Fully modified least squares and vector autoregression

Article Abstract:

Fully modified least squares (FM-OLS) procedures were used to develop a framework for studying vector autoregressions (VAR) that have several unit roots and cointegrating vectors. The framework eliminates the need for preliminary pretesting in analyzing nonstationary and potential cointegrating links between different time-series. In addition, an asymptotic theory for inference using FM-OLS and fully modified least squares-VAR regression was also developed.

Autoregression (Statistics), Least squares

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Econometric model determination

Article Abstract:

Several models are proposed for predicting economic time series. The models, which are based on Bayesian asymptotics, are evaluated by applying them to a series of problems in econometric model determination, including reduced rank regressions and Bayesian vector autoregressions. Results suggest that the proposed models have excellent behavioral properties and are very useful for ex ante macroeconomic forecasting.

Models, Usage, Econometrics, Macroeconomics

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An asymptotic theory of Bayesian inference for time series

Article Abstract:

Bayesian data density (BDD)is considered to formulate a general asymptotic theory of Bayesian inference for time series econometrics. BDD followed an asymptotically general exponential form across prior densities and different likelihood functions in both stationary and nonstationary systems. The asymptotic application is also not bound by specific rates of convergence or stationarity.

Time-series analysis, Time series analysis, Asymptotic distribution (Probability theory)

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