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Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models

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  • Chen, Yueh H.
  • Lin, Winston T.

Abstract

This research examines four interrelated issues at the country level: the value of information technology (IT), inputs substitution and complement, the complementarity phenomenon created by IT and national characteristics, and the productivity paradox, jointly and critically from a global perspective, using the so-called productive efficiency as the performance measure. To that end, we develop the three-factor constant elasticity of substitution (CES) stochastic production frontier model and apply it to a set of panel data from 15 countries over the period 1993-2003, along with the traditional two-factor CES models, within the one- and two-equation frameworks. In the two-equation setting, six national characteristics are selected as the contributing factors of the productive efficiency. The findings include: (i) the value of IT as measured by the productive efficiency is duly recognized: (ii) the productivity paradox is found to be absent from the production process in a majority of developed and developing countries considered, rejecting the existing argument that the paradox exists only in developing economies but does not exist in developed countries; however, the developed countries have used IT capital in their production systems more productively efficiently than the developing nations; (iii) traditional capital (non-IT capital), traditional labor, and IT capital are not pairwise substitutable, contrary to the notion that they are pairwise substitutable at the firm level; (iv) constant returns to scale, as commonly assumed, are not supported by the data; (v) different national characteristics affect a country's output (represented by gross domestic product or GDP) and its productive efficiency differently; and (vi) the complementarity phenomenon is observed in most of the countries (developed and developing) under study.

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  • Chen, Yueh H. & Lin, Winston T., 2009. "Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models," International Journal of Production Economics, Elsevier, vol. 120(2), pages 552-569, August.
    • Handle: RePEc:eee:proeco:v:120:y:2009:i:2:p:552-569
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    References listed on IDEAS

    as
    1. Winston Lin & Yueh Chen, 1998. "Forecasting foreign exchange rates with an intrinsically nonlinear dynamic speed of adjustment model," Applied Economics, Taylor & Francis Journals, vol. 30(3), pages 295-312.
    2. Miller, Victoria, 1998. "The Double Drain with a Cross-Border Twist: More on the Relationship between Banking and Currency Crises," American Economic Review, American Economic Association, vol. 88(2), pages 439-443, May.
    3. Fare,Rolf & Grosskopf,Shawna & Lovell,C. A. Knox, 2008. "Production Frontiers," Cambridge Books, Cambridge University Press, number 9780521072069.
    4. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    5. Berndt, Ernst R. & Morrison, Catherine J., 1995. "High-tech capital formation and economic performance in U.S. manufacturing industries An exploratory analysis," Journal of Econometrics, Elsevier, vol. 65(1), pages 9-43, January.
    6. Sanjeev Dewan & Kenneth L. Kraemer, 2000. "Information Technology and Productivity: Evidence from Country-Level Data," Management Science, INFORMS, vol. 46(4), pages 548-562, April.
    7. Jack E. Triplett, 1999. "The Solow productivity paradox: what do computers do to productivity?," Canadian Journal of Economics, Canadian Economics Association, vol. 32(2), pages 309-334, April.
    8. Waldman, Donald M., 1982. "A stationary point for the stochastic frontier likelihood," Journal of Econometrics, Elsevier, vol. 18(2), pages 275-279, February.
    9. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    10. Park, Soo-Uk & Lesourd, Jean-Baptiste, 2000. "The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches," International Journal of Production Economics, Elsevier, vol. 63(1), pages 59-67, January.
    11. Winston T. Lin, 2005. "Currency forecasting based on an error components-seemingly unrelated nonlinear regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 593-605.
    12. James Bessen, 2002. "Technology Adoption Costs and Productivity Growth: The Transition to Information Technology," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 443-469, April.
    13. Anandhi S. Bharadwaj & Sundar G. Bharadwaj & Benn R. Konsynski, 1999. "Information Technology Effects on Firm Performance as Measured by Tobin's q," Management Science, INFORMS, vol. 45(7), pages 1008-1024, July.
    14. Donald Siegel, 1997. "The Impact Of Computers On Manufacturing Productivity Growth: A Multiple-Indicators, Multiple-Causes Approach," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 68-78, February.
    15. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    16. Kraemer, Kenneth L. & Dedrick, Jason, 1994. "Payoffs from investment in information technology: Lessons from the Asia-Pacific region," World Development, Elsevier, vol. 22(12), pages 1921-1931, December.
    17. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
    18. Ritchie, P. C. & Rowcroft, J. E., 1996. "Choice of metric in the measurement of relative productive efficiency," International Journal of Production Economics, Elsevier, vol. 46(1), pages 433-439, December.
    19. David, Paul A, 1990. "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox," American Economic Review, American Economic Association, vol. 80(2), pages 355-361, May.
    20. Sarv Devaraj & Rajiv Kohli, 2003. "Performance Impacts of Information Technology: Is Actual Usage the Missing Link?," Management Science, INFORMS, vol. 49(3), pages 273-289, March.
    21. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    22. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    23. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    24. Phelps, Charlotte D, 1969. "Real and Monetary Determinants of State and Local Highway Investment, 1951-66," American Economic Review, American Economic Association, vol. 59(4), pages 507-521, Part I Se.
    25. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
    26. Lin, Winston T., 1988. "The dynamic behavior of production in the extractive industry," Resources and Energy, Elsevier, vol. 10(3), pages 225-246, September.
    27. Bresnahan, Timothy F, 1986. "Measuring the Spillovers from Technical Advance: Mainframe Computers inFinancial Services," American Economic Review, American Economic Association, vol. 76(4), pages 742-755, September.
    28. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    29. Ngwenyama, Ojelanki & Guergachi, Aziz & McLaren, Tim, 2007. "Using the learning curve to maximize IT productivity: A decision analysis model for timing software upgrades," International Journal of Production Economics, Elsevier, vol. 105(2), pages 524-535, February.
    30. Lin, Winston T, 1986. "Analysis of Lumber and Pulpwood Production in a Partial Adjustment Model with Dynamic and Variable Speeds of Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(3), pages 305-316, July.
    31. Chen, Tain-jy & Tang, De-piao, 1987. "Comparing technical efficiency between import-substitution-oriented and export-oriented foreign firms in a developing economy," Journal of Development Economics, Elsevier, vol. 26(2), pages 277-289, August.
    32. Erik Brynjolfsson & Lorin Hitt, 1996. "Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending," Management Science, INFORMS, vol. 42(4), pages 541-558, April.
    33. Zarnowitz, Victor, 1985. "Rational Expectations and Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 293-311, October.
    34. Tridas Mukhopadhyay & Surendra Rajiv & Kannan Srinivasan, 1997. "Information Technology Impact on Process Output and Quality," Management Science, INFORMS, vol. 43(12), pages 1645-1659, December.
    35. Tohidi, Hamid & Tarokh, Mohammad Jafar, 2006. "Productivity outcomes of teamwork as an effect of information technology and team size," International Journal of Production Economics, Elsevier, vol. 103(2), pages 610-615, October.
    36. Lin, Hong-Jen & Lin, Winston T, 2000. "A Dynamic and Stochastic Beta and Its Implications in Global Capital Markets," International Finance, Wiley Blackwell, vol. 3(1), pages 123-160, April.
    37. Murillo-Zamorano, Luis R. & Vega-Cervera, Juan A., 2001. "The use of parametric and non-parametric frontier methods to measure the productive efficiency in the industrial sector: A comparative study," International Journal of Production Economics, Elsevier, vol. 69(3), pages 265-275, February.
    38. B. S. Fisher & Carolyn Tanner, 1978. "The Formulation of Price Expectations: An Empirical Test of Theoretical Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 60(2), pages 245-248.
    39. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    40. Sanjeev Dewan & Chung-ki Min, 1997. "The Substitution of Information Technology for Other Factors of Production: A Firm Level Analysis," Management Science, INFORMS, vol. 43(12), pages 1660-1675, December.
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    Cited by:

