This letter proposes a simple test for the linearity of a time series. We compare the small and large samples properties of the suggested test via Monte Carlo techniques with well known time domain linearity tests. Our results suggest that the suggested test over performs the power of the other competitive tests in small samples.
In this paper we investigate the effects of temporal aggregation and systematic sampling using some well known linear and nonlinear Granger causality tests.
This short paper demonstrates that the use of temporally aggregated data may affect the power and the size of the well known the Ramsey's (1969) RESET test.
This paper examines the existence of a linear or nonlinear interaction between the Advance/Decline ratio index and the returns of the Athens General Index.
A variety of standard forecasting accuracy criteria and one suggestion are applied to evaluate the OECD's macroeconomic forecasts for Greece for the aggregate demand and output, the GDP implicit price deflator, the investment, the imports and the exports of goods and services.
Various methods have been developed to improve mortality forecasts. The authors proposed a neuro-fuzzy model to forecast the mortality. The forecasting of mortality is curried out by an ANFIS model which uses a first order Sugeno-type FIS.
The paper presents a new technique in the field of unemployment modeling in order to forecast unemployment index. Techniques from the Artificial Neural Networks and from fuzzy logic have been combined to generate a neuro-fuzzy model.
This short paper demonstrates the effects of using missing data on the power of the well-known Hausman (1978) test for simultaneity in structural econometric models.
A crucial aspect of empirical research based on ARIMA(p,q) model is the choice of the appropriate lag order. Several criteria have been used in order to identify the appropriate order of a ARIMA(p,q) process. In this paper we investigate the effects of using a variation of selection criteria under different temporal aggregation levels.
This letter proposes a simple test for the linearity of a time series. We compare the small and large samples properties of the suggested test via Monte Carlo techniques with well known time domain linearity tests.
In this paper we are interested in the problem of comparisons with the best population. One case where comparisons with the best arise naturally is the measurement of productive efficiency.
We study the construction of confidence intervals for efficiency levels of individual firms in stochastic frontier models with panel data.
We propose a generalized methods of moments procedure by which both the number of factors and the regression coefficients can be consistently estimated. Some important identification issues are also discussed. Our simulation results indicate that the proposed methods produce reliable estimates.
Our study sheds light on the issue of volatility forecasting under risk management environment and on the evaluation procedure of various risk models.
This paper is using simple nonlinearity tests to provide evidence of a positive and significant causal relationship going from stock market development to economic growth in Greece during the last 10 years.
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