participants were supplied with DNA extracted from 15 archive colon carcinoma samples and from the corresponding normal tissues. Every group was asked to assess the MSI status of the samples by using the BAT25, BAT26, NR21, NR24, and NR27 mononucleotide markers. Four institutions repeated the analysis using the NCI reference panel to confirm the results obtained with the MNR markers. The overall concordance among institutions for MSI analyses at single locus level was 97.7% when using the MNR panel and 95.0% with the NCI one. The laboratories obtained a full agreement in scoring the MSI status of each patient sample, both using the mononucleotide and the NCI marker sets. With the NCI marker set, however, concordance was lowered to 85.7% when considering the MSI-Low phenotype. Concordance between the 2 panels in scoring the MSI status of each sample was complete if no discrimination was made between MSI-Stable and MSI-L, whereas it dropped to 76.7% if MSI-L was considered. In conclusion, the use of the MNR panel seems to be a robust approach that yields a very high level of reproducibility. The results obtained with the 5 MNR are diagnostically consistent with those obtained by the use of the NCI markers, except for the MSI-Low phenotype.

Panel index VAR models: Specification, Estimation, Testing and Leading Indicators

This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

Testing for hysteresis in unemployment in OECD countries: new evidence using stationarity panel tests with breaks

This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

Testing for hysteresis in unemployment in OECD countries: new evidence using stationarity panel tests with breaks

This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

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.

Testing for non-stationarity and cointegration allowing for the possibility of a structural break: an application to EuroSterling interest rates

In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

Testing linear cointegration against smooth-transition cointegration

This paper studies a smooth-transition (ST) type cointegration. The proposed ST cointegration allows for regime switching structure in a cointegrated system. It nests the linear cointegration developed by Engle and Granger (1987) and the threshold cointegration studied by Balke and Fomby (1997). We develop F-type tests to examine linear cointegration against ST cointegration in ST-type cointegrating regression models with or without time trends. The null asymptotic distributions of the tests are derived with stationary transition variables in ST cointegrating regression models. And it is shown that our tests have nonstandard limiting distributions expressed in terms of standard Brownian motion when regressors are pure random walks, while have standard asymptotic distributions when regressors contain random walks with nonzero drift. Finite-sample distributions of those tests are studied by Monto Carlo simulations. The small-sample performance of the tests states that our F-type tests have a better power when the system contains ST cointegration than when the system is linearly cointegrated. An empirical example for the purchasing power parity (PPP) data (monthly US dollar, Italy lira and dollar-lira exchange rate from 1973:01 to 1989:10) is illustrated by applying the testing procedures in this paper. It is found that there is no linear cointegration in the system, but there exits the ST-type cointegration in the PPP data.

Testing the externalities hypothesis of endogenous growth using cointegration

The initial endogenous growth models emphasized the importance of externaI effects in explaining sustainable growth across time. Empirically, this hypothesis can be confirmed if the coefficient of physical capital per hour is unity in the aggregate production function. Although cross-section results concur with theory, previous estimates using time series data rejected this hypothesis, showing a small coefficient far from unity. It seems that the problem lies not with the theory but with the techniques employed, which are unable to capture low frequency movements in high frequency data. This paper uses cointegration - a technique designed to capture the existence of long-run relationships in multivariate time series - to test the externalities hypothesis of endogenous growth. The results confirm the theory' and conform to previous cross-section estimates. We show that there is long-run proportionality between output per hour and a measure of capital per hour. U sing this result, we confmn the hypothesis that the implied Solow residual can be explained by government expenditures on infra-structure, which suggests a supply side role for government affecting productivity and a decrease on the extent that the Solow residual explains the variation of output.

Testing the long-run implications of the expectation hypothesis using cointegration techniques with structural change

This paper investigates whether or not multivariate cointegrated process with structural change can describe the Brazilian term structure of interest rate data from 1995 to 2006. In this work the break point and the number of cointegrated vector are assumed to be known. The estimated model has four regimes. Only three of them are statistically different. The first starts at the beginning of the sample and goes until September of 1997. The second starts at October of 1997 until December of 1998. The third starts at January of 1999 and goes until the end of the sample. It is used monthly data. Models that allows for some similarities across the regimes are also estimated and tested. The models are estimated using the Generalized Reduced-Rank Regressions developed by Hansen (2003). All imposed restrictions can be tested using likelihood ratio test with standard asymptotic 1 qui-squared distribution. The results of the paper show evidence in favor of the long run implications of the expectation hypothesis for Brazil.

Consideration of three proposals to conduct research on possible health effects of radiation from nuclear weapon testing in Arizona, Nevada, and Utah, and nuclear weapon testing and studies related to health effects : an historical summary : responding to recommendations by the panel of experts on the archive of PHS documents /

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