A market-consistent framework for the fair evaluation of insurance contracts under Solvency II

Decisions in Economics and Finance - The entry into force of the Solvency II regulatory regime is pushing insurance companies in engaging into market consistence evaluation of their balance sheet,...     

Urban Economic Openness and IPO Underpricing

This paper represents a first attempt to employ a macroeconomic approach to explain the high and varying IPO underpricing within a single emerging market. We examine the empirical impact of trade openness on the short-run underpricing of initial public offerings (IPOs) using city-level data. Particularly, we argue that urban economic openness (UEO) has a significant impact on the productivity and on prices of both direct and indirect real estate due to productivity gains of companies in more open areas. This in turn positively affects the firm’s profitability, enhancing the confidence in local real estate markets and future company performance, hence decreasing the uncertainty of the IPO valuation. As a result, issuers have less incentive to underprice IPO shares. We use a sample of Chinese real estate IPOs, which offer a suitable laboratory thanks to their strong geographic investment patterns focused locally and a country with a highly heterogeneous openness across regions. Controlling for traditional firm- and issuing-specific characteristics of IPOs that are used for developed markets and Chinese-related features (i.e. listing location and state ownership), we find the evidence that companies investing in economically more open areas experience less IPO underpricing. Our results show great explanatory power and are robust to different specifications.     

When do thick venture capital markets foster innovation? An evolutionary analysis

In this paper, we examine the trade off between different effects of the availability of venture capital on the speed of technological progress in an industry. We consider an evolutionary industry simulation model based on Nelson and Winter (1982), in which R&D efforts of an incumbent firm generate technological know-how embodied in key R&D employees, who might use this know-how to found a spinoff of the incumbent. Venture capital is needed to finance a spinoff, so that the expected profits from founding a spinoff depend on how easily venture capital can be acquired. Accordingly, thick venture capital markets might have two opposing effects. First, incentives of firms to invest in R&D might be reduced and, second, if spinoff formation results in technological spillovers between the parent firm and the spinoffs, the generation of spinoff firms might positively influence the future efficiency of the incumbent’s innovation efforts. We study the manner in which this tradeoff influences the effect of venture capital on innovation expenditures, speed of technological change and evolution of industry concentration in several scenarios with different industry characteristics.     

A MODEL OF MONOPOLISTIC COMPETITION WITH PERSONAL INCOME DISPERSION

We introduce non‐homothetic preferences in the Dixit–Stiglitz model of monopolistic competition, and enquire about the effects of a change in income dispersion on the firms’ optimal decisions and market equilibrium. Income dispersion, modeled as a mean preserving spread, is shown to affect only the degree of product differentiation under the standard negligibility hypothesis on the firms’ decision making process, while it generates a positive co‐movement of demand and demand elasticity, when this assumption is removed and the price index effect is taken into account.     

A medium-N approach to macroeconomic forecasting

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not sufficiently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a body of empirical research suggesting that popular data-rich prediction methods perform best when N ranges from 20 to 40. In order to accomplish our goal, we resort to partial least squares and principal component regression to consistently estimate a stable dynamic regression model with many predictors as only the number of observations, T, diverges. We show both by simulations and empirical applications that the considered methods, especially partial least squares, compare well to models that are widely used in macroeconomic forecasting.     

The Power of the Euro–Sterling Rates in Explaining Asset Market Rates: A High‐frequency Analysis

This article makes use of high‐frequency asset market data to explain unexpected changes in interest rates using the methodology proposed by Cochrane and Piazzesi (2002) . This work departs from the existing literature because it uses UK market expectations to capture unexpected movements in the base rate, and explores its effect on a large number of asset market variables. Results indicate that the relation between asset market data and unexpected base rate changes is stronger and more consistent than the relation between asset market data and raw base rate changes. Results appear to be robust to extreme value changes.     

