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  • 1.
    Berglund, Johanna
    Nerikes Allehanda.
    Örebroforskare: Inför parallell valuta2015In: Nerikes Allehanda, ISSN 1103-971X, article id 1.3067276Article in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

    Att införa en parallell valuta skulle kunna lösa Greklandskrisen. Det menar örebroforskaren Panagiotis Mantalos som blev inbjuden till det grekiska parlamentet för att presentera sitt förslag.

  • 2.
    Hultkrantz, Lars
    et al.
    Örebro University.
    Andersson, Linda
    Örebro University.
    Mantalos, Panagiotis
    Örebro University.
    Stumpage prices in Sweden 1909-2012: Testing for non-stationarity2014In: Journal of Forest Economics, ISSN 1104-6899, E-ISSN 1618-1530, Vol. 20, no 1, p. 33-46Article in journal (Refereed)
    Abstract [en]

    The price of timber stumpage is one of the few natural-resource rents that can be directly observed as a market price. Rules for optimal timber harvesting under uncertainty have been found to depend on whether the timber rent price is non-stationary or stationary. In this study we extend previous research by Hultkrantz (1995) that tested for unit-root with an exogenous break point in Swedish stumpage prices from 1909 to 1990, employing data up to 2012, hence for 104 years, and unit-root tests with endogenously selected break points. We find support for a structural level break at the end of WW2 and that non-stationarity can be rejected. We show that this is a robust conclusion. There is thus no sign of a new break in the extended recent time period and no signal of a secular increase of timber resource scarcity.

  • 3.
    Hultkrantz, Lars
    et al.
    Örebro University.
    Krüger, Niclas
    Örebro University.
    Mantalos, Panagiotis
    Örebro University.
    Risk-adjusted long-term social rates of discount for transportation infrastructure investment2014In: Research in Transportation Economics, ISSN 0739-8859, E-ISSN 1875-7979, Vol. 47, p. 70-81Article in journal (Refereed)
    Abstract [en]

    We modify a method recently suggested by Weitzman (2012, 2013) for determining a risk-adjusted social discount rate (SDR) term structure consistent with both the (augmented) Ramsey rule and the consumption-based CAPM. Using this approach we estimate SDR for transportation infrastructure investments based on an analysis of correlations between transportation, split between road and rail, and between passenger travel and freight transport, and GDP in Sweden 1950–2011. We show that this can be estimated from two time-series following a random walk with drift, even if the variables are not co-integrated. Based on current estimates of the risk-free rate and the equity risk premium, we estimate the relevant SDR to be 5–6 per cent, possibly somewhat lower for investment in railroads for passenger travel, and only slowly declining within the investment horizon. This is higher than the current rates used in, for instance, Sweden, Germany and the UK.

  • 4.
    Hultkrantz, Lars
    et al.
    Örebro University.
    Mantalos, Panagiotis
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Hedging with trees: Tail-hedge discounting of long-term forestry returns2018In: Journal of Forest Economics, ISSN 1104-6899, E-ISSN 1618-1530, Vol. 30, p. 52-57Article in journal (Refereed)
    Abstract [en]

    Tail-hedge discounting is based on decomposition of returns from long-term investments in a fraction (gamma) that is correlated with consumption and another that is not. The first part is discounted at a discount rate that includes a risk premium, the other with the risk-free rate. We estimate gamma for forestry on Swedish data for stumpage prices and GDP per capita 1909-2012. We demonstrate that the result considerably changes the expected present value of medium-term and long-term forest investments. (C) 2018 Department of Forest Economics, Swedish University of Agricultural Sciences, Umea. Published by Elsevier GmbH. All rights reserved.

  • 5.
    Javed, Farrukh
    et al.
    Lund University.
    Mantalos, Panagiotis
    Örebro University.
    GARCH-Type Models and Performance of Information Criteria2013In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 42, no 8, p. 1917-1933Article in journal (Refereed)
    Abstract [en]

    This article discusses the ability of information criteria toward the correct selection of different especially higher-order generalized autoregressive conditional heteroscedasticity (GARCH) processes, based on their probability of correct selection as a measure of performance. Each of the considered GARCH processes is further simulated at different parameter combinations to study the possible effect of different volatility structures on these information criteria. We notice an impact from the volatility structure of time series on the performance of these criteria. Moreover, the influence of sample size, having an impact on the performance of these criteria toward correct selection, is observed.

