Post carbon city and real estate market: Testing the dataset of reggio calabria market using spline smoothing semiparametric method

Smart Innovation, Systems and Technologies

Volumn 100, Issue , 2019, Pages 206-214

  Del Giudice, Vincenzo ^a   Massimo, Domenico Enrico ^b   De Paola, Pierfrancesco ^a   Forte, Fabiana ^c   Musolino, Mariangela ^b   Malerba, Alessandro ^b  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b UNIVERSITY MEDITERRANEA OF REGGIO CALABRIA   (Italy)

^c SECOND UNIVERSITY OF NAPLES   (Italy)

Author keywords

Green buildings; Penalized spline semiparametric method; Post carbon city; Real estate market analysis; Semiparametric regression

Indexed keywords

CARBON; STATISTICAL TESTS;

GREEN BUILDINGS; POST CARBON CITY; REAL ESTATE MARKET; SEMI-PARAMETRIC REGRESSIONS; SEMIPARAMETRIC;

COMMERCE;

EID: 85048017355     PISSN: 21903018     EISSN: 21903026     Source Type: Book Series    
DOI: 10.1007/978-3-319-92099-3_25     Document Type: Conference Paper

References (29)

1. Ruppert, D., Wand, M.P., Carroll, R.J.: Semiparametris Regressions. Cambridge University Press, Cambridge (2003)
2. Hastie, T., Tibshirani, R.: Generalized Additive Models. Chapman & Hall, New York (1990)
3. Bao, H., Wan, A.: On the use of spline smoothing in estimating hedonic housing price models: empirical evidence using Hong Kong data. Real Estate Econ. 32(3), 487–507 (2004)
4. Opsomer, J.D., Claeskens, G., Ranalli, M.G., Kauermann, G., Breidt, F.J.: Nonparametric small area estimation using penalized spline regression. J. Roy. Stat. Soc. Ser. B 70(1), 265– 286 (2008)
5. Montanari, G.E., Ranalli, M.G.: A mixed model-assisted regression estimator that uses variables employed at the design stage. Stat. Methods Appl. 15(2), 139–149 (2006)
6. Bin, O.: A prediction comparison of housing sales prices by parametric versus semiparametric regressions. J. Hous. Econ. 13(1), 68–84 (2004)
7. Clapp, J.: A semiparametric method for estimating local house price indices. Real Estate Econ. 32(1), 127–160 (2004)
8. Wand, M.P.: Smoothing and mixed models. Comput. Stat. 18, 223–249 (2003)
9. Morano, P., Locurcio, M., Tajani, F., Guarini, M.R.: Fuzzy logic and coherence control in multi-criteria evaluation of urban redevelopment projects. Int. J. Bus. Intell. Data Min. 10(1), 73–93 (2015). Inderscience Enterprises Ltd.
10. Del Giudice, V., De Paola, P.: Spatial analysis of residential real estate rental market. In: D’Amato, M., Kauko, T. (eds.) Advances in Automated Valuation Modeling. Studies in System, Decision and Control, vol. 86. Springer, Cham (2017)
11. Del Giudice, V., De Paola, P., Forte, F.: The appraisal of office towers in bilateral monopoly’s market: evidence from application of Newton’s physical laws to the Directional Centre of Naples. Int. J. Appl. Eng. Res. 11(18), 9455–9459 (2016)
12. Saaty, T.L., De Paola, P.: Rethinking design and urban planning for the cities of the future. Buildings 7, 76 (2017)
13. Del Giudice, V., Manganelli, B., De Paola, P.: Depreciation methods for firm’s assets. In: ICCSA, Part III, Lecture Notes in Computer Science, vol. 9788, pp. 214–227. Springer, Cham (2016)
14. Manganelli, B., Del Giudice, V., De Paola, P.: Linear programming in a multi-criteria model for real estate appraisal. In: ICCSA, Part I, Lecture Notes in Computer Science, vol. 9786, pp. 182–192. Springer, Heidelberg (2016)
15. Del Giudice, V., De Paola, P., Manganelli, B.: Spline smoothing for estimating hedonic housing price models. In: ICCSA, Part III, Lecture Notes in Computer Science, vol. 9157, pp. 210–219. Springer, Cham (2015)
16. Ciuna, M., Milazzo, L., Salvo, F.: A mass appraisal model based on market segment parameters. Buildings 7, 34 (2017)
17. Del Giudice, V., De Paola, P., Manganelli, B., Forte, F.: The monetary valuation of environmental externalities through the analysis of real estate prices. Sustain. MDPI Switz. 9 (2), 229 (2017)
18. Del Giudice, V., De Paola, P., Cantisani, G.B.: Rough set theory for real estate appraisals: an application to Directional District of Naples. Build. MDPI Switz. 7(1), 12 (2017)
19. Del Giudice, V., De Paola, P., Cantisani, G.B.: Valuation of real estate investments through fuzzy logic. Build. MDPI 7(1), 26 (2017)
20. Del Giudice, V., De Paola, P., Forte, F.: Using genetic algorithms for real estate appraisal. Build. MDPI 7(2), 31 (2017)
21. Del Giudice, V., Manganelli, B., De Paola, P.: Hedonic analysis of housing sales prices with semiparametric methods. Int. J. Agric. Environ. Inf. Syst. 8(2), 65–77 (2017). IGI Global Publishing
22. Del Giudice, V., De Paola, P., Forte, F., Manganelli, B.: Real estate appraisals with Bayesian Approach and Markov Chain Hybrid Monte Carlo Method: an application to a Central Urban Area of Naples. Sustainability 9, 2138 (2017)
23. Massimo, D.E.: Stima del green premium per la sostenibilità architettonica mediante Market Comparison Approach. Valori e Valutazioni (2010)
24. Massimo, D.E.: Green building: characteristics, energy implications and environmental impacts. case study in Reggio Calabria, Italy. In: Mildred, C.-S. (ed.) Green Building and Phase Change Materials: Characteristics, Energy Implications and Environmental Impacts, vol. 01, pp. 71–101. Nova Science Publishers (2015)
25. Massimo, D.E. Emerging issues in real estate appraisal: market premium for building sustainability, Aestimum, pp. 653–673 (2013)
26. Massimo D.E., Del Giudice, V., De Paola, P., Forte, F., Musolino, M., Malerba, A.: Geographically weighted regression for the post carbon city and real estate market analysis: a case study. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer. Berlin (2018). ISBN 978-3-319-92098-6
27. De Paola, P., Del Giudice, V., Massimo D.E., Forte, F., Musolino, M., Malerba, A.: Isovalore maps for the spatial analysis of real estate market: a case study for a Central Urban Area of Reggio Calabria, Italy. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6
28. Spampinato, G., Massimo D.E., Musarella, C.M., De Paola, P., Malerba, A., Musolino, M.: Carbon sequestration by cork oak forests and raw material to built up post carbon city. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6
29. Malerba, A., Massimo D.E., Musolino, M., De Paola, P., Nicoletti, F.: Post carbon city: building valuation and energy performance simulation programs. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6