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Mantalos, Panagiotis
Publications (10 of 13) Show all publications
Mantalos, P. (2015). Greek debt Crisis: The "@-euro" a New Possible Solution to the Greek Debt Crisis. International Journal of Financial Crisis and Black Money, 1(1), 1-6, Article ID Mgmt-109.
Open this publication in new window or tab >>Greek debt Crisis: The "@-euro" a New Possible Solution to the Greek Debt Crisis
2015 (English)In: International Journal of Financial Crisis and Black Money, Vol. 1, no 1, p. 1-6, article id Mgmt-109Article in journal (Refereed) Published
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!

Place, publisher, year, edition, pages
Delhi, India: Cloud Publications, 2015
Keywords
Austerity, Government Budget, “@-euro”
National Category
Economics
Research subject
Economics; Statistics
Identifiers
urn:nbn:se:oru:diva-43988 (URN)
Available from: 2015-03-31 Created: 2015-04-01 Last updated: 2019-04-08Bibliographically approved
Javed, F. & Mantalos, P. (2015). Sensitivity of the causality in variance tests to GARCH(1,1) processes. Chilean Journal of Statistics, 6(1), 49-65
Open this publication in new window or tab >>Sensitivity of the causality in variance tests to GARCH(1,1) processes
2015 (English)In: Chilean Journal of Statistics, ISSN 0718-7912, E-ISSN 0718-7920, Vol. 6, no 1, p. 49-65Article in journal (Refereed) Published
Abstract [en]

This paper studies the impact of a number of volatile data sets on volatility spillover tests. We investigate a type of data generating process, AR(1)-GARCH(1,1), with an extensive set of Monte Carlo simulations. It is found that causation pattern, due to causality between two series, is influenced by the intensity of volatility clustering. Two testing procedures are applied for testing causality in the variance. We notice a severe size and power distortion when the clustering parameter is high and when the process is near integration. Furthermore, whenever there is a severe size distortion, there is a serial autocorrelation in the standardized residuals. This is seen when the asymptotic distribution of the statistics is used to define a critical region. So, instead of relying on the asymptotic distribution, we calculate the percentiles of the test statistic with the null hypothesis of no spillover effect and use them as a critical region for both size and power. We observe a significant improvement in the results.

Keywords
Causality, GARCH, Spillover, Volatility
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:oru:diva-54702 (URN)000360110300004 ()
Available from: 2017-01-13 Created: 2017-01-13 Last updated: 2017-11-08Bibliographically approved
Hultkrantz, L., Krüger, N. & Mantalos, P. (2014). Risk-adjusted long-term social rates of discount for transportation infrastructure investment. Research in Transportation Economics, 47, 70-81
Open this publication in new window or tab >>Risk-adjusted long-term social rates of discount for transportation infrastructure investment
2014 (English)In: Research in Transportation Economics, ISSN 0739-8859, E-ISSN 1875-7979, Vol. 47, p. 70-81Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2014
Keywords
Cost-benefit analysis, Rate of interest, Term structure, Risk, Ramsey equation
National Category
Economics
Research subject
Economics
Identifiers
urn:nbn:se:oru:diva-38641 (URN)10.1016/j.retrec.2014.09.020 (DOI)000349567700008 ()2-s2.0-84913554418 (Scopus ID)
Available from: 2014-11-15 Created: 2014-11-15 Last updated: 2017-12-05Bibliographically approved
Hultkrantz, L., Andersson, L. & Mantalos, P. (2014). Stumpage prices in Sweden 1909-2012: Testing for non-stationarity. Journal of Forest Economics, 20(1), 33-46
Open this publication in new window or tab >>Stumpage prices in Sweden 1909-2012: Testing for non-stationarity
2014 (English)In: Journal of Forest Economics, ISSN 1104-6899, E-ISSN 1618-1530, Vol. 20, no 1, p. 33-46Article in journal (Refereed) Published
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. (C) 2013 Department of Forest Economics, Swedish University of Agricultural Sciences, Lima Published by Elsevier GmbH. All rights reserved.

Place, publisher, year, edition, pages
Jena: Urban & Fischer, 2014
Keywords
Roundwood, Timber, Natural-resource rents, Unit root
National Category
Economics and Business
Research subject
Business Studies
Identifiers
urn:nbn:se:oru:diva-34643 (URN)10.1016/j.jfe.2013.07.003 (DOI)000332191000003 ()2-s2.0-84893806898 (Scopus ID)
Available from: 2014-04-09 Created: 2014-04-09 Last updated: 2017-10-18Bibliographically approved
Javed, F. & Mantalos, P. (2013). GARCH-Type Models and Performance of Information Criteria. Communications in statistics. Simulation and computation, 42(8), 1917-1933
Open this publication in new window or tab >>GARCH-Type Models and Performance of Information Criteria
2013 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 42, no 8, p. 1917-1933Article in journal (Refereed) Published
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.

