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  • 1.
    Lindmark, Magnus
    et al.
    Department of Geography and Economic History, Umeå University.
    Nguyen Thu, Huong
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences. Division of Mathematical Statistics, Department of Mathematics, Stockholm University.
    Stage, Jesper
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Weak support for weak sustainability: Genuine savings and long-term wellbeing in Sweden, 1850 – 20002018In: Ecological Economics, ISSN 0921-8009, E-ISSN 1873-6106, Vol. 145, p. 339-345Article in journal (Refereed)
    Abstract [en]

    We study genuine savings as an indicator of long-term welfare for Sweden for the period 1850 to 2000. Sweden has developed long series of comprehensive ‘green’ national accounts for this entire period and is, therefore, interesting as a testing ground for the hypotheses linking green accounting and sustainability. We find support for the weakest of the hypotheses in the theoretical literature on weak sustainability and genuine savings, namely that genuine savings are correlated with future economic well-being. However, the stronger hypotheses in this literature are not supported: there is no one-to-one relationship between genuine savings and prosperity, there is no indication that the relationship becomes stronger for longer time horizons, or with more comprehensive savings measures. The findings suggest that genuine savings, at least as currently measured in national accounts and satellite accounts, may not be a good forward-looking indicator of future prosperity.

  • 2.
    Lindmark, Magnus
    et al.
    Department of Economic History, Umeå university, Umeå universitet.
    Stage, Jesper
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Weak support for weak sustainability: Genuine savings and long term wellbeing in Sweden, 1850 - 20002016Conference paper (Other academic)
    Abstract [en]

    In this paper, we study genuine savings as an indicator of long term welfare for Sweden for the period 1850 to 2000. Sweden has developed long series of comprehensive “green” national accounts for this entire period and is therefore interesting as a testing ground for the hypotheses linking green accounting and sustainability. We find support for the weakest of the hypotheses in the theoretical literature on weak sustainability and genuine savings, that genuine savings is correlated with future economic well-being. However, we find little support for any of the stronger hypotheses in the literature; there is no one-to-one relationship between genuine savings and prosperity, there is no indication that the relationship becomes stronger for longer time horizons, and other hypotheses linked to this literature are also rejected. The findings suggest that genuine savings, at least as currently measured in national accounts and satellite accounts, may not be a good predictor of future prosperity.

  • 3.
    Stage, Jesper
    et al.
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Lindmark, Magnus
    Department of Geography and Economic History and Centre for Environmental and Resource Economics.
    Nguyen Thu, Huong
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Nguyen, Hoang
    Department of Statistics, Universidad Carlos III de Madrid.
    What are the drivers of the Swedish sustainable development path?: New evidence from Bayesian Dynamic Linear Models2017Conference paper (Refereed)
    Abstract [en]

    In this paper, we use Swedish Genuine Savings (GS) indicators, extended to account for a wider range of impacts on natural and human capital than previous GS indicators, to study Swedish long-term sustainability. Following Ferreira et al (2008) and Greasley et al (2014), technological progress and population effect are also included in the GS measures. We introduce a new quantitative methodology to the literature on sustainable development by applying Bayesian analysis of Dynamic Linear Models (DLMs) to GS indicators. This is the first time that parameter uncertainty has been used in examining the links between GS and long term well-being, providing new empirical evidence on the driving forces that underpin Swedish sustainable development.

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    fulltext
  • 4.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    A note on the distribution of residual autocorrelations in VARMA(p,q) models2015In: Journal of Statistical and Econometric Methods, ISSN 2241-0384, E-ISSN 2241-0376, Vol. 4, no 3, p. 93-99Article in journal (Refereed)
    Abstract [en]

    This paper generalizes the distribution of residual autocovariance matrices in VARMA(p,q) models obtained previously in Hosking (1980). A new simplified version of the multivariate relation between sample correlation matrix of the errors and its residuals is also established. The modifications are effective tools for identifying and dealing with the curse of dimensionality in multivariate time series.

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    fulltext
  • 5.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Diagnostic checks in multiple time series modelling2016In: 2016 Proceedings of the International work-conference on Time Series, Granada, Spain, 2016, p. 308-315Conference paper (Refereed)
  • 6.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences. Foreign Trade University, Department of Mathematics, Hanoi, Vietnam.
    Diagnostic Checks in Multiple Time Series Modelling2017In: Advances in Time Series Analysis and Forecasting: Selected Contributions from ITISE 2016 / [ed] Ignacio Rojas, Héctor Pomares, Olga Valenzuela, Cham: Springer , 2017, p. 147-158Conference paper (Refereed)
    Abstract [en]

    The multivariate relation between sample covariance matrices of errors and their residuals is an important tool in goodness-of-fit methods. This paper generalizes a widely used relation between sample covariance matrices of errors and their residuals proposed by Hosking (J Am Stat Assoc 75(371):602–608, 1980 [6]). Consequently, the asymptotic distribution of the residual correlation matrices is introduced. As an extension of Box and Pierce (J Am Stat Assoc 65(332):1509–1526, 1970 [11]), the asymptotic distribution recommends a graphical diagnostic method to select a proper VARMA(p, q) model. Several examples and simulations illustrate the findings

