Cost-effectiveness analysis of mechanical thrombectomy with stent retriever in the treatment of acute ischemic stroke in Italy

Background: Stroke has a significant disease burden in terms of acute and long-term disability in Italy and throughout the world. Endovascular treatments for the management of a stroke event have been coupled in the past years with the possibility to mechanically remove the occlusion by means of specially designed thrombectomy devices, and their exclusive use showed levels of effectiveness in line with those of the existing pharmacological treatments.

Objective: To assess the cost-effectiveness of mechanical thrombectomy (MT) with the Solitaire Revascularization Device (stent retriever) for the treatment of acute ischemic stroke (AIS) in patients with large vessel occlusions (LVOs), comparing MT plus intravenous tissue plasminogen activation (MT plus IV t-PA) vs IV t-PA alone, in Italy.

Methods: A Markov model was used to simulate costs and benefits of MT plus IV t-PA and IV t-PA alone over a 5-year time horizon and considering the perspective of the Italian National Health Service (NHS). Results are reported in terms of Incremental Cost Effectiveness Ratio (ICER). Deterministic and probabilistic sensitivity analyses are carried out in order to test the robustness of the results.

Results: Total costs of MT plus IV t-PA and IV t-PA alone are equal to €31,798 and €34,855, respectively. The MT allows incremental QALYs for 0.77, determining a dominant ICER. The utilities associated to the mRS health states are the parameters with the highest impact on the results. Multiway sensitivity analyses determined a 90% probability of dominance.

Conclusions: MT plus IV t-PA for AIS patients with LVO is cost-effective from year 1 through year 3, and cost-saving from year 4 onward in the Italian context, achieving better results, both in terms of efficacy and in terms of resource consumption.     

Identifying the Independent Sources of Consumption Variation

By representing a system of budget shares as an approximate factor model we determine its rank, i.e. the number of common functional forms or factors, and we estimate a base of the factor space by means of approximate principal components. We assume that the extracted factors span the same space of basic Engel curves representing the fundamental forces driving consumers' behaviour. We identify these curves by imposing statistical independence and by studying their dependence on total expenditure using local linear regressions. We prove consistency of the estimates. Using data from the UK Family Expenditure Survey from 1977 to 2006, we find strong evidence of two common factors and mixed evidence of a third factor. These are identified as decreasing, increasing, and almost constant Engel curves. The household consumption behaviour is therefore driven by two factors respectively related to necessities (e.g. food), luxuries (e.g. vehicles), and in some cases by a third factor related to goods to which is allocated the same percentage of total budget both by rich and poor households (e.g. housing). Copyright © 2015 John Wiley & Sons, Ltd.     

A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering

We introduce a new factor model for log volatilities that considers contributions, and performs dimensionality reduction, at a global level through the market, and at a local level through clusters and their interactions. We do not assume a-priori the number of clusters in the data, instead using the Directed Bubble Hierarchical Tree algorithm to fix the number of factors. We use the factor model to study how the log volatility contributes to volatility clustering, quantifying the strength of the volatility clustering using a new nonparametric integrated proxy. Indeed finding a link between volatility and volatility clustering, we find that a global analysis reveals that only the market contributes to the volatility clustering. A local analysis reveals that for some clusters, the cluster itself contributes statistically to the volatility clustering effect. This is significantly advantageous over other factor models, since it offers a way of selecting factors in a statistical way, whilst also keeping economically relevant factors. Finally, we show that the log volatility factor model explains a similar amount of memory to a principal components analysis factor model and an exploratory factor model.     

Non‐Fundamentalness in Structural Econometric Models: A Review

Current economic theory typically assumes that all the macroeconomic variables belonging to a given economy are driven by a small number of structural shocks. As recently argued, apart from negligible cases, the structural shocks can be recovered if the information set contains current and past values of a large, potentially infinite, set of macroeconomic variables. However, the usual practice of estimating small size causal Vector AutoRegressions can be extremely misleading as in many cases such models could fully recover the structural shocks only if future values of the few variables considered were observable. In other words, the structural shocks may be non‐fundamental with respect to the small dimensional vector used in current macroeconomic practice. By reviewing a recent strand of econometric literature, we show that, as a solution, econometricians should enlarge the space of observations, and thus consider models able to handle very large panels of related time series. Among several alternatives, we review dynamic factor models together with their economic interpretation, and we show how non‐fundamentalness is non‐generic in this framework. Finally, using a factor model, we provide new empirical evidence on the effect of technology shocks on labour productivity and hours worked.     

