Application of spatial econometric methods to analyze factors attracting young faculty to Russian universities

Authors

  • Anastasia Byvaltseva-Stankevich HSE University (Moscow, Russian Federation) Автор
  • Anna Panova HSE University (Moscow, Russian Federation) Автор

DOI:

https://doi.org/10.22394/1993-7601-2025-77-91-115

Keywords:

пространственная эконометрика, российские университеты, молодые преподаватели

Abstract

The aging of university faculty is a crucial problem. We study the issue of attracting young faculty to leading and non-leading Russian universities in 2014–2022. It is the first work where spatial econometric methods use the Russian higher education sector data to account for university interdependence. The study uses three different weight matrices—neighborhood matrix, five nearest neighbors matrix, and inverse distances matrix. An important methodological aspect is the adaptation of matrices built on macrodata (regions) to mesodata (universities). The regression analysis results are robust to the change of spatial matrices. There is a spatial dependence between Russian universities. It is especially noticeable in two separate clusters: leading and non-leading universities; leading universities appear to compete with each other for young faculty. To attract young faculty, Russian universities may increase the remuneration level and decrease the pressure regarding young scholars' publishing activity.
Received: 29 December 2023 · Accepted: 10 October 2024

Agencies

The article was prepared within the framework of the HSE University Basic Research Program.

Downloads

Download data is not yet available.

References

Буфетова А. Н., Коломак Е. А. (2021). Национальная неоднородность в регионах России: оценка, изменение, влияние на экономическое развитие. Вопросы экономики, 1, 120–142. DOI: 10.32609/0042-8736-2021-1-120-142.

Вакуленко Е. С. (2015). Анализ связи между региональными рынками труда в России с использованием модели Оукена. Прикладная эконометрика, 40, 28–48.

Демидова О. А. (2014). Пространственно-авторегрессионная модель для двух групп взаимосвязанных регионов (на примере восточной и западной части России). Прикладная эконометрика, 34, 19–35.

Демидова O. А. (2021). Методы пространственной эконометрики и оценка эффективности государственных программ. Прикладная эконометрика, 64, 107–134.

Демидова О. А., Каяшева Е. В., Демьяненко А. В. (2021). Государственные расходы на здравоохранение и экономический рост в России: региональный аспект. Пространственная экономика, 17 (1), 97–122. DOI: 10.14530/se.2021.1.097-122.

Ефимова Г. З., Грибовский М. В., Сорокин А. Н. (2022). Социальный престиж научно-педагогического работника в России и Европе: специфика субъективного восприятия профессии. Вопросы образования, 2, 117–139. DOI: 10.17323/1814-9545-2022-2-117-139.

Кузьминов Я., Юдкевич М. (2021). Университеты в России: как это работает. М.: Изд. дом Высшей школы экономики. DOI: 10.17323/978-5-7598-2373-5.

Лободина О. Н., Шмидт Ю. Д. (2013). Оценка влияния пространственных факторов на интенсивность инновационных процессов. Известия Дальневосточного федерального университета. Экономика и управление, 3 (67), 20–30.

Рудаков В. Н. (2023). Заработная плата российских преподавателей и ученых: дифференциация, структура и составляющие эффективного контракта. Информационный бюллетень, 7 (49). М.: НИУ ВШЭ.

Семерикова Е. В., Демидова О. А. (2016). Использование пространственных эконометрических моделей при прогнозе регионального уровня безработицы. Прикладная эконометрика, 43, 29–51.

Ackers L., Gill B. (2005). Attracting and retaining 'early career' researchers in English higher education institutions. Innovation, 18 (3), 277–299. DOI: 10.1080/13511610500186649.

Agasisti T., Barra C., Zotti R. (2019). Research, knowledge transfer, and innovation: The effect of Italian universities' efficiency on local economic development 2006–2012. Journal of Regional Science, 59 (5), 819–849. DOI: 10.1111/jors.12427.

Altbach P. G., Yudkevich M., Rumbley L. E. (2015). Academic inbreeding: Local challenge, global problem. Asia Pacific Education Review, 16, 317–330. DOI: 10.1007/s12564-015-9391-8.