Keywords
GARCH, Leverage, Spillover, Volatility, Primary 62J02, Secondary 65C05, 65C60
National Category
Economics and Business
Research subject
Economics
Identifiers
urn:nbn:se:oru:diva-34330 (URN)000314352500015 ()
Note

DOI 10.1080/03610918.2012.683924

Available from: 2014-03-14 Created: 2014-03-14 Last updated: 2018-05-22Bibliographically approved
Mantalos, P. & Karagrigoriou, A. (2012). Bootstrapping the augmented Dickey-Fuller test for unit root using the MDIC. Journal of Statistical Computation and Simulation, 82(3), 431-443
Open this publication in new window or tab >>Bootstrapping the augmented Dickey-Fuller test for unit root using the MDIC
2012 (English)In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 82, no 3, p. 431-443Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Taylor & Francis, 2012
Keywords
model selection, time series, bootstrap
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:oru:diva-40399 (URN)10.1080/00949655.2010.539219 (DOI)000302056900007 ()2-s2.0-84858124135 (Scopus ID)
Available from: 2015-01-08 Created: 2015-01-08 Last updated: 2017-12-05Bibliographically approved
Jentsch, C., Kreiss, J. P., Mantalos, P. & Paparoditis, E. (2012). Hybrid bootstrap aided unit root testing. Computational statistics (Zeitschrift), 27(4), 779-797
Open this publication in new window or tab >>Hybrid bootstrap aided unit root testing
2012 (English)In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 27, no 4, p. 779-797Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2012
Keywords
Hybrid bootstrap; Sieve bootstrap; Unit root testing; ADF tests
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:oru:diva-22938 (URN)10.1007/s00180-011-0290-0 (DOI)000310379900010 ()2-s2.0-84868343332 (Scopus ID)
Available from: 2012-05-23 Created: 2012-05-23 Last updated: 2018-05-08Bibliographically approved
Mantalos, P., Mattheou, K. & Karagrigoriou, A. (2010). An Improved Divergence Information Criterion for the Determination of the Order of an AR Process. Communications in statistics. Simulation and computation, 39(5), 865-879
Open this publication in new window or tab >>An Improved Divergence Information Criterion for the Determination of the Order of an AR Process
2010 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 39, no 5, p. 865-879Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Taylor & Francis, 2010
Keywords
AR process, Information criterion, Measure of divergence, Model selection, 62M10, 62F07, 91B84, 94A15
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:oru:diva-40400 (URN)10.1080/03610911003650391 (DOI)000277568500001 ()2-s2.0-77952391452 (Scopus ID)
Available from: 2015-01-08 Created: 2015-01-08 Last updated: 2017-12-05Bibliographically approved
Mantalos, P., Mattheou, K. & Karagrigoriou, A. (2010). Forecasting ARMA models: a comparative study of information criteria focusing on MDIC. Journal of Statistical Computation and Simulation, 80(1), 61-73
Open this publication in new window or tab >>Forecasting ARMA models: a comparative study of information criteria focusing on MDIC
2010 (English)In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 80, no 1, p. 61-73Article in journal (Refereed) Published
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).

Place, publisher, year, edition, pages
Taylor & Francis, 2010
Keywords
ARMA process, information criterion, model selection, MDIC, NMSFE
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:oru:diva-40402 (URN)10.1080/00949650802464137 (DOI)000273913800005 ()2-s2.0-77649139313 (Scopus ID)
Available from: 2015-01-08 Created: 2015-01-08 Last updated: 2018-04-24Bibliographically approved
Mantalos, P. & Shukur, G. (2010). The effect of spillover on the Granger causality test. Journal of Applied Statistics, 37(9), 1473-1486
Open this publication in new window or tab >>The effect of spillover on the Granger causality test
2010 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 37, no 9, p. 1473-1486Article in journal (Refereed) Published
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, that is, 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 processes are used. The results show that the Wald test over-rejects the null hypothesis both with and without the spillover effect, and that the over-rejection 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 a spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.

Place, publisher, year, edition, pages
Routledge, 2010
Keywords
causality in variance, GARCH, Granger causality, volatility spillover
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:oru:diva-40401 (URN)10.1080/02664760903046094 (DOI)000281652200004 ()2-s2.0-77956415698 (Scopus ID)
Available from: 2015-01-08 Created: 2015-01-08 Last updated: 2018-04-24Bibliographically approved
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