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Dynamic Q-investment functions for Germany using panel balance sheet data and a new algorithm for the capital stock at replacement values

Author

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  • Bellgardt, Egon
  • Behr, Andreas

Abstract

The paper explores the investment behaviour of German firms in the context of the Qapproach, which plays a dominant role in empirical investment research. The analysis is based on the Deutsche Bundesbank's corporate balance sheet statistics. The panel data set contains some 2,300 German firms' balance sheet data covering the years 1988-1998. While the Q-theory is mainly applied on the basis of stock market data, which facilitates the exploitation of market expectations and the calculation of average Q, the direct forecasting approach (Chirinko 1993) suggested by Abel and Blanchard (1986) and extended to panel data by Gilchrist and Himmelberg (1995, 1998) enables the Q-theory to be applied to non-quoted firms which are by far the majority in Germany. One of the key variables when using balance sheet data, which has attracted much detailed research, is firms' net capital stock at replacement costs. The challenge is to transform historical cost data, depreciated at non-economic, tax-oriented depreciation rates, into unreported and probably unknown economically meaningful data at actual replacement values. We suggest a complex procedure for calculating reliable replacement values of a firm's capital stock. To calculate Q we follow two different operationalisation strategies. First we estimate average Q based on balance sheet data by forecasting the present value of future profits using a VAR model. Second, we estimate marginal Q following the approach suggested by Gilchrist and Himmelberg. We compare the results from two different estimation techniques for dynamic investment models, GMM and direct bias correction. The results show that marginal as well as average Q influence investment significantly. When classifying the firms by size, we find that smaller firms react more strongly to Q and, to a lesser extent, to lagged investment.

Suggested Citation

  • Bellgardt, Egon & Behr, Andreas, 2002. "Dynamic Q-investment functions for Germany using panel balance sheet data and a new algorithm for the capital stock at replacement values," Discussion Paper Series 1: Economic Studies 2002,23, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdp1:4188
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    Citations

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    Cited by:

    1. Panagiotidis, Theodore & Printzis, Panagiotis, 2020. "What is the investment loss due to uncertainty?," Global Finance Journal, Elsevier, vol. 45(C).
    2. Weinert, Gunter & Wohlers, Eckhardt & Bruck, Christiane & Fieber, Eva-Ulrike & Hinze, Jorg & Kirchesch, Kai & Matthies, Klaus & Schumacher, Christian, 2003. "Zwischen Hoffen und Bangen - Konjunktur 2003," Report Series 26082, Hamburg Institute of International Economics.
    3. Behr Andreas, 2005. "Investment, Q and Liquidity / Investitionen, Q und Liquidität: Evidence for Germany Using Firm Level Balance Sheet Data / Empirische Ergebnisse auf Basis von Unternehmensdaten," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(1), pages 2-21, February.
    4. Weinert, Günter, 2003. "Zwischen Hoffen und Bangen - Konjunktur 2003," HWWA Reports 224, Hamburg Institute of International Economics (HWWA).

    More about this item

    Keywords

    investment; Q; capital stock; replacement costs; VAR; dynamic panel data;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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