caerCentral Asian Economic ReviewCentral Asian Economic Review2789-43982789-4401Университет Нархоз10.52821/2789-4401-2023-1-6-21caer-796Research ArticleГОСУДАРСТВО И БИЗНЕС: ТЕОРИЯ И ПРАКТИКА УПРАВЛЕНИЯSTATE AND BUSINESS: THEORY AND PRACTICE OF MANAGEMENTПРОСТРАНСТВЕННАЯ КОНЦЕНТРАЦИЯ И ПРОИЗВОДИТЕЛЬНОСТЬ ФИРМ В КАЗАХСТАНЕSPATIAL CONCENTRATION AND FIRM-LEVEL PRODUCTIVITY IN KAZAKHSTANhttps://orcid.org/0000-0002-7206-6290АдилхановаЗ. М.AdilkhanovaZ. M.

Астана

Adilkhanova Zarina Muratovna – master of arts in economics, senior researcher, Economic Modeling Development Center

Astana

zarina.adilkhanova@nu.edu.kzNAC Analytica, Назарбаев УниверситетКазахстанNAC Analytica, Nazarbayev UniversityKazakhstan20232006202301621Copyright © Адилханова З.М., 20232023Адилханова З.М.Adilkhanova Z.M.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://caer.narxoz.kz/jour/article/view/796Цель исследования

Цель исследования. В данной статье изучается влияние пространственной агломерации на общую факторную производительность предприятий в Казахстане с использованием панельных данных с 2009 по 2017 год.

Методология

Методология. Мы используем двухэтапную стратегию оценки и контролируем отклонения эндогенности, используя подход обобщенного метода моментов (GMM). Данные на уровне предприятий получены от Бюро национальной статистики Агентства стратегического планирования и реформ Республики Казахстан.

Оригинальность / ценность исследования. Это исследование вносит вклад в эмпирическое исследование пространственной концентрации и производительности на уровне компаний в развивающихся странах и дает ценную информацию для политиков, которую следует учитывать перед реализацией государственных программ.

Результаты исследования

Результаты исследования. Результаты показывают, что производительность увеличивается при объединении в кластеры: 10 % увеличение числа сотрудников соседних фирм в той же отрасли увеличивает производительность на уровне фирмы на 1,36 %, а 10 % увеличение занятости в других отраслях повышает производительность фирмы на 1,95 %. Прирост производительности выше на двузначном региональном уровне, а не на 9-значном субрегиональном уровне географической агрегации, что означает, что более плотная география повышает производительность компаний.

Purpose of the research

Purpose of the research. This paper studies the effect of spatial agglomeration on firms’ total factor productivity in Kazakhstan using panel data from 2009 to 2017.

Methodology

Methodology. We employ a two-stage estimation strategy and control for endogeneity biases by making use of the GMM approach. The firm-level data is obtained from the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan.

Originality / value of the research. This study contributes to an empirical study of spatial concentration and firm-level productivity in developing countries and provides valuable insights for policymakers to consider before implementing government programs.

Findings

Findings. The results suggest that productivity increases with clustering: a 10 % increase in the number of employees of the neighboring firms inside the same industry increases firm-level productivity by 1.36 %, while a 10 % increase in employment in other industries enhances firm performance by 1.95 %. The productivity gains are higher at the 2-digit regional level rather than at the 9-digit sub-regional level of geographical aggregation, implying that the denser geography increases firms’ performance.

