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  • 1.
    Brandt, Daniel
    et al.
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Heldt, Tobias
    Dalarna University, School of Technology and Business Studies, Economics.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Potential research areas for big data in tourism2016In: Proceedings of the IFITTtalk@Östersund Workshop on Big Data & Business Intelligence in the Travel & Tourism Domain / [ed] Fuchs, M., Lexhagen, M. & Höpken, W., 2016Conference paper (Refereed)
  • 2.
    Brandt, Daniel
    et al.
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Education and careers in the Swedish tourism sector: How important is education for building a successful career?2015Conference paper (Refereed)
  • 3. Fredman, P.
    et al.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Income elasticity of demand for tourism at Fulufjället National Park2018In: Tourism Economics, ISSN 1354-8166, E-ISSN 2044-0375, Vol. 24, no 1, p. 51-63Article in journal (Refereed)
  • 4.
    Fredman, Peter
    et al.
    Mittuniversitetet.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Besök och besökare i Fulufjällets nationalpark sommaren 2014 (med jämförelser åren 2001 och 2003)2015Report (Other academic)
  • 5.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A finite sample improvement of the fixed effects estimator applied to technical inefficiency2015In: Journal of Productivity Analysis, ISSN 0895-562X, E-ISSN 1573-0441, Vol. 43, no 1, p. 29-46Article in journal (Refereed)
    Abstract [en]

    The fixed effects (‘FE’) estimator of technical inefficiency performs poorly when N (the ’number of firms’) is large and T (the ‘number of time observations’) is small. We propose kernel estimators, which includes the FE estimator as a special case. In terms of criteria based on collective conditional ‘mean square error’, it is demonstrated that some kernel estimators are more efficient than the FE estimators of firm effects and inefficiencies in finite sample settings. Monte Carlo simulations support our theoretical findings, and we use an empirical example to show how FE estimation and kernel estimation lead to very different conclusions about technical inefficiency among Indonesian rice farmers.

  • 6.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A finite sample improvement of the fixed effects estimator: applied to technical infficiency2013Report (Other academic)
    Abstract [en]

    The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

  • 7.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A Note on Proxy Variables and Instrument Variable Regression2015Report (Other academic)
    Abstract [en]

    This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

  • 8.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015Report (Other academic)
  • 9.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015In: Economics Letters, ISSN 0165-1765, E-ISSN 1873-7374, Vol. 137, p. 62-69Article in journal (Refereed)
    Abstract [en]

    About a decade ago William H. Greene introduced the so-called ‘True fixed effects’ (TFE) model, which is intended to discriminate between heterogeneity and efficiency in stochastic frontier analysis. We would say that the TFE model has had a huge impact on applied stochastic frontier analysis. One problem with the original TFE estimator, is its inconsistency in cases with finite time observations, at least for the variance components. For the normal-half-normal model, this problem was solved by Chen et al. (2014) based on maximum likelihood estimation of the within-transformed model. In this study, we illustrate the possibilities offered by method of moments estimation. This approach is more flexible than the MLE proposed by Chen et al. (2014), since the method of moments estimators are not so closely dependent on the distributional assumptions and do not hinge on an explicit distribution of the random error. We only assume symmetry, as well as a fixed fourth-order cumulant for more complicated models. Greene’s methodology can, and has been, generalized to other models than the normal-half-normal model. However, the method of moments estimators proposed here are consistent.

  • 10.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Modified fixed effects estimation of technical inefficiency2016In: Journal of Productivity Analysis, ISSN 0895-562X, E-ISSN 1573-0441, Vol. 46, no 1, p. 83-86Article in journal (Refereed)
    Abstract [en]

    We consider method-of-moments fixed effects (FE) estimation of technical inefficiency. When dealing with a large number of cross-sectional observations, N, it is possible to obtain consistent moment estimators of the inefficiency distribution. It is well known that the classical FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. The method-of-moments FE estimators do not suffer from this type of bias in large-N settings. The proposed methodology bridges classical FE and maximum likelihood estimation, leading to a reduction in bias without making the random effects assumption.

  • 11.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciencies.
    Modified Fixed Effects Estimation of Technical Inefficiency2013Report (Other academic)
    Abstract [en]

    We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

  • 12.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Slutrapport om kväveoxidavgiftens effekt på kväveoxidutsläppen2015Report (Other academic)
  • 13.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    The true fixed effects model with non-stationary inefficiency distribution2015Report (Other academic)
  • 14.
    Wikström, Daniel
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Heldt, Tobias
    Dalarna University, School of Technology and Business Studies, Economics.
    A business intelligence solution of handling traveling data with R and Shiny2016In: Proceedings of the IFITTtalk@Östersund Workshop on Big Data & Business Intelligence in the Travel & Tourism Domain / [ed] Fuchs, M., Lexhagen, M. & Höpken, W., 2016Conference paper (Refereed)
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  • de-DE
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