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A Comparative Study Of Alternative Econometric Packages: An Application To Italian Deposit Interest Rates

Author

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  • Ricardo De Bonis

    (Banca dItalia)

  • Giuseppe Bruno

    (Banca d'Italia)

Abstract

In examining the determinants of Italian deposit interest rates, we compares alternative econometric packages for estimating panel data. We focus on bank deposits, one of the main forms Italian households use to invest their financial wealth. We survey the literature on deposit rates, with particular reference to the large number of US studies. The empirical analysis is based on more than 8,000 observations for the years 1990-1996. Bank interest rates are taken from the Central Credit Register. We consider the rates on current accounts, certificates of deposit, and total deposits. Other variables are obtained from the Banking Supervision1s statistical returns. We look at the influence on interest rates of the Herfindahl index, the number of banks in each province, the rate of growth in deposits, the custodial holdings of bonds, the ratio of banking costs to total assets.With this abundance of panel data, many different specifications have been estimated using the fixed- and random-effects models. Our purpose is to examine the caveats about numerical accuracy raised by McCullogh and Vinod, who are concerned that little attention is paid to numerical accuracy in the selection of econometric packages. We compare the numerical value of the estimates of three of the most popular econometric packages featuring built-in panel data estimation algorithms: LIMDEP, STATA, and TSP. As a numerical benchmark we used Modeleasy, a general-purpose language allowing matrix operations.The preliminary results look quite promising:1) fixed-effects algorithms are numerically the same to the available decimal places.2) random-effects algorithms yield slightly different results because of the method for computing the variance components.In addition, we compare the relative efficiency of the random-effects algorithms provided by the three packages. This is done by means of a set of suitably designed Monte Carlo experiments, varying the time span and the number of provinces taken into account.

Suggested Citation

  • Ricardo De Bonis & Giuseppe Bruno, 2000. "A Comparative Study Of Alternative Econometric Packages: An Application To Italian Deposit Interest Rates," Computing in Economics and Finance 2000 160, Society for Computational Economics.
    • Handle: RePEc:sce:scecf0:160
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    1. Bellmann, L & Breitung, J & Wagner, Joachim, 1989. "Bias Correction and Bootstrapping of Error Component Models for Panel Data: Theory and Applications," Empirical Economics, Springer, vol. 14(4), pages 329-342.
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    6. Allen, Linda & Saunders, Anthony & Udell, Gregory F., 1991. "The pricing of retail deposits: Concentration and information," Journal of Financial Intermediation, Elsevier, vol. 1(4), pages 335-361, December.
    7. repec:bla:jindec:v:46:y:1998:i:4:p:433-52 is not listed on IDEAS
    8. Steven A. Sharpe, 1992. "Consumer switching costs, market structure and prices: the theory and its application in the bank deposit market," Finance and Economics Discussion Series 183, Board of Governors of the Federal Reserve System (U.S.).
    9. Lawrence J. Radecki, 1998. "The expanding geographic reach of retail banking markets," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Jun), pages 15-34.
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    12. Jonathan A. Neuberger & Gary C. Zimmerman, 1990. "Bank pricing of retail deposit accounts and \"the California rate mystery\"," Economic Review, Federal Reserve Bank of San Francisco, issue Spr, pages 3-16.
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    Cited by:

    1. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June.
    2. repec:ebl:ecbull:v:3:y:2002:i:23:p:1-10 is not listed on IDEAS
    3. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    4. A. Yalta & A. Yalta, 2010. "Should Economists Use Open Source Software for Doing Research?," Computational Economics, Springer;Society for Computational Economics, vol. 35(4), pages 371-394, April.

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