Steffen Henzel

Dimensions of Macroeconomic Uncertainty: A Common Factor Analysis

Uncertainty about the future course of the economy is a possible driver of aggregate fluctuations. To identify the different dimensions of uncertainty in the macroeconomy we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors which account for the common dynamics in this dataset. These factors are interpreted as macroeconomic uncertainty. The first factor mainly captures business cycle uncertainty while the second factor is identified as oil and commodity price uncertainty. While both types of uncertainty foreshadow a decline in output, surprise increases in oil and commodity price uncertainty appear to be more important for fluctuations in real activity.

Quantifying Inflation Expectations with the Carlson-Parkin Method: A Survey-based Determination of the Just Noticeable Difference

This paper presents a new methodology for the quantification of qualitative survey data. Traditional conversion methods, such as the probability approach of Carlson and Parkin (1975) or the time-varying parameters model of Seitz (1988), require very restrictive assumptions concerning the expectations formation process of survey respondents. Above all, the unbiasedness of expectations, which is a necessary condition for rationality, is imposed. Our approach avoids this assumptions. The novelty lies in the way the boundaries inside of which survey respondents expect the variable under consideration to remain unchanged are determined. Instead of deriving these boundaries from the statistical properties of the reference time-series (which necessitates the unbiasedness assumption), we directly queried them from survey respondents by a special question in the Ifo World Economic Survey. The new methodology is then applied to expectations about the future development of inflation obtained from the Ifo World Economic Survey.

Nowcasting Regional GDP: The Case of the Free State of Saxony

Abstract We tackle the nowcasting problem at the regional level, using a large set of indicators (regional, national and international) for the years 1998 to 2013. We explicitly take into account the ragged-edge data structure and consider the different information sets faced by a regional forecaster within each quarter. It appears that regional survey results in particular improve forecasting accuracy. Among the 10% best performing models for the short forecasting horizon, one fourth contain regional indicators. Hard indicators from the German manufacturing sector and the Composite Leading Indicator for Europe also deliver useful information for the prediction of regional GDP in Saxony. Unlike national GDP forecasts, the performance of regional GDP is similar across different information sets within a quarter.

INTERNATIONAL SYNCHRONIZATION AND CHANGES IN LONG-TERM INFLATION UNCERTAINTY

We investigate the international linkages of uncertainty associated with the long-term movements of inflation. In the first step, we establish that inflation uncertainty in the G7 is intertwined, and the degree of synchronization has increased during the recent two decades. We also document a rise in inflation uncertainty accompanying the global financial crisis. Based on a factor–structural vector autoregression, we provide evidence of a common international shock. We disclose that this shock is closely related to oil and commodity price uncertainty, and it explains large parts of the recent rise in inflation uncertainty. Moreover, increased synchronization can be explained by greater relative importance of this global shock. We also document that inflation uncertainty has become more stable, because domestic shocks translate less extensively into individual economies. This finding lends support to the “good policy†hypothesis.