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Journals / International Journal of Social Sciences and Humanity Studies / 2009 / Cilt: 1 Sayı: 2

COMPARISON OF SIMPLE SUM AND DIVISIA MONETARY AGGREGATES USING PANEL DATA ANALYSIS

Sadullah Celik
Seda Uzun
Pages
1–13
Publication Date
2009-12-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

After investigating the order of stationarity of the panel data set through several panel unit root tests, we perform advanced panel cointegration tests to check the existence of a long run link between the Divisia monetary aggregates and income and interest rates in a simple Keynesian money demand function

📌 3 Key Takeaways

🎯
Objective & Hypothesis:It is well documented that financial innovation has led to poor performance of simple sum method of monetary aggregation destabilizing the historical relationship between monetary aggregates and ultimate target variables like rate of growth and rate of unemployment during the liberalization period of 1980s.
📊
Key Findings & Data:This study tries to emphasize the superiority of an alternative method of aggregation over the simple sum method, namely Divisia monetary aggregates, employing panel data analysis for United States, United Kingdom, Euro Area and Japan for the period between 1980Q1 and 1993Q3.
💡
Conclusion & Impact:After investigating the order of stationarity of the panel data set through several panel unit root tests, we perform advanced panel cointegration tests to check the existence of a long run link between the Divisia monetary aggregates and income and interest rates in a simple Keynesian money demand function
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Divisia · Simple Sum · Monetary Aggregation

Abstract

It is well documented that financial innovation has led to poor performance of simple sum method of monetary aggregation destabilizing the historical relationship between monetary aggregates and ultimate target variables like rate of growth and rate of unemployment during the liberalization period of 1980s. This study tries to emphasize the superiority of an alternative method of aggregation over the simple sum method, namely Divisia monetary aggregates, employing panel data analysis for United States, United Kingdom, Euro Area and Japan for the period between 1980Q1 and 1993Q3. After investigating the order of stationarity of the panel data set through several panel unit root tests, we perform advanced panel cointegration tests to check the existence of a long run link between the Divisia monetary aggregates and income and interest rates in a simple Keynesian money demand function

🔖

Cite This Article

Celik, S., Uzun, S. (2009). COMPARISON OF SIMPLE SUM AND DIVISIA MONETARY AGGREGATES USING PANEL DATA ANALYSIS. International Journal of Social Sciences and Humanity Studies, Cilt: 1 Sayı: 2, 1–13. https://ajindex.com/articles/997111

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References (38)

