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  • 1.
    Almasri, Abdullah
    et al.
    Department of Economics and Statistics, Karlstad University, Karlstad, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Göteborg University, Göteborg, Sweden.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    A wavelet-based panel unit-root test in the presence of an unknown structural break and cross-sectional dependency, with an application of purchasing power parity theory in developing countries2017In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 49, no 21, p. 2096-2105Article in journal (Refereed)
    Abstract [en]

    This article introduces two different non-parametric wavelet-based panel unit-root tests in the presence of unknown structural breaks and cross-sectional dependencies in the data. These tests are compared with a previously suggested non-parametric wavelet test, the parameteric Im-Pesaran and Shin (IPS) test and a Wald type of test. The results from the Monte Carlo simulations clearly show that the new wavelet-ratio tests are superior to the traditional tests both in terms of size and power in panel unit-root tests because of its robustness to cross-section dependency and structural breaks. Based on an empirical Central American panel application, we can, in contrast to previous research (where bias due to structural breaks is simply disregarded), find strong, clear-cut support for purchasing power parity (PPP) in this developing region.

  • 2.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A comparison of two estimation methods of the common principal component modelManuscript (preprint) (Other academic)
  • 3.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Aspects of common principal components2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The focus of this thesis is the common principal component (CPC) model, the generalization of principal components to several populations. Common principal components refer to a group of multidimensional datasets such that their inner products share the same eigenvectors and are therefore simultaneously diagonalized by a common decorrelator matrix. Common principal component analysis is essentially applied in the same areas and analysis as its one-population counterpart. The generalization to multiple populations comes at the cost of being more mathematically involved, and many problems in the area remains to be solved.

    This thesis consists of three individual papers and an introduction chapter.In the first paper, the performance of two different estimation methods of the CPC model is compared for two real-world datasets and in a Monte Carlo simulation study. The second papers show that the orthogonal group and the Haar measure on this group plays an important role in PCA, both in single- and multi-population principal component analysis. The last paper considers using common principal component analysis as a tool for imposing restrictions on system-wise regression models. When the exogenous variables of a multi-dimensional model share common principal components, then each of the marginal models in the system is, up to their eigenvalues, identical. They henceform a class of regression models situated in between the classical seemingly unrelated regressions, where each set of explanatory variables is unique, and multivariate regression, where each marginal model shares the same common set of regressors.

  • 4.
    Duras, Toni
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A small excursion on the Haar measure on OpManuscript (preprint) (Other academic)
  • 5.
    Duras, Toni
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Common principal components with applications in regressionManuscript (preprint) (Other academic)
  • 6.
    Florida, Richard
    et al.
    Rotman School of Management, University of Toronto.
    Mellander, Charlotta
    Jönköping University, Jönköping International Business School, JIBS, The Prosperity Institute of Scandinavia (PIS). Jönköping University, Jönköping International Business School, JIBS, Economics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Up in the air: The role of airports for regional economic development2015In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592, Vol. 54, no 1, p. 197-214Article in journal (Refereed)
    Abstract [en]

    Our research examines the role of airports in regional development. Specifically, we examine two things: (1) the factors associated with whether or not a metro will have an airport, and (2) the effect of airport activities on regional economic development. Based on multiple regression analysis for U.S. metros, our research generates four key findings. First, airports are more likely to be located in larger metros with higher shares of cultural workers and warmer winters. Second, airports add significantly to regional development measured as economic output per capita. Third, the effect of airports on regional development occurs through two channels—their capacity to move both people and cargo, with the former being somewhat more important. Fourth, the impact of airports on regional development varies with their size and scale.

