Collecting data on wages is central to socio-economic research. However, besides high rates of people not answering wage-related questions, measurement issues are also relevant. Most data from official statistics are too aggregated to allow for detailed individual-level analyses which are crucial for encouraging innovative political-economic solutions in the long run. In this context, web surveys seem to offer various advantages, such as worldwide coverage, cost benefits and a fast data collection process. In particular for sensitive questions, like income, they might provide more reliable results because social desirability effects can be eliminated. While web surveys could represent a good supplement to official statistics data, they pose many methodological challenges. A core problem concerns the representativeness of the data as the sub-population with Internet access might be quite specific. The talk will provide an overview of the application of common and advanced calibration methods to enhance the representativeness of different types of web surveys; and it will explore the potentials and constraints of different adjustment methods for probability and non-probability web surveys. In addition, the question will be addressed whether more creative recruitment strategies (such as mass media attention) might be a promissing alternative  to tackle the occurring biases in non-probability web-surveys.