Trust,risk and time preferences: evidence from survey data

The paper shows that time preferences and risk preferences are key covariates of self-reported trust. They both predict negatively a measure of generalized trust; however, risk aversion is positively correlated with an index of particularized trusting behaviour (which refers to the circle of known people).     

The effect of opposite sex siblings on cognitive and noncognitive skills in early childhood

We investigate the effect of having opposite sex siblings on cognitive and noncognitive skills of children in the United States at the onset of formal education. Our identification strategy rests on the assumption that, conditional on covariates, the sibling sex composition of the two firstborn children in a family is arguably exogenous. With regard to cognitive skills, learning skills and self-control measured in kindergarten, we find that boys benefit from having a sister, while there is no effect for girls. We also find evidence for the effect fading out as early as first grade.     

Interest rate assumptions and predictive accuracy of central bank forecasts

The interest rate assumptions for macroeconomic forecasts differ among central banks. Common approaches are given by the assumptions that interest rates remain constant over the forecast horizon, follow a path as expected by market participants or follow a path as expected by the central bank itself. Theoretical papers such as Svensson (The instrument-rate projection under inflation targeting: the Norwegian example. Centre for European Policy Studies Working Paper (127), 2006) and Galí (J Monet Econ 58:537–550, 2011) suggest an accuracy ranking for these forecasts, from employing central bank expectations yielding the highest forecast accuracy to conditioning on constant interest rates yielding the lowest. Yet, when investigating the predictive accuracy of the Bank of England’s and the Banco Central do Brasil’s forecasts for interest rates, inflation and output growth, we hardly find any significant differences between forecasts based on the different interest rate paths. Our results suggest that the choice of the interest rate assumption appears to be of minor relevance empirically.     

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.     

The Outsourcing of Manufacturing and the Rise of Giant Global Contractors: A Marxian Approach to Some Recent Transformations of Global Value Chains

This article aims to show that the Marxian ‘law of value’ can provide solid foundations for the comprehension of the constitution and dynamics of Global Value Chains (GVC). It offers an explanation of the social processes of ‘value creation and capture’ within a chain based on the system-wide motion of global capital accumulation. A firm connection is thus established between the particular dynamics internal to each industry and the general dynamics of the ‘system as a whole’, which is, precisely, where the greatest weakness of the GVC approach lies. Furthermore, the usefulness of those general theoretical insights is then shown through a more empirical discussion of recent transformations in the composition and governance structure of GVC resulting from two interrelated processes: the tendency for a growing de-linking between innovation and manufacturing and the rise of highly concentrated global contractors. These phenomena have paradigmatically developed in the electronics industry, giving rise to the formation of the so-called modular or turnkey production networks. The discussion therefore focuses on that particular industrial sector.     

The Impact of Interactive Corporate Social Responsibility Communication on Corporate Reputation

Companies increasingly communicate about corporate social responsibility (CSR) through interactive online media. We examine whether using such media is beneficial to a company’s reputation. We conducted an online experiment to examine the impacts of interactivity in CSR messages on corporate reputation and word-of-mouth intentions. Our findings suggest that an increase in perceived interactivity leads to higher message credibility and stronger feelings of identification with the company, which also boost corporate reputation and word-of-mouth. This result implies that using interactive channels to communicate about CSR can improve corporate reputation. Our results also show that the detrimental impacts of negative user evaluations on corporate reputation are much higher than the favorable impacts of positive evaluations. This finding suggests that, despite the effectiveness of interactive communication channels, firms need to carefully monitor these channels.     

Qualitative valuation of environmental criteria through a group consensus based on stochastic dominance

This paper introduces a qualitative valuation method to elicit stakeholders' intensities of preferences for a complex environmental issue and multiple social groups. Environmental valuation studies have shown that in any complex environment with a diversity of environmental services, stakeholders have difficulties using a monetary valuation to make trade-offs between different environmental services. Stated preference methods such as the Contingent Valuation Method (CVM) have been criticised for their individualistic format and assumptions of commensurability between environmental criteria. To alleviate both of these criticisms, we propose a qualitative valuation method. The method contains a discursive step to allow stakeholders to discuss and construct a list of environmental criteria and alternative plans. The list of criteria and plans is subsequently used by a group of experts to formulate an Impact Matrix (IM), which is to be used in the succeeding individualistic steps of the methodology. The first individualistic step consists of asking the stakeholders to rank Alternative Impacts (AIs) in the IM for each single criterion. The stakeholders are then asked to express intensities of their preferences through pairwise comparisons between the AIs of the constructed rank order on each single criterion. These intensities are expressed on a qualitative scale. Subsequently, to provide social intensities of preferences, a social preference (social rank order) is first determined for each single criterion. We propose to use the median value among the intensities of preferences as the social intensity of preference by assuming interpersonal comparability and taking into account stochastic monotonocity. This is a pre-processing step, which allows us to reach social intensities of preferences in the Lar rangeland (Iran), where several social groups have conflicting interests on rangeland services, leading to conflicting preferences on environmental criteria.     

Economics of externalities and public policy

In this paper we study a particular case of “multiple” externalities associated to the production of a good/activity, whose external effects can change from positive to negative depending on the level of output (intersecting externalities). To analyze their impact on the public policy we propose a very simple two-agent partial equilibrium model in the technological context of externalities. In a static framework, the centralized solution always implies an optimal policy, which may consist of taxation or subsidization depending on the individual optimum and on the technology parameters. In a dynamic model with local knowledge of the efficiency function and instantaneous output adjustments, such an optimal policy can be structurally stable or unstable. In the latter case, under small changes of the parameters the policy may switch from low taxation/subsidization to high taxation/subsidization or vice versa, or even jump discontinuously from taxation to subsidization or vice versa. Furthermore, the decentralized solution based upon “tradable rights” can be economically equivalent to the centralized solution in the form of taxation policy but the two solutions may be not politically equivalent.

Limit theory for panel data models with cross sectional dependence and sequential exogeneity

The paper derives a general Central Limit Theorem (CLT) and asymptotic distributions for sample moments related to panel data models with large n$n$. The results allow for the data to be cross sectionally dependent, while at the same time allowing the regressors to be only sequentially rather than strictly exogenous. The setup is sufficiently general to accommodate situations where cross sectional dependence stems from spatial interactions and/or from the presence of common factors. The latter leads to the need for random norming. The limit theorem for sample moments is derived by showing that the moment conditions can be recast such that a martingale difference array central limit theorem can be applied. We prove such a central limit theorem by first extending results for stable convergence in Hall and Heyde (1980) to non-nested martingale arrays relevant for our applications. We illustrate our result by establishing a generalized estimation theory for GMM estimators of a fixed effect panel model without imposing i.i.d. or strict exogeneity conditions. We also discuss a class of Maximum Likelihood (ML) estimators that can be analyzed using our CLT.     

When do Non‐Family CEOs Outperform in Family Firms? Agency and Behavioural Agency Perspectives

Family firms represent a globally dominant form of organization, yet they confront a steep challenge of finding and managing competent leaders. Sometimes, these leaders cannot be found within the owning family. To date we know little about the governance contexts under which non‐family leaders thrive or founder. Guided by concepts from agency theory and behavioural agency theory, we examine the conditions of ownership and leadership that promote superior performance among non‐family CEOs of family firms. Our analysis of 893 Italian family firms demonstrates that these leaders outperform when they are monitored by multiple major family owners as opposed to a single owner; they also outperform when they are not required to share power with co‐CEOs who are family members, and who may be motivated by parochial family socioemotional priorities.