Anselin L. (2010). Thirty years of spatial econometrics. Papers in Regional Science, 89 (1), 3–25. DOI: 10.1111/j.1435-5957.2010.00279.x.

Bottasso A., Conti M., Ferrari C., Tei A. (2014). Ports and regional development: A spatial analysis on a panel of European regions. Transportation Research Part A: Policy and Practice, 65, 44–55. DOI: 10.1016/j.tra.2014.04.006.

Brooks K. L., Shepherd J. M. (1989). The issue of aging faculty in higher education. Journal of Professional Nursing, 5 (2), 77–82. DOI: 10.1016/S8755-7223(89)80010-9.

Case A. C. (1991). Spatial patterns in household demand. Econometrica, 59 (4), 953–965. DOI: 10.2307/2938168.

Coates H., Goedegebuure L. (2012). Recasting the academic workforce: Why the attractiveness of the academic profession needs to be increased and eight possible strategies for how to go about this from an Australian perspective. Higher Education, 64, 875–889. DOI: 10.1007/s10734-012-9534-3.

Cole M. A., Elliott R. J., Okubo T., Zhou Y. (2013). The carbon dioxide emissions of firms: A spatial analysis. Journal of Environmental Economics and Management, 65 (2), 290–309. DOI: 10.1016/j.jeem.2012.07.002.

Cordes J., Castro M. C. (2020). Spatial analysis of COVID-19 clusters and contextual factors in New York City. Spatial and Spatio-Temporal Epidemiology, 34, 100355. DOI: 10.1016/j.sste.2020.100355.

Dorenkamp I., Süß S. (2017). Work-life conflict among young academics: Antecedents and gender effects. European Journal of Higher Education, 7 (4), 402–423. DOI: 10.1080/21568235.2017.1304824.

Elhorst J. P. (2010). Applied spatial econometrics: Raising the bar. Spatial Economic Analysis, 5 (1), 9–28. DOI: 10.1080/17421770903541772.

Franch-Pardo I., Napoletano B. M., Rosete-Verges F., Billa L. (2020). Spatial analysis and GIS in the study of COVID-19. A review. Science of the Total Environment, 739, 140033. DOI: 10.1016/j.scitotenv.2020.140033.

Getis A. (2009). Spatial weights matrices. Geographical Analysis, 41 (4), 404–410. DOI: 10.1111/j.1538-4632.2009.00768.x.

Horváth K., Berbegal-Mirabent J. (2022). The role of universities on the consolidation of knowledge-based sectors: A spatial econometric analysis of KIBS formation rates in Spanish regions. Socio-Economic Planning Sciences, 81, 100900. DOI: 10.1016/j.seps.2020.100900.

Karmaeva N. (2018). Career aspirations of young academics in Russia. European Education, 50 (3), 283–299. DOI: 10.1080/10564934.2018.1446177.

Kelejian H., Piras G. (2017). Spatial econometrics. Academic Press.

Lee L. F., Yu J. (2010). Estimation of spatial autoregressive panel data models with fixed effects. Journal of Econometrics, 154 (2), 165–185. DOI: 10.1016/j.jeconom.2009.08.001.

Lim K. S., Moon J. W., Son E. Y., Kim H. R., Lee H. J. (2019). A study on Ph. D. graduate students participation experience in Brain Korea (BK) 21 plus projects. The Journal of Career Education Research, 32 (1), 119–142.

Lovakov A., Panova A., Sterligov I., Yudkevich M. (2021). Does government support of a few leading universities have a broader impact on the higher education system? Evaluation of the Russian University Excellence Initiative. Research Evaluation, 30 (3), 240–255. DOI: 10.1093/reseval/rvab006.

Manski C. F. (1993). Identification of endogenous social effects: The reflection problem. The Review of Economic Studies, 60 (3), 531–542. DOI: 10.2307/2298123.

Mayer J. D. (1983). The role of spatial analysis and geographic data in the detection of disease causation. Social Science & Medicine, 17 (16), 1213–1221. DOI: 10.1016/0277-9536(83)90014-X.

Neuländtner M., Scherngell T. (2022). R&D networks and their effects on knowledge exploration versus knowledge exploitation: Evidence from a spatial econometric perspective. Industry and Innovation, 29 (7), 847–878. DOI: 10.1080/13662716.2022.2063110.

