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  • 51. Månsson, Kristofer
    et al.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics.
    Granger Causality Test in the Presence of Spillover Effects2009In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 38, no 10, p. 2039-2059Article in journal (Refereed)
    Abstract [en]

    In this article, we investigate the effect of spillover (i.e., causality in variance) on the reliability of Granger causality test based on ordinary least square estimates. We studied eight different versions of the test both, with and without Whites heteroskedasticity consistent covariance matrix (HCCME). The properties of the tests are investigated by means of a Monte Carlo experiment where 21 different data generating processes (DGP) are used and a number of factors that might affect the test are varied. The result shows that the best choice to test for Granger causality under the presence of spillover is the Lagrange Multiplier test with HCCME.

  • 52. Månsson, Kristofer
    et al.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    On Ridge Parameters in Logistic Regression2011In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 40, no 18, p. 3366-3388Article in journal (Refereed)
  • 53. Månsson, Kristofer
    et al.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Kibria, B. M. Golam
    On Some Ridge Regression Estimators: a Monte Carlo Simulation Study Under Different Error Variances2010In: Journal of Statistics, ISSN 1684-8403, Vol. 17, no 1, p. 1-22Article in journal (Refereed)
  • 54.
    Månsson, Kristofer
    et al.
    Jönköping University.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Kibria, B. M. Golam
    Florida International University, USA.
    Performance of Some Ridge Regression Estimators for the Multinomial Logit Model2018In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 47, no 12, p. 2795-2804Article in journal (Refereed)
    Abstract [en]

    This paper considers several estimators for estimating the ridge parameter  for multinomial logit model based on the work of Khalaf and Shukur (2005), Alkhamisi, Khalaf and Shukur (2006) and  Muniz, Kibria and Shukur (2012). The mean square error (MSE) is considered as the performance criterion. A simulation study has been conducted to compare the performance of the estimators.  Based on the simulation study we found that, increasing the correlation between the independent variables and the number of regressors has negative effect on the MSE. However, when the sample size increases the MSE decreases even when the correlation between the independent variables is large. Based on the minimum MSE criterion some useful estimators for estimating the ridge parameter k are recommended for the practitioners.

  • 55.
    Månsson, Kristofer
    et al.
    Jönköping University, Sweden.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University, Sweden.
    Sjölander, Pär
    Jönköping University, Sweden.
    A New Asymmetric Interaction Ridge (AIR) Regression Method2014In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 3, p. 616-643Article in journal (Refereed)
    Abstract [en]

    Despite that interaction terms are standard tools of regression analysis, the side effects of the inclusion of these terms in models estimated by ordinary least squares (OLS) are yet not fully penetrated. The inclusion of interaction effects induces multicollinearity problems since all non-zero values are equal between the interaction term and the regressor. In this article we propose a procedure to remedy this problem by the use of new ridge regression (RR) shrinkage parameters – which we call the asymmetric interaction ridge (AIR) regression method. By means of Monte Carlo simulations we evaluate both OLS and AIR using the mean square error (MSE) performance criterion. The result from the simulation study confirms our hypothesis that AIR always should be preferred to OLS since it has a lower estimated MSE. Moreover, the advantages of our new method are demonstrated in an empirical application where positive asymmetric price transmission effects are exposed for the mortgage interest rates of Handelsbanken Stadshypotek. It is observed that the mortgage interest rates increase more fully and rapidly to an increase in the bank’s borrowing costs than to a decrease. This asymmetry is defined as positive asymmetric price transmission (APT).

  • 56.
    Månsson, Kristofer
    et al.
    Jönköping University.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Sjölander, Pär
    Jönköping University.
    A New Ridge Regression Causality Test in the Presence of Multicollinearity2014In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 2, p. 235-248Article in journal (Refereed)
    Abstract [en]

    The VAR lag structure applied for the traditional Granger causality (GC) test is always severely affected by multicollinearity due to autocorrelation among the lags. Therefore, as a remedy to this problem we introduce a new Ridge Regression Granger Causality (RRGC) test, which is compared to the GC test by means of Monte Carlo simulations. Based on the simulation study we conclude that the traditional OLS version of the GC test over-rejects the true null hypothesis when there are relatively high (but empirically normal) levels of multicollinearity, while the new RRGC test will remedy or substantially decrease this problem.

