By employing the vector error correction model (VECM) in a system of seven equations, we find that the Japanese stock market is cointegrated with a group of six macroeconomic variables. The signs of the long-term elasticity coefficients of the macroeconomic variables on stock prices generally support the hypothesized equilibrium relations. Our findings are robust to different combinations of macroeconomic variables in six-dimension systems and two subperiods. Also, the VECM consistently outperforms the vector autoregressive model in forecasting ability.

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This study examines the relationship between inflation and inflation uncertainty for both developed and emerging countries using the asymmetric power GARCH model. We find new evidence that suggests that positive inflationary shocks have stronger impacts on inflation uncertainty for mainly Latin American countries. We also find that inflation causes inflation uncertainty for most countries but the evidence for causality of the opposite direction is mixed.

A system of reduced forms with cointegrated variables may be estimated in two ways: as a vector autoregression in levels, or as a vector error correction model. The latter is a restricted version of the former. If there is cointegration, imposing this restriction will yield more efficient estimates. However, at short horizons, vector error correction estimates are known to perform poorly relative to those from a vector autoregression. We examine how this property affects impulse response functions. A Monte Carlo experiment, and an example, suggest that impulse response functions of the two models are similar at short horizons, but different at long horizons. This suggests that the loss of efficiency from vector autoregression estimation is not critical at the commonly used short horizon. Our results complement parallel arguments focusing on forecast errors made by Clements and Hendry (1995), Hoffman and Rasche (1996), and Lin and Tsay (1996).

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