  • 7.
    Habimana, Olivier
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Department of Applied Statistics, College of Business and Economics, University of Rwanda, Kigali, Rwanda.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for nonlinear unit roots in the presence of a structural break2015In: Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday / [ed] Thomas Holgersson, Växjö: Linnaeus University Press , 2015Chapter in book (Other academic)
  • 8.
    Habimana, Olivier
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Department of Applied Statistics, College of Business and Economics, University of Rwanda, Kigali, Rwanda.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis2018In: International journal of finance and economics, ISSN 1076-9307, E-ISSN 1099-1158, Vol. 23, no 3, p. 221-232Article in journal (Refereed)
    Abstract [en]

    This paper applies Monte Carlo simulations to evaluate the size and power properties in the presence of a structural break, for the standard Augmented Dickey-Fuller (ADF) test versus nonlinear exponential smooth transition autoregressive unit root tests. The break causes the tests to be undersized, and the statistical power considerably decreases. Moreover, the effect is intensified in small samples and very much increased for more persistent nonlinear series. As a remedy, we modify the standard ADF and exponential smooth transition autoregressive unit root tests in order to adjust for a structural break. This improves both the power and the size considerably, even though the empirical size still is lower than the nominal one. More persistent series are more affected by structural breaks, and the new tests are most powerful under the existence of a rather persistent nonlinear data generating process (which is an empirically relevant and common type of data generating process). The proposed tests are applied to investigate mean reversion in the real effective exchange rates of 5 East and Southeast Asian countries, taking into account the structural change in exchange rate regime brought about by the 1997 Asian financial crisis. The empirical findings corroborate our simulation results; the modified more powerful tests are able to reject the unit root in all 5 countries, whereas the tests that do not consider the structural break could only reject in one of these cases.

  • 9.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday2015Collection (editor) (Other academic)
  • 10.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Centre for Data Intensive Sciences and Applications, Linnaeus University, Växjö, Sweden.
    Kekezi, Orsa
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Towards a multivariate innovation index2018In: Economics of Innovation and New Technology, ISSN 1043-8599, E-ISSN 1476-8364, Vol. 27, no 3, p. 254-272Article in journal (Refereed)
    Abstract [en]

    This paper argues that traditional measures of innovation as a univariate phenomenon may not be dynamic enough to adequately describe the complex nature of innovation. Consequently, the purpose is to develop a multidimensional index of innovation that is able to reflect innovation enablers and outputs. The index may then be used (i) to assess and quantify temporal changes of innovation, (ii) to describe regional differences and similarities of innovation, and (iii) serve as exogenous variables to analyze the importance of innovation for other economic phenomena. Our index is defined in a four-dimensional space of orthogonal axes. An empirical case study is used for demonstration of the index, where 44 variables are collected for all municipalities in Sweden. The index spanning the four-dimensional innovation comprises size, accessibility, firm performance, and agglomeration. The proposed index offers a new way of defining and analyzing innovation and should have a wide range of important applications in a world where innovation is receiving a great deal of recognition.

  • 11.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Linnaeus University, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Göteborg University, Sweden .
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for panel unit roots under general cross-sectional dependence2016In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 45, no 5, p. 1785-1801Article in journal (Refereed)
    Abstract [en]

    In this paper we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables. A Monte Carlo simulation is included to compare and contrast the tests with two well-established ones.

  • 12.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Nordström, Louise
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Öner, Özge
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.2016In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 8, p. 1564-1565Article in journal (Other academic)
  • 13.
    Johansson, Börje
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Klaesson, Johan
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Wallin, Tina
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Warda, Peter
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Vad betyder högskolan för Region Jönköpings ekonomi?2014Report (Other academic)
  • 14.
    Karlsson, Hyunjoo Kim
    et al.
    Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Investigation of the nonlinear behaviour in real exchange rates in developing regions2018In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 25, no 5, p. 335-339Article in journal (Refereed)
    Abstract [en]

    This article examines whether the purchasing power parity (PPP) theory holds or not for the economies in different developing regions located in Africa, Asia and Latin America. In order to investigate this issue, a nonlinear panel unit root test is used to determine if some or all of the real exchange rates in a panel follow a stationary exponential smooth transition autoregressive process. By applying the nonlinear panel unit root test, our results demonstrate an empirical support for the theory of PPP for the economies in developing regions.

  • 15.
    Karlsson, Peter S.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Point estimators of the Mahalanobis distance in high-dimensional dataManuscript (preprint) (Other academic)
    Abstract [en]

    This paper concerns the problem of estimating the Mahalanobis distance when the dimension of the data matrix is comparable to the sample size. Two different ridge-shrinkage estimators are considered and estimators of related risk functions are derived. The properties of these point estimators are investigated in terms of excess risk and bias relative to the traditional estimator.