  • 7.
    Thu, Huong Nguyen
    Foreign Trade University.
    Forecasting methods based on ARIMA models2004Report (Other academic)
  • 8.
    Thu, Huong Nguyen
    Universidad Carlos III de Madrid, Department of Statistics, Facultad de Ciencias Sociales y Jurıdicas, Campus de Getafe.
    Goodness-of-fit in Multivariate Time Series2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Goodness-of-fit is an important task in time series analysis. In this thesis, wepropose a new family of statistics and a new goodness-of-fit process for the wellknownmultivariate autoregressive moving average VARMA(p,q) model.Some preliminary results are studied first for an initial goodness-of-fit method.Since the residuals of the fit play an important role in identification and diagnosticchecking, relations between least squares residuals and true errors are studied. Anexplicit representation of the information matrix as a limit is also obtained.Second, we generalize a univariate goodness-of-fit process studied in Ubierna andVelilla (2007). An explicit form of the limit covariance function is presented, aswell as a characterization of its limit properties in terms of a parametric Gaussianprocess. This motivates the introduction of a new goodness-of-fit process based ona transformed correlation matrix sequence. The construction and properties of theassociated transformation matrices are investigated. We also prove the convergenceof this new process to the Brownian bridge. Thus, statistics defined as functionals of our process use a null distribution that is free of unknown parameters.Finally, simulations, comparisons, and examples of application are presented toillustrate our theoretical findings and contributions. Our proposed goodness-of-fitstatistics are shown to be quite sensitive for detecting lack of fit. They also seem tobe relatively independent of the choice of a particular lag.

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    FULLTEXT01
  • 9.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    On Multivariate Model Selection Involving Time Series of Environmental Kuznets curve2015Conference paper (Other academic)
    Abstract [en]

    This paper studies a generalized version of the relation between the sample correlation matrices of errors and their residuals. The results suggest confidence bands to select a proper multivariate time series model. Several simulations illustrate the theoretical findings. The literature of Environmental Kuznets Curve (EKC) received particular interest, however, the empirical research on the EKC has mainly used a reduced form approach. Therefore, the proposed techniques can be applied to identify the multivariate relation between economic growth, environmental degradation and population. A real data application is provided for the case of Sweden.

  • 10.
    Thu, Huong Nguyen
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    On Multivariate Model Selection Involving Time Series of Environmental Kuznets Curve2016In: International Journal of Ecological Economics and Statistics, ISSN 0973-1385, E-ISSN 0973-7537, Vol. 37, no 3, p. 20-29Article in journal (Refereed)
    Abstract [en]

    This paper studies a generalized version of the relation between the sample correlation matrices of errors and their residuals. The results suggest confidence bands to select a proper multivariate time series model. The literature of Environmental Kuznets Curve received particular interest, however, the empirical research on the Environmental Kuznets Curve has mainly used a reduced form approach. Therefore, the proposed techniques can be applied to identify the multivariate relation between economic growth, environmental degradation and population. A real data application is provided for the case of Sweden.

  • 11.
    Velilla, Santiago
    et al.
    Universidad Carlos III de Madrid, Department of Statistics, Facultad de Ciencias Sociales y Jurıdicas, Campus de Getafe.
    Thu, Huong Nguyen
    Universidad Carlos III de Madrid, Department of Statistics, Facultad de Ciencias Sociales y Jurıdicas, Campus de Getafe.
    A basic goodness-of-fit process for VARMA(p,q) models2011Report (Other academic)
    Abstract [en]

    As an extension of the univariate technique in Ubierna and Velilla (2007), we present a goodness-of-fit process for VARMA(p,q) models in which the residuals of the fit are considered. We also formulatean explicit form of the asymptotic covariance function, as well as a suitable representation of the limitprocess. More importantly, we propose a new goodness-of-fit process based on a transformed correlationmatrix sequence. The new goodness-of-fit process is proved to converge weakly to the Brownian bridge.Several simulations, comparisons, and examples are presented. These results illustrate the scope of bothour theoretical findings and contributions. Our method is shown to be sensitive to detect lack of fit.Thus, it can be considered as a useful tool tool for identifying a proper time series model.

    Download full text (pdf)
    FULLTEXT01
  • 12.
    Velilla, Santiago
    et al.
    Universidad Carlos III de Madrid, Department of Statistics, Facultad de Ciencias Sociales y Jurıdicas, Campus de Getafe.
    Thu, Huong Nguyen
    Universidad Carlos III de Madrid, Department of Statistics, Facultad de Ciencias Sociales y Jurıdicas, Campus de Getafe.
    A new goodness-of-fit process for VARMA(p,q) models: construction and empirical properties2013Report (Other academic)
    Abstract [en]

    As an extension of the univariate technique in Ubierna and Velilla (2007), we present a goodness-of-fit process for VARMA(p,q) models in which the residuals of the fit are considered. We also formulatean explicit form of the asymptotic covariance function, as well as a suitable representation of the limitprocess. More importantly, we propose a new goodness-of-fit process based on a transformed correlationmatrix sequence. The new goodness-of-fit process is proved to converge weakly to the Brownian bridge.Several simulations, comparisons, and examples are presented. These results illustrate the scope of bothour theoretical findings and contributions. Our method is shown to be sensitive to detect lack of fit.Thus, it can be considered as a useful tool tool for identifying a proper time series model.

    Download full text (pdf)
    FULLTEXT01
1 - 12 of 12
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