The impact of strong emotions or mood on decision making and risk taking is well recognized in behavioral economics and finance. Yet, and in spite of the immense interest, no study, so far, has provided any comprehensive evidence on the impact of weather conditions. This paper provides the theoretical framework to study the impact of weather through its influence on bank managerís mood on bank inefficiency. In particular, we provide empirical evidence of the dynamic interactions between weather and bank loan inefficiency, using a panel data set that includes 69 banks operating in the US spanning the period 1994 to 2009. Bank loan inefficiency is derived using both a standard stochastic frontier production approach for bank loans and a directional distance function. Then, we employ a Panel-VAR model to derive orthogonalised impulse response functions and variance decompositions, which show responses of the main variables, weather and bank loan inefficiency, to orthogonal shocks. The results provide evidence insinuating the importance of specific weather characteristics, such as temperature and cloud cover time, in explaining the variation of gross loans.