The issue of labor productivity has constantly been debated among analysts and government officials. The common understanding here is that labor productivity is low and needs to be ramped up. According to our business survey, the level of satisfaction with labor productivity reached its peak in...

Objective: In this article, the methods used to simplify the business modelling and founding of new companies are presented and critically reflected. Furthermore, it is discussed to what extent a specific method is advantageous, disadvantageous, applicable, not applicable, or even...

In the first quarter of 2022, the Stanford Computational Antitrust project team invited the partnering antitrust agencies to share their advances in implementing computational tools. Here are the results of the survey

Computational antitrust is a new domain of legal informatics which seeks to develop computational methods for the automation of antitrust procedures and the improvement of antitrust analysis. The present article first introduces it, then explores how agencies, policymakers, and market...

We investigate the circumstances in which business cycle forecasting is beneficial for business by addressing both the short-run and the long-run aspects. For an assessment of short-run forecasting we make a distinction between using publicly available information of cycle probabilities and the...

This paper presents findings from a census of more than 79,000 stock-keeping units (SKUs) in 37 consumer packaged goods categories totaling $55 billion in annual revenue. It shows that, in 86% of product categories, the relationship between market share and retail distribution is increasing and...

In the first quarter of 2023, the Stanford Computational Antitrust project team invited the partnering antitrust agencies to share their advances in implementing computational tools. Here are the 26 contributions we received

Within this paper, we present the GridEcon Platform, a testbed for designing and evaluating economics-aware services in a commercial Cloud computing setting. The Platform is based on the idea that the exact working of such services is difficult to predict in the context of a market and,...

Aiming to become one of the world's top five economies, Russia's economy should advance in real terms by 30% (in nominal terms by 50%) by 2024 over 2016. To reach this goal, investments should represent up to 25% of GDP by 2024. Economic boost can be driven by key investment-led sectors, namely...

In this contribution, we exploit machine learning techniques to predict out-of-sample firms' ability to export based on the financial accounts of both exporters and non-exporters. Therefore, we show how forecasts can be used as exporting scores, i.e., to measure the distance of non-exporters...