  • 16.
    Karlsson, Peter S.
    et al.
    Departments of Economics and Statistics, Linnaeus University, Växjö, Sweden .
    Behrenz, Lars
    Departments of Economics and Statistics, Linnaeus University, Växjö, Sweden .
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Performances of Model Selection Criteria When Variables are Ill Conditioned2017In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, p. 1-22Article in journal (Refereed)
    Abstract [en]

    Model selection criteria are often used to find a “proper” model for the data under investigation when building models in cases in which the dependent or explained variables are assumed to be functions of several independent or explanatory variables. For this purpose, researchers have suggested using a large number of such criteria. These criteria have been shown to act differently, under the same or different conditions, when trying to select the “correct” number of explanatory variables to be included in a given model; this, unfortunately, leads to severe problems and confusion for researchers. In this paper, using Monte Carlo methods, we investigate the properties of four of the most common criteria under a number of realistic situations. These criteria are the adjusted coefficient of determination ((Formula presented.)-adj), Akaike’s information criterion (AIC), the Hannan–Quinn information criterion (HQC) and the Bayesian information criterion (BIC). The results from this investigation indicate that the HQC outperforms the BIC, the AIC and the (Formula presented.)-adj under specific circumstances. None of them perform satisfactorily, however, when the degree of multicollinearity is high, the sample sizes are small or when the fit of the model is poor (i.e., there is a low (Formula presented.). In the presence of all these factors, the criteria perform very badly and are not very useful. In these cases, the criteria are often not able to select the true model. 

  • 17.
    Kibria, B. M. Golam
    et al.
    Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A simulation study of some biasing parameters for the ridge type estimation of Poisson regression2015In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 44, no 4, p. 943-957Article in journal (Refereed)
    Abstract [en]

    This paper proposes several estimators for estimating the ridge parameter k based for Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criterion are very informative because, if several estimators have an equal estimated MSE then those with low average value and standard deviation of k should be preferred. Based on the simulated results we may recommend some biasing parameters which may be useful for the practitioners in the field of health, social and physical sciences.

  • 18.
    Kim Karlsson, Hyunjoo
    et al.
    The Linnaeus University, Växjö, Sweden.
    Karlsson, Peter
    Jönköping University, Jönköping International Business School, JIBS, Statistics. The Linnaeus University, Växjö, Sweden .
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Wavelet quantile analysis of asymmetric pricing on the Swedish power market2017In: Empirica, ISSN 0340-8744, E-ISSN 1573-6911, Vol. 44, no 2, p. 249-260Article in journal (Refereed)
    Abstract [en]

    In this article we investigate if the Swedish consumer prices for electricity are adjusted equally fast regardless of whether the NordPool power market prices are decreased or increased. Due to relatively moderate variations in the variables, we have applied quantile regression, since it is mainly the large changes (above the median) that essentially tend to have a considerable effect on the consumer prices. Moreover, in order to adjust for stochastic- and deterministic trends, autocorrelation, structural breaks as well as to measure APT effects in the short- and in the medium-run, we apply a wavelet decomposition approach. Our results show evidence that significantly positive asymmetric price transmission (APT) effects exist in this market. More specifically, in the short-run (based on the wavelet decomposition D1 for 1–2 months cycles), we find that that there is a higher propensity to rapidly and systematically increase the consumer prices subsequently to an increase in the NordPool market price, compared with the propensity to decrease their customers prices subsequently to a corresponding drop in the NordPool market prices. However, no significant APT effects were detected in the medium- or in the long-run (i.e. the asymmetric price transmission effects are observed only in the short-run). In summary, we could isolate significant APT effects in the short-run (1–2 months decomposition cycles), and for large changes in the dependent variable (percentiles = 0.9). Therefore, only large changes in the NordPool prices lead to feedback effects in the form of asymmetric price transmission effects. Our evidence supports the notion of firms’ downward stickiness of retail prices for maximizing profit, which are not expected to be found on a fully efficient market. Although our finding shows that the price inefficiency is short-lived, these large temporal inefficiencies are still costly for the consumers. It should be noted that blunt traditional powerless methods do not detect these APT effects, while our wavelet quantile methods are powerful and make a significant contribution in the literature by providing new empirical evidence.