  • 6.
    Javed, Farrukh
    et al.
    Lund University.
    Mantalos, Panagiotis
    Lund University.
    Sensitivity of the causality in variance tests to GARCH (1,1) parameters2011Other (Other academic)
    Abstract [en]

    We discuss the sensitivity to the GARCH(1; 1) parameters in the causality of variance tests. Themotivation behind the study is to observe the impact of dierent volatile data sets on volatility spillovertests. We investigate a data generating process AR(1)-GARCH(1,1) with an extensive set of MonteCarlo experiments for dierent GARCH(1; 1) processes. It is found that the causation pattern, dueto causality between two series, is in uenced by the intensity of volatility clustering. Dierent testingprocedures are applied for testing the Causality in variance. We observe a severe size and powerdistortion when the clustering parameter is high and when the process is near integration. Thesendings are noticed when the asymptotic distribution of the statistics is used to dene a critical region.So instead of relying on the asymptotic distribution, we calculate the percentiles of true underlyingprocess with no-spillover eect and use them as a critical rigion for both size and power. We observea meaningful improvement in the results.

  • 7.
    Jentsch, Carlstein
    et al.
    University of Mannheim, Germany.
    Kreiss, Jens P.
    Technische Universität Braunschweig, Germany.
    Mantalos, Panagiotis
    Örebro University.
    Paparoditis, Efstathios
    University of Cyprus, Cyprus .
    Hybrid bootstrap aided unit root testing2012In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 27, no 4, p. 779-797Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a hybrid bootstrap procedure for augmented Dickey-Fuller (ADF) tests for the presence of a unit root. This hybrid proposal combines a time domain parametric autoregressive fit to the data and a nonparametric correction applied in the frequency domain to capture features that are possibly not represented by the parametric model. It is known that considerable size and power problems can occur in small samples for unit root testing in the presence of an MA parameter using critical values of the asymptotic Dickey-Fuller distribution. The benefit of the sieve bootstrap in this situation has been investigated by Chang and Park (J Time Ser Anal 24:379–400, 2003). They showed asymptotic validity as well as substantial improvements for small sample sizes, but the actual sizes of their bootstrap tests were still quite far away from the nominal size. The finite sample performances of our procedure are extensively investigated through Monte Carlo simulations and compared to the sieve bootstrap approach. Regarding the size of the tests, our results show that the hybrid bootstrap remarkably outperforms the sieve bootstrap.

  • 8.
    Mantalos, Panagiotis
    Örebro University.
    Greek Debt Crisis: “An Introduction to the Economic Effects of Austerity”2015Report (Other academic)
    Abstract [en]

    We trace the reasons for the negative development of Greek government debt from 1980 to 2014 by studying the deficits of the Greek state under the same period. We also see the Greek debt under the different political regimes. We briefly describe the two bailout programs for Greece and finally we name the amount and Euro states that own the Greek loans. The negative effects of austerity are about 22% less GDP and total household and government consumption and monthly wages; finally, the unemployment rate grew 21%.

  • 9.
    Mantalos, Panagiotis
    Örebro University.
    Greek debt Crisis: The "@-euro" a New Possible Solution to the Greek Debt Crisis2015In: International Journal of Financial Crisis and Black Money, Vol. 1, no 1, p. 1-6Article in journal (Refereed)
    Abstract [en]

    We introducing the new idea, of "@-euro" is a self-part-financiering monetary policy. This new idea, introduced more money (liquidity) to Greek state, and a system to collect taxes from the black economy. This idea, which is a possible solution to the Greek Crisis applied in a 7-years alternative Budget. The "@-euro" has two characteristics, first self-financiering and self-discipline. The produced new MTFS with exceptional positive results, with 43, 00 billion surplus after that we have pay 113, 00 billion Euro back to the creditors in a 7 year period. Moreover, no negative effects of austerity. There is fiscal stimulus without inflation!

