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.     

Real effects of private equity investments: Evidence from European buyouts

This study investigates the effects of buyout deals on the ex-post performance of target companies. The analysis is based on a sample of 241 private-to-private buyouts involving European companies between 1997 and 2004 and a control sample of non-buyouts selected through a propensity score matching methodology. The paper explores three different dimensions of firm performance: size, profitability and productivity. The results indicate a positive impact of buyouts on the growth of total assets and of employment in target firms in the short- and mid-term. An equivalent clear pattern cannot be identified for productivity, while we estimate a lower operating profitability for buyout companies with respect to the control group three years after a deal is made. When we restrict the analysis to the sub-sample of buyout companies, we find that generalist funds negatively and significantly impact the mean ex-post operating profitability of PE-backed firms, while turnaround specialists are positively associated with operating profitability. The evidence also highlights that target companies whose lead investor is located in the same country show relatively higher ex-post profitability performance.     

Obsolescence risk in advanced technologies for retailing: A management perspective

In recent years, a great deal of research focused on the introduction of advanced technologies for making traditional stores more appealing and attractive, with several benefits for the retail process. Since the introduction of these innovative systems involves several risks that can have a negative impact on business profitability, this paper aims at investigating to what extent it is possible to reduce these risks by proposing an explorative framework for a successful risk management strategies in retail context. Key results of this research concern the importance of the risk management also for retail sector, with emphasis on the introduction/adoption decision of innovative technologies in the points of sale, with consequences for retail-oriented industries. To achieve this task, the current study synthesizes findings from several fields such as management, marketing, and computer science.     

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.     

Partnership,reciprocity and team design

This paper studies the effect of intention-based reciprocity preferences on the free-riding problem arising in partnerships. Our results suggest a tendency of efficient partnerships to consist of members whose sensitivity to reciprocity is – individually or jointly – sufficiently high. Sufficient conditions for the implementation of the efficient strategy profile require a reciprocity-based sharing rule so that each partner gets a fraction of the output, which is a percentage of his own sensitivity to reciprocity with respect to the overall sensitivity in the team. Finally, we introduce the concept of psychological strong Nash equilibrium and show that it allows for the unique and collusion-proof implementation of the efficient strategy profile.     

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.     

Testing for unit roots in time series models with non-stationary volatility

Many of the key macro-economic and financial variables in developed economies are characterized by permanent volatility shifts. It is known that conventional unit root tests are potentially unreliable in the presence of such behaviour, depending on a particular function (the variance profile) of the underlying volatility process. Somewhat surprisingly then, very little work has been undertaken to develop unit root tests which are robust to the presence of permanent volatility shifts. In this paper we fill this gap in the literature by proposing tests which are valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth-transition) volatility change processes as special cases. Our solution uses numerical methods to simulate the asymptotic null distribution of the statistics based on a consistent estimate of the variance profile which we also develop. The practitioner is not required to specify a parametric model for volatility. An empirical illustration using producer price inflation series from the Stock–Watson database is reported.