Are Venture Capitalists a Catalyst for Innovation?

In this paper we test two hypotheses concerning the presence of innovation in venture capital investments and the growth of innovative venture backed firms. To examine these hypotheses we considered sample of 37 Italian venture backed firms that went public on the Italian Stock Exchange between 1995 and 2004 and by a statistical matching procedure we picked 37 twin firms among the non‐venture backed IPOs for the same period. Our evidence shows that innovation is an important factor during the selection phase but once the investment is made, the company does not promote continued innovation and concentrates all efforts to improve other economic and managerial aspects.     

Modeling society with statistical mechanics: an application to cultural contact and immigration

We introduce a general modeling framework to predict the outcomes, at the population level, of individual psychology and behavior. The framework prescribes that researchers build a cost function that embodies knowledge of what trait values (opinions, behaviors, etc.) are favored by individual interactions under given social conditions. Predictions at the population level are then drawn using methods from statistical mechanics, a branch of theoretical physics born to link the microscopic and macroscopic behavior of physical systems. We demonstrate our approach building a model of cultural contact between two cultures (e.g., immigration), showing that it is possible to make predictions about how contact changes the two cultures.     

Notes and Comments: An approximation of caplet implied volatilities in Gaussian models

Abstract It is market practice to quote interest rate derivatives traded “over the counter” in terms of their implied volatility. For this reason, the term structure of at-the-money cap volatilities as well as the volatility surface of at-the-money swaptions are directly observed. This paper analyzes the case of caps. Any analysis of these markets would most likely report two main facts. The first is that the level of the volatility is inversely related to the level of the interest rates. The second is that the term structure is either a decreasing or a humped function of maturity. For a reference, see Rebonato (2003) and Brigo and Mercurio (2001). Rebonato (2003) suggests that the structure of implied volatility is humped in periods of normal market conditions and decreasing when markets are “excited”. Interpreting and explaining such phenomena is indeed an interesting and important issue. Mathematics Subject Classification (2000): 91B70 Journal of Economic Literature Classification: E43, C13     

Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .     

A Self‐Tuning Model for Smart Manufacturing SMEs: Effects on Digital Innovation

With the changing way people live, communicate, and work, enterprises are striving to shift their existing business model into a “self‐tuning” one. Enterprises are becoming more agile, adaptive, and ambidextrous in order to boost innovation in the current digital transformation era. Nowadays, “digital innovation” is closely associated with Industry 4.0 enablers and smart enterprises. Prior research has shown that while multinational enterprises—across many sectors—have already embraced the aforementioned advancements, their adoption by small and‐medium‐sized enterprises (SMEs) has so far taken place mainly in the manufacturing sector. Thus, based on a sample of 280 self‐tuned smart manufacturing SMEs and having utilized the structural equation modeling (SEM), this study was aimed to investigate how digital innovation is influenced by the three pillars of self‐tuning models—agility, adaptation, and ambidexterity. Our paper has focussed on the digital systems in which SMEs, spurred by networking and open innovation solutions, operate and innovate in response to external triggers, displaying a balance between exploration and exploitation, and a strong agile capacity.     

The effects of social media on brand attitude and WOM during a brand crisis: Evidences from the Barilla case

Brand crises endanger companies. Social media are a key platform where stakeholders elaborate and react to crises. This research explores whether social media audience and traditional mass media audience react differently to a brand crisis in terms of their (1) attitude towards the brand and (2) word-of-mouth (WOM). As to the brand attitude, we argue that stakeholders mainly exposed to the brand crisis via social media have a more negative reaction towards the brand compared to those who are principally exposed via traditional media. As to the behaviour, we posit that social media exposure intensifies WOM. By analysing the Barilla crisis, the findings suggest that the social media act as ‘multipliers’ of the reaction of stakeholders to a brand crisis.     

On the source of contrarian and momentum strategies in the Italian equity market

This paper investigates the source of momentum profits, while inferring the validity of the assumptions underlying rational and behavioural theories. Using a unique sample of securities listed in the Italian Stock Exchange from 1950 to 1995, we observe that buying better performing stocks in the previous 3-12 months and selling worse performing stocks over the same period yields significant profits in the short term (less than 1 year). Results also hold when conditioned upon different risk specifications. On the other hand, the continuation effect seems to significantly revert over a longer period. More importantly, in contrast with Conrad and Kaul [Rev. Financ. Stud. 11 (1998) 489], bootstrap and Monte Carlo simulations show that momentum profits are more likely to be generated by stock returns time series properties rather than by their cross-sectional differences. While the overall findings cannot reject the market efficiency hypothesis, we argue that behavioural theory may be a possible “story” to interpret the continuation effect.     

INTEREG: A Twenty-region Input–Output Model for Italy

Since the regional scale turns out to be the scale at which fiscal devolution is likely to be accomplished in Italy, and that at which trade and growth interdependencies as well as regional convergence can be most conveniently investigated, a new 20-region input–output model for Italy seems to be a useful tool of analysis. Although various regional and interregional models have been constructed since the 1950s, none has been implemented for the whole system of 20 Italian administrative regions considered in their tight mutual dependence; also, the pool approach has not been greatly favoured, even in situations where direct information on regional trade is lacking. The main purpose of this paper is to report on the structure of the model, the rather complex procedure used in the model construction and the adopted solution technique. Some space is devoted to the problems encountered in handling regional trade endogenously in an input–output setting and to a comparison between the pool approach, used in the Italian model, and other current techniques. The paper also reports on some preliminary results regarding the regional impact of fiscal policy.     

THE IMPACT OF THE EU EMISSIONS TRADING SYSTEM ON COMPETITIVENESS AND CARBON LEAKAGE: THE ECONOMETRIC EVIDENCE

This paper carefully surveys the econometric literature that tests for competitiveness effects and related carbon leakage caused by the EU Emissions Trading System (EU ETS). The results of this literature tell us that to date there is no evidence of the EU ETS having had widespread negative or positive effects on the competitiveness of regulated firms, nor is there evidence of significant carbon leakage. However, the paper also identifies three important caveats to this general conclusion. Firstly, the evidence we have still largely refers to the first two trading periods, namely Phases I (2005–2007) and II (2008–2012). Secondly, some heterogeneity of estimated effects is observed, but patterns, notably sectoral patterns, hardly emerge. Thirdly, very little explored is whether the EU ETS has had long-term effects on the economy via investment leakage or firm dynamics. Further empirical studies investigating these long-term effects are particularly desirable.