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  • 1.
    Ander, Malin
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
    Grönqvist, Helena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
    Cernvall, Martin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
    Engvall, Gunn
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics.
    Hedström, Mariann
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Caring Sciences.
    Ljungman, Gustaf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, Pediatrics.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Mattsson, Elisabet
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
    von Essen, Louise
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Clinical Psychology in Healthcare.
    Development of health-related quality of life and symptoms of anxiety and depression among persons diagnosed with cancer during adolescence: a 10-year follow-up study2016In: Psycho-Oncology, ISSN 1057-9249, E-ISSN 1099-1611, Vol. 25, no 5, p. 582-589Article in journal (Refereed)
    Abstract [en]

    Objective: The main aim was to investigate the development of health-related quality of life (HRQOL) and symptoms of anxiety and depression in a cohort diagnosed with cancer during adolescence from shortly after up to 10 years after diagnosis.

    Methods: Participants (n = 61) completed the SF-36 and the HADS shortly; six, 12, and 18 months; and two, three, four, and 10 years (n = 28) after diagnosis. Polynomial change trajectories were used to model development.

    Results: Polynomial change trajectories showed an initial increase which abated over time into a decrease which abated over time for the SF-36 subscales Mental Health and Vitality; an initial decline which abated over time into an increase for HADS anxiety; and an initial decline which abated over time into an increase which abated over time for HADS depression. The SF-36 mental component summary showed no change from two to 10 years after diagnosis whereas the SF-36 physical component summary showed an increase from two years after diagnosis which declined over time. Ten years after diagnosis 29% reported possible anxiety.

    Conclusions: Development of HRQOL and symptoms of anxiety and depression appears to be nonlinear among persons diagnosed with cancer during adolescence. Well into permanent survivorship an increase in symptoms of anxiety is shown and approximately a third of the participants report possible anxiety. The findings indicate the need for: studies designed to pinpoint the times of highest psychological risk, clinical follow-up focusing on psychological problems, and development of effective psychological interventions for survivors of adolescent cancer

  • 2.
    Andersson, Jonas
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Lyhagen, Johan
    A long memory panel unit root test: PPP revisited1999Report (Other academic)
  • 3. Andersson, Michael
    et al.
    Eklund, Bruno
    Lyhagen, Johan
    Uppsala University.
    A Simple Linear Time Series Model with Misleading Nonlinear Properties1999In: Economics Letters, Vol. 65, no 3, p. 281-284Article in journal (Refereed)
  • 4.
    Berg, Lennart
    et al.
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Economics.
    Lyhagen, Johan
    Department of Information Science.
    Short and long run dependence in Swedish stock returns1998In: Applied Financial Economics, Vol. 8, p. 435-443Article in journal (Refereed)
  • 5. Jacobson, Tor
    et al.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Larsson, Rolf
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Nessén, Marianne
    Inflation, Exchange Rates and PPP in a Multivariate Panel Cointegration Model2008In: Econometrics Journal, ISSN 1368-4221, E-ISSN 1368-423X, Vol. 11, no 1, p. 58-79Article in journal (Refereed)
    Abstract [en]

    New multivariate panel cointegration methods are used to analyze nominal exchange rates and prices in four major economies in Europe: France, Germany, Italy and the United Kingdom for the post-Bretton Woods period. We test for purchasing power parity (PPP) between these four countries and find that the theoretical PPP relationship does not hold. However, the estimated unrestricted relationship is found to be remarkably close to the theoretical one (1, -1.5, 0.9 instead of 1, -1,1). Relevant asymptotic results are stated, proved, and evaluated using Monte Carlo simulations. The asymptotic results are general and may hence be used in similar empirical contexts using the same model structure. Parametric bootstrap inference is used in order to deal with test size distortions.

  • 6.
    John, Östh
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Social and Economic Geography.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Reggiani, Aura
    Department of Economics, University of Bologna, Italy..
    A new way of determining distance decay parameters in spatial interaction models with application to job accessibility analysis in Sweden2016In: European Journal of Transport and Infrastructure Research, ISSN 1567-7133, E-ISSN 1567-7141, Vol. 16, no 2, p. 344-362Article in journal (Refereed)
    Abstract [en]

    In this paper we explore and compare various techniques for the calculation of distance decay parameters which are estimated using statistical methods with half-life decay parameters which are derived mathematically. Half-life models appear to be a valid alternative to traditional spatial interaction models, especially in the presence of spatially highly disaggregate data. Our results indicate that Half-life models are more accurate for the construction of decay parameters than are unconstrained spatial interaction models in 'medium' sized datasets but not as accurate as doubly-constrained models. However, using highly detailed and disaggregate datasets Half-life models may be viable alternatives to doubly-constrained spatial interaction models as the latter will be difficult to estimate when the number of origins and destinations increase. In addition, Half-life models rise in accuracy with increasing degrees of disaggregation due to reductions of systematic errors between observed individual level commuting distance and modelled distances between origins and destinations.

