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Econometric Analysis of Irreversible Investment with Financial Constraints: Comparison of Parametric and Semiparametric Estimations

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  • ASANO Hirokatsu
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    Abstract

    This analysis investigates irreversible investment with financial constraints by parametric and semiparametric estimations. The analysis examines four U.S. industries, employing a sample selection model as it develops its econometric model in accordance with real options theory. The analysis finds that liquidity positively affects capital investment, which is compatible with the theory. In addition, while investment is insensitive to sales revenue and operating costs, capital stock negatively affects investment. The analysis also finds that the sample selection bias is large and that a biased OLS estimator underestimates the coefficients of interest. The analysis' model selection is inconclusive.

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    File URL: http://www.rieti.go.jp/jp/publications/dp/08e032.pdf
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    Bibliographic Info

    Paper provided by Research Institute of Economy, Trade and Industry (RIETI) in its series Discussion papers with number 08032.

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    Length: 30 pages
    Date of creation: Aug 2008
    Date of revision:
    Handle: RePEc:eti:dpaper:08032

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    1. Steven Fazzari & R. Glenn Hubbard & Bruce C. Petersen, 1988. "Financing Constraints and Corporate Investment," NBER Working Papers 2387, National Bureau of Economic Research, Inc.
    2. Whitney Newey, 1999. "Two Step Series Estimation of Sample Selection Models," Working papers 99-04, Massachusetts Institute of Technology (MIT), Department of Economics.
    3. Andrew B. Abel & Janice C. Eberly, 1997. "The Mix and Scale of Factors with Irreversibility and Fixed Costs of Investment," NBER Working Papers 6148, National Bureau of Economic Research, Inc.
    4. Ichimura, H., 1991. "Semiparametric Least Squares (sls) and Weighted SLS Estimation of Single- Index Models," Papers 264, Minnesota - Center for Economic Research.
    5. Asano, Hirokatsu, 2002. "Costly Reversible Investment with Fixed Costs: An Empirical Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 227-40, April.
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