The Timing of Investment Episodes in the Netherlands |
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Authors: | Julian Fennema Wilko Letterie Gerard Pfann |
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Institution: | (1) Department of Accountancy and Finance, Heriot-Watt University, Edinburgh, EH14 4AS, United Kingdom;(2) BIRC, Department of Organization and Strategy, Faculty of Economics and Business Administration, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands;(3) BIRC, Department of Organization and Strategy, Department of Quantitative Economics, Faculty of Economics and Business Administration, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, The Netherlands |
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Abstract: | Summary We investigate the timing of large investment episodes at the micro level. On examination of a large sample of Dutch firms we find considerable lumpiness in the accumulation of fixed capital. We therefore define investment spikes and estimate the probability of these spikes, conditional on time since the last spike. We also control for unobserved heterogeneity. Our first result is that the probability of a spike is very high the year following an investment spike. We also find some evidence the hazard rate does increase as time since the previous spike passes by. Therefore, our results indicate the presence of convex adjustment costs or time to build lags. In addition, a tentative conclusion is that fixed adjustment costs are relevant.We like to thank two referees of this journal for their helpful and stimulating comments. The authors gratefully acknowledge the financial support of METEOR at Maastricht University and the PIONIER program (grant number 400-10-041) of the Netherlands Foundation for Scientific Research (NWO). This work was carried out at the Centre for Research of Economic Microdata (CEREM) and we would like to thank Bert Balk, Ellen Hoogenboom-Spijker and Hans Pijpers for their help with the data. The views herein expressed are those of the authors and do not necessarily reflect the policies of Statistics Netherlands. All errors remain our own. |
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Keywords: | lumpy investments duration models |
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