The shrinking middle: exploring the nexus between information and communication technology, growth, and inequality
Abstract
To implement specific actions to respond to challenges accompanied by technological advances, it is essential to realize the foreseen future at different levels. This study aims to generate the forecasts of different prospects of different industries, labor market, and households, depending on the pervasiveness of the information and communication (ICT) software (SW) in production. For the analysis, we propose a computable general equilibrium (CGE) model that explicitly incorporates diverse impact channels induced by ICT SW investments. Our simulation results suggest that the development of ICT SW technology can bring about both opportunities and challenges in the economic system. The results also show that advancements in ICT SW can aggravate inequalities within the economic system, while driving higher economic growth effects by accelerating the polarization of the labor market and wages/income distributions. Accordingly, our results suggest that policymakers should formulate tailored policy options to mitigate structural problems and widen income disparities driven by ICT-specific technological advances to achieve economic inclusiveness.
Keyword : ICT advances, ICT SW, growth, distribution, computable general equilibrium
How to Cite
Yeo, Y., Hwang, W.-S., & Lee, J.-D. (2023). The shrinking middle: exploring the nexus between information and communication technology, growth, and inequality. Technological and Economic Development of Economy, 29(3), 874–901. https://doi.org/10.3846/tede.2023.18713
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Babatunde, K. A., Begum, R. A., & Said, F. F. (2017). Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review. Renewable and Sustainable Energy Reviews, 78, 61–71. https://doi.org/10.1016/j.rser.2017.04.064
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Eden, M., & Gaggl, P. (2018). On the welfare implications of automation. Review of Economic Dynamics, 29, 15–43. https://doi.org/10.1016/j.red.2017.12.003
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Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
Giuri, P., Torrisi, S., & Zinovyeva, N. (2008). ICT, skills, and organizational change: Evidence from Italian manufacturing firms. Industrial and Corporate Change, 17(1), 29–64. https://doi.org/10.1093/icc/dtm038
Goos, M., Manning, A., & Salomons, A. (2014). Explaining job polarization: Routine-biased technological change and offshoring. American Economic Review, 104(8), 2509–2526. https://doi.org/10.1257/aer.104.8.2509
Grossman, G. M., & Oberfield, E. (2022). The elusive explanation for the declining labor share. Annual Review of Economics, 14, 93–124. https://doi.org/10.1146/annurev-economics-080921-103046
Guo, Z., Zhang, X., Ding, Y., & Zhao, X. (2021). A forecasting analysis on China’s energy use and carbon emissions based on a dynamic computable general equilibrium model. Emerging Markets Finance and Trade, 57(3), 727–739. https://doi.org/10.1080/1540496X.2019.1597704
Hagsten, E., & Sabadash, A. (2017). A neglected input to production: The role of ICT-schooled employees in firm performance. International Journal of Manpower, 38(3), 373–391. https://doi.org/10.1108/IJM-05-2015-0073
Hesenius, M., Schwenzfeier, N., Meyer, O., Koop, W., & Gruhn, V. (2019, May). Towards a software engineering process for developing data-driven applications. In 2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) (pp. 35–41), Montreal, QC, Canada. IEEE. https://doi.org/10.1109/RAISE.2019.00014
Heyman, F. (2016). Job polarization, job tasks and the role of firms. Economics Letters, 145, 246–251. https://doi.org/10.1016/j.econlet.2016.06.032
Hong, C., & Lee, J. D. (2016). Macroeconomic effects of R&D tax credits on small and medium enterprises. Economic Systems Research, 28(4), 467–481. https://doi.org/10.1080/09535314.2016.1240067
Hwang, W. S., & Shim, D. (2021). Measuring the impact of ICT-driven product and process innovation on the Korean economy. Global Economic Review, 50(3), 235–253. https://doi.org/10.1080/1226508X.2021.1884114
Hwang, W. S., & Shin, J. (2017). ICT-specific technological change and economic growth in Korea. Telecommunications Policy, 41(4), 282–294. https://doi.org/10.1016/j.telpol.2016.12.006
Hwang, W. S., Yeo, Y., Oh, I., Hong, C., Jung, S., Yang, H., & Lee, J. D. (2021). CGE analysis of R&D investment policy considering trade-offs between economic growth and stability. Science and Public Policy, 48(3), 295–308. https://doi.org/10.1093/scipol/scaa068
Järvensivu, P., Räisänen, H., & Hukkinen, J. I. (2021). A simulation exercise for incorporating long-term path dependencies in urgent decision-making. Futures, 132, 102812. https://doi.org/10.1016/j.futures.2021.102812
Jorgenson, D. W., & Vu, K. M. (2016). The ICT revolution, world economic growth, and policy issues. Telecommunications Policy, 40(5), 383–397. https://doi.org/10.1016/j.telpol.2016.01.002
Jung, S., Lee, J. D., Hwang, W. S., & Yeo, Y. (2017). Growth versus equity: A CGE analysis for effects of factor-biased technical progress on economic growth and employment. Economic Modelling, 60, 424–438. https://doi.org/10.1016/j.econmod.2016.10.014
Korean Productivity Center. (2016). Productivity statistics. Korea Productivity Center.
