The goal of Statista’s market model is to estimate the development of industries in different countries across the world. To facilitate our clients’ usage of the forecasts, Statista applies a standardized model for all countries and industries. Our focus is on the revenue trends for different industries up to 2020. Forecast modeling is conducted annually, based on the latest data. Each market prognosis will be made immediately available upon completion on Statista.com.
The latest results have been analyzed and an overview is available for download here.
Up to 400 industries from each country are comprehensively analyzed by our experts. The industrial classification is based on renowned classification systems, e.g. the North American Industry Classification System (NAICS), the UK Standard Industrial Classification (UK SIC), and the Statistical Classification of Economic Activities in the European Community (NACE Rev. 2). The prognoses are conducted by applying the classification codes with up to six levels of sub-divisions, depending on the corresponding data situation.
The prognosis model is applied to more than 40 countries.
- In Europe:
The historical data for every industry was gathered from the
national statistical offices of every country.
The future trends of national industries are based in part on economic trends in each country and in part on industry-specific trends. The Statista model for each country’s development is derived from data provided by the World Economic Outlook Database (WEO) of the International Monetary Fund, the prognoses of the OECD and the European Commission’s Business Confidence Surveys.
The development of industries is based on historical developments within each industry as well as major drivers in the respective country. Statista has identified crucial market drivers, which allows for reliable updating of the market data and for the modeling of future industry trends. Depending on historical data and the individual drivers, we developed regression models and updated trends accordingly. Each statistical series has been checked for plausibility and approved by experts.
Further information about the methodology is available for download here.
Dr. Friedrich Schwandt
Dr. Friedrich Schwandt studied Economics with a specialization in Econometrics. He has been the CEO of Statista GmbH since 2007. He has worked at the Humboldt University in Berlin, the Organization for Economic Co-operation and Development (OECD) and the Boston Consulting Group (BCG).
Dr. Rebecca Newland
Dr. Rebecca Newland holds a Masters in 'Physics with Space Science' and a PhD in 'Astronautical Engineering'. The focus of her PhD research was on forecasting of the development of the space debris environment around Earth and identifying problematic objects using complex network theory. She has work experience in data analysis in the housing industry and computer modelling and analysis of parachute systems for spacecraft and aircraft in the aerospace industry.
Mr. Hubertus Bitting studied Economics in Bonn, Oxford, Madrid and Paris and holds a Masters in European Management from ESCP Europe and City University, London. As Head of Research & Analysis at Statista, Mr. Bitting is responsible for all modeling and market analyses activities of Statista. Formerly he worked for strategy consultancies such as Oliver Wyman, Roland Berger Strategy Consultants and Kienbaum International Consultants as well as for Deutsche Bank.
Mr. Philipp Huhn studied “Industrial Engineering and Management” at four universities in Hamburg and holds a Masters with specialization in Energy Technology as well as Operations and Supply Chain Management. During his studies he concentrated on numerical stress analysis and computational fluid simulations as well as mathematical programming. Since 2014 he has worked for Statista on several projects as a specialist for tool programming as well as data analysis.
Ms. Birte Janßen holds a Diploma in Business Administration with a specialization in Logistics and Marketing. The focus of her Diploma Thesis was on analyzing success drivers of movies by using statistical models including regression analysis. She has been an Analyst at Statista since its launch in 2008 and has broad work experience in data analysis in the Media and Internet industries. She is author of several studies and publications e.g. the leading E-Commerce-Study of Germany.
Mr. Volker Staffa studied Business with focus on Logistics and Supply Chain Management in Hamburg and Rhode Island. Before working as an Analyst at Statista he gathered experience in the aviation industry, working for the German Air Traffic Control in the business development department, modelling and analyzing operation processes, and Lufthansa Technik’s quality management.
Ms. Kristin Ramcke holds a Research Master degree (M.Sc.) in Communication Science from the University of Amsterdam. During her studies, Ms. Ramcke carried out several academic research projects on polling techniques and forecast models for political opinion. She has profound knowledge in advanced data analysis techniques including time series data analysis and multilevel modeling. Prior to joining Statista Research & Analysis, Ms. Ramcke has worked for and collaborated with some of Germany's largest market research and polling institutes (GfK, IfD).
All prognosis models take the development of historical values into account. Unpredictable events like financial crises or wars, which can crucially influence the development of certain industries or even entire countries, are not considered. The models, originally created in 2014, are subject to a continuous improvement process.
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