Many governments have banned strikes in public transportation. Whether this can be justified depends on whether strikes endanger public safety or health. We use time-series and cross-sectional variation in powerful registry data to quantify the effects of public transit strikes on urban...

Purpose: The main goal of this study is to exact an optimal forecasting method by answering the research question: which is the best model for capturing short-term seasonal components of passenger traffic in Greek coastal shipping? Design/methodology/approach: There are not a lot of scientific...

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...

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...

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...

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...

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,...

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...