Lankisch, C., Prettner, K., & Prskawetz, A. (2019). How can robots affect wage inequality? Economic Modelling, 81, 161–169. https://doi.org/10.1016/j.econmod.2018.12.015
Mallick, S. K., & Sousa, R. M. (2017). The skill premium effect of technological change: New evidence from United States manufacturing. International Labour Review, 156(1), 113–131. https://doi.org/10.1111/j.1564-913X.2015.00047.x
Michaels, G., Natraj, A., & Van Reenen, J. (2014). Has ICT polarized skill demand? Evidence from eleven countries over twenty-five years. Review of Economics and Statistics, 96(1), 60–77. https://doi.org/10.1162/REST_a_00366
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Park, C., & Park, J. (2020). COVID-19 and the Korean Economy: When, how, and what changes? Asian Journal of Innovation and Policy, 9(2), 187–206. https://doi.org/10.7545/ajip.2020.9.2.187
Park, J., Moore, J. E., Gordon, P., & Richardson, H. W. (2017). A new approach to quantifying the impact of hurricane-disrupted oil refinery operations utilizing secondary data. Group Decision and Negotiation, 26(6), 1125–1144. https://doi.org/10.1007/s10726-017-9537-7
Pyo, H. K., Hee, K., & Ha, B. (2009). Estimation of labor and total factor productivity by 72 industries in Korea (1970–2003). In Productivity measurement and analysis (pp. 527–550). OECD Publishing, Paris. https://doi.org/10.1787/9789264044616-25-en
Richmond, K., & Triplett, R. E. (2018). ICT and income inequality: A cross-national perspective. International Review of Applied Economics, 32(2), 195–214. https://doi.org/10.1080/02692171.2017.1338677
Rickman, D. S. (2010). Modern macroeconomics and regional economic modeling. Journal of Regional Science, 50(1), 23–41. https://doi.org/10.1111/j.1467-9787.2009.00647.x
Sawng, Y. W., Kim, P. R., & Park, J. (2021). ICT investment and GDP growth: Causality analysis for the case of Korea. Telecommunications Policy, 45(7), 102157. https://doi.org/10.1016/j.telpol.2021.102157
Schreyer, P. (2000). The contribution of information and communication technology to output growth: A study of the G7 countries. OECD Publishing.
Tambe, P., Hitt, L., Rock, D., & Brynjolfsson, E. (2020). Digital capital and superstar firms (NBER Working Paper 28285). National Bureau of Economic Research. https://doi.org/10.3386/w28285
Taniguchi, H., & Yamada, K. (2019). ICT capital-skill complementarity and wage inequality: Evidence from OECD countries. OECD publishing.