Panova A., Yudkevich M. (2021). Research and higher education in Russia: Moving closer together. In: Universities in the knowledge society: The nexus of national systems of innovation and higher education. The Changing Academy — The Changing Academic Profession in International Comparative Perspective, 22, 183–201. Cham: Springer International Publishing. DOI: 10.1007/978-3-030-76579-8_11.

Pfeiffer D. U., Robinson T. P., Stevenson M., Stevens K. B., Rogers D. J., Clements A. C. (2008). Spatial analysis in epidemiology. OUP Oxford.

RAEX (RAEX-Analitika). (2018). Rejting luchshih vuzov Rossii RAEX-100 (2018 god) (in Russian). https://raex-rr.com/education/russian_universities/top-100_universities/2018/methods/.

Rao M., Vasa L., Xu Y., Chen P. (2023). Spatial and heterogeneity analysis of environmental taxes' impact on China's green economy development: A sustainable development perspective. Sustainability, 15 (12), 9332. DOI: 10.3390/su15129332.

Sardadvar S., Vakulenko E. (2020). Estimating and interpreting internal migration flows in Russia by accounting for network effects. Socio-Economic Planning Sciences, 69, 100685. DOI: 10.1016/j.seps.2019.01.007.

Shah I. A., Yadav A., Afzal F., Shah S. M. Z. A., Junaid D., Azam S., Jonkman M., De Boer F., Ahammad R., Shanmugam B. (2020). Factors affecting staff turnover of young academics: Job embeddedness and creative work performance in higher academic institutions. Frontiers in Psychology, 11, 570345. DOI: 10.3389/fpsyg.2020.570345.

Sivak E., Yudkevich M. (2017). The academic profession in Russia's two capitals: The impact of 20 years of transition. European Educational Research Journal, 16 (5), 626–644. DOI: 10.1177/1474904117701142.

Voytenkov V., Demidova O. (2023). Impact of COVID-19 on household consumption in Russia. Applied Econometrics, 72, 73–99. DOI: 10.22394/1993-7601-2023-72-73-99.

World Bank. (2018). Rolling back Russia's spatial disparities: Re-assembling the Soviet jigsaw under a market economy. World Bank.

Yu D., Wei Y. D. (2008). Spatial data analysis of regional development in Greater Beijing, China, in a GIS environment. Papers in Regional Science, 87 (1), 97–117. DOI: 10.1111/j.1435-5957.2007.00148.x.

Bufetova A., Kolomak E. (2021). National heterogeneity in the regions of Russia: Assessment, change, impact on economic development. Voprosy Ekonomiki, 1, 120–142 (in Russian). DOI: 10.32609/0042‑8736‑2021‑1‑120‑142.

Vakulenko Е. (2015). Analysis of the relationship between regional labour markets in Russia using Okun’s model. Applied Econometrics, 40, 28–48 (in Russian).

Demidova O. (2014). Spatial‑ autoregressive model for the two groups of related regions (eastern and

western parts of Russia). Applied Econometrics, 34, 19–35 (in Russian).

Demidova O. (2021). Methods of spatial econometrics and evaluation of government programs effectiveness. Applied Econometrics, 64, 107–134 (in Russian).

Demidova O., Kayasheva E., Demyanenko A. (2021). Government spending on healthcare and economic growth in Russia: A regional aspect. Spatial Economics, 17 (1), 97–122 (in Russian). DOI: 10.14530/se.2021.1.097‑122.

Efimova G., Gribovskiy M., Sorokin A. (2022). Social prestige of a scientific and pedagogical specialists in Russia and Europe: Paradoxes of subjective perception of the profession. Voprosy Obrazovaniya / Educational Studies Moscow, 2, 117–139 (in Russian). DOI: 10.17323/1814‑9545‑2022‑2‑117‑139.

Kuzminov Y., Yudkevich М. (2021). Universiteti v Rossii: kak eto rabotaet. M.: Higher School of Economics Publishing House (in Russian). DOI: 10.17323/978‑5‑7598‑2373‑5.

