ISSN (print) 1995-2732
ISSN (online) 2412-9003

download PDF

DOI: 10.18503/1995-2732-2026-24-1-176-191

Abstract

The spatial variation in prices depends on the influence of various factors. In the existing literature, empirical studies on this topic differ significantly depending on the type of goods, the objectives of the research and its methodology, and the level of spatial hierarchy under consideration. In this paper, we analyze the studies devoted to the spatial variation of prices of the most common goods, their main determinants, the analytical methods used, and the presence or absence of a spatial component in price changes. Using a systematic approach and the PRISMA method, we have reviewed 278 articles and conducted a content analysis based on the Scopus database and the Tandfonline journal resource. The results have shown that the contemporary literature is dominated by studies related to variations in housing and land prices. The most significant factors influencing the difference in housing prices include architectural characteristics, location (geographical variables), social and economic factors, the presence of local amenities or disamenities, as well as the specifics of housing purchase transactions. The determinants of land price variation are closely related to the type of land plot: residential land prices depend on the accessibility of infrastructure and distance from various social facilities (such as education and healthcare). The most common spatial unit of analysis in land price studies is the country, while the urban scale analyses dominate in research on housing prices. The contribution of this study to the scientific literature is as follows. Firstly, the selected articles in terms of the different types of prices and the methods used to assess the influence of factors on the spatial variation of prices at different levels of space are analyzed. The results obtained may serve as a basis for researchers studying the spatial dynamics of prices. Secondly, it has been found that food prices represent the most promising area for studying seasonal and temporal aspects of spatial price variation.

Keywords

spatial price variation; spatial volatility; housing prices, land prices

The study was carried out with the financial support of the Russian Science Foundation grant No. 24-28-00774, https://rscf.ru/project/24-28-00774/

For citation

Krasnoselskaya D.Kh., Timiryanova V.M., Prudnikov V.B., Gaintseva E.S. Spatial Prices Variation in the Regional Context: a Systematic Review of Foreigh Literature. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2026, vol. 24, no. 1, pp. 176-191. https://doi.org/10.18503/1995-2732-2026-24-1-176-191

Dina Kh. Krasnoselskaya – PhD (Eng.), Senior Researcher, Ufa University of Science and Technology, Ufa, Russia.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-1668-2937

Venera M. Timiryanova – DrSc (Eng.), Chief Researcher, Ufa University of Science and Technology, Ufa, Russia.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-1004-0722

Vadim B. Prudnikov – PhD (Eng.), Associate Professor, Senior Researcher, Ufa University of Science and Technology, Ufa, Russia.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0001-9892-3257

Ekaterina S. Gaintseva – PhD (Eng.), Associate Professor, Ufa University of Science and Technology, Ufa, Russia.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0001-5828-7241

1. Girardin E., Sall Ch. A.T. Inflation dynamics of franc-zone countries determinants, co-movements and spatial interactions. Open Economies Review. 2018;(29(2)):295-320. https://doi.org/10.1007/s11079-017-9456-x

2. Wu G., Zhang C., Liu P., Ren W., Zheng Y., Guo F., Chen X., Higgs R. Spatial quantitative analysis of garlic price data based. Computers, Materials & Continua. 2019;(58(1)):183-195. https://doi.org/10.32604/cmc.2019.03792

3. Cunha A.M., Loureiro R. Housing price dynamics and elasticities: Portugal's conundrum. National Accounting Review. 2024;(6(1)):75-94. https://doi.org/10.3934/NAR.2024004

4. Gray D. Housing market activity diffusion in England and Wales. National Accounting Review. 2023;(5(2)):125-144. https://doi.org/10.3934/nar.2023008

5. Kirikos D.G. An evaluation of quantitative easing effectiveness based on out-of-sample forecasts. National Accounting Review. 2022;(4(4)):378-389. https://doi.org/10.3934/nar.2022021

6. Timiryanova V.M., Lakman I.A., Krasnoselskaya D.Kh., Stol A.V. Dynamics of spatial dependences of prices for vegetables and fruits. Prostranstvennaya ekonomika [Spatial Economics]. 2023;(19(2)):94-125. https://doi.org/10.14530/se.2023.2.094-125. (In Russ.)

