Aging, industrial robot input and export performance: evidence from Chinese industrial firms

DOI: https://doi.org/10.3846/tede.2026.26766

Abstract

With the acceleration of aging and the development of robot, it affects the economic and trade development of countries around the world. However, few papers have provided insight into whether and how industrial robot input affects export in an aging real economy. This study examines the relationship between aging, industrial robot input and export performance from both theoretical and empirical perspectives. Theoretically, it integrates aging and industrial robot into a model of heterogeneous firms for analysis. Empirically, the study utilizes industrial firm data, customs data and census data in China from 2002 to 2016, established a fixed-effect regression model, complemented by a series of robustness tests and analyses of heterogeneity. The findings indicate that, although aging results in increased labour costs for firms and constrains research and development expenditure by both local governments and businesses, the negative impact of aging can be somewhat mitigated by the substitution, creation, and productivity effects of industrial robot inputs. While we may be unable to control the inevitability of aging and the rapid advancement of artificial intelligence, we can attain a deeper understanding of their theoretical mechanisms and transmission pathways. By adapting to these trends, we can offer valuable policy recommendations and theoretical foundations to support the economic development of countries.

First published online 8 June 2026

Keywords:

population aging, industrial robot input, export, labor market, artificial intelligence

How to Cite

Liu, X., Su, R., & Wei, S. (2026). Aging, industrial robot input and export performance: evidence from Chinese industrial firms. Technological and Economic Development of Economy, 1-29. https://doi.org/10.3846/tede.2026.26766

Share

Published in Issue
June 8, 2026
Abstract Views
56

References

Acemoglu, D., & Restrepo, P. (2017). Robots and jobs: Evidence from us labor markets (MIT Department of Economics Working Paper No. 17-04). https://doi.org/10.2139/ssrn.2940245

Acemoglu, D., & Restrepo, P. (2018). Demographics and automation (Working Paper No. 24421). National Bureau of Economic Research. https://doi.org/10.3386/w24421

Acemoglu, D. (2022). Obedience in the labour market and social mobility: A socioeconomic approach. Economica, 89(S1), S2–S37. https://doi.org/10.1111/ecca.12406

Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in U.S. wage inequality. Econometrica, 90(5), 1973–2016. https://doi.org/10.3982/ECTA19815

Acemoglu, D., Autor, D., Hazell, J., & Restrepo, P. (2022). Artificial intelligence and jobs: Evidence from online vacancies. Journal of Labor Economics, 40(S1). https://doi.org/10.1086/718327

Bas, M., & Strauss-Kahn, V. (2015). Input-trade liberalization, export prices and quality upgrading. Journal of International Economics, 95(2), 250–262. https://doi.org/10.1016/j.jinteco.2014.12.005

Artuc, E., Bastos, P., & Rijkers, B. (2023). Robots, tasks, and trade. Journal of International Economics, 145, Article 103828. https://doi.org/10.1016/j.jinteco.2023.103828

Bekkers, E. (2011). Heterogeneous popularity and exporting uncertainty. Open Economies Review, 22, 797–824. https://doi.org/10.1007/s11079-010-9176-y

Bertschek, I., & Meyer, J. (2009). Do older workers lower it-enabled productivity? Firm-level evidence from Germany (ZEW – Centre for European Economic Research Discussion Paper No. 08-129). https://doi.org/10.2139/ssrn.1389201

Bester, H., & Petrakis, E. (2003). Wages and productivity growth in a competitive industry. Journal of Economic Theory, 109(1), 52–69. https://doi.org/10.1016/S0022-0531(02)00037-6

Bloom, D. E., Chatterji, S., Kowal, P., Lloyd-Sherlock, P., Mckee, M., Rechel, B., Rosenberg, L., & Smith, J. (2015). Macroeconomic implications of population aging and selected policy responses. The Lancet, 385(9968), 649–657. https://doi.org/10.1016/S0140-6736(14)61464-1

Cai, F. (2010). Demographic transition, demographic dividend, and Lewis turning point in China. Economic Research, 45(4), 4–13.

Cai, Z., & Qi, J. (2021). Does the adoption of industrial robots upgrade the export product quality – evidence from Chinese manufacturing enterprises. Journal of International Trade, (10), 17–33. https://doi.org/10.13510/j.cnki.jit.2021.10.002

Cai, H. B., & Han. J. Y. (2022). Population aging and the transformation of urban export. China Industrial Economics, (11), 61–77.

Cheng, H. F. (2002). Foreign direct investment and open endogenous economic growth. Economic Research, (10), 71–78+96.