    In sum, our findings are as follows. First, since unconstrained and doubly-constrained spatial interaction models become increasingly difficult to estimate and/or less accurate to use compared to Half-life models as the spatial disaggregation increases choice of decay parameter estimation model should be considered in relation to level of disaggregation. Secondly, Half-life models are not affected by the systematic errors observed in the statistically derived models. Finally, using Half-life models for the estimation of decay parameters is simple which may make it easy to employ among practitioners lacking skills or computer means for the estimation of more complex statistically derived models.

  • 7.
    Larsson, Rolf
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    Inference in panel cointegration models with long panels2007Article in journal (Refereed)
    Abstract [en]

    This article presents a general likelihood-based framework for inference in panel vector autoregressive (VAR) models with cointegration restrictions. The cointegrating relationships are restricted to each cross section while the rest of the model is unrestricted. The homogeneous restriction of common cointegrating space is also considered. Asymptotic distributions of parameter estimators and the test statistics for the cointegrating rank and the homogeneous restriction are derived. The asymptotic distribution for the cointegrating rank is shown to be the convolution of the standard distribution of the trace statistic and the X 2 distribution. The homogeneous restriction test statistic is asymptotically chi(2). A Monte Carlo simulation investigates the small-sample properties of the two tests. The empirical size of the test for the cointegrating rank is well above the nominal. A Bartlett-corrected test statistic is shown to have size very close to the nominal. We give an empirical example for a consumption model, including consumption, income, and inflation as well as considering the monetary exchange rate model of Groen and Kleibergen.

  • 8.
    Larsson, Rolf
    et al.
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Lyhagen, Johan
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Löthgren, Mickael
    Likelihood based cointegration tests in heterogenous panels2001In: Econometrics Journal, Vol. 4, p. 109-142Article in journal (Refereed)
  • 9.
    Larsson, Rolf
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Westerlund, Joakim
    Likelihood Ratio Tests for a Unit Root in Panels with Random Effects2016In: Statistics (Berlin), ISSN 0233-1888, E-ISSN 1029-4910Article in journal (Refereed)
    Abstract [en]

    Because of the fixed heterogeneity of their models, most panel unit root tests impose restrictions on the rate at which the number of time periods, T, and the number of  rosssection units, N, go to infinity. A common example of such a restriction is N/T → 0, which in practice means that T >> N, a condition that is not always met. In the current paper the heterogeneity is given a parsimonious random effects specification, which is used as a basis for developing a new likelihood ratio test for a unit root. The asymptotic analysis shows that the new test is valid for all (N, T) expansion paths satisfying N/T5 0, which represents a substantial improvement when compared to the existing fixed effects literature.

  • 10.
    Luo, Hao
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Yang-Wallentin, Fan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Analysis of Ordinal Variables Using Rank-Based Polychoric CorrelationManuscript (preprint) (Other academic)
  • 11.
    Lyhagen, Johan
    Uppsala University.
    A matrix evaluation of the moving-average representation1997In: ECONOMICS LETTERS, ISSN 0165-1765, Vol. 55, no 2, p. 179-183Article in journal (Refereed)
    Abstract [en]

    In this paper we introduce a simple equation system, the solution of which is the moving average representation. The proposed solution is easy to derive since the equation system is recursive. We exemplify with the derivation of the moving average represe

  • 12.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    A method to generate multivariate data with the desired moments2008In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 37, no 10, p. 2063-2075Article in journal (Refereed)
    Abstract [en]

    We show how it is possible to generate multivariate data which has moments arbitrary close to the desired ones. They are generated as linear combinations of variables with known theoretical moments. It is shown how to derive the weights of the linear combinations in both the univariate and the multivariate setting. The use in bootstrapping is discussed and the method is exemplified with a Monte Carlo simulation where the importance of the ability of generating data with control of higher moments is shown.

  • 13.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    A note on the representation of E (x⊗xx') and E (xx'⊗xx') for the random vector x2012In: Statistical papers, ISSN 0932-5026, E-ISSN 1613-9798, Vol. 53, no 3, p. 697-701Article in journal (Refereed)
    Abstract [en]

    In this paper we consider E(x⊗xx') and E( xx'⊗xx') for a random vector x where x_i has existing moments up to the fourth order and where the higher moments may depend on i. This extends previous results which assumed a common higher moment and E(xx')=I.

