Forecasting monthly industrial production in real-time: from single equations to factor-based models

The aim of this paper is to analyze the performance of alternative forecasting methods to predict the index of industrial production in Italy from 1 to 3 months ahead. We use twelve different models, from simple ARIMA to dynamic factor models exploiting the timely information of up to 110 short-term indicators, both qualitative and quantitative. This allows to assess the relevance for the forecasting practice of alternative combinations of types of data (real-time and latest available), estimation methods and periods. Out-of-sample predictive ability tests stress the relevance of more indicators in disaggregate models over sample periods covering a complete business cycle (about 7 years in Italy). Our findings downgrade the emphasis on both the estimation method and data revision issues. In line with the classical “average puzzle”, the use of simple averages of alternative forecasts often improves the predictive ability of their single components, mainly over short horizons. Finally, selected indicators and factor-based models always perform significantly better than ARIMA models, suggesting that the short-run indicator signal always dominates the noise component. On this regard, selected indicators models can further increase the amount of signal extracted to improve up to 30–40% the short-run predictive ability of factor-based models and to forecast-encompass them.     

A dynamic model of R&D competition

This study considers a dynamic model of R&D competition in a situation of no uncertainty with identical firms in a perfect foresight. We are going to find out about the effects of firms' absorptive capacity on R&D strategies in the presence of technological spillovers. The conditions for the existence and uniqueness of a feedback–Nash equilibrium on firms' R&D expense will be also discussed. Numerical simulations will show as the introduction of the absorptive capacity reduces the impact of spillovers degree on firms' R&D strategies.     

An investment-function-based measure of capacity utilisation.: Potential output and utilised capacity in the Bank of Italy's quarterly model

Measures of potential output and the output gap are increasingly being developed and used to concisely quantify and monitor the risk of price accelerations stemming from rises in aggregate demand that are not met by a corresponding increase in supply. They often play a prominent role in the price determination mechanisms of macroeconometric models. In this paper we build a measure of potential private-sector value added for the Italian economy that is consistent with the capital accumulation process in the Banca d'Italia's Quarterly Model — and more generally with the rest of the supply-side block of that model. More specifically, we exploit the fact that the investment function can be thought of as a relationship transforming desired gross additions to capacity output into capital accumulation by means of a conversion factor (the optimal capital/output ratio). Thus, if one removes the component of investment decisions that stems from changes in the relative price of the production factors, (i.e. in the optimal capital/output ratio), then a measure of the desired gross addition to capacity may be constructed. The results draw a cyclical picture of the degree of capacity utilisation for the period 1970–1997 that is roughly in line with those produced by the Wharton and Hodrick–Prescott filter approaches, as well as with the pictures resulting from the ISAE, IMF, European Commission and OECD measures of the output gap. Our investment-function-based measure appears to be a promising indicator of the pressure exerted on prices by demand accelerations. Its empirical properties are, on the whole, acceptable and plausible.     

An agent-based model of innovation diffusion: network structure and coexistence under different information regimes

The paper analyzes how the structure of social networks affects innovation diffusion and competition under different information regimes. Diffusion is modeled as the result of idiosyncratic adoption thresholds, local network effects and information diffusion (broadcasting and demonstration effect from previous adopters). A high social cohesion decreases the probability of one innovation cornering the market. Nonetheless, with imperfect information, in small-world networks the higher speed of diffusion produced by the low average distance increases this probability. A low social cohesion also increases the probability of falling into traps of under-adoption. However, such probability is significantly lower with imperfect information, because such regime is characterized by higher levels of market concentrations and this reduces the frictions due to the coexistence of non-compatible product innovations.     

AHP-based approaches for supplier evaluation: Problems and perspectives

Supplier evaluation has assumed a strategic role in determining competitiveness of large manufacturing companies. An increasing number of researches have been devoted to the development of different kind of methodologies to cope with this problem. Nevertheless, while the number of applications is growing, there is little empirical evidence of the practical usefulness of such tools with a dichotomy between theoretical approaches and empirical applications. Considering this evidence, the goal of this paper is to contribute to understand the above dichotomy by implementing, in a corporate environment, a model for supplier evaluation based on the Analytical Hierarchical Process (AHP), one of the most prominent methodologies used to address the problem. The analysis of the implementation process of the methodology allows the identification of strengths and weaknesses of using formalized supplier selection models to tackle the supplier evaluation problem, also highlighting potential barriers preventing firms to adopt such methods. Relevant issues arising from the application and managerial implications for both customer and suppliers are discussed.     

Government Size,the Role of Commitments*

We explore the hypothesis that long‐term commitments affect the dynamics of government expenditure. With the aid of a simple median‐voter model we interpret the pattern of increasing‐then‐constant tax rates observed in OECD countries in the second half of the last century: persistence of public expenditure and a lower bound on new interventions will push government size upward, and preferences of the electorate put a halt to this growth at some point. In this view, the fiscal policy variable is seen to consist of only a part of the total expenditure, the rest being predetermined by its past level.     

Assessing the reassessment: A panel analysis of the Lisbon Strategy

We assess the employment impact of the Lisbon Strategy, examining long-run growth in total, female and old-age employment rates from 1994 to 2009. The Strategy had some impact, especially for old-age workers, but no improvement ensued from its mid-term reassessment.     

Growth and social capital: an evolutionary model

In this paper, we analyze the role of cooperation between firms through a model of growth and social capital. In a growth model à la Solow we incorporate the set of resources that a relational network has at its disposals, as a distinct production factor, and thus examine its dissemination through evolutionary type processes in firm interactions. Dynamic analysis of the model demonstrates that cooperation is able to increase the productivity of factors, fostering a higher rate of growth in the long term. The most significant result is that scarcity of social capital can produce a general collapse of the economic system in areas in which long term growth is usually sustained by the learning by doing and spillover of knowledge phenomena. This conclusion leads to reconsider the role of local development economic policies that should concentrate on activities that promote repeated interaction between firms proven to be cooperative or that encourage the formation of technological consortia.     

Power,Intergroup Conflicts and Social Stratification in the United States: What has the Global Crisis Taught us?

Abstract

Drawing on early sociological analyses of how power and intergroup conflicts can affect the development of modern economies, this paper investigates how the recent Global Crisis (GC) has affected the stratification of the US society. The paper argues that the consumerist society has reinforced the historical stratification of social identities with white men in high-paid, high-social status managerial and financial occupations at the top, and black women in low-paid, low-status service occupations at the bottom. This paper calls for a deconstruction of the neoliberal individual into a unique combination of identities in a stratified capitalist society in order to reveal how social stratification has evolved during the GC. The paper finally concludes on the importance of heterogeneous identities in reflecting the diversity of societal and economic interests in order to address the issues of financial stability and sustainability at the corporate and societal levels.