Taştan, H., & Gönel, F. (2020). ICT labor, software usage, and productivity: Firm-level evidence from Turkey. Journal of Productivity Analysis, 53(2), 265–285. https://doi.org/10.1007/s11123-020-00573-x
Vu, K., Hanafizadeh, P., & Bohlin, E. (2020). ICT as a driver of economic growth: A survey of the literature and directions for future research. Telecommunications Policy, 44(2), 101922. https://doi.org/10.1016/j.telpol.2020.101922
Yeo, Y., & Lee, J. D. (2020). Revitalizing the race between technology and education: Investigating the growth strategy for the knowledge-based economy based on a CGE analysis. Technology in Society, 62, 101295. https://doi.org/10.1016/j.techsoc.2020.101295
Yeo, Y., Lee, J. D., & Jung, S. (2021). Winners and losers in a knowledge-based economy: Investigating the policy packages for an inclusive growth based on a computable general equilibrium analysis of Korea. Journal of the Asia Pacific Economy, 1–37. https://doi.org/10.1080/13547860.2021.1982193
Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716
Acemoglu, D., & Restrepo, P. (2022). Demographics and automation. The Review of Economic Studies, 89(1), 1–44. https://doi.org/10.1093/restud/rdab031
Akerman, A., Gaarder, I., & Mogstad, M. (2015). The skill complementarity of broadband internet. The Quarterly Journal of Economics, 130(4), 1781–1824. https://doi.org/10.1093/qje/qjv028
Alvarez-Cuadrado, F., Van Long, N., & Poschke, M. (2018). Capital-labor substitution, structural change and the labor income share. Journal of Economic Dynamics and Control, 87, 206–231. https://doi.org/10.1016/j.jedc.2017.12.010
Autor, D., & Salomons, A. (2018). Is automation labor-displacing? Productivity growth, employment, and the labor share (NBER No. 24871). National Bureau of Economic Research. https://doi.org/10.3386/w24871
Babatunde, K. A., Begum, R. A., & Said, F. F. (2017). Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review. Renewable and Sustainable Energy Reviews, 78, 61–71. https://doi.org/10.1016/j.rser.2017.04.064
Berg, A., Buffie, E. F., & Zanna, L. F. (2018). Should we fear the robot revolution? (The correct answer is yes). Journal of Monetary Economics, 97, 117–148. https://doi.org/10.1016/j.jmoneco.2018.05.014
Böhm, M. J. (2020). The price of polarization: Estimating task prices under routine‐biased technical change. Quantitative Economics, 11(2), 761–799. https://doi.org/10.3982/QE1031
Brynjolfsson, E., Rock, D., & Syverson, C. (2019). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. University of Chicago Press. https://doi.org/10.7208/chicago/9780226613475.003.0001
Buera, F. J., Kaboski, J. P., Rogerson, R., & Vizcaino, J. I. (2022). Skill-biased structural change. The Review of Economic Studies, 89(2), 592–625. https://doi.org/10.1093/restud/rdab035
Caines, C., Hoffmann, F., & Kambourov, G. (2017). Complex-task biased technological change and the labor market. Review of Economic Dynamics, 25, 298–319. https://doi.org/10.1016/j.red.2017.01.008
Cardona, M., Kretschmer, T., & Strobel, T. (2013). ICT and productivity: Conclusions from the empirical literature. Information Economics and Policy, 25(3), 109–125. https://doi.org/10.1016/j.infoecopol.2012.12.002
Chen, H., Yu, J., & Wakeland, W. (2016). Generating technology development paths to the desired future through system dynamics modeling and simulation. Futures, 81, 81–97. https://doi.org/10.1016/j.futures.2016.01.002
Cirillo, V., Evangelista, R., Guarascio, D., & Sostero, M. (2021). Digitalization, routineness and employment: An exploration on Italian task-based data. Research Policy, 50(7), 104079. https://doi.org/10.1016/j.respol.2020.104079
DeStefano, T., Kneller, R., & Timmis, J. (2018). Broadband infrastructure, ICT use and firm performance: Evidence for UK firms. Journal of Economic Behavior & Organization, 155, 110–139. https://doi.org/10.1016/j.jebo.2018.08.020