  • 14.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Estimating Nonlinear structural models: EMM and the Kenny-Judd model2007In: Structural Equation Modeling, ISSN 1070-5511, E-ISSN 1532-8007, Vol. 14, no 3, p. 391-403Article in journal (Refereed)
    Abstract [en]

    The estimation of nonlinear structural models is not trivial. One reason for this is that a closed form solution of the likelihood may not be feasible or does not exist. We propose to estimate nonlinear structural models using the efficient method of moments, as generating data according to the models is often very easy. A simulation study of the interaction model of Kenny-Judd shows promising results, for example, the bias of the parameter for the interaction effect is less for the efficient method of moments compared to quasi-maximum likelihood (QML) and characteristic function estimator (CFE) (Blom & Christoffersson 2001) and comparable to latent moderated structural equations (LMS) (Schermelleh-Engel, Klein, & Moosbrugger, 1998).

  • 15.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    Identification of the order of a fractionally differenced ARMA model1999In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 14, no 2, p. 161-169Article in journal (Refereed)
    Abstract [en]

    Long term dependence in time series can be modelled by fractionally integrated ARMA (ARFIMA) models. For an ARFIMA process it is however impossible to identify the order of the short memory polynomials by inspection of the autocorrelation and partial autocorrelation functions. Instead information criteria such as AIC, BIC and HQIC are used to identify the order. This paper investigates the performance of the three information criteria when identifying the order in an ARFIMA model. The impression is that BIC outperforms AIC and HQIC, at least for the ARFIMA models used in this simulation. The overall performance of the information criteria, however, is poor for mixtures of AR and MA processes. Introducing long memory increases the likelihood of identifying the correct orders.

  • 16.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    Starting values in estimation of cointegrating vectors with restrictions2001In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 8, no 8, p. 521-524Article in journal (Refereed)
  • 17.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    The effect of precautionary saving on consumption in Sweden2001In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 33, no 5, p. 673-681Article in journal (Refereed)
    Abstract [en]

    Uncertainty concerning future income lowers consumption. This is often called the precautionary demand for savings. In this paper the existence of precautionary savings. In this paper the existence of precautionary saving is investigated using Swedish data for the years 1973–1992. As there are no variables for consumers' uncertainty a proxy is used. Assuming an underlying distribution of attitudinal data, a variance series is derived. Including the proxy in different specifications of the consumption function, indication of precautionary saving can be found. As a result, no uncertainty would raise consumption by 4.9%.

  • 18.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    The Exact Covariance Matrix of Dynamic Models with Latent Variables2005In: Statistics and Probability Letters, ISSN 0167-7152, E-ISSN 1879-2103, Vol. 75, no 2, p. 133-139Article in journal (Refereed)
  • 19.
    Lyhagen, Johan
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Statistik.
    The seasonal KPSS statistic2006In: Economics Bulletin, Vol. 3, p. 1-9Article in journal (Refereed)
  • 20.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Why not use standard panel unit root test for testing PPP2008In: Economics Bulletin, ISSN 1545-2921, E-ISSN 1545-2921, Vol. 3, no 26, p. 1-11Article in journal (Refereed)
  • 21.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Ekberg, Stefan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Eidestedt, Richard
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Beating the VAR: Improving Swedish GDP Forecasts Using Error and Intercept Corrections2015In: Journal of Forecasting, ISSN 0277-6693, E-ISSN 1099-131X, Vol. 34, no 5, p. 354-363Article in journal (Refereed)
    Abstract [en]

    This paper examines the forecast accuracy of an unrestricted vector autoregressive (VAR) model for GDP, relative to a comparable vector error correction model (VECM) that recognizes that the data are characterized by co-integration. In addition, an alternative forecast method, intercept correction, is considered for further comparison. Recursive out-of-sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperforms the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, whereas there is no such indication when applied to the VAR model. For certain forecast horizons there is a significant difference in forecast ability between the intercept corrected VECM compared to the VAR model.

  • 22.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Ekberg, Stefan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Eidestedt, Richard
    Beating the VAR: Improving Swedish GDP forecasts using error and intercept correctionsIn: Journal of Forecasting, ISSN 0277-6693, E-ISSN 1099-131XArticle in journal (Refereed)
    Abstract [en]

    This paper examines the forecast accuracy of an unrestricted Vector Autoregressive (VAR) model for GDP, relative to a comparable Vector Error Correction model (VECM) that recognizes that the data is characterized by co-integration. In addition, an alternative forecast method, Intercept Correction, is considered for further comparison. Recursive out-of-sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperform the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, while there is no such indication when applied to the VAR model. For certain forecast horizons there is a signicant di erence in forecast ability between the intercept corrected VECM compared to the VAR model.

