Gone are the days when it was questioned whether recessions still exist. Dating different types of boom and recessions allows us to better understand drivers of business cycles and eventually to improve the forecasting of turning points. Survey data provide a timely source of information of the state of the economy therefore are often used to construct leading indicators. Other key elements are an understanding of firms investment behavior and their innovation (e.g. patent) activity.
The first part of the Ph.D. thesis “Business Cycle Turning Points: Dating and Forecasting” is dedicated to dating business cycles in the Swiss economy based on different internationally recognized methodologies. The second part develops an early warning system for turning points based on data from Swiss corporations using a Markov Switching model.
Responsible for the exogenous assumptions (world economic outlook: baseline and risk scenarios) in the structural macro forecasting model of the SNB ◦ forecasting the Swiss economy using the SNB structural model ◦ contributed to the ‘Inflation Perspective Report’ to brief the SNB Board members in advance of policy decisions.
Conceptual design and implementation of the information and documentation center (IDC) for CIRET members ◦ conference organization.
Econometric research and development of business cycle indicators ◦ responsible for ‘KOF–Business Cycle-Barometer’ with regards to methodology, reports, and press relations (1994-2000).
Swiss Statistical Office ◦ ‘Vorort’ (now ‘economiesuisse’) ◦ Government Council Zurich, Switzerland
Qualitative surveys of the investment behaviour and related studies and reports in the annual KOF/ETH-publication ‘Investment behaviour of Swiss firms’ ◦ studies, forecasts and reports for the periodical KOF/ETH-publications ‘Konjunktur’ and ‘Halbjahresprognose’.
Econometric research on innovation behaviour and industrial economics ◦ analysis and forecast of investment behaviour of Swiss firms with an adaptive projection methodology on behalf of the Swiss Federal Statistical Office.
