  Emerging trends in smartphones, online maps, social media, and the resulting
geo-located data, provide opportunities to collect traces of people's
socio-economical activities in a much more granular and direct fashion,
triggering a revolution in empirical research. These vast mobile data offer new
perspectives and approaches for measurements of economic dynamics and are
broadening the research fields of social science and economics. In this paper,
we explore the potential of using mobile big data for measuring economic
activities of China. Firstly, We build indices for gauging employment and
consumer trends based on billions of geo-positioning data. Secondly, we advance
the estimation of store offline foot traffic via location search data derived
from Baidu Maps, which is then applied to predict revenues of Apple in China
and detect box-office fraud accurately. Thirdly, we construct consumption
indicators to track the trends of various industries in service sector, which
are verified by several existing indicators. To the best of our knowledge, we
are the first to measure the second largest economy by mining such
unprecedentedly large scale and fine granular spatial-temporal data. Our
research provides new approaches and insights on measuring economic activities.