  • 57.
    Månsson, Kristofer
    et al.
    Jönköping University.
    Shukur, Ghazi
    Jönköping University.
    Sjölander, Pär
    Asymmetric Quantile Analysis of the Swedish Mortgage Price Discovery Process2013In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 45, no 21, p. 3088-3101Article in journal (Refereed)
    Abstract [en]

    Based on Swedish banking data we discover robust and significantly positive Asymmetric Price Transmission (APT) effects over all analysed regression quantiles of our mortgage interest rates, with even larger positive APT for the higher percentiles. The analysis was enabled through unique access to a Swedish bank's (SEB) own records of their true borrowing costs. Our central contribution is that there is a higher propensity for the bank to rapidly increase its mortgage interest rates for customers following an increase in its borrowing costs, compared with the propensity for the bank to decrease its customers’ mortgage rates subsequent to a corresponding borrowing cost decrease.

  • 58. Månsson, Kristofer
    et al.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Sjölander, Pär
    Testing for panel unit roots in the presence of spatial dependency2013In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 45, no 29, p. 4152-4159Article in journal (Refereed)
    Abstract [en]

    In this article, the size and power properties of the Common-factor Im, Pesaran and Shin (CIPS), Wald (W), Likelihood Ratio (LR) and Lagrange Multiplier (LM) tests are investigated when the error term follows a spatial error model. In this study, the results from the Monte Carlo simulations, first, show that the CIPS test over-estimates the nominal size. Second, the simulation results show that the empirical size of the W test approaches the nominal size quickly, while the LR and LM tests underestimate the null hypothesis in both small and moderate sample sizes. Finally, the results also show that even though the LM and LR tests under-reject the true-null hypothesis they have higher power than the W test.

  • 59.
    Månsson, Kristofer
    et al.
    Jönköping university.
    Sjölander, Pär
    Jönköping university.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping university.
    Market concentration and market power of the swedish mortgage sector: a wavelet panel efficiency analysis2018In: Studies in Nonlinear Dynamics and Econometrics, ISSN 1081-1826, E-ISSN 1558-3708, Vol. 22, no 4, article id 20160021Article in journal (Refereed)
    Abstract [en]

    Based on a panel wavelet efficiency analysis, we conclude that there is a systematic pattern of positive asymmetric price transmission inefficiencies in the interest rates of the largest Swedish mortgage lenders. Thus, there seems to be a higher propensity for mortgage lenders to swiftly increase their customers’ mortgage interest rates subsequent to an increase in its borrowing costs, than to decrease their customers’ mortgage rates subsequent to a corresponding decrease in the cost of borrowing. A unique contribution is our proposed wavelet method which enables a robust detection of positive asymmetric price transmission effects at various time-frequency scales, while simultaneously controlling for non-stationary trends, autocorrelation, and structural breaks. Since traditional time-series analysis methods essentially implies that several wavelet time scales are aggregated into one single time series, the blunt traditional error correction analysis totally failed to discover APT effects for this data set. In summary, using the wavelet method we show that even though the customers in the end finally will benefit from decreases in the mortgage lenders’ financing costs, the lenders wait disproportionally long before the customers’ mortgage rates are decreased.