Czaja, S. J., & Lee, C. C. (2007). The impact of aging on access to technology. Universal Access in the Information Society, 5, 341–349. https://doi.org/10.1007/s10209-006-0060-x

Czarnitzki, D., & Licht, G. (2010). Additionality of public R&D grants in a transition economy. Economics of Transition, 14(1), 101–131. https://doi.org/10.1111/j.1468-0351.2006.00236.x

Díaz Pavez, L. R., & Martínez-Zarzoso, I. (2024). The impact of automation on labour market outcomes in emerging countries. The World Economy, 47, 298–331. https://doi.org/10.1111/twec.13523

Destefano, T., & Timmis, J. (2024). Robots and export quality. Journal of Development Economics, 168, Article 103248. https://doi.org/10.1016/j.jdeveco.2023.103248

Dou, J. C. (2019). The effect of aging on innovation: Mechanism and its implications to China. Population and Economics, (5), 78–93.

Du, Y., & Qu, Y. (2009). Labor reward, labor productivity and the advantage of labor cost – an empirical analysis based on the data of manufacturing firm from 2000–2007. China Industrial Economics, (5), 25–35.

Du, L., & Lin, W. (2022). Does the application of industrial robots overcome the Solow paradox? Evidence from China. Technology in Society, 68, Article 101932. https://doi.org/10.1016/j.techsoc.2022.101932

Engbom, N. (2019). Firm and worker dynamics in an aging labor market (Working Paper No. 756). Federal Reserve bank of Mineapolis, Research Department. https://doi.org/10.21034/wp.756

Fan, H., Hu, Y., & Tang, L.(2021). Labor costs and the adoption of robots in China. Journal of Economic Behavior and Organization, 186, 608–631. https://doi.org/10.1016/j.jebo.2020.11.024

Feng, J., & Li. Y. T. (2023). Population aging and firm entry: A study based on China’s prefecture-level cities. The Journal of World Economy, (4), 170–191.

Feng, J., Zhao, F. Q., & Song, H. (2024). What we lose in hake we Shall have in herring: Aging and changes in labor productivity in the automation era. Journal of Social Sciences, (8), 142–155.

Graetz, G., & Michaels, G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753–768. https://doi.org/10.1162/rest_a_00754

Goh, S. K., McNown, R., & Wong, K. N. (2020). Macroeconomic implications of population aging: Evidence from Japan. Journal of Asian Economics, 68, Article 101198. https://doi.org/10.1016/j.asieco.2020.101198

Gong, C., Yang, X., Tan, H., & Lu, X. (2023). Industrial robots, economic growth, and sustainable development in an aging society. Sustainability, 15(5), Article 4590. https://doi.org/10.3390/su15054590

He, X. G., Guo, X. B., & Kuang, Y. Q. (2024). Can robot application promote firm exports? Based on the win-win perspective of efficiency and quality. Research on Financial and Economic Issues, (4), 57–70.

Kanfer, R., & Ackerman, P. (2000). Individual differences in work motivation: Further explorations of a trait framework. Applied Psychology, 49(3), 470–482. https://doi.org/10.1111/1464-0597.00026

Kapetaniou, C., & Pissarides, C. A. (2025). Productive robots and industrial employment: The role of national innovation systems. International Economic Review, 66(1), 25–52. https://doi.org/10.1111/iere.12738

Krueger, D. (2006). On the consequences of demographic change for international capital flows, rates of returns to capital, and the distribution of wealth and welfare (Working Paper No. 12453). National Bureau of Economic Reserch. https://doi.org/10.3386/w12453

Li, L., Wang, X. X., & Bao, Q. (2021). The employment effect of robots: Mechanism and evidence from China. Management World, (9), 104–119.

Liu, C. K., & Lin, M. Y. (2020). Population aging, human capital accumulation and high-quality. Economic Development, (07), 168–179.

Long, Y. T., Liu, H. B., & Cai, Y. Z. (2020). The study of the impact of artificial intelligence on labor’s employment – from the perspective of literature review. China Soft Science, (12), 56–64.

Lutz, W., Sanderson, W., & Scherbov, S. (2008). The coming acceleration of global population ageing. Nature, 451, 716–719. https://doi.org/10.1038/nature06516

Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6), 1695–1725. https://doi.org/10.1111/1468-0262.00467

Naito, T., & Zhao, L. (2009). Aging, transitional dynamics, and gains from trade. Journal of Economic Dynamics and Control, 33(8), 1531–1542. https://doi.org/10.1016/j.jedc.2009.02.006

Naudé, W., Gries, T., & Bilkic, N. (2015). Playing the lottery or dressing up? A model of firm-level heterogeneity and the decision to export. The Quarterly Review of Economics and Finance, 58, 1–17. https://doi.org/10.1016/j.qref.2015.02.010

Nie, H., Jiang, T., & Yang, R. (2012). The current usage status and potential problems of the Chinese industrial enterprise database. The Journal of World Economy, 35(5), 142–158. https://doi.org/10.19985/j.cnki.cassjwe.2012.05.009

Ndubuisi, G., & Avenyo, E. (2018). Estimating the effects of robotization on exports (MERIT Working Paper No. 2018-046). United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology.