7. Timiryanova V., Lakman I., Prudnikov V., Krasnoselskaya D. Spatial dependence of average prices for product categories and its change over time: Evidence from daily data. Forecasting. 2022;(5(1)):102-126. https://doi.org/10.3390/forecast5010004

8. Gluschenko K. Distribution dynamics of Russian regional prices. Empirical Economics. 2016;(51(3)):1193-1213. https://doi.org/10.1007/s00181-015-1039-3.

9. Stupnikova A.V. Spatial behavior of prices in the Russian Federation in 2003–2012. Ekonomicheskie i sotsialnye peremeny: fakty, tendentsii, prognoz [Economic and Social Changes: Facts, Trends, Forecast]. 2014;(3(33)):248-261. https://doi.org/10.15838/esc/2014.3.33.19. (In Russ.)

10. Sinelnikov-Murylev S.G., Perevyshin Y.N., Trunin P.V. Inflation differences in the Russian regions: An empirical analysis. Economy of Region. 2020;(16(2)):479-493. https://doi.org/10.17059/2020-2-11.

11. Kirillov A.M. Spatial analysis of food inflation in Russian regions. Prostranstvennaya ekonomika [Spatial Economics]. 2017;(4):41-58. https://doi.org/10.14530/se.2017.4.041-058. (In Russ.)

12. Ivanova V.I. Convergence of prices on the grain market: the historical aspect. Prostranstvennaya ekonomika [Spatial Economics]. 2015;(3):34-56. https://doi.org/10.14530/se.2015.3.034-056. (In Russ.)

13. Santeramo F.G., Lamonaca E., Contò F., Nardone G., Stasi A. Drivers of grain price volatility: a cursory critical review. Agricultural Economics. 2018;(64(8)):347-356. https://doi.org/10.17221/55/2017-agricecon

14. Gilbert C.L., Morgan C.W. Food price volatility. Philosophical Transactions of the Royal Society B: Biological Sciences. 2010;(365(1554)):3023-3034. https://doi.org/10.1098/rstb.2010.0139

15. Li N., Li R., Nuttapong J. Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database. Property Management. 2022;(40(5)):780-796. https://doi.org/10.1108/pm-11-2020-0078

16. Zheng X., Qian M., Ye X., Zhang M., Zhan C., Li H., Luo T. Implications for long COVID: A systematic review and meta-aggregation of experience of patients diagnosed with COVID-19. Journal of Clinical Nursing. 2024;(33(1)):40-57. https://doi.org/10.1111/jocn.16537

17. Ten S., Raga J.A., Aznar F.J. Epibiotic fauna on cetaceans worldwide: A systematic review of records and indicator potential. Frontiers in Marine Science. 2022;(9). https://doi.org/10.3389/fmars.2022.846558

18. Meerow S., Newell J.P., Stults M. Defining urban resilience: A review. Landscape and urban planning. 2016;(147):38-49. https://doi.org/10.1016/j.landurbplan.2015.11.011

19. Heyman A.V., Law S., Berghauser P.M. How is location measured in housing valuation? A systematic review of accessibility specifications in hedonic price models. Urban Science. 2018;(3(1)). https://doi.org/10.3390/urbansci3010003

20. Rapsomnikis G., Hallam D., Conforti P. Market Integration and Price Transmission in Selected Food and Cash Crop Markets of Developing Countries: Review and Applications. Commodity Market Review. 2003;51-75. Available at: https://openknowledge.fao.org/server/api/core/bitstreams/a41bf51e-e53f-4b0e-afff-dc0aa4c7f5fa/content (Accessed June 17, 2025)