  • 60.
    Salman, A. Khalik
    et al.
    Mid Sweden University.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Investigating causal relations between the GDP cycle and unemployment: data from Finland2014In: International Journal of Economics and Finance, ISSN 1916-9728, E-ISSN 1916-971X, Vol. 5, no 4, p. 118-134Article in journal (Refereed)
    Abstract [en]

    This paper investigates the causal relationship between two macroeconomic variables, the gross domestic product (GDP) cycle and unemployment, in Finland. This has been done using the vector autoregressive (VAR) model for the period Q1 1995 to Q2 2011. The goal of this study is to gather further evidence for the relationship between the GDP cycle and total, male and female unemployment individually, with special reference to Finland which is a member state of the EU, and has been part of European monetary union, since 1995. The relationship has been investigated using the Granger-causality test in accordance with Okun’s (1962) formula. The empirical facts mostly indicate the existence of a uni-directional causal relationship from the GDP cycle to unemployment. This pattern is not found to be significant when using the model for unemployment in women however. The coefficients of unemployment, total, male and female, are abstracted from the Okun’s coefficient and found to be around -4 per cent total, male and female unemployment individually, -5 per cent and -1 per cent respectively. These results also have important implications for determining macroeconomic and labor-market policy.

  • 61.
    Salman, A Khalik
    et al.
    Mid-Sweden University, Sweden.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University, Sweden.
    Purchasing Power Parity Theory Determinants – A Swedish Destination Study of International Tourists: a Count Data Approach2015In: American International Journal of Social Science, ISSN 2325-4149, Vol. 4, no 2, p. 294-316Article in journal (Refereed)
    Abstract [en]

    This paper employs the time-series negative binomial regression model (TNBM) to test the hypothesis effects of purchasing power parity (PPP) theory on the counts data of visitors to the north-west of Sweden (SW6 region). We consider a sample of monthly time-series count data from 1993:01 to 2008:12 taken from five countries: Denmark, the United Kingdom, Switzerland, Japan and the United States. For each visiting country, we specify separate equations by including the relative available information. We then estimate these equations using the time - series negative binomial model (TNBM). The benefit of this model is that it is much more flexible and therefore likely to fit better (if the data is not Poisson distributed) and hence is more efficient than single-equation estimation methods such as least squares. We found that the number of visitors to Sweden is negatively related to the absolute PPP and relative PPP. This result is in accordance with macroeconomic theory and the PPP theory. The results also show that some lagged dependent variables, and several monthly dummies (representing seasonal effects), have a significant impact on the number of visitors to north-west Sweden. We also find that, in at least some cases, absolute PPP, relative PPP and relative price have significant effects on international tourism demand. 

  • 62. Salman, A. Khalik
    et al.
    von Friedrichs Grängsjö, Yvonne
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    The Determinants of Failure of Small Manufacturing Firms: Assessing the Macroeconomic Factors2011In: International Business Research, ISSN 1913-9004, E-ISSN 1913-9012, Vol. 4, no 3, p. 22-32Article in journal (Refereed)
  • 63.
    Salman, A. Khalik
    et al.
    Mid Sweden University.
    Zampatti, Davide
    University of Brescia, Italy.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Macroeconomic determinants, innovation and the birth of new firms: negative binomial regression approach2013In: International Journal of Economics and Finance, ISSN 1916-9728, E-ISSN 1916-971X, Vol. 5, no 11, p. 72-81Article in journal (Refereed)
    Abstract [en]

    This paper employs the random-effects negative binomial regression model (RENBM) to test the relationship between macroeconomic factors and the birth of new firms. The test is across countries and uses count data. We consider a sample of 135 panel-data observations, taken from 27 countries in the European Union (EU) during the period 2004 to 2008. We found that the birth of new firms is positively related to the growth of gross domestic product (GDP), inflation and openness, and is negatively related to unemployment. This result is in accordance with macroeconomic theory. The results also show that expenditure on research and development (R&D) has a significant positive effect on the number of new firms. This result further supports the hypothesis of new economic growth theory. Moreover, the empirical evidence shows a positive correlation between the number of new businesses and ethnic heterogeneity.

