Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

Nonlinear economic growth: Some theory and cross-country evidence

This paper aims to test the existence of different growth regimes, that is of different relationships between growth rate and income level. We propose a simple nonlinear growth model and test its empirical implications by estimating Markov transition matrices and stochastic kernels. We show that growth is indeed nonlinear: a first phase of slow or zero growth is followed by a take-off and, finally, by a phase of deceleration. We discuss the relevance of these results with respect to the issue of convergence and reversibility of development, in the light of models of structural change and technological diffusion.     

Going Public and the Enrichment of a Supportive Network

Past research on initial public offerings suggests that the reputation of a company positively affects the success of the offering. Success is usually measured in financial terms as if the essence of the operation lay only in the short-term inflow of money. In this paper, we investigate important albeit often neglected implications of going public by combining evidence from a series of preliminary case studies taken from the results of a survey of 57 Italian initial public offerings. Evidence from our research suggests that, besides providing an important inflow of capital, going public may actually improve the reputational and social capital of a company, by increasing its visibility, prestige and perceived trustworthiness. Therefore, going public may be an important way to support entrepreneurial activity, as it may expand and reinforce the network of relationships that offer access to external resources, complementary skills and investment opportunities.     

The potential impact of markets for irrigation water in Italy and Spain: a comparison of two study areas*

The viability of irrigated systems in Southern Europe is closely linked to efficient institutional settings and water‐allocation mechanisms. A significant, although not widely used, mechanism for water allocation is an intra‐sectorial water market. The objective of this paper is to evaluate to what extent water markets may contribute to the improvement of the efficiency of water allocation and to the profitability of irrigated agriculture. The related issues of water allocation among farm types and farm specialisation are also addressed. The analysis is based on a basin‐level linear programming model, comparing the situation with and without a market. It includes both fixed and variable transaction costs and estimates their combined effects on market performances. The model is applied in two areas in Southern Italy and Spain, and simulates the behaviour of different farm types, derived from cluster analysis on a sample of farms in each area. The paper confirms that water markets could potentially improve the economic efficiency of water use, in terms of higher profit per hectare, given limited water availability. The potential improvements are associated with a more intense specialisation of farms and are strongly differentiated among farmers, particularly where significant restrictions to water availability occur. This corroborates the expectations of institutional difficulties in implementing water markets. However, the exchanges, and consequently the potential effects of water markets, are heavily affected by the actual level of water availability, as well as the size and the structure (fixed vs. proportional) of transaction costs. The paper calls for a more in‐depth analysis of the connections between market performances and institutional settings, as related to the issue of water‐agriculture policy design and coordination.     

The Open Innovation Journey: How firms dynamically implement the emerging innovation management paradigm

Open Innovation is currently one of the most debated topics in management literature. Nevertheless, there are still many unanswered questions in Open Innovation research. Especially two issues require further investigation: (i) understanding the relevance of Open Innovation beyond high-tech industries and (ii) studying how firms implement Open Innovation in practice. The paper addresses these topics by studying, through an in-depth case study, the journey that the Italian leading cement manufacturer, has undergone to move from a Closed to an Open Innovation paradigm.The paper shows that the Open Innovation paradigm is implemented along a three-phase process that comprises the stages of unfreezing, moving and institutionalising. Moreover, it emerges that the changes through which Open Innovation has been implemented involve four major dimensions, i.e. networks, organisational structures, evaluation processes and knowledge management systems. They should be therefore conceived as the managerial and organisational levers an innovating firm can act upon to streamline its journey toward Open Innovation. Theoretical and managerial implications of using these levers for implementing Open Innovation are discussed at length.     

PFIs involving multiple public partners: a case study from the Italian healthcare sector

The financial crisis experienced by many countries since 2008 has given new importance to private finance initiatives (PFIs) for providing public services. This paper analyses the relationships between multiple public and private sector actors participating in a PFI in the healthcare sector in order to better understand the motives and behaviour of public and private sector partners. High levels of trust and the active participation of a regulatory body were found to be significant factors in terms of creating a partnership that benefits all sides.     

Conditional assessment of the impact of a Hausman pretest on confidence intervals

In the analysis of clustered and longitudinal data, which includes a covariate that varies both between and within clusters, a Hausman pretest is commonly used to decide whether subsequent inference is made using the linear random intercept model or the fixed effects model. We assess the effect of this pretest on the coverage probability and expected length of a confidence interval for the slope, conditional on the observed values of the covariate. This assessment has the advantages that it (i) relates to the values of this covariate at hand, (ii) is valid irrespective of how this covariate is generated, (iii) uses exact finite sample results, and (iv) results in an assessment that is determined by the values of this covariate and only two unknown parameters. For two real data sets, our conditional analysis shows that the confidence interval constructed after a Hausman pretest should not be used.     

Stable Asymptotics for M‐estimators

We review some first‐order and higher‐order asymptotic techniques for M‐estimators, and we study their stability in the presence of data contaminations. We show that the estimating function (ψ) and its derivative with respect to the parameter play a central role. We discuss in detail the first‐order Gaussian density approximation, saddlepoint density approximation, saddlepoint test, tail area approximation via the Lugannani–Rice formula and empirical saddlepoint density approximation (a technique related to the empirical likelihood method). For all these asymptotics, we show that a bounded ψ (in the Euclidean norm) and a bounded (e.g. in the Frobenius norm) yield stable inference in the presence of data contamination. We motivate and illustrate our findings by theoretical and numerical examples about the benchmark case of one‐dimensional location model.     

Fiscal policy under loose commitment

Due to time-inconsistency or political turnover, policymakers' promises are not always fulfilled. We analyze an optimal fiscal policy problem where the plans made by the benevolent government are periodically revised. In this loose commitment setting, the properties of labor and capital income taxes are significantly different than under the full-commitment and no-commitment assumptions. Because of the occasional reoptimizations, the average capital income tax is positive even in the long-run. Also, the autocorrelation of taxes is lower, their volatility with respect to output increases and the correlation between capital income taxes and output changes sign. Our method can be used to analyze the plausibility and the importance of commitment in a wide-class of dynamic problems.