Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities
References
- Asamoah, R. O., Baiden, B. K., Nani, G., & Kissi, E. (2019). Review of exogenous economic indicators influencing construction industry. Advances in Civil Engineering, 2019, 1–8. Advance online publication. https://doi.org/10.1155/2019/6073289
- Athey, S. (2019). The Impact of Machine Learning on Economics. The Economics of Artificial Intelligence: An Agenda,. 548–551.
- Athey, S., & Luca, M. (2019). Economists (and economics) in tech companies. The Journal of Economic Perspectives, 33(1), 209–230. https://doi.org/10.1257/jep.33.1.209
- Augustyński, I., & Laskoś-Grabowski, P. (2018). Clustering macroeconomic time series. econometrics, 22(2), 74–88. https://doi.org/10.15611/eada.2018.2.06
- Blien, U., Hirschenauer, F., & Thi Hong Van, P. (2010). Classification of regional labour markets for purposes of labour market policy. Papers in Regional Science, 89(4), 859–880. https://doi.org/10.1111/j.1435-5957.2010.00331.x
- Brauksa, I. (2013). Use of Cluster Analysis in Exploring Economic Indicator Differences among Regions: The Case of Latvia. Journal of Economics, Business and Management, 1(1), 42–45. https://doi.org/10.7763/JOEBM.2013.V1.10
- Burinskienė, M., & Rudzkiene, V. (2004). Comparison of spatial-temporal regional development and sustainable development strategy in Lithuania. International Journal of Strategic Property Management, 8(3), 163–176. https://doi.org/10.3846/1648715X.2004.9637515
- Einav, L., & Levin, J. (2013). The Data Revolution and Economic Analysis. In NBER Working Paper 53. https://doi.org/10.3386/w19035
- Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2019). On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness. Social Indicators Research, 141(1), 61–94. https://doi.org/10.1007/s11205-017-1832-9
- Gružauskas, V., Kriščiūnas, A., Čalnerytė, D., & Navickas, V. (2020). Analytical Method for Correction Coefficient Determination for Applying Comparative Method for Real Estate Valuation. Real Estate Management and Valuation, 28(2), 52–62. https://doi.org/10.1515/remav-2020-0015
- Kazak, J., van Hoof, J., Świąder, M., & Szewrański, S. (2017). Real estate for the ageing society–the perspective of a new market. Real Estate Management and Valuation, 25(4), 13–24. https://doi.org/10.1515/remav-2017-0026
- Kleinert, C., Vosseler, A., & Blien, U. (2018). Classifying vocational training markets. The Annals of Regional Science, 61(1), 31–48. https://doi.org/10.1007/s00168-017-0856-z
- Kokot, S. (2020). Socio-Economic Factors as a Criterion for the Classification of Housing Markets in Selected Cities in Poland. Real Estate Management and Valuation, 28(3), 77–90. https://doi.org/10.1515/remav-2020-0025
- Li, H. (2019). Multivariate time series clustering based on common principal component analysis. Neurocomputing, 349, 239–247. https://doi.org/10.1016/j.neucom.2019.03.060
- Majerova, I., & Nevima, J. (2017). The measurement of human development using the ward method of cluster analysis. Journal of International Students, 10(2), 239–257. https://doi.org/10.14254/2071-8330.2017/10-2/17
- Manzhynski, S., Siniak, N., Źróbek-Różańska, A., & Źróbek, S. (2016). Sustainability performance in the Baltic Sea Region. Land Use Policy, 57, 489–498. https://doi.org/10.1016/j.landusepol.2016.06.003
- Mattes, M. D., & Sloane, M. A. (2015). Reflections on Hope and Its Implications for End-of-Life Care. Journal of the American Geriatrics Society, 63(5), 993–996. https://doi.org/10.1111/jgs.13392 PMID:25940710
- Nugroho, A. A., Purnama, M. Y. I., & Fauzia, L. R. (2020). Clustering and regional growth in the housing market: Evidence from Indonesia. Jurnal Keuangan Dan Perbankan, 24(1), 83–94. https://doi.org/10.26905/jkdp.v24i1.3565
- Řezanková, H. (2014). Cluster analysis of economic data. Statistika, 94(1), 73–86.
- Rovan, J., & Sambt, J. (2003). Socio-economic Differences Among Slovenian Municipalities : A Cluster Analysis Approach. Developments in Applied Statistics.
- Salvati, L., & Carlucci, M. (2014). A composite index of sustainable development at the local scale: Italy as a case study. Ecological Indicators, 43, 162–171. https://doi.org/10.1016/j.ecolind.2014.02.021
- Seidel, C., Heckelei, T., & Lakner, S. (2019). Conventionalization of Organic Farms in Germany: An Empirical Investigation Based on a Composite Indicator Approach. Sustainability (Basel), 11(10), 2934. https://doi.org/10.3390/su11102934
- de Senna, L. D., Maia, A. G., & de Medeiros, J. D. F. (2019). The use of principal component analysis for the construction of the Water Poverty Index. RBRH (Brazilian Journal of Water Resources), 24, e19, 1–14. https://doi.org/10.1590/2318-0331.241920180084
- Serra, P., Vera, A., & Tulla, A. F. (2014). Spatial and Socio-environmental Dynamics of Catalan Regional Planning from a Multivariate Statistical Analysis Using 1980s and 2000s Data. European Planning Studies, 22(6), 1280–1300. https://doi.org/10.1080/09654313.2013.782388
- Usman, H., Lizam, M., & Adekunle, M. U. (2020). Property price modelling, market segmentation and submarket classifications: A review. Real Estate Management and Valuation, 28(3), 24–35. https://doi.org/10.1515/remav-2020-0021
- Vilnius Institute of Policy Analysis. (2019). Municipality welfare index.
DOI: https://doi.org/10.2478/remav-2021-0020 | Journal eISSN: 2300-5289
Language: English
Page range: 39 - 51
Published on: Aug 13, 2021
Published by: Real Estate Management and Valuation
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
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© 2021 Valentas Gružauskas, Dalia Čalnerytė, Tautvydas Fyleris, Andrius Kriščiūnas, published by Real Estate Management and Valuation
This work is licensed under the Creative Commons Attribution 4.0 License.