196 research outputs found
Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression.
We propose testing for business cycle asymmetries in Markov-switching autoregressive (MS-AR) models. We derive the parametric restrictions on MS-AR models that rule out types of asymmetries such as deepness, steepness, and sharpness, and set out a testing procedure based on Wald statistics which have standard asymptotic. For a two-regime model, such as that popularized by Hamilton (1989), we show that deepness implies sharpness (and vice versa) while the process is always non-steep. We illustrate with two and three-state MS models of US GNP growth, and with models of US output and employment. Our findings are compared with those obtained from standard non-parametric tests.BUSINESS CYCLES ; TESTS
Forecasts with Single-Equation Markov-Switching Model: An Application to the Gross Domestic Product of Latvia
A Markov-switching vector equilibrium correction model of the UK labour market
There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. In this paper we present a statistical model that offers a congruent representation of part of the UK labour market since the mid 1960s. We use a cointegrated vector autoregressive Markov-switching model in which some parameters change according to the phase of the business cycle. Output, employment, labour supply and real earnings are found to have a common cyclical component. The long run dynamics are characterized by one cointegrating vector relating unemployment to trend-adjusted real wages and output. Despite there having been many changes affecting this sector of the UK economy, the Markov-switching vector-equilibrium-correction model with three regimes (representing recession, normal growth, and high growth) provides a good characterization of the sample data, and performs well relative to alternative linear and non-linear models. The results of an impulse-response analysis highlight the dangers of using VARs when the constancy of the estimated coefficients has not been established, and demonstrate the advantages of generating regime dependent responses
Monetary and fiscal policy interactions in Brazil: an application of the fiscal theory of the price level
Is there a Common European Business Cycle? New Insights from a Frequency Domain Analysis
To assess the synchronization of business cycles in Europe we extract the cyclical component of industrial production in five European countries using the filter of Baxter and King (1999). The hypothesis of a joint business cycle is tested by using the frequency domain common cycle test suggested by Breitung and Candelon (2000). The common cycle hypothesis is clearly rejected for U.K. data whereas some weak evidence for a joint cyclical pattern is found for France, The Netherlands, Austria and Germany.
Zusammenfassung
Gibt es einen gemeinsamen europäischen Konjunkturzyklus? Neue Erkenntnisse durch eine Spektralanalyse
Um die Synchronität der Konjunkturzyklen in Europa zu bewerten, wird die Zykluskomponente der Industrieproduktion in fünf europäischen Ländern identifiziert, indem der Baxter-King-Filter (1999) angewendet wird. Die Hypothese eines gemeinsamen Konjunkturzyklus wird durch einen Test auf einen gemeinsamen Zyklus im Frequenzbereich nach Breitung und Candelon (2000) überprüft. Ein gemeinsamer Konjunkturzyklus muss demnach für Großbritannien klar zurückgewiesen werden, wohingegen einige schwache Anzeichen für ein gemeinsames Konjunkturmuster für Frankreich, die Niederlande, Österreich und Deutschland gefunden werden konnten
Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting
Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series
Disentangling Demand and Supply Shocks in the Crude Oil Market: How to Check Sign Restrictions in Structural VARs
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