Lobodina O., Shmidt Y. (2013). Estimation of the influence of spatial factors on the intensity of innovation processes. Izvestia Dal’nevostochnogo Federal’nogo Universiteta. Ekonomika I Upravlenie,

3 (67), 20–30 (in Russian).

Rudakov V. N. (2023). Salaries of Russian university faculty and researchers: Differentiation, structure

and incentive contracts. Information Bulletin, 7 (49). HSE University, Moscow (in Russian).

Semerikova E., Demidova O. (2016). Using spatial econometric models for regional unemployment forecasting. Applied Econometrics, 43, 29–51 (in Russian).

Ackers L., Gill B. (2005). Attracting and retaining 'early career' researchers in English higher education institutions. Innovation, 18 (3), 277–299. DOI: 10.1080/13511610500186649.

Agasisti T., Barra C., Zotti R. (2019). Research, knowledge transfer, and innovation: The effect of Italian universities' efficiency on local economic development 2006–2012. Journal of Regional Science, 59 (5), 819–849. DOI: 10.1111/jors.12427.

Altbach P. G., Yudkevich M., Rumbley L. E. (2015). Academic inbreeding: Local challenge, global problem. Asia Pacific Education Review, 16, 317–330. DOI: 10.1007/s12564-015-9391-8.

Anselin L. (2010). Thirty years of spatial econometrics. Papers in Regional Science, 89 (1), 3–25. DOI: 10.1111/j.1435-5957.2010.00279.x.

Bottasso A., Conti M., Ferrari C., Tei A. (2014). Ports and regional development: A spatial analysis on a panel of European regions. Transportation Research Part A: Policy and Practice, 65, 44–55. DOI: 10.1016/j.tra.2014.04.006.

Brooks K. L., Shepherd J. M. (1989). The issue of aging faculty in higher education. Journal of Professional Nursing, 5 (2), 77–82. DOI: 10.1016/S8755-7223(89)80010-9.

Case A. C. (1991). Spatial patterns in household demand. Econometrica, 59 (4), 953–965. DOI: 10.2307/2938168.

Coates H., Goedegebuure L. (2012). Recasting the academic workforce: Why the attractiveness of the academic profession needs to be increased and eight possible strategies for how to go about this from an Australian perspective. Higher Education, 64, 875–889. DOI: 10.1007/s10734-012-9534-3.

Cole M. A., Elliott R. J., Okubo T., Zhou Y. (2013). The carbon dioxide emissions of firms: A spatial analysis. Journal of Environmental Economics and Management, 65 (2), 290–309. DOI: 10.1016/j.jeem.2012.07.002.

Cordes J., Castro M. C. (2020). Spatial analysis of COVID-19 clusters and contextual factors in New York City. Spatial and Spatio-Temporal Epidemiology, 34, 100355. DOI: 10.1016/j.sste.2020.100355.

Dorenkamp I., Süß S. (2017). Work-life conflict among young academics: Antecedents and gender effects. European Journal of Higher Education, 7 (4), 402–423. DOI: 10.1080/21568235.2017.1304824.

Elhorst J. P. (2010). Applied spatial econometrics: Raising the bar. Spatial Economic Analysis, 5 (1), 9–28. DOI: 10.1080/17421770903541772.

Franch-Pardo I., Napoletano B. M., Rosete-Verges F., Billa L. (2020). Spatial analysis and GIS in the study of COVID-19. A review. Science of the Total Environment, 739, 140033. DOI: 10.1016/j.scitotenv.2020.140033.

Getis A. (2009). Spatial weights matrices. Geographical Analysis, 41 (4), 404–410. DOI: 10.1111/j.1538-4632.2009.00768.x.

Horváth K., Berbegal-Mirabent J. (2022). The role of universities on the consolidation of knowledge-based sectors: A spatial econometric analysis of KIBS formation rates in Spanish regions. Socio-Economic Planning Sciences, 81, 100900. DOI: 10.1016/j.seps.2020.100900.

Karmaeva N. (2018). Career aspirations of young academics in Russia. European Education, 50 (3), 283–299. DOI: 10.1080/10564934.2018.1446177.

Kelejian H., Piras G. (2017). Spatial econometrics. Academic Press.

