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Holgersson, Thomas
Publications (10 of 32) Show all publications
Holgersson, T. & Kekezi, O. (2018). Towards a multivariate innovation index. Economics of Innovation and New Technology, 27(3), 254-272
Open this publication in new window or tab >>Towards a multivariate innovation index
2018 (English)In: Economics of Innovation and New Technology, ISSN 1043-8599, E-ISSN 1476-8364, Vol. 27, no 3, p. 254-272Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Taylor & Francis, 2018
Keywords
factor analysis, multivariate index, Regional innovation
National Category
Economics
Identifiers
urn:nbn:se:hj:diva-36604 (URN)10.1080/10438599.2017.1331788 (DOI)000438041100004 ()2-s2.0-85020272337 (Scopus ID)
Available from: 2017-07-04 Created: 2017-07-04 Last updated: 2018-09-11Bibliographically approved
Holgersson, T., Nordström, L. & Öner, Ö. (2016). On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.. Journal of Applied Statistics, 43(8), 1564-1565
Open this publication in new window or tab >>On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.
2016 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 8, p. 1564-1565Article in journal (Other academic) Published
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-29088 (URN)10.1080/02664763.2015.1092711 (DOI)000368584400006 ()2-s2.0-84945205542 (Scopus ID)
Note

Rejoinder on Holgersson et al., Journal of Applied Statistics, DOI: 10.1080/02664763.2015.1092711

Available from: 2016-01-14 Created: 2016-01-14 Last updated: 2017-11-30Bibliographically approved
Holgersson, T., Månsson, K. & Shukur, G. (2016). Testing for panel unit roots under general cross-sectional dependence. Communications in statistics. Simulation and computation, 45(5), 1785-1801
Open this publication in new window or tab >>Testing for panel unit roots under general cross-sectional dependence
2016 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 45, no 5, p. 1785-1801Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Taylor & Francis, 2016
Keywords
Panel data, unit roots, linear hypothesis, invariance
National Category
Social Sciences Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-22426 (URN)10.1080/03610918.2013.879178 (DOI)000374951900028 ()2-s2.0-84964687191 (Scopus ID)
Available from: 2013-10-16 Created: 2013-10-16 Last updated: 2017-12-06Bibliographically approved
Holgersson, T. (Ed.). (2015). Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday. Växjö: Linnaeus University Press
Open this publication in new window or tab >>Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday
2015 (English)Collection (editor) (Other academic)
Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2015
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-29089 (URN)978-91-87925-90-0 (ISBN)
Available from: 2016-01-14 Created: 2016-01-14 Last updated: 2016-01-14Bibliographically approved
Florida, R., Mellander, C. & Holgersson, T. (2015). Up in the air: The role of airports for regional economic development. The annals of regional science, 54(1), 197-214
Open this publication in new window or tab >>Up in the air: The role of airports for regional economic development
2015 (English)In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592, Vol. 54, no 1, p. 197-214Article in journal (Refereed) Published
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.

Keywords
Headquarters, information, cities, impact
National Category
Economics
Identifiers
urn:nbn:se:hj:diva-28363 (URN)10.1007/s00168-014-0651-z (DOI)000350035800008 ()2-s2.0-84925511444 (Scopus ID)IHHPISIS (Local ID)IHHPISIS (Archive number)IHHPISIS (OAI)
Available from: 2015-11-22 Created: 2015-11-22 Last updated: 2017-12-01Bibliographically approved
Holgersson, T. (2014). A Note on a commonly used ridge regression Monte Carlo design. Communications in Statistics - Theory and Methods, 44(10), 2176-2179
Open this publication in new window or tab >>A Note on a commonly used ridge regression Monte Carlo design
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 44, no 10, p. 2176-2179Article in journal (Refereed) Published
Abstract [en]

Ridge estimators are usually examined through Monte Carlo simulations since their properties are difficult to obtain analytically. In this paper we argue that a simulation design commonly used in the literature will give biased results of Monte Carlo simulations in favour of ridge regression over ordinary least square (OLS) estimators. Specifically, it is argued that the properties of ridge estimators that are functions of p distinct regressor eigenvalues should not be evaluated through Monte Carlo designs using only two distinct eigenvalues.

