Open vs. sealed-bid auctions: testing for revenue equivalence under Singapore's vehicle quota system

Using data from the auction of vehicle quota licenses in Singapore, we study if revenue equivalence holds when the auction format was switched from a sealed-bid format (May 1990 to June 2001) to an open bidding format since July 2001. Our econometric analysis indicates the change in auction format led to a change in bidding behavior. On average, the quota license premium under the open bidding format is about US$1000 (about 7.5% of the Category E license price in June 2001) lower, compared to the forecast level that would have prevailed if there had been no change in the auction format.     

Direct effects of money on aggregate demand: another look at the evidence

Now that a number of central banks are faced with short-term nominal interest rates close to or at the zero lower bound, there is a renewed interest in the long-running debate about whether or not changes in the stock of money have direct effects. In particular, do changes in money have additional effects on aggregate demand outside of those induced by changes in short-term nominal interest rates? This article revisits and reinterprets the empirical evidence based on single equation regressions which is quite mixed, with some results supporting and other results denying the existence of direct effects. We use a structural model with no direct effects of money to show that the finding of positive and statistically significant coefficients on real money growth can be misleading. The model generates data that, when used to estimate analogues of the empirical regressions, produce positive and statistically significant coefficients on real money growth, similar to those often found when using actual data. The problem is that single equation regressions leave out a set of variables, which in turn, give rise to an omitted variables bias in the estimated coefficients on real money growth. Hence, they are an unreliable guide to calibrate monetary policies, in general, including at the zero lower bound.     

A graphical representation of an estimated DSGE model

We write a New Keynesian model as an aggregate demand curve and an aggregate supply curve, relating inflation to output growth. The graphical representation shows how structural shocks move aggregate demand and supply simultaneously. We estimate the curves on US data from 1948 to 2010 and study two recessions: the 2001 recession and the Great Recession of 2008–2009. The Great Recession is explained by a collapse of aggregate demand driven by adverse preference and permanent technology shocks, and expectations of low inflation.     

Matthew effect,capabilities and innovation policy: the Argentinean case

The purpose of this paper is to test the presence of Matthew effects in different types of public funding for innovation – non-refundable grants, subsidized loans and tax credits. According to the literature, Matthew effect refers to the impact of past accessing to public funds on reputation, which increases the probability of accessing in the present. The dataset is made of 966 firms that accessed the Technological Argentinean Fund (FONTAR), main instrument to foster innovation in Argentina, during 2007–2013 – 3300 observations. Results confirm the existence of Matthew effects: past accessing to FONTAR increases the probability of accessing in the present, but only when different instruments are taken altogether. Then, Matthew effect is positively associated with the diversification of access to promotional instruments rather than the repeated access to one type of funding tool. Additionally, results show that firm’s innovation investments, R&D activities, and human resources, explain the increase in probability of accessing, which provides evidence regarding the presence of capability effects. All of this suggests that once the firm enters the system of public funding, it remains with an active innovative behaviour, not just because of reputation effects, but because it has accumulated capabilities in the pursuit of a technological advantage.     

External stakeholder engagement: Complementary and substitutive effects on firms' eco-innovation

In this paper, we investigate whether firms' engagements in collaboration agreements with different types of external stakeholders produce complementary effects on the likelihood of eco-innovation. Although collaboration network and open eco-innovation theories affirm that the combination of external partners such as scientific partners, suppliers and customers produces complementary effects on the firm's likelihood of eco-innovation, several empirical studies found the existence of substitutive effects between them. To bridge this gap in the literature, we shape the nature of the interaction between different external partners, analysing an unbalanced panel sample of 10,918 innovative Spanish firms, covering the period 2008–2016. Consequently, we can show how firms benefit the most from collaboration with external partners. Our results show that firms that simultaneously collaborate with scientific partners, suppliers and customers generate partial complementary effects, which increase the firm's likelihood to eco-innovate the most, and that the combination of customer-collaboration with scientific partners, or supplier-collaboration, produces partial substitutive effects. Taking this in account, our results also confirm that engaging with scientific partners, suppliers or customers, independent of one another, increases firms' likelihood of eco-innovation more than noncollaboration. These results have important implications for managers, researchers and policy designers. For managers, this study provides a correct understanding of the benefits that they can expect to obtain from multi-partner external collaboration. For researchers, it introduces the marginal analysis to estimate interaction on nonlinear models. Finally, for policy designers, it shows the need for sponsored R&D collaboration to encourage coordinated ecosystems in which sustainability goals are pursued together.