Donati, C., & Sarno, D. (2013). The impact of ICT on productivity of Italian firms: Evaluation of the micro-complementarity hypothesis. Applied Economics Letters, 20(4), 349–352. https://doi.org/10.1080/13504851.2012.703309
Doraszelski, U., & Jaumandreu, J. (2018). Measuring the bias of technological change. Journal of Political Economy, 126(3), 1027–1084. https://doi.org/10.1086/697204
Eden, M., & Gaggl, P. (2018). On the welfare implications of automation. Review of Economic Dynamics, 29, 15–43. https://doi.org/10.1016/j.red.2017.12.003
Feng, A., & Graetz, G. (2015). Rise of the machines: The effects of labor-saving innovations on jobs and wages (IZA Discussion Paper No. 8836). https://doi.org/10.2139/ssrn.2564969
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
Giuri, P., Torrisi, S., & Zinovyeva, N. (2008). ICT, skills, and organizational change: Evidence from Italian manufacturing firms. Industrial and Corporate Change, 17(1), 29–64. https://doi.org/10.1093/icc/dtm038
Goos, M., Manning, A., & Salomons, A. (2014). Explaining job polarization: Routine-biased technological change and offshoring. American Economic Review, 104(8), 2509–2526. https://doi.org/10.1257/aer.104.8.2509
Grossman, G. M., & Oberfield, E. (2022). The elusive explanation for the declining labor share. Annual Review of Economics, 14, 93–124. https://doi.org/10.1146/annurev-economics-080921-103046
Guo, Z., Zhang, X., Ding, Y., & Zhao, X. (2021). A forecasting analysis on China’s energy use and carbon emissions based on a dynamic computable general equilibrium model. Emerging Markets Finance and Trade, 57(3), 727–739. https://doi.org/10.1080/1540496X.2019.1597704
Hagsten, E., & Sabadash, A. (2017). A neglected input to production: The role of ICT-schooled employees in firm performance. International Journal of Manpower, 38(3), 373–391. https://doi.org/10.1108/IJM-05-2015-0073
Hesenius, M., Schwenzfeier, N., Meyer, O., Koop, W., & Gruhn, V. (2019, May). Towards a software engineering process for developing data-driven applications. In 2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) (pp. 35–41), Montreal, QC, Canada. IEEE. https://doi.org/10.1109/RAISE.2019.00014
Heyman, F. (2016). Job polarization, job tasks and the role of firms. Economics Letters, 145, 246–251. https://doi.org/10.1016/j.econlet.2016.06.032
Hong, C., & Lee, J. D. (2016). Macroeconomic effects of R&D tax credits on small and medium enterprises. Economic Systems Research, 28(4), 467–481. https://doi.org/10.1080/09535314.2016.1240067
Hwang, W. S., & Shim, D. (2021). Measuring the impact of ICT-driven product and process innovation on the Korean economy. Global Economic Review, 50(3), 235–253. https://doi.org/10.1080/1226508X.2021.1884114
Hwang, W. S., & Shin, J. (2017). ICT-specific technological change and economic growth in Korea. Telecommunications Policy, 41(4), 282–294. https://doi.org/10.1016/j.telpol.2016.12.006
Hwang, W. S., Yeo, Y., Oh, I., Hong, C., Jung, S., Yang, H., & Lee, J. D. (2021). CGE analysis of R&D investment policy considering trade-offs between economic growth and stability. Science and Public Policy, 48(3), 295–308. https://doi.org/10.1093/scipol/scaa068
Järvensivu, P., Räisänen, H., & Hukkinen, J. I. (2021). A simulation exercise for incorporating long-term path dependencies in urgent decision-making. Futures, 132, 102812. https://doi.org/10.1016/j.futures.2021.102812
Jorgenson, D. W., & Vu, K. M. (2016). The ICT revolution, world economic growth, and policy issues. Telecommunications Policy, 40(5), 383–397. https://doi.org/10.1016/j.telpol.2016.01.002
Jung, S., Lee, J. D., Hwang, W. S., & Yeo, Y. (2017). Growth versus equity: A CGE analysis for effects of factor-biased technical progress on economic growth and employment. Economic Modelling, 60, 424–438. https://doi.org/10.1016/j.econmod.2016.10.014
Korean Productivity Center. (2016). Productivity statistics. Korea Productivity Center.