  • 10.
    Mantalos, Panagiotis
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Robust critical values for unit root tests for series with conditional heteroscedasticity errors: an application of the simple NoVaS transformation2017In: Cogent Economics & Finance, E-ISSN 2332-2039, Vol. 5, no 1, p. 23article id 1274282Article in journal (Refereed)
    Abstract [en]

    In this paper, we introduce a set of critical values for unit root tests that are robust in the presence of conditional heteroscedasticity errors using the normalizing and variance-stabilizing transformation (NoVaS) in Politis (2007) and examine their properties using Monte Carlo methods. In terms of the size of the test, our analysis reveals that unit root tests with NoVaS-modified critical values have actual sizes close to the nominal size. For the power of the test, we find that unit root tests with NoVaS-modified critical values either have the same power as, or slightly better than, tests using conventional Dickey–Fuller critical values across the sample range considered.

  • 11.
    Mantalos, Panagiotis
    Jönköping University.
    Three different measures of sample skewness and kurtosis and their effects on the Jarque–Bera test for normality2011In: International Journal of Computational Economics and Econometrics, ISSN 1757-1170, E-ISSN 1757-1189, Vol. 2, no 1, p. 47-62, article id 40576Article in journal (Refereed)
    Abstract [en]

    Monte Carlo methods are used to study the size and the power of three versions of the Jarque and Bera Lagrangian multiplier test for normality, JB(g1, g2), JB(b1, b2) and, finally, JB(k1, k2). The difference between these tests comes from the different definitions (estimates) of sample skewness and kurtosis. The Jarque and Bera test has rather poor small sample properties: the slow convergence of the test statistic to its limiting distribution makes the test oversized for small nominal level and undersized for larger than 3% levels even in a reasonably large sample. However, the JB(k1, k2) for a 5% nominal level shows good properties for all samples. The power of the tests shows the same erratic form.

  • 12.
    Mantalos, Panagiotis
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Hultkrantz, Lars
    Örebro University.
    Estimating 'gamma' for tail-hedge discount rates when project returns are cointegrated with GDP2018In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 50, no 37, p. 4074-4085Article in journal (Refereed)
    Abstract [en]

    Martin Weitzman has suggested a method for calculating social discount rates for long-term investments when project returns are covariant with consumption or other macroeconomic variables, so-called tail-hedge discounting'. This method relies on a parameter called real project gamma' that measures the proportion of project returns that is covariant with the macroeconomic variable. We compare two approaches for estimation of this gamma when the project returns and the macroeconomic variable are cointegrated. First, we use Weitzman's own approach, and second a simple data transformation that keeps gamma within the zero to one interval. In a Monte-Carlo study, we show that the method of using a standardized series is better and robust under different data-generating processes. Both approaches are examined in a Monte-Carlo experiment and applied to Swedish time-series data from 1950-2011 for annual time-series data for rail freight (a measure of returns from rail investments) and GDP.

  • 13.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Karagrigoriou, A.
    University of Cyprus, Cyrpus.
    Bootstrapping the augmented Dickey-Fuller test for unit root using the MDIC2012In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 82, no 3, p. 431-443Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider the bootstrap procedure for the augmented Dickey–Fuller (ADF) unit root test by implementing the modified divergence information criterion (MDIC, Mantalos et al. [An improved divergence information criterion for the determination of the order of an AR process, Commun. Statist. Comput. Simul. 39(5) (2010a), pp. 865–879; Forecasting ARMA models: A comparative study of information criteria focusing on MDIC, J. Statist. Comput. Simul. 80(1) (2010b), pp. 61–73]) for the selection of the optimum number of lags in the estimated model. The asymptotic distribution of the resulting bootstrap ADF/MDIC test is established and its finite sample performance is investigated through Monte-Carlo simulations. The proposed bootstrap tests are found to have finite sample sizes that are generally much closer to their nominal values, than those tests that rely on other information criteria, like the Akaike information criterion [H. Akaike, Information theory and an extension of the maximum likelihood principle, in Proceedings of the 2nd International Symposium on Information Theory, B.N. Petrov and F. Csáki, eds., Akademiai Kaido, Budapest, 1973, pp. 267–281]. The simulations reveal that the proposed procedure is quite satisfactory even for models with large negative moving average coefficients.

