R&D and subsidies at the firm level: an application of parametric and semiparametric two‐step selection models

Abstract

Die Discussion Papers dienen einer möglichst schnellen Verbreitung von neueren Forschungsarbeiten des ZEW. Die Beiträge liegen in alleiniger Verantwortung der Autoren und stellen nicht notwendigerweise die Meinung des ZEW dar.Discussion Papers are intended to make results of ZEW research promptly available to other economists in order to encourage discussion and suggestions for revisions. The authors are solely responsible for the contents which do not necessarily represent the opinion of the ZEW.Download this ZEW Discussion Paper from our ftp server:ftp://ftp.zew.de/pub/zew-docs/dp/dp0363.pdf Non-Technical SummaryDo public R&D subsidies stimulate or simply crowd out private investment? The economic literature concerning external effects indicates that innovations suffer from market failure. Innovation projects with high social returns may not be implemented, because the induced private benefits do not exceed the private costs. The rationale of public R&D funding is to reduce private costs and therefore raise the investment in the R&D projects and the number of conducted R&D projects. However there is an incentive for all firms to apply for public funding, even for those who could perform their innovation activities using their own funds. Thus, the impact of the public R&D funding is questionable.The focus of this paper is on the direct funding of R&D projects in the German manufacturing sector granted by the Federal Ministry of Education and Research (BMBF). This study applies parametric and semiparametric two-step selection models. Selection models treat the receipt of public R&D funding as endogeneous and include a selection correction for this non-random selection process, in the structural equation on the firms' R&D expenditure. In a first step, firms' probability of receiving public R&D funding is estimated and in a second step, the effect of the public funds on firms' R&D expenditure is considered. Selection models control for unobservable characteristics entering both the selection and the structural part of the model.The parametric two-step Heckman model serves as a benchmark. Alternatively, a dummy variables estimator (Cosslett, 1991), a series estimator (Newey, 1999) and Robinson's (1988) estimator as a partial linear model are applied. Semiparametric estimators identify only the slope parameters of the structural equation. Hence, an additional estimator for the intercept is needed to identify the treatment effects. This study uses the intercept estimators developed by Heckman (1990) and Andrews and Schafgans (1998).In line with previous studies, the finding is that R&D subsidies have a positive effect on firms' R&D expenditure for all estimated models. However, it also outlines that the level of the "average treatment effect on the treated" varies with the different assumptions of the applied selection model. November 2003Abstract This paper analyzes the effects of public R&D subsidies on R&D expenditure in the German manufacturing sector. The focus is on the question whether public R&D funding stim...

R&D subsidies and productivity in SMEs

“…2 Many authors have reported that R&D subsidies stimulate private investments (e.g. Almus and Czarnitzki, 2003;Hyytinen and Toivanen, 2005;Czarnitzki, 2006;Görg and Strobl, 2007;Özçelik and Taymaz, 2008;Aerts and Schmidt, 2008;Hussinger, 2008;Meuleman and Maeseneire, 2012;Czarnitzki and Lopes-Bento, 2013), but studies have also found that these funds partly or fully crowd out some private investments (e.g. Wallsten, 2000;Lach, 2002;Busom, 2000;González and Pazó, 2008;Gelabert et al, 2009 Bronzini andIachini, 2014).…”

“…These variables (combined with other matching variables) are important for minimising the selection problem concerning firm-specific R&D variables (e.g. Hussinger, 2008). Our other control variables include firm age (age and age squared) and size (number of employees and turnover) because firm innovativeness is known to be related to these factors (e.g.…”

“…It is also plausible that there are regional and industry-specific differences between the probability of receiving an R&D subsidy and firm performance (e.g. Almus and Czarnitzki, 2003;Aerts and Schmidt, 2008;Hussinger, 2008). Thus, we include 18 regional dummies in our matching equation, and we also control for whether the firm is located in a regional centre municipality (centre).…”

China's R&D Subsidies - Allocation and Effectiveness

“…However, investigations of the effectiveness of prior subsidies on R&D expenditures are still scarce. For German manufacturing firms, Hussinger (2008) confirms additionality and Aschhof (2009) finds additionality for frequent recipients but neutrality for first-time receivers.…”

The impact of R&D subsidies on R&D employment composition

“…The wealth of information provided by the PITEC allows an exhaustive set of variables to be selected and similar controls to be included as those used in previous evaluation studies (see, among others, Aerts and Schmidt, 2008;Almus and Czarnitzki, 2003;Antonelli and Crespi, 2013;Czarnitzki and Lopes-Bento, 2013;Czarnitzki and LopesBento, 2014;González and Pazó, 2008;Hussinger, 2008).…”