21. Majumder A., Ray R., Santra S. The spatial price map of India drawn using pseudo unit values. Indian Growth and Development Review. 2020;(13(3)):537-560. https://doi.org/10.1108/igdr-09-2019-0092

22. Mishra A., Ray R. Spatial Variation in Prices and Expenditure Inequalities in Australia. Economic Record. 2014;(90(289)):137–159. https://doi.org/10.1111/1475-4932.12109

23. Bergeaud A., Raimbault J. An empirical analysis of the spatial variability of fuel prices in the United States. Transportation Research Part A: Policy and Practice. 2020;(132):131-143. https://doi.org/10.1016/j.tra.2019.10.016

24. Payne M.T., Smith M.G. Price determination and efficiency in the market for water rights in New Mexico’s Middle Rio Grande Basin. International Journal of Water Resources Development. 2013;(29(4)):588-604. https://doi.org/10.1080/07900627.2012.730670

25. Xiao H., Kant S., Xie Y. A spatial hedonic stumpage analysis of standing timber auctions in Jiangxi Province of China. Forest Policy and Economics. 2018;(96(3)):63-74. https://doi.org/10.1016/j.forpol.2018.08.004

26. Pu Z., Li Z., Ash J., Zhu W., Wang Y. Evaluation of spatial heterogeneity in the sensitivity of on-street parking occupancy to price change. Transportation Research Part C: Emerging Technologies. 2017;(77):67-79. https://doi.org/10.1016/j.trc.2017.01.008

27. Latinopoulos D. Using a spatial hedonic analysis to evaluate the effect of sea view on hotel prices. Tourism Management. 2018;(65):87-99. https://doi.org/10.1016/j.tourman.2017.09.019

28. Jiang, Y., Zhang, H., Cao, X., Wei, G., & Yang, Y. How to better incorporate geographic variation in Airbnb price modeling? Tourism Economics. 2023;(29(5)):1181-1203. https://doi.org/10.1177/13548166221097585

29. Chiou, L., Kafali E. Nilay; Rysman M. Internet use, competition, and geographical rescoping in Yellow Pages advertising. Information Economics and Policy. 2020;(52):100867. https://doi.org/10.1016/j.infoecopol.2020.100867

30. Mohammed I., Guillet B.D., Law R. Modeling dynamic price dispersion of hotel rooms in a spatially agglomerated tourism city for weekend and midweek stays. Tourism Economics. 2019;(25(8)):1245-1264. https://doi.org/10.1177/1354816619826829

31. Lee C., Park K. Analyzing the rent-to-price ratio for the housing market at the micro-spatial scale. International Journal of Strategic Property Management. 2018;(22(3)):223-233. https://doi.org/10.3846/ijspm.2018.1416

32. Geng B., Bao H., Liang Y. A study of the effect of a high-speed rail station on spatial variations in housing price based on the hedonic model. Habitat International. 2015;(49):333-339. https://doi.org/10.1016/j.habitatint.2015.06.005

33. Wang B. Is Walmart the same as ten years ago? A non-parametric difference-in-differences analysis of Walmart development. Regional Science and Urban Economics. 2023;(99):103863. https://doi.org/10.1016/j.regsciurbeco.2022.103863

34. De UK, Vupru V. Housing demand and its determinant in a small town in India. J Urban Plan Dev. 2021;147(1):05020036. https://doi:10.1061/(asce)up.1943-5444.0000647.

