A PANIC Attack on Unit Roots and Cointegration

This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of nonstationarity in the data. We refer to it as PANIC—Panel Analysis of Nonstationarity in Idiosyncratic and Common components. PANIC can detect whether the nonstationarity in a series is pervasive, or variable‐specific, or both. It can determine the number of independent stochastic trends driving the common factors. PANIC also permits valid pooling of individual statistics and thus panel tests can be constructed. A distinctive feature of PANIC is that it tests the unobserved components of the data instead of the observed series. The key to PANIC is consistent estimation of the space spanned by the unobserved common factors and the idiosyncratic errors without knowing a priori whether these are stationary or integrated processes. We provide a rigorous theory for estimation and inference and show that the tests have good finite sample properties.     

Determining the Number of Factors in Approximate Factor Models

In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross‐sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria have good finite sample properties in many configurations of the panel data encountered in practice.     

Just for fun? Alcohol and drugs in youth lifestyles: a survey

The article presents an analysis of the relationship between young people and alcohol and drug use, examining both their attitudes and behaviors. The analysis is based on statistics collected through a structured-questionnaire survey of 1071 students from the secondary schools of Rome and the Province. The first part of the article examines patterns and levels of alcohol and drug use and typical places of use. The central part is dedicated to the perceptions and opinions on alcohol and drugs, with particular regard to the dimensions of risk and sociality, and to the different roles of school and family in raising risk awareness. Sociality appears as a crucial element in young people's tendency to associate alcohol and drugs with an effect of relaxation and disinhibition that makes social relations easier. The article finally examines the relationship between young people and social norms, identifying transgressive models and habits. On the whole, the study highlights a connection between alcohol and drug use and desire of sociality, which is experienced more as a situational and ever-changing practice than as a search for close friendships.     

Long-term Growth Perspectives and Economic Convergence of CEE and SEE Countries

The paper first investigates the main drivers of economic growth and real convergence in CEE and SEE Countries. In the theoretical framework provided by the growth-accounting approach, both are shown to be driven by capital accumulation and total factor productivity changes, with the latter making however a major contribution. The nominal convergence path towards the Eurozone is then analysed. Despite considerable results obtained in the last decade, most EU new members are still found to face severe challenges in the process of converging towards Maastricht criteria. The need to reconcile exchange rate stability with inflation convergence is in particular seen to be at the heart of their de facto decision to delay the EMU entry date until a higher degree of real convergence will have been achieved.

Brand management: Unveiling the delusion of control

Mainstream brand management literature views brands as products or organisations carrying brand names and brand managers as being in control of brand-related actions and outcomes. By contrast, recent empirical research shows the substantial influence of stakeholders on brands. Together with brand management, stakeholders shape brands by participating in brand-related interaction. European brand research accordingly treats brands as ongoing and complex processes in constant flux. Nevertheless, literature suffers from a significant lack of theoretical underpinnings for understanding brands as complex processes; in this respect, building on European philosophy is a fruitful avenue. This paper introduces the metaphor of the rhizome and draws on European process philosophy to further develop an integrative processual understanding of brands. Brand management claiming control over brands as processes turns out to be a delusion.     

Italian Social Enterprises at the Crossroads: Their Role in the Evolution of the Welfare State

This paper investigates the relationship between the emergence of social enterprises (SEs) and the historical development of the Italian welfare state. Our research offers a comprehensive overview of the internal and external influences that shaped the constitutive relations between the welfare state and SEs. A qualitative methodology based on semi-structured interviews and focus groups has been adopted. This study suggests that two interconnected dynamics—the emergence of new social needs being answered by private organisations and the increased prominence of third sector actors during the privatisation of the welfare state—shaped the co-evolution of the welfare state and SEs in Italy. The study also suggests that the emergence and evolution of Social Enterprises in the years leading up to 2001 was mainly a bottom-up phenomena stemming from the actions of citizens setting up private organisations (often cooperatives) to answer to social problems created by new social needs and the structural reform of the welfare state. After 2001 especially with the new law on SEs in 2016, the evolution of SEs seems to have been increasingly influenced by the surrounding ecosystem of actors and supranational policy discourses rather than SEs themselves.     

Bayesian Estimators for Small Area Models when Auxiliary Information is Measured with Error

Small area estimators in linear models are typically expressed as a convex combination of direct estimators and synthetic estimators from a suitable model. When auxiliary information used in the model is measured with error, a new estimator, accounting for the measurement error in the covariates, has been proposed in the literature. Recently, for area‐level model, Ybarra & Lohr (Biometrika, 95, 2008, 919) suggested a suitable modification to the estimates of small area means based on Fay & Herriot (J. Am. Stat. Assoc., 74, 1979, 269) model where some of the covariates are measured with error. They used a frequentist approach based on the method of moments. Adopting a Bayesian approach, we propose to rewrite the measurement error model as a hierarchical model; we use improper non‐informative priors on the model parameters and show, under a mild condition, that the joint posterior distribution is proper and the marginal posterior distributions of the model parameters have finite variances. We conduct a simulation study exploring different scenarios. The Bayesian predictors we propose show smaller empirical mean squared errors than the frequentist predictors of Ybarra & Lohr (Biometrika, 95, 2008, 919), and they seem also to be more stable in terms of variability and bias. We apply the proposed methodology to two real examples.     

Using Linked Longitudinal Administrative Data to Identify Social Disadvantage

Social Indicators Research - Administrative data are widely used to construct indicators of social disadvantage, such as Free School Meals eligibility and Indices of Multiple Deprivation, for...