  • 64. Salman, khalik
    et al.
    Arnesson, Leif
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics.
    Coach succession and  team performance; the impact of ability and timing:: Swedish ice hockey data2009In: Journal of Quantitative Analysis in Sports (JQAS), ISSN 1559-0410, E-ISSN 1559-0410, Vol. 5, no 1Article in journal (Refereed)
    Abstract [en]

    The purpose of this study is to identify a function for the team performance for professional ice hockey teams in Sweden. In order to understand how team performance relates to key variables such as coaching ability and coaching experience and succession, the OLS (Ordinary Least Squares) and the more robust quantile regression techniques are used to estimate team performance for the ice hockey teams. Quarterly data for the period 1975-2006 is used for this purpose. The results have shown that coaching ability has a rather significant positive effect on team performance, and that managerial succession during the season is found to have a rather significant negative effect on team performance. The results also indicate a strong correlation between coaching ability and team performance. Moreover, the quantile regression approach provided a better understanding regarding the dynamics of the factors that affect performance and provided more interesting results than the OLS normally does.

  • 65. Salman, Khalik
    et al.
    Shukur, Ghazi
    Växjö University, Faculty of Humanities and Social Sciences, School of Management and Economics. Nationalekonomi och Statistik.
    von Bergmann-Winberg, Marie-Louise
    Comparison of econometric modelling for domestic and international tourism demand: Swedish data2007In: Current issues in Tourism Journal, Vol. 10, no 4Article in journal (Other (popular science, discussion, etc.))
  • 66.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Dynamic Specification and Misspecification in Systems of Demand Equations; A Testing Strategy for Model Selection2002In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 34, p. 709-725Article in journal (Refereed)
  • 67.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    The Robustness of the Systemwise Breauch-Godfrey Autocorrelation Test for Non-normal Error Terms2000In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 29, no 2, p. 419-448Article in journal (Refereed)
  • 68.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Alkhamisi, Mahdi A.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Bayesian Analysis of a Linear Mixed  Model with AR(p) errors Via MCMC2005In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 32, no 7, p. 741-755Article in journal (Refereed)
  • 69.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Almasri, Abdullah
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    An Illustration of the Causality Relation between Government Spending and Revenue Using Wavelets Analysis on Finnish Data2003In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 30, p. 571-584Article in journal (Refereed)
  • 70.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Almasri, Abdullah
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Modelling the relation between Sunspots and Temperature using Wavelets Analysis2005In: Journal of Modern Applied Statistical, Vol. 4, no 1, p. 134-139Article in journal (Refereed)
  • 71.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Arnesson, Leif
    Salman, Khalik
    Sörensson, Anna
    Estimating International Tourism Demand for Selected Regions in Sweden and Norway with Iterative Seemingly Unrelated Regressions (ISUR)2010In: Scandinavian Journal of Hospitality and Tourism, ISSN 1502-2250, E-ISSN 1502-2269, Vol. 10, no 4, p. 395-410Article in journal (Refereed)
  • 72.
    Shukur, Ghazi
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Doszyń, Mariusz
    Szczecin University, Poland.
    Dmytrów, Krzysztof
    Szczecin University, Poland.
    Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions2017In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 46, no 5, p. 3667-3679Article in journal (Refereed)
    Abstract [en]

    The Forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g. econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U2 coefficient and unbiasedness coefficient.

