Efficient solar energy installations depend largely on the availability of meteorological and geographical data (geographical coordinates, solar radiation, ambient temperature, wind speed) and the technical characteristics of the photovoltaic arrays. Usually, both, radiation and meteorological measurements are based on hourly surface observational data, not always easily accessible therefore requiring enormous memory capacity to be processed. From a practical point of view, this work investigated whether or not monthly average resource data can be used to assess the efficiency of the photovoltaic conversion (and thus the electrical energy obtained from this conversion) whenever hourly-based meteorological data are scarce or unreliable. Photovoltaic efficiency was calculated from predicted temperature of the cell by making use of classical analytical models of photovoltaic conversion. Calculations performed based on monthly average solar resource data reproduced within 0.5 K the temperature of the photovoltaic array and within 6% the total amount of energy converted as compared to hourly average solar resource data made available by official solar radiation and meteorological data bases.