Lankisch, C., Prettner, K., & Prskawetz, A. (2019). How can robots affect wage inequality? Economic Modelling, 81, 161–169. https://doi.org/10.1016/j.econmod.2018.12.015
Mallick, S. K., & Sousa, R. M. (2017). The skill premium effect of technological change: New evidence from United States manufacturing. International Labour Review, 156(1), 113–131. https://doi.org/10.1111/j.1564-913X.2015.00047.x
Michaels, G., Natraj, A., & Van Reenen, J. (2014). Has ICT polarized skill demand? Evidence from eleven countries over twenty-five years. Review of Economics and Statistics, 96(1), 60–77. https://doi.org/10.1162/REST_a_00366
Network Readiness Index. (2020). Network Readiness Index 2020: South Korea. Portulans Institute.
Park, C., & Park, J. (2020). COVID-19 and the Korean Economy: When, how, and what changes? Asian Journal of Innovation and Policy, 9(2), 187–206. https://doi.org/10.7545/ajip.2020.9.2.187
Park, J., Moore, J. E., Gordon, P., & Richardson, H. W. (2017). A new approach to quantifying the impact of hurricane-disrupted oil refinery operations utilizing secondary data. Group Decision and Negotiation, 26(6), 1125–1144. https://doi.org/10.1007/s10726-017-9537-7
Pyo, H. K., Hee, K., & Ha, B. (2009). Estimation of labor and total factor productivity by 72 industries in Korea (1970–2003). In Productivity measurement and analysis (pp. 527–550). OECD Publishing, Paris. https://doi.org/10.1787/9789264044616-25-en
Richmond, K., & Triplett, R. E. (2018). ICT and income inequality: A cross-national perspective. International Review of Applied Economics, 32(2), 195–214. https://doi.org/10.1080/02692171.2017.1338677
Rickman, D. S. (2010). Modern macroeconomics and regional economic modeling. Journal of Regional Science, 50(1), 23–41. https://doi.org/10.1111/j.1467-9787.2009.00647.x
Sawng, Y. W., Kim, P. R., & Park, J. (2021). ICT investment and GDP growth: Causality analysis for the case of Korea. Telecommunications Policy, 45(7), 102157. https://doi.org/10.1016/j.telpol.2021.102157
Schreyer, P. (2000). The contribution of information and communication technology to output growth: A study of the G7 countries. OECD Publishing.
Tambe, P., Hitt, L., Rock, D., & Brynjolfsson, E. (2020). Digital capital and superstar firms (NBER Working Paper 28285). National Bureau of Economic Research. https://doi.org/10.3386/w28285
Taniguchi, H., & Yamada, K. (2019). ICT capital-skill complementarity and wage inequality: Evidence from OECD countries. OECD publishing.
Taştan, H., & Gönel, F. (2020). ICT labor, software usage, and productivity: Firm-level evidence from Turkey. Journal of Productivity Analysis, 53(2), 265–285. https://doi.org/10.1007/s11123-020-00573-x
Vu, K., Hanafizadeh, P., & Bohlin, E. (2020). ICT as a driver of economic growth: A survey of the literature and directions for future research. Telecommunications Policy, 44(2), 101922. https://doi.org/10.1016/j.telpol.2020.101922
Yeo, Y., & Lee, J. D. (2020). Revitalizing the race between technology and education: Investigating the growth strategy for the knowledge-based economy based on a CGE analysis. Technology in Society, 62, 101295. https://doi.org/10.1016/j.techsoc.2020.101295
Yeo, Y., Lee, J. D., & Jung, S. (2021). Winners and losers in a knowledge-based economy: Investigating the policy packages for an inclusive growth based on a computable general equilibrium analysis of Korea. Journal of the Asia Pacific Economy, 1–37. https://doi.org/10.1080/13547860.2021.1982193