    1. Lin, Winston T. & Chen, Yueh H. & Shao, Benjamin B.M., 2015. "Assessing the business values of information technology and e-commerce independently and jointly," European Journal of Operational Research, Elsevier, vol. 245(3), pages 815-827.
    2. Gunasekaran, Angappa & Subramanian, Nachiappan & Papadopoulos, Thanos, 2017. "Information technology for competitive advantage within logistics and supply chains: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 14-33.
    3. Greene, William & Orea, Luis & Wall, Alan, 2010. "Stochastic Frontiers using a Fixed-effect Vector Decomposition Approach with an Application to ICT and Regional Productivity in Spain," Efficiency Series Papers 2010/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    4. Winston T. Lin, 2013. "Assessing the impacts of the integration of the ICT investments of Taiwan and China upon economic growth in Taiwan," Chapters,in: Economic Integration Across the Taiwan Strait, chapter 3, pages 56-80 Edward Elgar Publishing.
    5. Lin, Winston T. & Chuang, Chia-Hung & Choi, Jeong Hoon, 2010. "A partial adjustment approach to evaluating and measuring the business value of information technology," International Journal of Production Economics, Elsevier, vol. 127(1), pages 158-172, September.
    6. Lin, Winston T. & Chuang, Chia-Hung, 2013. "Investigating and comparing the dynamic patterns of the business value of information technology over time," European Journal of Operational Research, Elsevier, vol. 228(1), pages 249-261.
    7. Lin, Winston T. & Kao, Ta-Wei (Daniel), 2014. "The partial adjustment valuation approach with dynamic and variable speeds of adjustment to evaluating and measuring the business value of information technology," European Journal of Operational Research, Elsevier, vol. 238(1), pages 208-220.
    8. Lin, Winston T. & Chiang, Chung-Yean, 2011. "The impacts of country characteristics upon the value of information technology as measured by productive efficiency," International Journal of Production Economics, Elsevier, vol. 132(1), pages 13-33, July.
    9. Ipatova, Irina & Peresetsky, Аnatoly, 2013. "Technical efficiency of Russian plastic and rubber production firms," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 32(4), pages 71-92.

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