This paper considers the macroeconomics of the oil price for the United States. It investigates the impact of large oil price hikes in a standard VAR framework by introducing a new Markov switching based oil price specification. The explanatory power of this new specification is compared to that of a number of prominent non-linear specifications. The key findings are: (1) the new oil price specification is appropriate in both empirical and theoretical terms and allows for a well-founded distinction between “large” and “normal” oil price increases. (2) The observed impact of oil price shocks on real GDP growth is largely attributable to no fewer than three large oil price increases, namely those of 1973-74, 1979 and 1991, while variables such as consumer and import prices are also affected by normal oil price increases.
This paper discusses how similar Bitcoin is to a commodity. The application of a number of both linear and non-linear GARCH models indicates that the role of extreme price movements is particularly pronounced. GARCH models with student-t innovations as well as combined jump-GARCH models are among the models with the best fit. The role of large movements is found to be stronger in the Bitcoin market than in the markets for crude oil and gold. As Bitcoin shares with these exhaustible resource commodities characteristics such as the fixed supply, the analysis of Bitcoin prices can generally learn from the analysis of exhaustible resource commodities. However, whereas the short-run supply of gold and oil are uncertain, there are no uncertainties on the Bitcoin supply-side. Thus, the observed movements of Bitcoin prices can be interpreted as results of Bitcoin demand shocks.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper is concerned with the statistical behavior of oil prices in two ways. It, firstly, applies a combined jump GARCH in order to characterize the behavior of daily, weekly as well as monthly oil prices. Secondly, it relates its empirical results to implications of Hotelling-type resource extraction models. The empirical analysis shows that oil prices are characterized by GARCH as well as conditional jump behavior and that a considerable portion of the total variance is triggered by sudden extreme price movements. This finding implies that, first, oil price signals are not reliable and, as a consequence, both finding optimal extraction paths and decisions regarding the transmission to alternative technologies are likely to be compromised. Second, this behavior is in stark contrast to the notion of deterministic trends in the price of oil.
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Documents inJEL-Code: C220, Q300.
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