  • 73.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Edgerton, David
    Some Questions Concerning Dynamic Almost Ideal Demand Systems1996In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 3, p. 693-695Article in journal (Refereed)
  • 74.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Edgerton, David
    Testing Autocorrelation in a System Perspective1999In: Econometric Reviews, ISSN 0747-4938, E-ISSN 1532-4168, Vol. 18, no 4, p. 343-386Article in journal (Refereed)
  • 75.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Edgerton, David
    The Small Sample Properties of the RESET Test as Applied to Systems of Equations2002In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 72, no 12, p. 909-924Article in journal (Refereed)
  • 76.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hatemi-J, Abdulnasser
    A Multivariate Based Causality Test of Twin Deficits in US2002In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 29, p. 817-824Article in journal (Refereed)
  • 77.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hatemi-J, Abdulnasser
    The Causal Nexus of Government Spending and Revenue in Finland: A Bootstrap Approach1999In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 6, p. 641-644Article in journal (Refereed)
  • 78.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Holgersson, Thomas
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Some Aspects of Non-Normality Tests in Systems of Regression Equations2001In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 30, no 2, p. 291-310Article in journal (Refereed)
  • 79.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Holgersson, Thomas
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Testing for Multivariate Heteroscedasticity2004In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 74, no 12, p. 879-896Article in journal (Refereed)
  • 80.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hussain, Shakir
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    A Simple Alternative Method for Detecting Fractional Cointegration Relation, An Application to Finnish Data2002In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 34, p. 607-615Article in journal (Refereed)
  • 81.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hussain, Shakir
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Estimation and Forecasting of Hospital Admission Due to Influenza - Planning for Winter Pressure2005In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 32, no 3, p. 191-205Article in journal (Refereed)
  • 82.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hussain, Shakir
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Testing for Autocorrelation in Non-stationary Dynamic Systems of Equations2003In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 30, no 4, p. 441-454Article in journal (Refereed)
  • 83.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Hussain, Shakir
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Almasi, Abdullah
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Albergali, Abdullah
    Parsimonious Modelling and Testing of Long-Range Dependence and Variance Change in Wind Speed2004In: Environmetrics, ISSN 1180-4009, E-ISSN 1099-095X, Vol. 15, p. 155-171Article in journal (Refereed)
  • 84.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Khalaf, gadban
    Choosing Ridge Parameter for Regression Problems2005In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 34, no 6, p. 1177-1182Article in journal (Refereed)
  • 85.
    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).

  • 86.
    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.

  • 87.
    Shukur, Ghazi
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Månsson, Kristofer
    BM Kibria, Golam
    A New Liu Type of Estimators for the Restricted SUR Estimator2019In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472Article in journal (Refereed)
  • 88.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Månsson, Kristofer
    Kibria, B. M. Golam
    A Simulation Study of Some Ridge Regression Estimators under Different Distributional Assumptions 2010In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 39, no 8, p. 1639-1670Article in journal (Refereed)
    Abstract [en]

    Based on the work of Khalaf and Shukur (2005), Alkhamisi et al. (2006), and Muniz et al. (2010), this article considers several estimators for estimating the ridge parameter k. This article differs from aforementioned articles in three ways: (1) Data are generated from Normal, Student's t, and F distributions with appropriate degrees of freedom; (2) The number of regressors considered are from 4-12 instead of 2-4, which are the usual practice; (3) Both mean square error (MSE) and prediction sum of square (PRESS) are considered as the performance criterion. A simulation study has been conducted to compare the performance of the estimators. Based on the simulation study we found that, increasing the correlation between the independent variables has negative effect on the MSE and PRESS. However, increasing the number of regressors has positive effect on MSE and PRESS. When the sample size increases the MSE decreases even when the correlation between the independent variables is large. It is interesting to note that the dominance pictures of the estimators are remained the same under both the MSE and PRESS criterion. However, the performance of the estimators depends on the choice of the assumption of the error distribution of the regression model.

  • 89.
    Shukur, Ghazi
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University ; HUI Research, Stockholm.
    Månsson, Kristofer
    Jönköping University ; Göteborgs Universitet.
    Sjölander, Pär
    Jönköping University ; HUI Research, Stockholm.
    Developing Interaction Shrinkage Parameters for the Liu Estimator — with an Application to the Electricity Retail Market2015In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 46, no 4, p. 539-550Article in journal (Refereed)
    Abstract [en]

    In this article we examine multicollinearity in the standard OLS interaction-term model—a problem often disregarded by practitioners and in previous research. As a remedy we propose a number of new shrinkage parameters based on the Liu (Commun Stat 22:393–402, 1993) estimator. Using Monte Carlo simulations, we evaluate the robustness of all models for different data-generating processes under varying conditions such as altered sample sizes and error distributions. In the simulation study it is demonstrated that the Liu estimator, which is robust to multicollinearity, systematically outperforms the traditionally applied OLS approach. The simple reason is that interaction models by definition always induce substantial multicollinearity, which in turn distorts the inference of OLS. Conversely, the Liu estimator is robust against multicollinearity in interaction-term models. The advantages of our Liu-based method are also demonstrated in practice when examining the efficiency of the Swedish power retailing market. By the use of this unique data set we find strong evidence of positive asymmetric price transmission effects. Increases in Nord Pool electricity wholesale spot prices lead to immediate and full increases in the electricity retail prices, but decreases in Nord Pool prices are not completely passed down or are delayed before being passed down to consumers. This finding suggests evidence of inefficient and unjust wealth transfers from consumers to retailers in the Swedish power market.