Exploring the contribution of innovation intermediaries to the new product development (NPD) process: a typology and an empirical study

In the ‘knowledge economy’ upheld by the European Lisbon strategy, knowledge‐intensive services are considered a key driver for innovation and competitiveness. A category of knowledge‐intensive services that has become of utmost importance in the last few decades is new product development (NPD) services, which interconnect distant knowledge domains with the client firms. In addition to NPD service providers, web‐based innovation intermediaries have started to help innovative firms access dispersed bodies of knowledge. Despite the heterogeneity of their characteristics, however, a clear typology of the strategies used by traditional NPD service providers and web‐based intermediaries to interact with their knowledge sources and with their clients is missing. This typology would be very useful for those firms that are willing to collaborate with innovation intermediaries because it could highlight the typologies of NPD problems different intermediaries are apt to address and the managerial challenges that working with them entails. Developing such a classification framework is the main goal of this paper. The typology proposed in this paper suggests that innovation intermediaries should be distinguished based on the following: (1) the way they access their distributed knowledge sources and (2) the way they deliver value to their clients. By combining these two dimensions, four categories of innovation intermediaries are identified, which are named brokers, mediators, collectors and connectors. A multiple case study analysis involving four innovation intermediaries and 12 of their clients is presented in the paper. The analysis provides exploratory insights into (1) the typologies of NPD problems that each class of intermediaries addresses and (2) the managerial challenges that working with each of them entails. These preliminary findings call for further theoretical and empirical research into the complex interaction among innovation intermediaries, their dispersed sources of knowledge and their clients.     

Licensing Under Bertrand Competition Revisited

This note indicates that the derivation of the royalty contract for licensing in Wang and Yang (Australian Economic Papers, 39 (1999) 106–119) is not correct. As a consequence, the profits of the innovator in the case of royalty licensing are underestimated.     

The impact of local and external university knowledge on the creation of knowledge-intensive firms: evidence from the Italian case

This paper investigates how far in space university knowledge goes to breed the creation of knowledge-intensive firms (KIFs), depending on the nature (either codified or tacit) and quality of this knowledge. We consider the impact of knowledge codified in academic patents and scientific publications and tacit knowledge embodied in university graduates on KIF creation in Italian provinces in 2010, while distinguishing between local university knowledge created by universities located in the same province and external university knowledge created by universities located outside the province. Our econometric estimates indicate that the positive effects of scientific publications and university graduates are confined within the boundaries of the province in which universities are located. Conversely, the creation of new KIFs in a focal province is positively affected by both local and external university knowledge codified in academic patents, even though the positive effect of this external knowledge rapidly diminishes with geographic distance. Furthermore, the above effects are confined to high-quality universities; low-quality universities have little effect on KIF creation.     

Risk-type density diagrams by crash type on two-lane rural roads

The research presented here aims to plot density diagrams per road crash risk type to identify all possible scenarios where driving is less than safe. The starting point was the prediction of injury crash rate on horizontal homogeneous segments of two-lane rural roads for three main injurious crash types (head-on/side collisions, rear-end crashes, and single-vehicle run-off-road crashes) as observed on the network. A careful analysis of the database shows that a wide variety of factors appear to be influenced or associated with the crash dynamic, as follows: the road scenario (combination of infrastructure and environmental conditions found at the site at the time of the crash), mean lane width, the horizontal curvature indicator (measurement of the curvature change rate), and mean speed. Crashes recorded from 2003 to 2010, of which 1597 were injurious, and 645 resulted only in damage to property, were analyzed on more than 3700?km of road network in Southern Italy. Generalized estimating equations with a negative binomial distribution were implemented. Risk-type density charts were plotted to thoroughly identify all possible combinations of existing explicative variables producing hazardous conditions on the road. The different shades in the diagrams represent different ranges of injurious crash rates: the white band shows low levels, while a black band shows high values. It is not possible to consider working on an explanatory variable to reduce hazardous conditions on the road network without also considering how this variation might affect the influence of the remaining explanatory variables on crash phenomena and, consequently, on the predictive model. The risk maps make it possible to keep under control in a simple and immediate approach the way each variable as a result of variations of a part or of all.