Box-Jenkins Methoden — Alternative Verfahren zur Prognose ökonomischer Zeitreihen

Summary In this paper we try to clarify whether the use ofBox-Jenkins methods would have improved the forecasting performance in Austria during the recession of 1975. For this purpose we estimate ARIMA models for gross national product, private consumption, investment in plant and equipment, and inventory investment. We then compare the forecasts derived from these models with the results of more convential forecasting techniques. It can not be expected that Box-Jenkins methods predict a business cycle turning point. But, as soon as the recession was under way Box-Jenkins methods were faster in adapting to the new situation than conventional forecasting techniques. We found that the accuracy of Box-Jenkins predictions depends to a large extent on the length of the forecasting horizon. Our results suggest that the forecasting horizon should not exceed one year. All in all, Box-Jenkins methods applied together with the forecasting techniques already in use could further improve the forecasting performance.     

Keynes at the periphery: Currency hierarchy and challenges for economic policy in emerging economies

While the post Keynesian literature offers a rather clear concept for growth-oriented policies, it is necessary to adapt them for peripheral emerging economies. We base our analysis of an appropriate Keynesian policy mix for these countries on the concept of currency hierarchy, where the currencies of peripheral emerging economies have a lower liquidity premium than the currencies of advanced economies. The international asymmetry related to the currency hierarchy, amplified by financial globalization, imposes major constraints to the adoption of Keynesian policies for these economies. Under these conditions, we argue that domestic economic policy coordination should lay a major focus on a low policy rate and, especially, a competitive exchange rate for obtaining, at least, a balanced current account, in order to prevent capital flows boom-bust-cycles with subsequent financial crises. We conclude that it is a rather ambitious and long-term goal to climb up the currency hierarchy, especially under the current condition of financial globalization.     

Utilization-focused performance reporting

How best to define performance measures is a much-debated issue. Mismatches between goals and indicators can lead to distortions that undermine impact-oriented steering. This article presents a model of goal and indicator development and explains its applicability, benefits and limitations.     

Coevolutionary cycles of convergence: An extrapolation from the ICT industry

Convergence between technologies can be regarded as an increasingly emerging trend, and has received particular attention in the coming-together of previously distinct products and solutions within the information and communication technologies (ICT) industry. In previous research, the overall impact of the convergence phenomenon remains ambiguous. Whereas some scholars suggest convergence to be associated with disintegration, entry and growth, others relate the phenomenon to opposite effects, such as consolidation and shakeouts. This inconsistency in managerial conceptions on convergence formulates a need for an integrated understanding. Within a multi-case study approach, the convergence within ICT has been observed through examining the coevolution of actors in a converging environment, and patterns in innovation dynamics and managerial responses have been identified. In reflection with existing models of innovation cycles, a model for convergence innovation processes is elaborated and discussed. In particular, the reasoning within the ICT case set is transferred onto the currently emerging entrepreneurial activities in the intersection between nano- and bio-technologies (NBT), resulting in a comparison between ICT and NBT convergences, and deriving recommendations from a retrospective to a predictive context.     

Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics

We study the dynamic pattern of business cycles using US GDP data between 1790 and 2015. To address difficulties in trend and cycle decomposition, we introduce a semiparametric estimation approach with an iterative plug‐in (IPI) algorithm for endogenous bandwidth selection. This algorithm identifies continuously moving growth trends with trend‐supporting growth periods. A simulation study demonstrates the value‐added of our trend identification. Afterwards, nonlinear SETAR models are fitted parametrically. Further, we test the trend using a recently developed test and the estimated SETAR models against their linear alternatives. The results indicate asymmetric characteristics during booms and busts.