  • 19.
    Locking, Håkan
    et al.
    Department of Economics and Statistics, Linnaeus University, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ridge estimators for probit regression: With an application to labour market data2015In: Bulletin of Economic Research, ISSN 0307-3378, E-ISSN 1467-8586, Vol. 66, no S1, p. S92-S103Article in journal (Refereed)
    Abstract [en]

    In this paper we propose ridge regression estimators for probit models since the commonly applied maximum likelihood (ML) method is sensitive to multicollinearity. An extensive Monte Carlo study is conducted where the performance of the ML method and the probit ridge regression (PRR) is investigated when the data is collinear. In the simulation study we evaluate a number of methods of estimating the ridge parameter k that have recently been developed for use in linear regression analysis. The results from the simulation study show that there is at least one group of the estimators of k that regularly has a lower MSE than the ML method for all different situations that has been evaluated. Finally, we show the benefit of the new method using the classical Dehejia and Wahba (1999) dataset which is based on a labor market experiment.

     

  • 20.
    Musafiri, Ildephonse
    et al.
    College of Business and Economics, University of Rwanda, Kigali, Rwanda.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    The importance of off-farm employment for smallholder farmers in Rwanda2018In: Journal of economic studies, ISSN 0144-3585, E-ISSN 1758-7387, Vol. 5, no 1, p. 14-26Article in journal (Refereed)
    Abstract [en]

    Purpose: Based on unique data the authors analyze the Rwandan non-farm employment expansion in rural areas and its relation to agricultural productivity. The purpose of this paper is to analyze the factors that determine off-farm work hours in Rwanda, and how farmers’ off-farm employment affects agricultural output. Since production efficiency may depend on off-farm work and off-farm work depend on production efficiency (Lien et al., 2010), both production and off-farm work are endogenous. While controlling for endogeneity, the authors investigate the relationship between off-farm work and agricultural production.

    Design/methodology/approach: In this paper the authors use a unique panel data set spanning over 26 years originating from household surveys conducted in the northwest and densely populated districts of Rwanda. Econometric estimations are based on a random effects two-stage Tobit model to control for endogeneity.

    Findings: The study confirms theoretical and empirical findings from other developing countries that off-farm employment is one of the essential conditions for having an economically viable agricultural business and vice versa.

    Research limitations/implications: The study is carried out in only one district of Rwanda. Even though most rural areas in Rwanda have similar features the findings cannot necessarily be generalized for the entire country of Rwanda. As in any study, the raw data set suffer from a number of shortcomings which cannot be fully eliminated by the econometric estimation, but this is a new data set which has the best data available for this research question in Rwanda.

    Practical implications: The authors can conclude that there are synergy effects of investing government resources into both on-farm and off-farm employment expansions. Thus, in Rwanda on-farm investments can actually partly contribute to a future natural smooth transformation to more off-farm total output and productivity and vice versa. Though there are still limited off-farm employment opportunities in the studied area, there are considerable potentials to generate income and increase agricultural production through the purchase of additional inputs.

    Social implications: The findings imply that a favorable business climate for off-farm businesses creates spill-over effects which enhance the smallholder farmers’ opportunities to survive, generate wealth, create employment and in effect reduce poverty.

    Originality/value: From the best of the authors’ knowledge, similar studies have not been conducted in Rwanda, nor elsewhere with this type of data set. The findings provide original insights regarding off-farm and agricultural relationships in rural areas under dense population pressure. The results provide some indications that off-farm employment in developing countries (such as Rwanda) is one of the essential conditions for having an economically viable agricultural business and vice versa. The second wave of data was collected by the authors and was used solely for the purpose of this paper. 

  • 21.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Developing a Liu estimator for the negative binomial regression model: method and application2013In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 83, no 9, p. 1773-1780Article in journal (Refereed)
    Abstract [en]

    This paper introduces a new shrinkage estimator for the negative binomial regression model that is a generalization of the estimator proposed for the linear regression model by Liu [A new class of biased estimate in linear regression, Comm. Stat. Theor. Meth. 22 (1993), pp. 393–402]. This shrinkage estimator is proposed in order to solve the problem of an inflated mean squared error of the classical maximum likelihood (ML) method in the presence of multicollinearity. Furthermore, the paper presents some methods of estimating the shrinkage parameter. By means of Monte Carlo simulations, it is shown that if the Liu estimator is applied with these shrinkage parameters, it always outperforms ML. The benefit of the new estimation method is also illustrated in an empirical application. Finally, based on the results from the simulation study and the empirical application, a recommendation regarding which estimator of the shrinkage parameter that should be used is given.