  • 14.
    Mantalos, Panagiotis
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karagrigoriou, A.
    Univ Aegean, Greece.
    Strelec, L.
    Mendel Univ Brno, Czech Republic.
    Jordanova, P.
    Shumen Univ, Bulgaria.
    Hermann, P.
    Johannes Kepler Univ Linz, Austria.
    Kiselak, J.
    Johannes Kepler Univ Linz, Austria;PJ Safarik Univ Kosice, Slovakia.
    Hudak, J.
    PJ Safarik Univ Kosice, Slovakia.
    Stehlik, M.
    Johannes Kepler Univ Linz, Austria;Univ Valparaiso, Chile;Univ Iowa, USA.
    On improved volatility modelling by fitting skewness in ARCH models2019In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532Article in journal (Refereed)
    Abstract [en]

    We study ARCH/GARCH effects under possible deviation from normality. Since skewness is the principal cause for deviations from normality in many practical applications, e.g. finance, we study in particular skewness. We propose robust tests for normality both for NoVaS and modified NoVaS transformed and original data. Such an approach is not applicable for EGARCH, but applicable for GARCH-GJR models. A novel test procedure is proposed for the skewness in autoregressive conditional volatility models. The power of the tests is investigated with various underlying models. Applications with financial data show the applicability and the capabilities of the proposed testing procedure.

  • 15.
    Mantalos, Panagiotis
    et al.
    Örebro University.
    Karagrigoriou, Alex
    University of Cyprus.
    Testing for skewness in ar conditional volatility models for financial return series2012Report (Other academic)
    Abstract [en]

    In this paper a test procedure is proposed for the skewness in autoregressive conditional volatility models. The size and the power of the test are investigated through a series of Monte Carlo simulations with various models. Furthermore, applications with financial data are analyzed in order to explore the applicability and the capabilities of the proposed testing procedure.

  • 16.
    Mantalos, Panagiotis
    et al.
    University of Lund.
    Mattheou, K.
    University of Cyprus, Cyprus.
    Karagrigoriou, A.
    University of Cyprus, Cyprus.
    An Improved Divergence Information Criterion for the Determination of the Order of an AR Process2010In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 39, no 5, p. 865-879Article in journal (Refereed)
    Abstract [en]

    In this article we propose a modification of the recently introduced divergence information criterion (DIC, Mattheou et al., 2009) for the determination of the order of an autoregressive process and show that it is an asymptotically unbiased estimator of the expected overall discrepancy, a nonnegative quantity that measures the distance between the true unknown model and a fitted approximating model. Further, we use Monte Carlo methods and various data generating processes for small, medium, and large sample sizes in order to explore the capabilities of the new criterion in selecting the optimal order in autoregressive processes and in general in a time series context. The new criterion shows remarkably good results by choosing the correct model more frequently than traditional information criteria.

  • 17.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Mattheou, K.
    University of Cyprus, Cyprus.
    Karagrigoriou, A.
    University of Cyprus, Cyprus.
    Forecasting ARMA models: a comparative study of information criteria focusing on MDIC2010In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 80, no 1, p. 61-73Article in journal (Refereed)
    Abstract [en]

    This paper deals with the implementation of model selection criteria to data generated by ARMA processes. The recently introduced modified divergence information criterion is used and compared with traditional selection criteria like the Akaike information criterion (AIC) and the Schwarz information criterion (SIC). The appropriateness of the selected model is tested for one- and five-step ahead predictions with the use of the normalized mean squared forecast errors (NMSFE).

  • 18.
    Mantalos, Panagiotis
    et al.
    Jönköping University.
    Månsson, Kristofer
    Jönköping University.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics. Jönköping University.
    The effect of spillover on the Johansens tests for Cointegration: A Monte Carlo Analysis2010In: International Journal of Computational Economics and Econometrics, ISSN 1757-1170, E-ISSN 1757-1189, Vol. 1, no 3/4, p. 327-342Article in journal (Refereed)
    Abstract [en]

    This paper investigates the effect of spillover (i.e. causality in variance) on the Johansens tests for cointegration by conducting a Monte Carlo experiment where 16 different data generating processes (DGP) are used and a number of factors that might affect the properties of the Johansens cointegration tests are varied. The result from the simulation study clearly shows that spillover effect leads to an over-rejection of the true null hypothesis. Hence, in the presence of spillover it becomes very hard to make inferential statements since it will often lead to erroneous claims that cointegration relationships exist.

