The capital gains tax: A curse but also a blessing for venture capital investment

This article documents a statistical association between the number and success of venture capital investments and the capital gains tax rate. To do this, we analyze investment data and taxes of 32 countries from 2000 to 2010. In our data, higher capital gains tax rates are associated with fewer firms financed and a lower probability for ventures receiving follow-up funding. However, if the first investment is received when taxes are high, the probability of a firm eventually going public or being acquired increases. We conclude that high tax rates are associated with fewer, but on average more successful companies. --capital gains tax,venture capital,investment

The Capital Gains Tax: A Curse but Also a Blessing for Venture Capital Investment

Our study analyzes the effect of the capital gains tax on the individual investment decisions of venture capitalists. By doing so, we are able to study the decisions for a sample of 76,852 funding rounds in 32 countries from 2000 to 2012. Our results support the predictions of the theoretical model that higher capital gains tax rates are associated with fewer start-ups financed and a lower probability of receiving follow-up funding. However, the results concerning the effect on the probability of success of start-ups show that a higher tax burden is associated with a higher probability of eventual start-up success

A New Design Paradigm for Secure Full-Duplex Multiuser Systems

We consider a full-duplex (FD) multiuser system where an FD base station (BS) is designed to simultaneously serve both downlink (DL) and uplink (UL) users in the presence of half-duplex eavesdroppers (Eves). The problem is to maximize the minimum (max-min) secrecy rate (SR) among all legitimate users, where the information signals at the FD-BS are accompanied with artificial noise to debilitate the Eves' channels. To enhance the max-min SR, a major part of the power budget should be allocated to serve the users with poor channel qualities, such as those far from the FD-BS, undermining the SR for other users, and thus compromising the SR per-user. In addition, the main obstacle in designing an FD system is due to the self-interference (SI) and co-channel interference (CCI) among users. We therefore propose an alternative solution, where the FD-BS uses a fraction of the time block to serve near DL users and far UL users, and the remaining fractional time to serve other users. The proposed scheme mitigates the harmful effects of SI, CCI and multiuser interference, and provides system robustness. The SR optimization problem has a highly nonconcave and nonsmooth objective, subject to nonconvex constraints. For the case of perfect channel state information (CSI), we develop a low-complexity path-following algorithm, which involves only a simple convex program of moderate dimension at each iteration. We show that our path-following algorithm guarantees convergence at least to a local optimum. Then, we extend the path-following algorithm to the cases of partially known Eves' CSI, where only statistics of CSI for the Eves are known, and worst-case scenario in which Eves can employ a more advanced linear decoder. The merit of our proposed approach is further demonstrated by extensive numerical results.Comment: Accepted for publication in IEEE Journal on Selected Areas in Communications (JSAC), 201

Mobile Air Quality Studies (MAQS) - an international project

Due to an increasing awareness of the potential hazardousness of air pollutants, new laws, rules and guidelines have recently been implemented globally. In this respect, numerous studies have addressed traffic-related exposure to particulate matter using stationary technology so far. By contrast, only few studies used the advanced technology of mobile exposure analysis. The Mobile Air Quality Study (MAQS) addresses the issue of air pollutant exposure by combining advanced high-granularity spatial-temporal analysis with vehicle-mounted, person-mounted and roadside sensors. The MAQS-platform will be used by international collaborators in order 1) to assess air pollutant exposure in relation to road structure, 2) to assess air pollutant exposure in relation to traffic density, 3) to assess air pollutant exposure in relation to weather conditions, 4) to compare exposure within vehicles between front and back seat (children) positions, and 5) to evaluate "traffic zone"- exposure in relation to non-"traffic zone"-exposure. Primarily, the MAQS-platform will focus on particulate matter. With the establishment of advanced mobile analysis tools, it is planed to extend the analysis to other pollutants including including NO2, SO2, nanoparticles, and ozone