Ruggeri, J., & Zou, Y. (2007). The fiscal burden of rising dependency ratios. Population Research and Policy Review, 26, 185–201. https://doi.org/10.1007/s11113-007-9027-8

Silvanto, S., Ryan, J., & McNulty, Y. (2015). An empirical study of nation branding for attracting internationally mobile skilled professionals. Career Development International, 20(3), 238–258. https://doi.org/10.1108/CDI-08-2014-0105

Tan, N., Liang, X., & Chang, L. (2024). Growing older and growing technologically backward? Population aging and high-technology exports of 171 countries. The Journal of the Economics of Aging, 29, Article 100530. https://doi.org/10.1016/j.jeoa.2024.100530

Tian, W., & Yu, S. J. (2014). Lntermediate goods trade liberalization and firm RandD: An empirical analysis based on Chinese data. The Journal of World Economy, (6), 90–112.

Tian, S. H., & Wang, X. (2021). Trade connections and exports effects of productive subsidies – empirical test based on export products micro-data at the HS-6 digit level. Journal of International Trade, (6), 63–79.

Torres, F. O. (2019). Firm heterogeneity and exports in Portugal: Identifying export potential (GEE Paper No. 118). Universidade NOVA de Lisboa (Portugal).

Tu, W.-J., Zeng, X., & Liu, Q. (2022). Aging tsunami coming: The main finding from China’s seventh national population census. Aging Clinical and Experimental Research, 34, 1159–1163. https://doi.org/10.1007/s40520-021-02017-4

United Nations. (2024). World population prospects 2024: Summary of results (UN DESA/POP/2024/TR/NO. 9). Department of Economic and Social Affairs. https://population.un.org/wpp/assets/Files/WPP2024_Summary-of-Results.pdf

Wang, W., Liu, Y. F., & Peng, D. (2015). Research on effects of population aging on industrial upgrading. China Industrial Economics, (11), 47–61.

Wang, L., Zhao, H., Cao, Z., & Dong, Z. (2024). Artificial intelligence and intergenerational occupational mobility. Journal of Asian Economics, 90, Article 101675. https://doi.org/10.1016/j.asieco.2023.101675

Wu, F., Yang, H., Gao, B., & Gu, Y. (2021). Old, not yet rich? The impact of population aging on export upgrading in developing countries. China Economic Review, 70, Article 101707. https://doi.org/10.1016/j.chieco.2021.101707

Xu, J. Y., Mao, Q. L., & Hu, A. G. (2017). Intermediate input imports and the quality upgrading of export product: Evidence from Chinese manufacturing firms. The Journal of World Economy, (3), 52–75.

Yakita, A. (2014). Effects of capital taxation on economies with different demographic changes: Short term versus long term. Journal of Popular Economy, 27, 257–273 https://doi.org/10.1007/s00148-013-0480-x

Yang, J., & Ma, Y. Q. (2011). China’s high savings rate and external imbalance: A demographic perspective. Journal of International Trade, (12), 148–157.

Yang, L. G., Xie, R., He, Z. C, Han, F., & Sun, Y. L. (2014). Research on the impact of rising labor cost on manufacturing structure upgrading – An empirical analysis based on the data of sub-sectors of Chinese manufacturing. China Soft Science, (12), 136–147.

Yuan, L. L., & Luo. C. L. (2023). Pension contribution rate changes and firms’ employment “Creation-destruction” adjustments. The Journal of Quantitative and Technical Economics, (4), 180–202.

Yuan, J., Liu, Q. R., & Zhao, C. (2024). Urban industrial robot penetration and China’s manufacturing exports: Evidence from multidimensional data. Economic Perspectives, (3), 25–43.

Yuan, Y., Chen, H., Ge, Y., Huang, X., & Yang, G. (2025). Industrial robot imports and firm innovation: A large language model. The World Economy, 48(10), 2242–2260. https://doi.org/10.1111/twec.13727

Zhao, R. L., Sun, C. R., & Chen, Y. B. (2016). The effect of minimum wage standards on firms’ export duration. The Journal of World Economy, 39(7), 97–120.

Zhou, H., Fan, J., & Gan, T. (2024). The impact of industrial robots on export stability. The World Economy, 47(9), 3780–3808. https://doi.org/10.1111/twec.13602

Zhou, H. M., & Lei, G. Y. (2017). Demographic dividend, investment and regional differences: An empirical analysis based on provincial data in China. Journal of Finance and Economics, (2), 35–40.

View article in other formats

CrossMark check

CrossMark logo

Published

2026-06-08

Issue

Section

Articles

How to Cite

Liu, X., Su, R., & Wei, S. (2026). Aging, industrial robot input and export performance: evidence from Chinese industrial firms. Technological and Economic Development of Economy, 1-29. https://doi.org/10.3846/tede.2026.26766

Share