  • 22.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Issues of multicollinearity and conditional heteroscedasticy in time series econometrics2012Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This doctoral thesis consists of four chapters all related to the field of time series econometrics. The main contribution is firstly the development of robust methods when testing for Granger causality in the presence of generalized autoregressive conditional heteroscedasticity (GARCH) and causality-in-variance (i.e. spillover) effects. The second contribution is the development of different shrinkage estimators for count data models which may be used when the explanatory variables are highly inter-correlated.

    The first essay investigated the effect of spillover on some tests for causality in a Granger sense. As a remedy to the problem of over-rejection caused by the spillover effects White’s heteroscedasticity consistent covariance matrix is proposed. In the second essay the effect of GARCH errors on the statistical tests for Granger causality is investigated. Here some wavelet denoising methods are proposed and by means of Monte Carlo simulations it is shown that the size properties of the tests based on wavelet filtered data is better than the ones based on raw data.

    In the third and fourth essays ridge regression estimators for the Poisson and negative binomial (NB) regression models are investigated respectively. Then finally in the fifth essaya Liu type of estimator is proposed for the NB regression model. By using Monte Carlo simulations it is shown that the estimated MSE is lower for the ridge and Liu type of estimators than maximum likelihood (ML).

  • 23.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Florida International University.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A restricted Liu estimator for binary regression models and its application to an applied demand system2016In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 6, p. 1119-1127Article in journal (Refereed)
    Abstract [en]

    In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by =r. First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.

  • 24.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Department of Mathematics and Statistics, Florida International University, Miami, FL, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Performance of some weighted Liu estimators for logit regression model: An application to Swedish accident data2015In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 44, no 2, p. 363-375Article in journal (Refereed)
    Abstract [en]

    In this article, we propose some new estimators for the shrinkage parameter d of the weighted Liu estimator along with the traditional maximum likelihood (ML) estimator for the logit regression model. A simulation study has been conducted to compare the performance of the proposed estimators. The mean squared error is considered as a performance criteria. The average value and standard deviation of the shrinkage parameter d are investigated. In an application, we analyze the effect of usage of cars, motorcycles, and trucks on the probability that pedestrians are getting killed in different counties in Sweden. In the example, the benefits of using the weighted Liu estimator are shown. Both results from the simulation study and the empirical application show that all proposed shrinkage estimators outperform the ML estimator. The proposed D9 estimator performed best and it is recommended for practitioners.

  • 25.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Department of mathematics and Statistics, Florida International University, Miami, Florida, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. The Linnaeus University, Department of Economics and Statistics, Växjö, Sweden.
    Some Liu Type Estimators for the dynamic OLS estimator: With an application to the carbon dioxide Kuznets curve for Turkey2017In: Communications in Statistics: Case Studies, Data Analysis and Applications, ISSN 2373-7484, Vol. 3, no 3-4, p. 55-61Article in journal (Refereed)
    Abstract [en]

    This paper suggests some Liu type shrinkage estimators for the dynamic ordinary least squares (DOLS) estimator that may be used to combat the multicollinearity problem. DOLS is an estimator suggested to solve the finite sample bias of OLS caused by endogeneity issue when estimating regression models based on cointegrated variables. In this paper using simulation techniques it is shown that multicollinearity and non-normality of the error term is a problem in finite samples for the DOLS model. The merit of proposed Liu type estimator are shown by means of a Monte Carlo simulation study and using an empirical application.

