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The purpose of this article is to investigate if and how social capital offline – stemming from face-to-face interactions – and social capital online – stemming from social digital media – can influence early-stage entrepreneurs, i.e. ventures with up to 42 months of existence.

The authors used herein a qualitative research approach. The method used was the case study. The authors investigated three early-stage entrepreneurs in order to achieve the objective of the paper. These entrepreneurs are both the unit of analysis and the unit of observation.

The outcomes of this research indicate (1) the combined importance of social capital offline and online; (2) the different performance of the two different types of social capital (they seem to operate in relatively distinct ways) and (3) the existence of recursiveness between resources stemming from the two social spheres (offline and online).

As research limitations, the authors point out the following: (1) the use of semistructured interviews as the only data collection instrument; (2) the limitation of the outcomes to entrepreneurs only (3) the absence of information on the performance of the business ventures; the focus of the paper was only on establishing causality between social capital offline and online and entrepreneurial performance.

This paper provides important research contributions. Initially, the paper presents a range of offline and online variables, which can be used in further research. At the same time, the paper emphasizes the combined impact of social capital offline and online, expanding the literature related to entrepreneurship. Moreover, this study proposes the creation of an integrative model. Finally, the authors point out the need for new theoretical and empirical studies on the subject, which still presents a gap in the literature.

Founded in 2015, the Impact Valuation Roundtable (IVR) is an informal group of companies who wish to operationalise the emerging field of Impact Valuation. IVR participants consider Impact Valuation a groundbreaking approach to measure and value the effects of business activities on the health and well-being of people and the planet – in economic, environmental, social and human dimensions.

Impact Valuation can support large and small companies alike. It uses the language of business, supports strategic decision-making by adding fact-based insights into business operations and strengthens the communication and engagement of business with stakeholders. This is showcased in case studies from adidas, Ambuja Cements Limited, BASF, Cementos Argos, Maersk, Natura, Novartis, Syngenta and UPM.

Although there is an increased recognition of the benefits of Impact Valuation, comparability in the calculation and communication of the results of Impact Valuation assessments across companies is one of the key challenges to the credibility and uptake of the concept. The IVR supports and encourages the development of consistent frameworks and standards that strive for maximum commonality across industries, pragmatism in their application, and allow for scaling up.

As importance and interest rises, the IVR continues to welcome other practitioners willing to contribute knowledge and experience to accelerate convergence and mainstreaming of Impact Valuation.

The purpose of this paper is to validate and apply enrichment diagrams (EDs) to determine metal and as enrichment and contamination in the sediments of Sepetiba Bay.

Through inducted coupled plasma – optical emission spectrophotometry, total element (As, Cd, Cu, Ni, Pb and Zn) concentrations were assessed for the construction of EDs and comparison with enrichment factors (EFs) in 65 samples collected in Sepetiba Bay.

Based on the EDs, it was observed that the sediments around the urban area of Sepetiba and ItaguaíHarbor were contaminated with Cd, Cu, Ni, Pb and Zn. These contaminants were expected due to the urban and industrial discharges into the bay and the activities at ItaguaíHarbor.

The ED was successful regarding its ability to evaluate inorganic contamination in Sepetiba Bay. In addition, this method was able to define a proper background sample for calculating EFs.

This paper analyzes the potential presence of time-varying asymmetries in the preference parameters of the Central Bank of Brazil during the inflation targeting regime.

Given the econometric issues inherent to classical time-varying parameter (TVP) regressions, a Bayesian estimation procedure is implemented in order to provide more robust parameter estimates. A stochastic volatility specification is also included to take into account the potential presence of conditional heteroskedasticity.

The obtained results show that the reduced form and structural parameters were not constant during the period considered. Moreover, the subsequent analysis of the preference parameters provided evidences of short periods in which asymmetry was an important feature to the conduction of monetary policy in Brazil. Yet, during most of the sample period, the loss function was considered to be symmetrical.

This paper aims to contribute to the rather scarce monetary debate on time-varying central bank preferences. The study of Lopes and Aragón (2014) is, to the best of the authors’ knowledge, the only study for Brazil considering specifically TVPs. The authors applied Kalman filter estimation to data from 2000:M1 to 2011:M12. Despite the similar structure of TVPs, the present paper extends the latter study by controlling for stochastic volatility. Ignoring conditional heteroskedasticity might lead to spurious movements in time-varying variables and inaccurate inference (Hamilton, 2010). Thus, the stochastic volatility specification is included to take this issue into account. The authors follow the theoretical scheme put forward by Surico (2007) and Aragón and Portugal (2010), in which the economy is modeled from a New Keynesian perspective and the central bank loss function is assumed to be asymmetric regarding the responses to inflation and output deviations from their targets. On the empirical side, the authors propose a TVP univariate regression with stochastic volatility for the Brazilian reduced-form reaction function, following closely the Bayesian econometric procedure developed by Nakajima (2011). Given the nonlinear non-Gaussian nature of the TVP regression with stochastic volatility, the choice of a nonlinear Bayesian approach using the Markov chain Monte Carlo (MCMC) method is justified due to the intractability of the associated likelihood function (Primiceri, 2005). Finally, based on the theoretical model specification, the authors intend to recover the central bank preference parameters as to further evaluate the degree of asymmetry and its potential time-variation under the inflation targeting regime.