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We investigate bilateral trade flows across the EU-15 countries from 1962 to 2003 by different specifications of the gravity model. We augment the basic gravity model with population and exchange rate variables, and then include time-varying country fixed effects, to account for Anderson and van Wincoop (Am Econ Rev 93(1):170–192, 2003) multilateral resistance terms. Then, following the previous theoretical derivations of the gravity model in the presence of panel data in a dynamic setting we change the specification of our gravity model. We compare the results of different specifications showing the improvement in each case. We claim the comparative superiority of the dynamic gravity model with time-varying exporter and importer fixed effects due to its higher explanatory power. Finally, we compare out-of-sample forecasting performance of different specifications of the gravity model. 相似文献
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We introduce ARFIMA-ARCH models, which simultaneously incorporate fractional differencing and conditional heteroskedasticity. We develop the likelihood function and we use it to construct the bias-corrected maximum (modified profile) likelihood estimator. Finite-sample properties of the estimation procedure are explored by Monte Carlo simulation. Backus and Zin (1993) have motivated the existence of fractional integration in interest rates by the persistence of the short rate and the variability of the long end of the yield curve. An empirical investigation of a daily one-month Swiss Euromarket interest rate finds a difference parameter of 0.72. This indicates non-stationary behavior. In contrast to first-order integrated models, the long-run cumulative response of shocks to the series is zero. 相似文献
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Journal of Economics - 相似文献
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Motivated by economic-theory concepts – the Fisher hypothesis and the theory of the term structure – we consider a small set of simple bivariate closed-loop time-series models for the prediction of price inflation and of long- and short-term interest rates. The set includes vector autoregressions (VAR) in levels and in differences, a cointegrated VAR and a non-linear VAR with threshold cointegration based on data from Germany, Japan, UK and the US. Following a traditional comparative evaluation of predictive accuracy, we subject all structures to a mutual validation using parametric bootstrapping. Ultimately, we utilize the recently developed technique of Mallows model averaging to explore the potential of improving upon the predictions through combinations. While the simulations confirm the traded wisdom that VARs in differences optimize one-step prediction and that error correction helps at larger horizons, the model-averaging experiments point at problems in allotting an adequate penalty for the complexity of candidate models. 相似文献
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This paper investigates the long-run relationships within a set of six quarterly time-series on the Austrian economy by means of cointegration. After analysing the univariate properties, especially with respect to the appropriate seasonal filter, the maximum-likelihood method proposed by Johansen (1988) is applied to estimate and test the cointegrating relationships. We found three such relations, implying that the system is driven by three independent stochastic time trends. In a next stage we investigate whether the empirically determined cointegrating relationships are compatible with implications derived from the neoclassical growth model with exogenous stochastic technical progress. It is found that the Austrian data strongly reject the propositions that the real interest rate and the log ratios of consumption to output, investment to output, and the real gross wage sum to output are stationary. 相似文献
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Robert M. Kunst 《Empirical Economics》1993,18(4):761-776
Seasonal cointegration generalizes the idea of cointegration to processes with unit roots at frequencies different from 0. Here, common seasonals, also a dual notion of common trends, is adopted for the seasonal case. The features are demonstrated in exemplary models for German and U.K. data. An evaluation of the predictive value of accounting for seasonal cointegration shows that seasonal cointegration may be difficult to exploit to improve predictive accuracy even in cases where seasonal non-cointegration is clearly rejected on statistical grounds. The findings from the real-world examples are corroborated by Monte Carlo simulation.Part of this paper was written while the author was visiting professor at the University of California San Diego. 相似文献
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Zusammenfassung Der in vielen westlichen Industriel?ndern zu beobachtende positive Zusammenhang zwischen Produktivit?ts- und Exportwachstum
führte zu zwei einander entgegengesetzten kausalen Hypothesen. Die erste, von Vertretern des “Export-led-growth”-Modells vorgebrachte
Hypothese geht davon aus, da? das Produktivit?tswachstum im wesentlichen über das Exportwachstum bestimmt wird. Dagegen sieht
die zweite, auf dem Ricardo-Modell und den Theorien des intra-industriellen Handels beruhende Hypothese das Wachstum der Exporte
von der Produktivit?t bestimmt.
Die Richtung in der Kausalit?t zwischen Exporten und Produktivit?t hat entsprechende Konsequenzen für die Einsch?tzung von
Instrumenten der Industriepolitik. W?hrend das “Export-led-growth”-Modell und jüngere Au?enhandelstheorien Wechselkursabwertungen
bzw. Exportsubventionen zur Ankurbelung der Exporte und damit der Produktivit?t nahelegen, ziehen die Theorien des intra-industriellen
Handels eine Subvention von Forschung und Entwicklung und/oder des Outputs als wirkungsvollere Ma?nahmen zur Beschleunigung
der Produktivit?t vor.
Der Aufsatz untersucht anhand ?sterreichischen Datenmaterials, welche der beiden Kausalhypothesen mit der beobachteten Entwicklung
der Exporte, der Produktivit?t und der Terms of Trade kompatibel ist. Dabei bedient sich die Arbeit des Wiener-Granger-Konzepts
als statistischer Test auf Kausalit?t. Zudem werden Simulationen durchgeführt, um die dynamischen Eigenschaften der untersuchten
Zeitreihen zu bestimmen.
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