  • 19.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Jönköping University.
    Bootstrap methods for autocorrelation test with uncorrelated but not independent errors2008In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 25, no 5, p. 1040-1050Article in journal (Refereed)
    Abstract [en]

    By using bootstrap technique we investigate the properties of the Breusch [Breusch, T.S., 1978. Testing for autocorrelation in dynamic linear models. Australian Economic Papers 17, 334–355]–Godfrey [Godfrey, L.G., 1978. Testing for higher order serial correlation in regression equations when the regressors include lagged dependent variables. Econometrica 46, 1303–1310] autocorrelation tests in dynamic models with uncorrelated but not independent errors. In this paper we show that, under conditions when the errors are uncorrelated but not independent, even the best likelihood ratio test cannot achieve the asymptotic distribution under the null hypothesis of no autocorrelation. Standard bootstrap methods also fail to produce consistent results. To overcome this problem we applied several bootstrap testing methods for the same purpose and found the stationary bootstrap and Wild bootstrap with static model to perform adequately among the other bootstrap methods.

  • 20.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Göteborg University.
    Bootstrapped Johansen Tests for Cointegrating Relationships: A Graphical analysis2001In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 68, no 4, p. 351-371Article in journal (Refereed)
    Abstract [en]

    Using Monte Carlo methods together with the bootstrap critical values, we have studied the properties of two tests (Trace and Lmax), derived by Johansen (1988) for testing for cointegration in VAR systems. Regarding the size of the tests, the results show that both of the test methods perform satisfactorily when there are mixed stationary and nonstationary components in the model. The analyses of the power functions indicate that both of the test methods can effectively detect the presence of cointegration vector(s). Finally, when considering the size and power properties, we could not find any noticeable differences between the two test methods.

  • 21.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Lund University.
    Size and Power of the Error Correction Model (ECM) of Cointegration Tests. A Bootstrap Approach1998In: Oxford Bulletin of Economics and Statistics, ISSN 0305-9049, E-ISSN 1468-0084, Vol. 60, no 2, p. 249-255Article in journal (Refereed)
    Abstract [en]

    The size and power of the ECM cointegration test are investigated by using the ‘bootstrap critical values’. The purpose of this paper is to show the ability of the bootstrap technique to produce critical values which are much more accurate than the asymptotic ones. The properties of the test have been studied, using Monte Carlo methods, for three different data generating processes. As regards the size of the test, we find that the ECM cointegration test together with the bootstrap critical values perform better than the ECM cointegration test based on the asymptotic critical values. While as regards the power of the tests, the results prove to be similar for the different versions.

  • 22.
    Mantalos, Panagiotis
    et al.
    Lund University .
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Jönköping University.
    The Effect of the GARCH(1,1) on Autocorrelation Tests in Dynamic Systems of Equations2005In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 35, no 16, p. 1907-1913Article in journal (Refereed)
    Abstract [en]

    Using Monte Carlo methods, the properties of systemwise generalizations of the Breusch–Godfrey test for autocorrelated errors are studied when there are some kinds of GARCH effects among the errors. The analysis, regarding the size of the test, reveals that the GARCH have considerable effects of the properties of the test regarding the size, especially in large systems of equations. The corrected LR tests, however, have been shown to perform satisfactorily in small systems when the errors are white noise or they have low GARCH effects, whilst the commonly used TR2 test behaves badly even in single equations. All tests perform badly, however, when the number of equations increases and the GARCH effect is strong. As regards the power of the test, the GARCH was not found to have any significant effects on the power properties of the test.

  • 23.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    The Effect of the Spillover on the Granger Causality Test 2010In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 37, no 9, p. 1473-1486Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate the properties of the Granger causality test in stationary and stable vector autoregressive models under the presence of spillover effects, i.e., causality in variance. The Wald test and the WW test (the Wald test with White’s proposed heteroskedasticity-consistent covariance matrix estimator imposed) are analyzed. The investigation is undertaken by using Monte Carlo simulation in which two different sample sizes and six different kinds of data generating process are used. The results show that the Wald test overrejects the null hypothesis both with and without the spillover effect, and that the overrejection in the latter case is more severe in larger samples. The size properties of the WW test are satisfactory when there is spillover between the variables. Only when there is feedback in the variance is the size of the WW test slightly affected. The Wald test is shown to have higher power than the WW test when the errors follow a GARCH(1,1) process without a spillover effect. When there is spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.

