The time series nature of repeated surveys is seldom taken into account. The few studies that take this into account usually smooth the period-wise estimates without using the cross sectional information. This leads to inefficient estimation. I present a statistical model of repeated surveys and...

Adaptive and innovative application of classical data mining principles and techniques in time series analysis has resulted in development of a concept known as time series data mining. Since the time series are present in all areas of business and scientific research, attractiveness of mining...

This paper describes how to use the R package gateveys to establish a transparent and reproducible aggregation work flow for longitudinal data stemming from business tendency surveys (BTS). Business tendency survey researchers are addressed in particular though the suggested work flow could also...

Firm-product data provide information for various research questions in international trade or innovation economics. However, working with this data requires harmonizing product classifications consistently over time to avoid internal validity issues. The researcher must consider product code...

In the monthly ifo Business Survey around 9,000 German companies answer questions about their current business situation, expectations and plans for the near future as well as on other business variables. This paper provides an overview of all regular questions (monthly, quarterly, bi-annually,...

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...

Business microdata have proven useful in a number of fields, but the main sources of comprehensive microdata are subject to significant confidentiality restrictions. A growing number of papers instead use a private data source seeking to cover the universe of U.S. business establishments, the...

The National Establishment Time Series (NETS) is a private sector source of U.S. business microdata. Researchers have used state-specific NETS extracts for many years, but relatively little is known about the accuracy and representativeness of the nationwide NETS sample. We explore the...

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...

We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to...