  • 90.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Salman, Khalik
    Studying the Causality Relation between Industrial Output and CPI in the Presence of Regime Shift: Swedish Data2004In: Journal of economic studies, ISSN 0144-3585, E-ISSN 1758-7387, Vol. 31, no 6, p. 492-499Article in journal (Refereed)
  • 91.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Zeebari, Zangin
    Developing Median Regression for SUR Models with Application to 3-Generation Immigrants’ data in Sweden2011In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 28, no 6, p. 2566-2578Article in journal (Refereed)
  • 92.
    Shukur, Ghazi
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Zeebari, Zangin
    Median Regression for SUR Models with the Same Explanatory Variables in Each Equation2012In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 8, p. 1765-1779Article in journal (Refereed)
    Abstract [en]

    In this paper we introduce an interesting feature of the Generalized Least Absolute Deviations (GLAD) method for Seemingly Unrelated Regression Equations (SURE) models. Contrary to the collapse of Generalized Least Squares (GLS) parameter estimations of SURE models to the Ordinary Least Squares (OLS) estimations of the individual equations when the same regressors are common between all equations, the estimations of the proposed methodology are not identical to the Least Absolute Deviations (LAD) estimations of the individual equations. This is important since contrary to the least squares methods, one can take advantage of efficiency gain due to cross-equation correlations even if the system includes the same regressors in each equation.

  • 93.
    Sjölander, Pär
    et al.
    Jönköping University.
    Månsson, Kristofer
    Jönköping University.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    A new nonlinear asymmetric cointegration approach using error correction models2017In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 46, no 2, p. 1661-1668Article in journal (Refereed)
    Abstract [en]

    In this article, two new powerful tests for cointegration are proposed. The general idea is based on an intuitively appealing extension of the traditional, rather restrictive cointegration concept. In this paper we allow for a nonlinear, but most importantly a different, asymmetric convergence process to account for negative and positive changes in our cointegration approach. Using Monte Carlo simulations we verify, that the estimated size of the first test depends on the unknown value of a signal-to-noise ratio q. However, our second test – which is based on the original ideas of Kanioura and Turner (2005) – is more successful and robust in the sense that it works in all of the different evaluated situations. Furthermore it is shown to be more powerful than the traditional residual based Enders and Siklos (2001) method. The new optimal test is also applied in an empirical example in order to test for potential nonlinear asymmetric price transmission effects on the Swedish power market. We find that there is a higher propensity for power retailers to rapidly and systematically increase their retail electricity prices subsequent to increases in Nordpool's wholesale prices, than there is for them to reduce their prices subsequent to a drop in wholesale spot prices.

  • 94.
    Sjölander, Pär
    et al.
    Jönköping University ; HUI Research.
    Månsson, Kristofer
    Jönköping University ; HUI Research.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University ; HUI Research.
    Testing for panel cointegration in an error-correction framework with an application to the Fisher hypothesis2017In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 46, no 3, p. 1735-1745Article in journal (Refereed)
    Abstract [en]

    In this article, three innovative panel error-correction model (PECM) tests are proposed. These tests are based on the multivariate versions of the Wald (W), likelihood ratio (LR), and Lagrange multiplier (LM) tests. Using Monte Carlo simulations, the size and power of the tests are investigated when the error terms exhibit both cross-sectional dependence and independence. We find that the LM test is the best option when the error terms follow independent white-noise processes. However, in the more empirically relevant case of cross-sectional dependence, we conclude that the W test is the optimal choice. In contrast to previous studies, our method is general and does not rely on the strict assumption that a common factor causes the cross-sectional dependency. In an empirical application, our method is also demonstrated in terms of the Fisher effect—a hypothesis about the existence of which there is still no clear consensus. Based on our sample of the five Nordic countries we utilize our powerful test and discover evidence which, in contrast to most previous research, confirms the Fisher effect.