35. Gao Y., Feng C. Impact of mixed land use on housing prices, spatial differentiation and implications: Empirical analysis based on Qingdao. Applied spatial analysis and policy. 2023;(16(4)):1345-1370. https://doi.org/10.1007/s12061-023-09514-1

36. Costello G, Leishman C, Rowley S., Watkins C. Drivers of spatial change in urban housing submarkets. The Geographical Journal. 2019;(185(4)):432-446. https://doi.org/10.1111/geoj.12303

37. Osland L., Thorsen I.S., Thorsen I. Accounting for local spatial heterogeneities in housing market studies. Journal of Regional Science. 2016;(56(5)):895-920. https://doi.org/10.1111/jors.12281

38. Banzhaf H.S., Farooque O. Interjurisdictional housing prices and spatial amenities: Which measures of housing prices reflect local public goods? Regional Science and Urban Economics. 2013;(43(4)):635-648. https://doi.org/10.1016/j.regsciurbeco.2013.0

39. Li Y., He L., Xu W., Wang H., He Z. Using GIS and Hedonic in the modelling of spatial variation of housing price in Xiamen city. International Review for Spatial Planning and Sustainable Development. 2013;(1(4)):29-42. https://doi.org/10.14246/irspsd.1.4_29

40. Chica-Olmo J., Cano-Guervos R., Chica-Rivas M. Estimation of housing price variations using spatio-temporal data. Sustainability. 2019;11(6):1551. https://doi.org/10.3390/su11061551

41. Yang F., Wu J., Wei Y.D., Wang L. Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China. Land Use Policy. 2018;(75):225-236. https://doi.org/10.1016/j.landusepol.2018.03.045

42. Zou Y. Air pollution and housing prices across Chinese cities. Journal of urban planning and development. 2019;(145(4)):04019012. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000517

43. De U.K., Vupru V. Housing demand and its determinant in a small town in India. Journal of Urban Planning and Development. 2021;(147(1)):05020036. https://doi.org/10.1061/(asce)up.1943-5444.0000647

44. De Bruyne K., Van H.J. Explaining the spatial variation in housing prices: an economic geography approach. Applied Economics. 2013;(45(13)):1673-1689. https://doi.org/10.1080/00036846.2011.636021

45. Rauf M.A., Weber O. Housing sustainability: The effects of speculation and property taxes on house prices within and beyond the jurisdiction. Sustainability. 2022;(14(12)):7496. https://doi.org/10.3390/su14127496

46. Fingleton B., Fuerst F., Szumilo N. Housing affordability: Is new local supply the key? Environment and planning A: economy and space. 2019;(51(1)):25-50. https://doi.org/10.1177/0308518X18798372

47. Duan K., Mishra T., Parhi M., Wolfe S. How effective are policy interventions in a spatially-embedded international real estate market? The journal of real estate finance and economics. 2019;(58(4)):596-637. https://doi.org/10.1007/s11146-018-9654-3

48. Zang T., Gu H. State-space modelling of housing sentiment for regressing changes of real estate prices following short-term control policy in China. Sustainability. 2023;(15(16)):12660. https://doi.org/10.3390/su151612660

49. Coulson N.E., McCoy S.J., McDonough I.K. Economic diversification and the resiliency hypothesis: Evidence from the impact of natural disasters on regional housing values. Regional Science and Urban Economics. 2020;(85):103581. https://doi.org/10.1016/j.regsciurbeco.2020.103581

50. Mou Y., He Q., Zou Bo. Detecting the spatially non-stationary relationships between housing price and its determinants in China: guide for housing market sustainability. Sustainability. 2017;(9(10)):1826. https://doi.org/10.3390/su9101826

51. Oikarinen E., Engblom J. Differences in housing price dynamics across cities: A comparison of different panel model specifications. Urban Studies. 2016;(53(11)):2312-2329. https://doi.org/10.1177/0042098015589883

52. Choi Y., Jeung I., Park J. Comparative Analysis of Spatial Impact of Living Social Overhead Capital on Housing Price by Residential type. KSCE Journal of Civil Engineering. 2021;(25(3)):1056-1065. https://doi.org/10.1007/s12205-021-1250-z

53. Bagheri B., Shaykh-Baygloo R. Spatial analysis of urban smart growth and its effects on housing price: The case of Isfahan, Iran. Sustainable Cities and Society. 2021;(68):102769. https://doi.org/10.1016/j.scs.2021.102769

