In this paper a two sector dynamic general equilibrium model is developed in order to evaluate the implications of the underground economy from a business cycle perspective. There are three main results. First, introducing an underground sector improves the fit of the model to the data, especially along several important labor market dimensions. Second, the model produces substantial internal propagation of temporary shocks. Third, it is shown that underground activities offer risk sharing opportunities by allowing households to smooth income through a proper labor allocation between the two sectors. Copyright Springer-Verlag Berlin/Heidelberg 2004Two-sector dynamic general equilibrium model, Underground economy, Propagation of shocks, Taxation.,

Vulnerability has garnered an increasing attention from academia, international community and industry. Nonetheless, formal definition, mainstreaming, and measurement of vulnerability are still flawed in the economic literature. Energy vulnerability, intended as the exposure of an energy system to adverse events and change, often overlaps with other energy policy concepts such as resilience, security, poverty, justice, and sustainability. This paper improves understanding of vulnerability in economics, energy, and sustainability studies by: i) constructing a dataset on energy vulnerability made of 180.000 observations; ii) formally defining energy vulnerability, while considering the regulatory framework and development agenda; iii) building a composite indicator on energy vulnerability; iv) analyzing and ranking the energy vulnerability of a vast number of OECD and non-OECD countries; v) testing for robustness checks. The analysis suggests that GDP is not necessarily a leading driver for energy vulnerability, whilst resource embedment is, since fossil and renewable energy producers are less vulnerable. Eventually, the paper validates that green countries are less vulnerable, differently from cold, heavily-industrialized, and highlyconsuming countries.

This paper explores the ability of a class of two-sector dynamic general equilibrium models to generate equilibrium time series for Money Laundering (ML), through numerical simulations in accordance with the works of Ingram, Kocherlakota and Savin (1997), Busato, Chiarini and Di Maro (2006), and Argentiero, Bagella and Busato (2008). The paper adopts this approach for the US and the EU-15 economies. The simulations show that ML accounts for 19 percent of GDP in the EU-15 economy, while it accounts for 13 percent in the US economy over the sample 2000:01-2007:04. Moreover, the ML simulated for the EU-15 is less volatile (relative standard deviation to GDP is 0.288 compared to a figure of almost 0.4 for the US economy), and negatively correlated with respect to GDP. The latter statistic is positive for the US economy.

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This paper implements a methodology that exploits firms and households' optimality conditions to measure money laundering for the Italian economy. This approach, first implemented by Ingram et al. (J Monet Econ 40:435-436, 1997) to the household production sector, and by Busato et al. (Using theory for measurement: an analysis of the behaviour of underground economy working paper, Aarhus University, 2006) for measuring the underground economy, allows to generate high frequency time-series for money laundering using a theoretical two-sector dynamic general equilibrium model calibrated over the sample 1981:01-2001:04. The analysis of the generated series suggests two main results. First, money laundering accounts for approximately 12 percent of aggregate GDP; second, money laundering is more volatile than aggregate GDP and it is negatively correlated with it