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Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error‐Correction Forecasting Models

Author

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  • Jane M. Binner
  • Alicia M. Gazely
  • Shu‐Heng Chen
  • Bin‐Tzong Chie
Abstract
In this article a Divisia monetary index is constructed for the Taiwan economy, and its inflation forecasting potential is compared with that of its traditional simple sum counterpart. The Divisia index is adjusted in two ways to allow for the financial liberalization that Taiwan has experienced since the 1970s. The powerful artificial intelligence technique of neural networks is used and is found to beat the conventional econometric techniques in a simple inflation forecasting experiment. The preferred inflation forecasting model is achieved using networks that employ a Divisia M2 measure of money that has been adjusted to incorporate a learning mechanism to allow individuals to gradually alter their perceptions of the increased productivity of money. The explanatory power of the two innovation‐adjusted Divisia aggregates dominates that of the simple sum counterpart in the majority of cases. (JEL C4, E4, E5)

Suggested Citation

  • Jane M. Binner & Alicia M. Gazely & Shu‐Heng Chen & Bin‐Tzong Chie, 2004. "Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error‐Correction Forecasting Models," Contemporary Economic Policy, Western Economic Association International, vol. 22(2), pages 213-224, April.
    • Handle: RePEc:bla:coecpo:v:22:y:2004:i:2:p:213-224
    DOI: 10.1093/cep/byh015
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    References listed on IDEAS

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    1. Varian, Hal R, 1982. "The Nonparametric Approach to Demand Analysis," Econometrica, Econometric Society, vol. 50(4), pages 945-973, July.
    2. Lars E. O. Svensson, 2000. "The First Year of the Eurosystem: Inflation Targeting or Not?," American Economic Review, American Economic Association, vol. 90(2), pages 95-99, May.
    3. William A. Barnett & Douglas Fisher & Apostolos Serletis, 2006. "Consumer Theory and the Demand for Money," World Scientific Book Chapters, in: Money And The Economy, chapter 1, pages 3-43, World Scientific Publishing Co. Pte. Ltd..
    4. Belongia, Michael T, 1996. "Measurement Matters: Recent Results from Monetary Economics Reexamined," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 1065-1083, October.
    5. Hallman, Jeffrey J & Porter, Richard D & Small, David H, 1991. "Is the Price Level Tied to the M2 Monetary Aggregate in the Long Run?," American Economic Review, American Economic Association, vol. 81(4), pages 841-858, September.
    6. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    7. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    8. William A. Barnett & Seungmook Choi, 2004. "A Monte Carlo Study of Tests of Blockwise Weak Separability," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 257-287, Emerald Group Publishing Limited.
    9. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    10. Ford, J.L., 1997. "Output, the Price Level, Broad Money, and Divisia Monetary Aggregates With and Without Innovation: Taiwan, 1967(1)-1995(4)," Discussion Papers 97-17, Department of Economics, University of Birmingham.
    11. Swofford, James L & Whitney, Gerald A, 1988. "Comparison of Nonparametric Tests of Weak Separability for Annual and Quarterly Data on Consumption, Leisure, and Money," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 241-246, April.
    12. William A. Barnett, 2000. "The User Cost of Money," Contributions to Economic Analysis, in: The Theory of Monetary Aggregation, pages 6-10, Emerald Group Publishing Limited.
    13. Leigh Drake & Andy Mullineux & Juda Agung, 1997. "One Divisia money for Europe?," Applied Economics, Taylor & Francis Journals, vol. 29(6), pages 775-786.
    14. A. M. Gazely & J. M. Binner, 2000. "The application of neural networks to the Divisia index debate: evidence from three countries," Applied Economics, Taylor & Francis Journals, vol. 32(12), pages 1607-1615.
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    Cited by:

    1. Rana Ejaz Ali Khan & Qazi Muhammad Adnan Hye, 2013. "Financial liberalization and demand for money: a case of Pakistan," Journal of Developing Areas, Tennessee State University, College of Business, vol. 47(2), pages 175-198, July-Dece.
    2. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    3. El-Shagi, Makram & Tochkov, Kiril, 2022. "Divisia monetary aggregates for Russia: Money demand, GDP nowcasting and the price puzzle," Economic Systems, Elsevier, vol. 46(4).
    4. Rosita Capurro & Michele Galeotti & Stefano Garzella, 2018. ""Mondo reale-tradizionale" e "mondo digitale", strategie aziendali e web intelligence: il futuro del controllo e della gestione delle informazioni," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2 Suppl.), pages 83-111.
    5. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    6. Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 71-88, August.
    7. Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
    8. Jane M. Binner & logan J. Kelly, 2017. "Modelling Money Shocks in a Small Open Economy: The Case of Taiwan," Manchester School, University of Manchester, vol. 85, pages 104-120, September.
    9. James, Gregory A., 2005. "Money demand and financial liberalization in Indonesia," Journal of Asian Economics, Elsevier, vol. 16(5), pages 817-829, October.
    10. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.
    11. Masudul Hasan Adil & Neeraj Hatekar & Pravakar Sahoo, 2020. "The Impact of Financial Innovation on the Money Demand Function: An Empirical Verification in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(1), pages 28-61, February.

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    More about this item

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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