Innovation policy in progress. Institutional intermediation in public procurement of innovation: satellite telecommunications in Italy

This paper aims to explore a mechanism of institutional intermediation to sustain public procurement of innovation. By exploring the development of innovative solutions for telecommunications satellites in Italy, this study proposes an analytical view on the role of supporting institutions in public procurement of innovation and discusses the relation between the source of public demand and the contracting companies. Eventually, it argues that a public agency can manage funds, coordinate companies’ technological capabilities, and stimulate a sense of cooperation to achieve innovation. The research finds originality in bringing the growing theory concerning public procurement into a dynamic institutional setting to discuss the emerging role of the public competent costumer. The case-analysis shows how institutionalization of an innovation intermediary enables efficient procurement. Propositions prescribe powerful instruments for dealing with market uncertainty and technological complexity, and find the agency to act as a knowledge intermediary and companies coordinator.     

Relational capital, profitability and access to credit: evidence from a sample of Italian small firms

This paper investigates the relationship between relational capital and profitability and accessibility to credit of a small firm. The extant literature shows a positive link between relational capital and other variables relevant to a firm’s development but does not cover access to credit. Here, a sample of 136 small firms from Piemonte (north-western Italy) is used. The results show that relational capital eases the access to credit and, in some cases, increases the probability of running positive profits.     

Robust martingale selection problem and its connections to the no‐arbitrage theory

We analyze the martingale selection problem of Rokhlin in a pointwise (robust) setting. We derive conditions for solvability of this problem and show how it is related to the classical no‐arbitrage deliberations. We obtain versions of the Fundamental Theorem of Asset Pricing in models spanning frictionless markets, models with proportional transaction costs, and models for illiquid markets. In all these models, we also incorporate trading constraints.     

The ‘Duce hometown effect’ on local industrial development: The case of Forlì

Abstract

The history of fascist intervention and rescue in support of Italian banks and firms (either through nationalisation or direct aid) in the inter-war years is well known. The case of Forlì adds an important piece of information to the broad literature on state-sponsored development. Benito Mussolini was born in Predappio, a small village in the Apennines in the province of Forlì. And Forlì was meant to become ‘la città del Duce’ (‘the Duce’s hometown’). The case of Forlì offers an original perspective: entrepreneurs who chose Mussolini’s hometown to obtain special concessions, a novel element in the crowded panorama of special relationships between government and industry in Italy. But on the other hand, this article will also underline the unsuitability of big business to local economic characteristics (and post-war challenges) and the return to a traditional growth path centred around the small-firm model specialising in traditional sectors and family-owned, centralised management. State-sponsored business failed and provided no stimulus to local growth: any talk of ‘industrial continuity’ in Forlì requires us to acknowledge that it is based on the steady presence and continuous regeneration of locally grown, small family businesses.     

Health Systems and Health Reform in Europe

The organisation of health care differs widely across Europe. Access to services, financing schemes, incentives for better care, and administrative efficiency are challenges that are being dealt with in a variety of ways. Are insurance-based systems the best solution for balancing resources and services or are national health funds preferable? Does the introduction of competition fulfil high hopes for better service at lower costs? What are the relative advantages and drawbacks of central and local management of health care?     

Evaluating the effect of monetary policy on unemployment with alternative inflation forecasts

This paper explores the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. We use the inflation forecasts of 8 competing models in a standard Bayesian VAR to analyse the size and the timing of these effects, as well as to quantify the uncertainty relative to the different inflation models under two rules. The results suggest that model uncertainty can be a serious issue and strengthen the case for a policy strategy that takes into account several sources of information. We find that combining inflation forecasts from many models not only yields more accurate forecasts than those of any specific model, but also reduces the uncertainty associated with the real effects of policy decisions. These results are in line with the model-combination approach that central banks already follow when conceiving their strategy.