  • 23.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Kraus, Katrin
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    The small sample performance of estimators of the standard errors of structural equation models2013In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 83, no 3, p. 458-471Article in journal (Refereed)
    Abstract [en]

    n this paper, we compare five asymptotically, under a correctly specified likelihood, equivalent estimators of the standard errors for parameters in structuralequation models. The estimators are evaluated under different conditions regarding (i)sample size, varying between N=50 and 3200, (ii) distributional assumption of the latent variables and the disturbance terms, namely normal, and heavy tailed (t), and (iii) thecomplexity of the model. For the assessment of the five estimators we use overallperformance, relative bias, MSE and coverage of confidence intervals. The analysis reveals substantial differences in the performance of the five asymptotically equalestimators. Most diversity was found for t distributed, i.e. heavy tailed, data.

  • 24.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Kraus, Katrin
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    The small sample performance of estimators of the standard errors of structural equation models2013In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 83, no 3, p. 458-471Article in journal (Refereed)
    Abstract [en]

    n this paper, we compare five asymptotically, under a correctly specified likelihood, equivalent estimators of the standard errors for parameters in structuralequation models. The estimators are evaluated under different conditions regarding (i)sample size, varying between N=50 and 3200, (ii) distributional assumption of the latent variables and the disturbance terms, namely normal, and heavy tailed (t), and (iii) thecomplexity of the model. For the assessment of the five estimators we use overallperformance, relative bias, MSE and coverage of confidence intervals. The analysis reveals substantial differences in the performance of the five asymptotically equalestimators. Most diversity was found for t distributed, i.e. heavy tailed, data.

  • 25.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science.
    Löf, Mårten
    On seasonal error correction when the processes include different numbers of unit roots2003In: Journal of Forecasting, ISSN 0277-6693, E-ISSN 1099-131X, Vol. 22, no 5, p. 377-389Article in journal (Refereed)
    Abstract [en]

    We propose a seasonal cointegration model (SECM) for quarterly data which includes variables with different numbers of unit roots and thus needs to be transformed in different ways in order to yield stationarity. A Monte Carlo simulation is carried out to investigate the consequences of specifying a SECM with all variables in annual diffrerences in this situation. The SECM in annual differences is compared to the correctly specified model. Pre-testing for unit roots using two different approaches, and where the models are specified according to the unit root test results, is also considered. The forecast mean squared error criterion and certain parameter estimation results indicate that, in practice, a cointegration model where all variables are transformed with the annual difference filter is more robust than one obtained by pre-testing for a smaller number of unit roots. The second-best choice when the true model is not known and when the aim is to forecast, is an ordinary VAR model also in annual differences.

  • 26.
    Lyhagen, Johan
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Rickne, Johanna
    Income inequality between Chinese regions: newfound harmony or continued discord?2014In: Empirical Economics, ISSN 0377-7332, E-ISSN 1435-8921, Vol. 47, no 1, p. 93-110Article in journal (Refereed)
    Abstract [en]

    This paper develops an improved test of economic convergence or divergence using time series methods by introducing nonlinear trends in the form of logarithmic trend functions into the vector error correction model. The usefulness of the method is illustrated in an analysis of the growth pattern between Chinese regions in 1952-2007. Comparing all combinations of regional pairs, the analysis yields support for economic divergence in roughly half of the cases. In the other half, we instead find that regions have grown while maintaining stable income differences. As such, the results show the co-existence of divergence and conditional convergence among China's regions.

  • 27. Löf, Mårten
    et al.
    Lyhagen, Johan
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Forecasting performance of seasonal cointegration models2002In: International Journal of Forecasting, Vol. 18, p. 31-44Article in journal (Refereed)
  • 28.
    Oke, Thimothy
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Lyhagen, Johan
    Small-sample properties of some tests for unit root with data-based choice of the degree of augmentation1999In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 30, no 4, p. 457-469Article in journal (Refereed)
    Abstract [en]

    In the augmented Dickey-Fuller (ADF) regression one usually decides on the level of the "augmentation" prior to the performing of unit root test. This is a purely data-dependent method that uses either some information criteria or some sequential test of significance on parameter estimates. Contrary to earlier beliefs, our analyses reveal that the presence and/or absence of a drift and a time trend in the data generating process has a remarkable effect on the behaviour of the subsequent tests for unit root.

  • 29.
    Petra, Ornstein
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Asymptotic properties of Spearman's rank correlation for variables with finite support2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 1, article id e0145595Article in journal (Refereed)
    Abstract [en]

    The asymptotic variance and distribution of Spearman's rank correlation have previously been known only under independence. For variables with finite support, [1] has derived the population version of Spearman's rank correlation. Using her results, we show convergence to a normal distribution irrespectively of dependence, and derive the asymptotic variance. A small simulation study indicates that the asymptotic properties are of practical importance.

  • 30.
    Wei, Jianxin
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Lyhagen, Johan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Bootstrap versus Bartlett type correction of the Dickey-Fuller test2013Report (Other academic)
1 - 30 of 30
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