Novel approaches to coherency conditions in dynamic LDV models: quantifying financing constraints and a firm's decision and ability to innovate

Vassilis Hajivassiliou and Frédérique Savignac

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We develop novel methods for establishing coherency conditions in Static and Dynamic Limited Dependent Variables (LDV) Models. We propose estimation strategies based on Conditional Maximum Likelihood Estimation for simultaneous LDV models without imposing recursivity. Monte-Carlo experiments confirm substantive Mean-Squared-Error improvements of our approach over other estimators. We analyse the impact of financing constraints on innovation: ceteris paribus, a firm facing bindingfinance constraints is substantially less likely to undertake innovation, while the probability that a firm encounters a binding finance constraint more than doubles if the firm is innovative. A strong role for state dependence in dynamic versions of our models is also established.

JEL-codes: C15 C51 C52 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2019-10
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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http://eprints.lse.ac.uk/102544/ Open access version. (application/pdf)

Related works:
Working Paper: Novel Approaches to Coherency Conditions in Dynamic LDV Models: Quantifying Financing Constraints and a Firm's Decision and Ability to Innovate (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:102544

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