Earnings functions are an important tool in labor economics as they allow to test a variety of labor market theories. Most empirical earnings functions research focuses on testing hypotheses about sign and magnitude for the variables of interest. In contrast, there is little attention for the explanation power of the econometric models employed. Measures for explanation power are of interest, however, for assessing how successful econometric models are in explaining the real world. Are researchers able to draw a complete picture of the determination of earnings or is there room for further theories leading to alternate econometric models? This article seeks to answer the question with a large microeconometric data set from Germany. Using linear regression estimated by OLS and R2 as well as adjusted R2 as measures for explanation power, the results show that up to 60 percent of wage variation can be explained using only observable variables.