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

Hajivassiliou, Vassilis ORCID: 0009-0000-7041-0791 and Savignac, Frédérique (2019) Novel approaches to coherency conditions in dynamic LDV models: quantifying financing constraints and a firm's decision and ability to innovate. Econometrics Papers (606). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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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.

Item Type:	Monograph (Working Paper)
Official URL:	http://sticerd.lse.ac.uk/
Additional Information:	© 2019 The Authors
Divisions:	Economics
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics
JEL classification:	C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C15 - Statistical Simulation Methods; Monte Carlo Methods; Bootstrap Methods
Date Deposited:	15 Nov 2019 11:51
Last Modified:	01 Nov 2024 04:57
URI:	http://eprints.lse.ac.uk/id/eprint/102544

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