Stalling innovation of Cognitive Radio: The case for a dedicated frequency band

After more than a decade of frantic R&D efforts, Cognitive Radio (CR) technology continues to fail to pass the first developmental milestone of a working prototype, suggesting that the CR innovation process may be stalling. This paper analyzes possible reasons for this situation from the perspective of innovation management and economics. The CR innovation process has developed in a complex environment shaped by a combination of technology-push and market-pull forces. This paper shows that this process is being stifled by two barriers emerging from the current reliance of CR technology on opportunistic dynamic spectrum access as the sole means for entry into the wireless market. The technology-push is affected by the barrier of technological complexities linked to the requirement to protect highly sensitive incumbent systems. The market-pull forces are being negated by market lock-in and a strong status quo of well-established wireless players. This paper argues that overcoming these barriers and revitalizing the practical development of CR could be possible with the aid of light-touch governmental intervention. This could take the form of designating a dedicated CR band, which would benefit CR through less strict spectrum access requirements. A vibrant cognitive environment could flourish in this type of band, supporting CR innovation.     

Asset pricing with Second-Order Esscher Transforms

The purpose of the paper is to introduce, in a discrete-time no-arbitrage pricing context, a bridge between the historical and the risk-neutral state vector dynamics which is wider than the one implied by a classical exponential-affine stochastic discount factor (SDF) and to preserve, at the same time, the tractability and flexibility of the associated asset pricing model. This goal is achieved by introducing the notion of exponential-quadratic SDF or, equivalently, the notion of Second-Order Esscher Transform. The log-pricing kernel is specified as a quadratic function of the factor and the associated sources of risk are priced by means of possibly non-linear stochastic first-order and second-order risk-correction coefficients. Focusing on security market models, this approach is developed in the multivariate conditionally Gaussian framework and its usefulness is testified by the specification and calibration of what we name the Second-Order GARCH Option Pricing Model. The associated European Call option pricing formula generates a rich family of implied volatility smiles and skews able to match the typically observed ones.     

Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation

Motivated by the need for a positive‐semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra‐high‐frequency asset prices in a state‐space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and expectation maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive‐semidefinite by construction. We show the performance of the KEM estimator using extensive Monte Carlo simulations that mimic the liquidity and market microstructure characteristics of the S&P 500 universe as well as in a high‐dimensional application on US stocks. KEM provides very accurate covariance matrix estimates and significantly outperforms alternative approaches recently introduced in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

A non-parametric statistical model for the control of Italian insurance companies

The problem of evaluating the solvency of insurance companies is tackled through the use of a non-parametric statistical model, constructed using decision-tree techniques. The model is tested on a sample of Italian non-life insurance companies and its performance over the test period compared with those of linear and quadratic parametric models.

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Riassunto Il problema della valutazione della solvibilità delle imprese di assicurazione è affrontato con l'impiego di un modello statistico non parametrico, costruito con le tecniche degli alberi delle decisioni. Viene proposta una sperimentazione del modello su un campione di imprese assicuratrici italiane operanti nei rami nonvita ed effettuata una analisi comparata intertemporale con gli standards di efficienza registrati su modelli parametrici lineare e quadratico.

     

Technology Gap and Cumulative Growth: Models and outcomes

Addressing the question of why productivity growth rates differ between countries from a disequilibrium standpoint, the paper explores the possibility of combining in a single formalisation two different but complementary theories of technical change and macroeconomic growth--namely the Kaldorian idea of cumulative causation and the technology-gap approach to economic growth. In order to investigate the complementarities between these two approaches, a two-country macroeconomic model of technology-gap and cumulative growth is presented. The analytical solutions of the model for the growth rates of productivity and demand, and the dynamics of the technology-gap show the existence of a large set of possible outcomes: the follower country can fall behind, partly or totally catch up, or overtake the leader. Moreover, even if the follower is able to close the technology-gap, it will not necessarily be able to close the growth rate differential. The empirical evidence on the experience of 26 OECD countries during 1991-99 shows the relevance of the model for explaining the recent performance of technological activities and productivity growth.     

EVOLUTIONARY AND NEW GROWTH THEORIES. ARE THEY CONVERGING?

Abstract.  This paper presents a critical review of evolutionary and new growth theories. The purpose is to discuss the often-made claim that the two approaches, both inspired by Schumpeter's seminal work, are becoming more and more similar in terms of the sources and mechanisms of the growth process on which they focus. According to this argument, some kind of theoretical convergence between the two paradigms is taking place. Differently from previous surveys of the field, this paper compares evolutionary and new growth theories by focusing on their major theoretical foundations. The discussion leads to the conclusion that the two approaches greatly differ with respect to all of their main theoretical building blocks, and that no convergence between the two paradigms is therefore taking place. This finding should be welcomed by both evolutionary and new growth scholars, because it is the process of interaction and the fruitful exchange of ideas between different approaches that lead to advances in growth theory, not their convergence to a common paradigm.     

Arbitrage, linear programming and martingales¶in securities markets with bid-ask spreads

In a general, finite-dimensional securities market model with bid-ask spreads, we characterize absence of arbitrage opportunities both by linear programming and in terms of martingales. We first show that absence of arbitrage is equivalent to the existence of solutions to the linear programming problems that compute the minimum costs of super-replicating the feasible future cashflows. Via duality, we show that absence of arbitrage is also equivalent to the existence of underlying frictionless (UF) state-prices. We then show how to transform the UF state-prices into state-price densities, and use them to characterize absence of arbitrage opportunities in terms of existence of a securities market with zero bid-ask spreads whose price process lies inside the bid-ask spread. Finally, we argue that our results extend those of Naik (1995) and Jouini and Kallal (1995) to the case of intermediate dividend payments and positive bid-ask spreads on all assets.     

Generic Existence and Robust Nonexistence of Numéraires in Finite Dimensional Securities Markets

A numéraire is a portfolio that, if prices and dividends are denominated in its units, admits an equivalent martingale measure that transforms all gains processes into martingales. We first supply a necessary and sufficient condition for the generic existence of numéraires in a finite dimensional setting. We then characterize the arbitrage‐free prices and dividends for which the absence of numéraires survives any small perturbation preserving no arbitrage. Finally, we identify the cases when any small, but otherwise arbitrary, perturbation of prices and dividends preserves either the existence of numéraires, or their nonexistence under no arbitrage.     

Service innovation and the proximity-concentration trade-off model of trade and FDI

This paper introduces service innovation in the proximity-concentration trade-off model of trade and foreign direct investments (FDI) [Helpman, E., M. Melitz, and S. R. Yeaple 2004 Helpman, E., M. Melitz, and S. R. Yeaple. 2004. “Export Versus FDI with Heterogeneous Firms.” American Economic Review 94 (1): 300–316. doi: 10.1257/000282804322970814[Crossref], [Web of Science ®] , [Google Scholar]. “Export Versus FDI with Heterogeneous Firms.” American Economic Review 94 (1): 300–316]. The idea is that innovation will have two main effects on service firms’ choice between exports and FDI. First, innovative firms will on average have higher productivity levels than non-innovative enterprises. Secondly, innovators will have to pay a higher relational distance cost for undertaking export activities, and they will, therefore, prefer to avoid (or reduce) these costs by choosing an FDI strategy instead. We test the empirical relevance of this idea on a new survey data set for a representative sample of firms in all business service sectors in Norway. The results show that firms are more likely to choose FDI rather than export the greater their productivity level and the higher the relational distance costs they face.