  • 95.
    Sjölander, Pär
    et al.
    Jönköping University, Sweden.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University, Sweden.
    Månsson, Kristofer
    Jönköping University, Sweden ; Gothenburg University, Sweden.
    Kekezi, Orsa
    Jönköping University, Sweden.
    The efficiency of the Scandinavian banking sector - a wavelet quantile regression analysis2015In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 47, no 50, p. 5378-5389Article in journal (Refereed)
    Abstract [en]

    In this article, the Scandinavian housing financing market is analysed in order to determine whether the interest rate price-discovery processes of Denmark, Norway and Sweden are efficient. Based on wavelet quantile regression analysis, we find systematic positive asymmetric price transmission (APT) inefficiencies. We conclude that there is a very high propensity for mortgage lenders to directly increase its customers’ mortgage interest rates subsequently to an increase in its borrowing costs. However, after a corresponding borrowing cost decrease, the same mortgage lenders are very slow to decrease its customers’ mortgage rates. These positive coefficients for so-called APT effects are found in all Scandinavian countries, even if the coefficients for Norway were not statistically significant. Wavelet quantile regression analysis, with a focus on the relevant higher percentiles, is easily motivated since the mortgage rates are adjusted very infrequently. Moreover, wavelet decomposition allows a robust analysis at different time frequency scales, while simultaneously controlling for nonstationary trends, autocorrelation and structural breaks. Except for the still positive but yet insignificant and inconclusive coefficients for Norway, the result is very clear-cut. Regardless of which wavelet scaling decomposition or quantile coefficient that is studied – positive APT effects are clearly identified and confirmed on the Scandinavian mortgage market.

  • 96.
    Zeebari, Zangin
    et al.
    Karolinska Institutet.
    Kibria, B. M. Golam
    Florida International University, USA.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Seemingly unrelated regressions with covariance matrix of cross-equation ridge regression residuals2018In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 47, no 20, p. 5029-5053Article in journal (Refereed)
    Abstract [en]

    Generalized least squares estimation of a system of seemingly unrelated regressions is usually a two-stage method: (1) estimation of cross-equation covariance matrix from ordinary least squares residuals for transforming data, and (2) application of least squares on transformed data. In presence of multicollinearity problem, conventionally ridge regression is applied at stage 2. We investigate the usage of ridge residuals at stage 1, and show analytically that the covariance matrix based on the least squares residuals does not always result in more efficient estimator. A simulation study and an application to a system of firms' gross investment support our finding.

  • 97.
    Zeebari, Zangin
    et al.
    Jönköping University, Sweden.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University, Sweden.
    On the least absolute deviations method for ridge estimation of SURE models2019In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed)
    Abstract [en]

    In this paper we examine the application of the Least Absolute Deviations (LAD) method for ridge-type parameter estimation of Seemingly Unrelated Regression Equations (SURE) models. The methodology is aimed to deal with the SURE models with non-Gaussian error terms and highly collinear predictors in each equation. Some biasing parameters used in the literature are taken and the efficiency of both Least Squares (LS) ridge estimation and the LAD ridge estimation of the SURE models, through the Mean Squared Error (MSE) of parameter estimators, is evaluated.

  • 98.
    Zeebari, Zangin
    et al.
    Jönköping University.
    Shukur, Ghazi
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Kibria, B. M. Golam
    Modified Ridge Parameters for Seemingly Unrelated Regression Model2012In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 41, no 9, p. 1675-1691Article in journal (Refereed)
    Abstract [en]

    In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine estimators of the ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and proportion of replications (out of 1,000) for which the SUR version of the generalised least squares (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified estimators of the ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge RMSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high the unbiased SUR, estimator produces a smaller TMSEs. 

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