Abstract

Sample surveys have been the foundation of official statistics produced by the US Department of Agriculture’s National Agricultural Statistics Service (NASS) and other National Statistical Institutes for more than half a century. Increasingly, information from diverse sources, such as administrative, weather, and remotely sensed data, is available and can be used to improve fully survey-based estimates. In addition, new products that inform official statistics can be developed, such as new metrics or maps of the scope and intensity of natural disasters. In this presentation, data science approaches that are being used in the production of official statistics are highlighted. Estimates of the propensity of response from a sampled unit have been incorporated in the sampling and data collection phases of surveys. Predictions of what crops will be grown where can inform editing processes. Survey and non-survey data have been combined through modeling to produce improved official statistics. The progress that has been made and important research questions that remain are discussed.