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Long-run Relationships (long-run + relationships)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	100%

Selected Abstracts

Modelling inbound international tourism demand to Portugal

INTERNATIONAL JOURNAL OF TOURISM RESEARCH, Issue 3 2002
Ana Cristina M. Daniel
Abstract In this paper the Johansen cointegration analysis of time series is used to model the Portuguese inbound international tourism demand from five countries of origin,France, Germany, The Netherlands, Spain and UK. This approach examines the long-run relationships between the demand for holiday visits and the variables that affect holiday travel such as income, destination prices and travel costs (airfares and road costs). Demand functions, for each country of origin, are estimated using annual data on tourism flows from 1975 to 1997. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Bank Interest Rate Adjustments: Are They Asymmetric?

THE ECONOMIC RECORD, Issue 237 2001
G.C. Lim
This paper is concerned with the asymmetric adjustments between three Australian bank interest rates: a bank bill rate, a loan rate and a deposit rate. A multivariate asymmetric error-correction model is applied to capture the interplay of long-run relationships between the levels of the rates and short-run relationships between the changes in the rates. The empirical analysis, for the sample period 1990:01,2000:04, shows that interest rate adjustments, in response to positive and negative shocks, are asymmetric in the short run, but not in the long run. In particular, the results suggest that banks adjust their loan and deposit rates, in response to a change in the bank-bill rate, at a faster rate during periods of monetary easings (negative changes) than during periods of monetary tightenings (positive changes). [source]

Forecasting oil price movements: Exploiting the information in the futures market

THE JOURNAL OF FUTURES MARKETS, Issue 1 2008
Andrea Coppola
Relying on the cost of carry model, the long-run relationship between spot and futures prices is investigated and the information implied in these cointegrating relationships is used to forecast out of sample oil spot and futures price movements. To forecast oil price movements, a vector error correction model (VECM) is employed, where the deviations from the long-run relationships between spot and futures prices constitute the equilibrium error. To evaluate forecasting performance, the random walk model (RWM) is used as a benchmark. It was found that (a) in-sample, the information in the futures market can explain a sizable portion of oil price movements; and (b) out-of-sample, the VECM outperforms the RWM in forecasting price movements of 1-month futures contracts. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:34,56, 2008 [source]

FORECASTING QUARTERLY AGGREGATE CRIME SERIES,

THE MANCHESTER SCHOOL, Issue 6 2005
MICHAEL P. CLEMENTS
In this paper we assess the forecasting performance of quarterly economic models of aggregate property and personal crime. We show that models that include long-run relationships between crime and its economic determinants tend to generate inaccurate forecasts, and attribute this to structural change. The forecast performance of the economic models is compared with that of time-series models, and forecast encompassing tests are reported. [source]