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Abstract: At present, photovoltaic grid-connected systems (PVGCS) are experiencing a formidable market growth. This is mainly due to a continuous downward trend in PV cost together with some government support programmes launched by many developed countries. However, government bodies and prospective owners/investors are concerned with how changes in existing economic factors – financial incentives and main economic parameters of the PVGCS – that configure a given scenario may affect the profitability of the investment in these systems. Consequently, not only is a mere estimate of the economic profitability in a specific moment required, but also how this profitability may vary according to changes in the existing scenario. In order to enlighten decision-makers and prospective owners/investors of PVGCS, a sensitivity analysis of the internal rate of return (IRR) to some economic factors has been carried out. Three different scenarios have been assumed to represent the three top geographical markets for PV: the Euro area, the USA and Japan. The results obtained in this analysis provide clear evidence that annual loan interest, normalised initial investment subsidy, normalised annual PV electricity yield, PV electricity unitary price and normalised initial investment are ordered from the lowest to the highest impact on the IRR. A short and broad analysis concerning the taxation impact is also provided. [Copyright &y& Elsevier]

We compare individual U.S. equity return data from Thomson Datastream (TDS) with similar data from the Center for Research in Security Prices (CRSP) to evaluate TDS for use in studies involving large numbers of individual equities in markets outside the United States. We document important issues of coverage, classification, and data integrity and find that naive use of TDS data can have a large impact on economic inferences. We show that after careful screening of the TDS data, inferences drawn from TDS data are similar to those drawn from CRSP. We illustrate the importance of the screens we develop using U.S. TDS data by applying the screens to TDS data from four European equity markets. [ABSTRACT FROM AUTHOR]