Lee L. F., Yu J. (2010). Estimation of spatial autoregressive panel data models with fixed effects. Journal of Econometrics, 154 (2), 165–185. DOI: 10.1016/j.jeconom.2009.08.001.

Lim K. S., Moon J. W., Son E. Y., Kim H. R., Lee H. J. (2019). A study on Ph. D. graduate students participation experience in Brain Korea (BK) 21 plus projects. The Journal of Career Education Research, 32 (1), 119–142.

Lovakov A., Panova A., Sterligov I., Yudkevich M. (2021). Does government support of a few leading universities have a broader impact on the higher education system? Evaluation of the Russian University Excellence Initiative. Research Evaluation, 30 (3), 240–255. DOI: 10.1093/reseval/rvab006.

Manski C. F. (1993). Identification of endogenous social effects: The reflection problem. The Review of Economic Studies, 60 (3), 531–542. DOI: 10.2307/2298123.

Mayer J. D. (1983). The role of spatial analysis and geographic data in the detection of disease causation. Social Science & Medicine, 17 (16), 1213–1221. DOI: 10.1016/0277-9536(83)90014-X.

Neuländtner M., Scherngell T. (2022). R&D networks and their effects on knowledge exploration versus knowledge exploitation: Evidence from a spatial econometric perspective. Industry and Innovation, 29 (7), 847–878. DOI: 10.1080/13662716.2022.2063110.

Panova A., Yudkevich M. (2021). Research and higher education in Russia: Moving closer together. In: Universities in the knowledge society: The nexus of national systems of innovation and higher education. The Changing Academy — The Changing Academic Profession in International Comparative Perspective, 22, 183–201. Cham: Springer International Publishing. DOI: 10.1007/978-3-030-76579-8_11.

Pfeiffer D. U., Robinson T. P., Stevenson M., Stevens K. B., Rogers D. J., Clements A. C. (2008). Spatial analysis in epidemiology. OUP Oxford.

RAEX (RAEX-Analitika). (2018). Rejting luchshih vuzov Rossii RAEX-100 (2018 god) (in Russian). https://raex-rr.com/education/russian_universities/top-100_universities/2018/methods/.

Rao M., Vasa L., Xu Y., Chen P. (2023). Spatial and heterogeneity analysis of environmental taxes' impact on China's green economy development: A sustainable development perspective. Sustainability, 15 (12), 9332. DOI: 10.3390/su15129332.

Sardadvar S., Vakulenko E. (2020). Estimating and interpreting internal migration flows in Russia by accounting for network effects. Socio-Economic Planning Sciences, 69, 100685. DOI: 10.1016/j.seps.2019.01.007.

Shah I. A., Yadav A., Afzal F., Shah S. M. Z. A., Junaid D., Azam S., Jonkman M., De Boer F., Ahammad R., Shanmugam B. (2020). Factors affecting staff turnover of young academics: Job embeddedness and creative work performance in higher academic institutions. Frontiers in Psychology, 11, 570345. DOI: 10.3389/fpsyg.2020.570345.

Sivak E., Yudkevich M. (2017). The academic profession in Russia's two capitals: The impact of 20 years of transition. European Educational Research Journal, 16 (5), 626–644. DOI: 10.1177/1474904117701142.

Voytenkov V., Demidova O. (2023). Impact of COVID-19 on household consumption in Russia. Applied Econometrics, 72, 73–99. DOI: 10.22394/1993-7601-2023-72-73-99.

World Bank. (2018). Rolling back Russia's spatial disparities: Re-assembling the Soviet jigsaw under a market economy. World Bank.

Yu D., Wei Y. D. (2008). Spatial data analysis of regional development in Greater Beijing, China, in a GIS environment. Papers in Regional Science, 87 (1), 97–117. DOI: 10.1111/j.1435-5957.2007.00148.x.

Downloads

Published

2025-01-15

Issue

Section

Статьи

How to Cite

Byvaltseva-Stankevich A., Panova A. Application of spatial econometric methods to analyze factors attracting young faculty to Russian universities // Applied Econometrics. 2025. Vol. 77, no. 1. P. 91–115. https://doi.org/10.22394/1993-7601-2025-77-91-115