  1. Acharya, Debashis and Bandi Kamaiah (2001), “Simple Sum vs. Divisia Monetary Aggregates:
  2. An Empirical Evaluation”, Economic and Political Weekly, Vol. 36, No. 4, Money, Banking and Finance, pp. 317-319 + 321-326. Anderson, Richard, Barry Jones and Travis Nesmith (1997), “Monetary Aggregation Theory and Statistical Index Numbers”, Federal Reserve Bank of St.Louis Review, January/February, pp.
  3. Bank of England, Interactive Database (last updated on June 30, 2009), http://www.bankofengland.co.uk/mfsd/iadb/FromShowColumns.asp?Travel=NIxAZxI1x&FromC ategoryList=Yes&NewMeaningId=LDVIN&CategId=6&HighlightCatValueDisplay=Divisia, Accessed 25.12.2008].
  4. Bank of England, Interactive Database (last updated on June 30, 2009), http://www.bankofengland.co.uk/mfsd/iadb/FromShowColumns.asp?Travel=NIxAZxI1x&FromC ategoryList=Yes&NewMeaningId=RNZC10&CategId=6&HighlightCatValueDisplay=Nominal% zero%20coupon,%2010%20year, [Accessed 25.12.2008].
  5. Barnett, A. William (1978), “The User Cost of Money”, Economic Letters, Vol. 1 No.2 pp.145-49.
  6. Barnett, A. William (1980), “Economic Monetary Aggregates: An Application of Index Number and Aggregation Theory”, Journal of Econometrics, Vol. 14, No. 1, pp. 11-48.
  7. Barnett, A. William, Douglas Fisher and Apostolos Serletis (1992), “Consumer Theory and the Demand for Money”, Journal of Economic Literature, Vol. 30, No. 4, pp. 2086-2119.
  8. Belongia, T. Micheal and K. Alec Chrystal (1991), “An Admissible Monetary Aggregate for the United Kingdom”, The Review of Economics and Statistics, Vol.73, No.3, pp. 497-503.
  9. Binner, M. Jane and Rakesh K. Bissoondeeal, Elger C. Thomas, Barry E. Jones and Andrew Mullineux (2009). “Admissible Monetary Aggregates for the Euro Area”, Journal of International
  10. Money and Finance, Vol. 28, No. 1, pp. 99-114. Chetty, V. Karuppan (1969), “On Measuring the Nearness of the Near-Moneys”, American
  11. Economic Review, Vol. 59, No. 3, pp. 270-81. Cysne, Rubens Penha (2000), “Divisia Indexes, Money and Welfare”, Economics Working Papers
  12. (Ensaios Economicos da EPGE) 396, Graduate School of Economics, Getulio Vargas Foundation (Brazil). Dahalan, Jauhari (2004), “Divisia Index Monetary Aggregates: Do They Matter for Monetary
  13. Policy in Malaysia? Malasian Management Journal, Vol. 8, No. 1, pp. 39-54. Divisia, Francois (1925), “L’indice Monetaire et la Theorie de la Monnaie”. Revue d’Economie Politique, Vol 39, pp. 980-1008.
  14. Diwert, Erwin (1976), “Exact and Superlative Index Numbers and Consistency in Aggregation”,
  15. Journal of Econometrics, Vol. 4, No. 2, pp. 115-45. European Central Bank, Statistical Data Warehouse,http://sdw.ecb.europa.eu/browse.do?node=210793, [Accessed 12.01.2009].
  16. Federal Reserve, Statistics and Historical Data, http://www.federalreserve.gov/releases/h15/current/h15.htm, [Accessed 23.12.2008].
  17. Federal Reserve Bank of St. Louis, Monetary Services Indexes, http://research.stlouisfed.org/msi/, Accessed 24.12.2008].
  18. Fisher, Douglas, Adrian Fleissig (1997), “Monetary Aggregation and Demand for Assets”. Journal of Money, Credit and Banking, Vol. 29, No.4, 458-475.
  19. Fisher, Irving (1922), The Making of Index Numbers: A Study of Their Varieties, Tests and Reliability, Houghton Mifflin, Boston, Mass.
  20. Friedman, Milton and Anna J. Schwarz (1970), Monetary Statistics of the United States: Estimates,
  21. Sources, Methods. New York: Columbia University Press for the National Bureau of Economic Research. Goldman, Stewen M. and Hirofumi Uzawa (1964), “A Note on Separability in Demand Analysis,” Econometrica, Vol. 32, pp. 1-38.
  22. Hutt, H. William (1963), Keynesianism: Retrospect and Prospect: A Critical Restatement of Basic
  23. Economic Principles, Henry Regnery Company, Chicago. Im, Kyung So, M. Hashem Pesaran and Yongcheol Shin (2003), "Testing for Unit Roots in
  24. Heterogeneous Panels," Journal of Econometrics, Vol. 115, No. 1, pp. 53-74. Levin, Andrew, Chien-Fu Lin and Chia-Shang James Chu (2002) "Unit Root Tests in Panel Data:
  25. Asymptotic and Finite-sample Properties," Journal of Econometrics, Vol. 108, No. 1, pp. 1-24. Marquez, Jaime (1985), “Currency Substitution and the New Divisia Monetary Aggregates: The U.S Case”, Federal Reserve Board, International Finance Discussion Papers 257, Washington, D.C.
  26. Mullineux, Andrew (1996), Financial Innovation, Banking and Monetary Aggregates, Edward
  27. Elgar Publishing Limited, United Kingdom. Oda, Nobuyuki and Kunio Okina (2001), “Further Monetary Easing Policies under the Non
  28. Negativity Constraints of Nominal Interest Rates: Summary of the Discussion Based on the Japan’s Experience”, Monetary and Economic Studies (Special Edition), February. Pedroni, Peter (1999), “Critical Values for Cointegration Tests in Heterogeneous Panels with
  29. Multiple Regressors” Oxford Bulletin of Economics and Statistics, Vol. 61, No.1, pp. 653-70. Pedroni, Peter (2004), “Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled
  30. Time Series Tests with An Application to The PPP Hypothesis”, Econometric Theory, Vol. 20, No., pp.597-625. Peseran, M. Hashem (2007), “A Simple Panel Unit Root Test in the Presence of Cross Section
  31. Dependence”, Journal of Applied Econometrics, Vol. 22, No. 2, pp. 265-312. Reimers, Hans-Eggert (2002), “Analysing Divisia Aggregates for the Euro Area”, Discussion
  32. Paper 13/02, Economic Research Centre of the Deutsche Bundesbank. Reuters 3000 Xtra Hosted Terminal Platform, Economic Indicator Chart, https://portal.hpd.global.reuters.com/auth/login.aspx, [Accessed 18.01.2009].
  33. Rotemberg, Julio, John Driscoll and James Poterba (1995), “Money, Output, and Prices: Evidence from a New Monetary Aggregate.” Journal of Business and Economic Statistics, Vol.13, pp. 67-83.
  34. Stracca, Livio (2001), “Does Liquidity Matter? Properties of a Synthetic Divisia Monetary
  35. Aggregate in the Euro Area”, Working Paper Series 79, European Central Bank. Westerlund, Joakim (2007), “Testing for Error Correction in Panel Data”, Oxford Bulletin of
  36. Economic and Statistics, Vol. 69, No. 6, pp. 709-748. Westerlund, Joakim and David L. Edgerton (2007), “New Improved Tests for Cointegration with
  37. Structural Breaks”, Journal of Time Series Analysis, Vol. 28, No. 2, pp. 188-224.
  38. Time Series Tests with An Application to The PPP Hypothesis”, Econometric Theory, Vol. 20, No., pp.597-625. Peseran, M. Hashem (2007), “A Simple Panel Unit Root Test in the Presence of Cross Section