54. Wu C., Ren F., Hu W., Du Q. Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices. International Journal of Geographical Information Science. 2018;(33(3)):489-511. https://doi.org/10.1080/13658816.2018.1545158

55. Chasco C., Le Gallo J., López F.A. A scan test for spatial groupwise heteroscedasticity in cross-sectional models with an application on houses prices in Madrid. Regional Science and Urban Economics. 2018;(68):226-238. https://doi.org/10.1016/j.regsciurbeco.2017.10.015

56. Mimis A., Rovolis A., Stamou M. Property valuation with artificial neural network: the case of Athens. Journal of Property Research. 2013;(30(2)):128-143. https://doi.org/10.1080/09599916.2012.755558

57. Seifert S., Hüttel S. Is there a risk of a winner’s curse in farmland auctions? European Review of Agricultural Economics. 2023;(50(3)):1140-1177. https://doi.org/10.1093/erae/jbad002

58. Zhang P., Hu S., Li W., Zhang C., Yang S., Qu S. Modeling fine-scale residential land price distribution: An experimental study using open data and machine learning. Applied Geography (Sevenoaks, England). 2021;(129):102442. https://doi.org/10.1016/j.apgeog.2021.102442

59. Yang S., Hu S., Li W., Zhang C., Song D. Spatio-Temporal nonstationary effects of impact factors on industrial land price in industrializing cities of China. Sustainability. 2020;(12(7)):2792. https://doi.org/10.3390/su12072792

60. Ahlfeldt G.M., Nitsch V., Wendland N. Ease vs. noise: Long-run changes in the value of transport (dis)amenities. Journal of Environmental Economics and Management. 2019;(98):102268. https://doi.org/10.1016/j.jeem.2019.102268

61. Chen W., Shen Y., Wang Y. Does industrial land price lead to industrial diffusion in China? An empirical study from a spatial perspective. Sustainable Cities and Society. 2018;(40):307-316. https://doi.org/10.1016/j.scs.2018.04.019

62. Rahardjo N., Marhaento H. Spatio-Temporal Visualization of Land Price Change in the Greater Yogyakarta City, Java, Indonesia. International Journal of Geoinformatics. 2019;(14(4)):47-59. Available at: http://journals.sfu.ca/ijg/index.php/journal/article/view/1233 (Accessed June 17, 2025)

63. Christensen G., Bronchetti E.T. Local food prices and the purchasing power of SNAP benefits. Food Policy. 2020;(95):101937. https://doi.org/10.1016/j.foodpol.2020.101937

64. Achoja F., Gbigbi T. Taze Domatesin Mekansal ve Mevsimsel Fiyat Varyasyonları: Nijerya Örneği. Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi. 2019;(29(2)):330-338. https://doi.org/10.29133/yyutbd.464931

65. Van Campenhout B., Lecoutere E., D’Exelle B. Inter-temporal and spatial price dispersion patterns and the well-being of maize producers in southern Tanzania. Journal of African Economies. 2015;(24(2)):230-253. https://doi.org/10.1093/jae/ejv002

66. Bekkerman A., Taylor M. The role of spatial density and technological investment on optimal pricing strategies in the grain handling industry. Review of Industrial Organization. 2020;(57(1)):27-58. https://doi.org/10.1007/s11151-019-09725-2

67. Katchova A.L., Sant’Anna A.C. Impact of Ethanol Plant Location on Corn Revenues for U.S. Farmers. Sustainability. 2019;(11(22)):6512. https://doi.org/10.3390/su11226512

68. Kitenge E.M., Morshed A.K. Price convergence among Indian cities: The role of linguistic differences, topography, and aggregation. Journal of Asian Economics. 2019;(61):34-50. https://doi.org/10.1016/j.asieco.2019.02.002