  • 24.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Nationalekonomi och Statistik.
    The Robustness of the RESET Test to Non-normal Error Terms2007In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 30, no 4, p. 393-408Article in journal (Refereed)
  • 25.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Nationalekonomi och Statistik.
    Sjölander, Per
    Jönköping University.
    The Effect of the GARCH(1,1) on the Granger Causality Test in Stable VAR Models2007In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 6, no 2, article id 12Article in journal (Refereed)
    Abstract [en]

    Using Monte Carlo methods, the properties of Granger causality test in stable VAR models are studied under the presence of different magnitudes of GARCH effects in the error terms. Analysis reveals that substantial GARCH effects influence the size properties of the Granger causality test, especially in small samples. The power functions of the test are usually slightly lower when GARCH effects are imposed among the residuals compared with the case of white noise residuals.

  • 26.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Nationalekonomi och Statistik.
    Sjölander, Pär
    Jönköping University.
    An Examination of the Robustness of the Vector Autoregressive Granger-Causality Test in the Presence of GARCH and Variance Shifts2007In: International Review of Business Research Papers, ISSN 1837-5685, Vol. 3, no 6, p. 280-296Article in journal (Refereed)
    Abstract [en]

    The properties of the Granger-causality test in stationary and stable Vector Autoregressive (VAR) models are studied with different types of volatility processes imposed on the unconditional variance. For this test, it is examined how the size and power properties are affected by different magnitudes of GARCH processes and by structural shifts in the volatility. The study has been conducted by means of Monte Carlo simulations for different sample sizes. Our analysis reveals that substantial GARCH effects influence the size properties of the Granger-causality test, especially in small samples. The power functions of the test are usually slightly lower in the presence of GARCH disturbances compared to the case of white noise residuals. When a structural variance break is imposed, the size problem is rather severe, and the power functions are lower compared to the case with the pure GARCH processes.

  • 27.
    Mantalos, Panagiotis
    et al.
    Lund University.
    Zografos, Konstantinos
    University of Ioannina.
    Interval estimation for a binomial proportion: a bootstrap approach2008In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 78, no 12, p. 1249-1263Article in journal (Refereed)
    Abstract [en]

    This paper discusses the classic but still current problem of interval estimation of a binomial proportion. Bootstrap methods are presented for constructing such confidence intervals in a routine, automatic way. Three confidence intervals for a binomial proportion are compared and studied by means of a simulation study, namely: the Wald confidence interval, the Agresti–Coull interval and the bootstrap-t interval. A new confidence interval, the Agresti–Coull interval with bootstrap critical values, is also introduced and its good behaviour related to the average coverage probability is established by means of simulations.

  • 28.
    Shukur, Ghazi
    et al.
    Göteborg University.
    Mantalos, Panagiotis
    Lund University.
    A Simple Investigation of the Granger-Causality Test in Integrated-Cointegrated VAR Systems2000In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 27, no 8, p. 1021-1031Article in journal (Refereed)
    Abstract [en]

    The size and power of various generalization tests for the Granger-causality in integrated-cointegrated VAR systems are considered. By using Monte Carlo methods, properties of eight versions of the test are studied in two different forms, the standard form and the modified form by Dolado & Lütkepohl (1996) in a study confined to properties of the Wald test only. In their study as well as in ours, both the standard and the modified Wald tests are shown to perform badly especially in small samples. We find, however, that the corrected LR tests exhibit correct size even in small samples. The power of the test is higher when the true VAR(2) model is estimated, and the modified test loses information by estimating the extra coefficients. The same is true when considering the power results in the VAR(3) model, and the power of the tests is somewhat lower than those in the VAR(2).

  • 29.
    Shukur, Ghazi
    et al.
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Jönköping University.
    Mantalos, Panagiotis
    Lund University.
    Size and Power of the RESET Test as Applied to Systems of Equations. A Bootstrap Approach2004In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 3, no 2, p. 370-385Article in journal (Refereed)
    Abstract [en]

    The size and power of various generalization of the RESET test for functional misspecification are investigated, using the “Bootsrap critical values”, in systems ranging from one to ten equations. The properties of 8 versions of the test are studied using Monte Carlo methods. The results are then compared with another study of Shukur and Edgerton (2002), in which they used the asymptotic critical values instead and found that in general only one version of the tests works well regarding size properties. In our study, when applying the bootstrap critical values, we find that all the tests exhibits correct size even in large systems. The power of the test is low, however, when the number of equations grows and the correlation between the omitted variables and the RESET proxies is small.

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