Capital Stock Approximation using Firm Level Panel Data: A Modified Perpetual Inventory Approach
Steffen Müller
Jahrbücher für Nationalökonomie und Statistik,
No. 4,
2008
Abstract
Many recent studies exploring conditional factor demand or factor substitution issues use firm level panel data. A considerable number of establishment panels contains no direct information on the capital input, necessary for production or cost function estimation. Incorrect measurement of capital leads to biased estimates and casts doubt on any inference on output elasticities or input substitution properties. The perpetual inventory approach, commonly used for long panels, is a method that attenuates these problems. In this paper a modified perpetual inventory approach is proposed. This method provides more reliable measures for capital input when short firm panels are used and no direct information on capital input is available. The empirical results based on a replication study of Addison et al. (2006) support the conclusion that modified perpetual inventory is superior to previous attempts in particular when fixed effects estimation techniques are used. The method thus makes a considerable number of recently established firm panels accessible to more sophisticated production function or factor demand analyses.
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Schätzunsicherheit oder Korrelation, Welche Risikokomponente sollten Unternehmen bei der Bewertung von Kreditportfoliorisiken wann berücksichtigen?
Henry Dannenberg
IWH Discussion Papers,
No. 5,
2007
Abstract
The use of probability of default estimates to assess the risks of a credit portfolio should not ignore estimation uncertainty. The latter can be quantified by confidence intervals. But assumptions about dependencies of these intervals are inconsistent with assumptions of conventional credit portfolio models. Based on simulation studies this paper shows, that a model which include estimation uncertainty but ignore default correlation might estimate the real credit risk more correctly than a model that implicates default correlation but ignore estimation uncertainty. The latter is a trait of conventional credit portfolio models. In this paper quantifying of estimation uncertainty based on the idea of confidence intervals and the underlying probability distributions of these intervals.
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The Loss Distribution of the Entrepreneurial Bad Debt Risk – a Simulation-based Model
Henry Dannenberg
IWH Discussion Papers,
No. 10,
2006
Abstract
The risk of bad debt losses evolves for companies which grant payment targets. Possible losses have to be covered by these companies equity and liquidity reserves. The question of how to quantify the level of risk of bad debt losses will be discussed in this paper. Input values of this risk are the probability of default, exposure at default and loss given default. It is shown how companies can derive probability functions to describe uncertainty and variability for each input value. Based on these probability functions a simulation model is developed to quantify the risk of bad debt losses. Based on an empirical study probability functions for probability of default and loss given default are presented.
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