агломерационные экономикиобщая факторная производительностьпространственная концентрациякластерыagglomeration economiestotal factor productivityspatial concentrationclustersReferencesStorper M., Venables A. Buzz: face-to-face contact and the urban economy // Journal of Economic Geography. – 2004. – № 4(4). – P. 351-370.Storper M., Venables A. Buzz: face-to-face contact and the urban economy // Journal of Economic Geography. – 2004. – № 4(4). – P. 351-370.Audretsch D., Feldman M. Knowledge spillovers and the geography of innovation // Elsevier: Handbook of Regional and Urban Economics. – 2004. – № 4. – P. 2713-2739.Audretsch D., Feldman M. Knowledge spillovers and the geography of innovation // Elsevier: Handbook of Regional and Urban Economics. – 2004. – № 4. – P. 2713-2739.Carreira C., Lopes L. Regional knowledge spillovers: a firm-based analysis of non-linear effects // Regional Studies. – 2018. – № 52(7). – P. 948-958.Carreira C., Lopes L. Regional knowledge spillovers: a firm-based analysis of non-linear effects // Regional Studies. – 2018. – № 52(7). – P. 948-958.Marshall A. Principles of economics. – Macmillan, London, 1890. – 320 p.Marshall A. Principles of economics. – Macmillan, London, 1890. – 320 p.Berliant M., Reed R., Wang P. Knowledge exchange, matching, and agglomeration // Journal of Urban Economics. – 2006. – № 60(1). – P. 69-95.Berliant M., Reed R., Wang P. Knowledge exchange, matching, and agglomeration // Journal of Urban Economics. – 2006. – № 60(1). – P. 69-95.Wooldridge J. On estimating firm-level production functions using proxy variables to control for unobservables // Economics Letters. – 2009. – № 104. – P. 112-114.Wooldridge J. On estimating firm-level production functions using proxy variables to control for unobservables // Economics Letters. – 2009. – № 104. – P. 112-114.Andersson M., Loof H. Agglomeration and Productivity – evidence from firm-level data // Working Paper Series in Economics and Institutions of Innovation. No. 170. – CESIS, 2009. – 39 p.Andersson M., Loof H. Agglomeration and Productivity – evidence from firm-level data // Working Paper Series in Economics and Institutions of Innovation. No. 170. – CESIS, 2009. – 39 p.Combes P.-P., Duranton G., Gobillon L., Puga D., Roux S. The productivity advantages of large cities: Distinguishing agglomeration from firm selection // Econometrica. – 2012. – № 80(6). – P. 2543-2594.Combes P.-P., Duranton G., Gobillon L., Puga D., Roux S. The productivity advantages of large cities: Distinguishing agglomeration from firm selection // Econometrica. – 2012. – № 80(6). – P. 2543-2594.Harris R., Moffat J. Total factor productivity growth in local enterprise partnership regions in Britain // Regional Studies. – 2015. – № 96(6). – P. 1019-1041.Harris R., Moffat J. Total factor productivity growth in local enterprise partnership regions in Britain // Regional Studies. – 2015. – № 96(6). – P. 1019-1041.Lopez R., Sudekum J. Vertical industry relations, spillovers, and productivity: Evidence from Chilean plants // Journal of Regional Science. – 2009. – № 49(4). – P. 721-747.Lopez R., Sudekum J. Vertical industry relations, spillovers, and productivity: Evidence from Chilean plants // Journal of Regional Science. – 2009. – № 49(4). – P. 721-747.Martin P., Mayer T., Mayneris F. Spatial concentration and plant-level productivity in France // Journal of Urban Economics. – 2011. – № 69(2). – P. 182-195.Martin P., Mayer T., Mayneris F. Spatial concentration and plant-level productivity in France // Journal of Urban Economics. – 2011. – № 69(2). – P. 182-195.Hashiguchi Y., Tanaka K. Agglomeration and firm-level productivity: A Bayesian spatial approach // Papers in Regional Science. – 2015. – № 94. – S95-S114.Hashiguchi Y., Tanaka K. Agglomeration and firm-level productivity: A Bayesian spatial approach // Papers in Regional Science. – 2015. – № 94. – S95-S114.Cainelli G., Ganau R. Distance-based agglomeration externalities and neighboring firms’ characteristics // Regional Studies. – 2018. – № 52(7). – P. 922-933.Cainelli G., Ganau R. Distance-based agglomeration externalities and neighboring firms’ characteristics // Regional Studies. – 2018. – № 52(7). – P. 922-933.DiGiacinto V., Gomellini M., Micucci G., Pagnini M. Mapping local productivity advantages in Italy: Industrial districts, cities or both? // Journal of Economic Geography. – 2014. – № 14. – P. 365-394.DiGiacinto V., Gomellini M., Micucci G., Pagnini M. Mapping local productivity advantages in Italy: Industrial districts, cities or both? // Journal of Economic Geography. – 2014. – № 14. – P. 365-394.Levinsohn J., Petrin A. Estimating production functions using inputs to control for unobservables //Review of Economic Studies. – 2003. – № 70(2). – P. 317-341.Levinsohn J., Petrin A. Estimating production functions using inputs to control for unobservables //Review of Economic Studies. – 2003. – № 70(2). – P. 317-341.Cainelli G., Fracasso A., Marzetti G. V. Spatial agglomeration and productivity in Italy: A panel smooth transition regression approach // Papers in Regional Science. – 2015. – № 94. – S39-S67.Cainelli G., Fracasso A., Marzetti G. V. Spatial agglomeration and productivity in Italy: A panel smooth transition regression approach // Papers in Regional Science. – 2015. – № 94. – S39-S67.Combes P.-P., Gobillon L. The empirics of agglomeration economies // Elsevier: Handbook of urban and regional economics. – 2015. – № 5. – P. 247-348.Combes P.-P., Gobillon L. The empirics of agglomeration economies // Elsevier: Handbook of urban and regional economics. – 2015. – № 5. – P. 247-348.Olley S., Pakes A. Dynamic behavioral responses in longitudinal data sets: Productivity in telecommunications equipment industry // Econometrica. – 1996. – № 64(6). – P. 1263-1297.Olley S., Pakes A. Dynamic behavioral responses in longitudinal data sets: Productivity in telecommunications equipment industry // Econometrica. – 1996. – № 64(6). – P. 1263-1297.Wooldridge J. Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity // Journal of applied econometrics. – 2005. – № 20(1). – P. 39-54.Wooldridge J. Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity // Journal of applied econometrics. – 2005. – № 20(1). – P. 39-54.Ackerberg D., Caves K., Frazer G. Structural identification of production functions? // MPRA Paper, 38349. – 2006. – 42 p.Ackerberg D., Caves K., Frazer G. Structural identification of production functions? // MPRA Paper, 38349. – 2006. – 42 p.Statistical forms for [Electronic resource] // Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan [website]. – 2021. – URL: https://stat.gov.kz/en/respondents/statistical-forms/ (Accessed: 16.01.2023).Statistical forms for [Electronic resource] // Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan [website]. – 2021. – URL: https://stat.gov.kz/en/respondents/statistical-forms/ (Accessed: 16.01.2023).Henderson J. V. Marshall’s scale economies // Journal of Urban Economics. – 2003. – № 53(1). – P. 1-28.Henderson J. V. Marshall’s scale economies // Journal of Urban Economics. – 2003. – № 53(1). – P. 1-28.

The authors declare that there are no conflicts of interest present.