  • 26.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Department of Mathematics and Statistics, Florida International University, Miami, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    On the Estimation of the CO2 Emission, Economic Growth and Energy Consumption Nexus Using Dynamic OLS in the Presence of Multicollinearity2018In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 10, no 5, article id 1315Article in journal (Refereed)
    Abstract [en]

    This paper introduces shrinkage estimators (Ridge DOLS) for the dynamic ordinary least squares (DOLS) cointegration estimator, which extends the model for use in the presence of multicollinearity between the explanatory variables in the cointegration vector. Both analytically and by using simulation techniques, we conclude that our new Ridge DOLS approach exhibits lower mean square errors (MSE) than the traditional DOLS method. Therefore, based on the MSE performance criteria, our Monte Carlo simulations demonstrate that our new method outperforms the DOLS under empirically relevant magnitudes of multicollinearity. Moreover, we show the advantages of this new method by more accurately estimating the environmental Kuznets curve (EKC), where the income and squared income are related to carbon dioxide emissions. Furthermore, we also illustrate the practical use of the method when augmenting the EKC curve with energy consumption. In summary, regardless of whether we use analytical, simulation-based, or empirical approaches, we can consistently conclude that it is possible to estimate these types of relationships in a considerably more accurate manner using our newly suggested method.

  • 27.
    Månsson, Kristofer
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Linnaeus University, Växjö, Sweden.
    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 4Article 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.

  • 28.
    Salman, A. Khalik
    et al.
    Department of Business Economics and Law Mid-Sweden University Sweden.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    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.

  • 29.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Doszyń, Mariusz
    Szczecin University, Econometrics and Statistics Institute.
    Dmytrów, Krzysztof
    Szczecin University, Econometrics and Statistics Institute.
    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.

  • 30.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, BM Golam
    FIU, Florida, USA.
    Performance of some ridge regression estimators for the multinomial logi model2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed)
  • 31.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    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.

  • 32.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    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 article, 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—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 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.

  • 33.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Kekezi, Orsa
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    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.

  • 34.
    Shukur, Ghazi
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    On the least absolut deviation method for ridge estimation of SURE models2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed)
  • 35.
    Sjölander, Pär
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics. HUI Research, Stockholm, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. HUI Research, Stockholm, Sweden.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. HUI Research, Stockholm, Sweden; Department of Economics and Statistics, Linnaeus University, Sweden.
    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.

  • 36.
    Wallentin, Erik
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Choice of the angler: Estimating single-site recreation demand using revealed preference data2016In: Tourism Economics, ISSN 1354-8166, E-ISSN 2044-0375, Vol. 22, no 6, p. 1338-1351Article in journal (Refereed)
    Abstract [en]

    The author proposes a novel application for estimating demand for a single recreation site when data are limited. An aggregated zonal travel cost model is outlined and estimated in a panel setting using a negative binomial estimator with time-specific constants to capture unobserved time-varying quality attributes. The data are based on catch records for the Mörrum river salmon fishery, one of the most popular sport fishing destinations in Northern Europe. These are aggregated to the municipal level for the zonal estimation and give number of visits per municipality per week for the period 1999-2011. The results confirm the expected negative influence of travel cost on visits. Further, the inclusion of time-specific constants does not render all time-varying quality attributes insignificant. 

  • 37.
    Wallentin, Erik
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Demand for cinema and diverging tastes of critics and audiences2016In: Journal of Retailing and Consumer Services, ISSN 0969-6989, E-ISSN 1873-1384, Vol. 33, p. 72-81Article in journal (Refereed)
    Abstract [en]

    Cinema is an experience good and consumers will use reviews by professional critics to reduce the inherent uncertainty of consumption. Two aspects of demand for cinema is analyzed; the demand of critics and the demand of the audience. Estimations are done in two steps on a set of Swedish data covering cinema ticket sales and review scores. I conclude that there is a great deal of discrepancy between which characteristics the audience favor and which ones professional critics value. On average it is however concluded that there is a positive relationship between review scores and ticket sales. Due to data limitations one cannot conclude whether this is a case of predication or influence.

  • 38.
    Wallin, Tina
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Entrepreneurship as a career choice - Incorporating family and space into the equation2016Conference paper (Refereed)
  • 39.
    Zeebari, Zangin
    et al.
    Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden.
    Kibria, B. M. G.
    Department of Mathematics and Statistics, Florida International University, Miami, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    Seemingly unrelated regressions with covariance matrix of cross-equation ridge regression residuals2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle 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.

1 - 39 of 39
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