Place, publisher, year, edition, pages
London: Taylor & Francis Group, 2014
Keywords
Design matrix, Excess mean square error, Monte carlo simulation, Multicollinearity, Ridge regression
National Category
Other Social Sciences
Identifiers
urn:nbn:se:hj:diva-20545 (URN)10.1080/03610926.2013.775299 (DOI)000356857700013 ()2-s2.0-84930698293 (Scopus ID)
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2017-12-06Bibliographically approved
Holgersson, T., Nordström, L. & Öner, Ö. (2014). Dummy variables vs. category-wise models. Journal of Applied Statistics, 41(2), 233-241
Open this publication in new window or tab >>Dummy variables vs. category-wise models
2014 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, no 2, p. 233-241Article in journal (Refereed) Published
Abstract [en]

Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.

Keywords
regression analysis, dummy variables, group heterogeneity, parameter restrictions
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-21802 (URN)10.1080/02664763.2013.838665 (DOI)000327237200001 ()2-s2.0-84889096817 (Scopus ID)
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2017-12-06Bibliographically approved
Holgersson, T., Norman, T. & Tavassoli, S. (2014). In the quest for economic significance: assessing variable importance through mean value decomposition. Applied Economics Letters, 21(8), 545-549
Open this publication in new window or tab >>In the quest for economic significance: assessing variable importance through mean value decomposition
2014 (English)In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 21, no 8, p. 545-549Article in journal (Refereed) Published
Abstract [en]

Economic significance is frequently assessed through statistical hypothesis testing, which however, does not always correspond to the implicit economical questions being addressed. In this article we propose using mean value decomposition to assess economic significance. Unlike most previously suggested methods the proposed one is intuitive and simple to conduct. The technique is demonstrated and contrasted with hypothesis tests by an empirical example involving the income of Mexican children, which shows that the two inference approaches provide different and supplementary pieces of information.

Keywords
mean value decomposition, goodness-of-fit, conditioning, regression analysis, economic significance
National Category
Economics
Identifiers
urn:nbn:se:hj:diva-25915 (URN)10.1080/13504851.2013.872757 (DOI)000332196800008 ()2-s2.0-84895766784 (Scopus ID)
Available from: 2015-02-18 Created: 2015-02-18 Last updated: 2019-02-21Bibliographically approved
Holgersson, T. & Mansoor, R. (2013). Assessing Normality of High-Dimensional Data. Communications in statistics. Simulation and computation, 42(2), 360-369
Open this publication in new window or tab >>Assessing Normality of High-Dimensional Data
2013 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 42, no 2, p. 360-369Article in journal (Refereed) Published
Abstract [en]

The assumption of normality is crucial in many multivariate inference methods and may be even more important when the dimension of data is proportional to the sample size. It is therefore necessary that tests for multivariate non normality remain well behaved in such settings. In this article, we examine the properties of three common moment-based tests for non normality under increasing dimension asymptotics (IDA). It is demonstrated through Monte Carlo simulations that one of the tests is inconsistent under IDA and that one of them stands out as uniformly superior to the other two.

Keywords
Multivariate skewness and kurtosis, Increasing dimension, Asymptotics, Non normality
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-16439 (URN)10.1080/03610918.2011.636164 (DOI)2-s2.0-84870900232 (Scopus ID)
Available from: 2011-10-24 Created: 2011-10-24 Last updated: 2019-02-21Bibliographically approved
Holgersson, T., Karlsson, P. & Dai, D. (2013). Expected and Unexpected Values of Individual mahalanobis Distances. In: : . Paper presented at Statistiche Woche, 17-20 September 2013.
Open this publication in new window or tab >>Expected and Unexpected Values of Individual mahalanobis Distances
2013 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hj:diva-22003 (URN)
Conference
Statistiche Woche, 17-20 September 2013
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2013-09-23
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