Determining what drives stock returns: Proper inference is crucial: Evidence from the UK

This paper employs a century of the UK stock market data to examine various sate-space model specifications and Vector Autoregression (VAR) models to investigate how much expected returns and expected dividend growth contribute to movements in the UK price-dividend ratio. We show that the results of the estimated state-space models and the estimated VAR return decomposition models that attempt to estimate the contribution of expected returns and dividend growth to movements in the price-dividend ratio provide different results when one corrects for proper inference for both models. The corrected inference indicates that the contribution of expected returns to fluctuations in the price-dividend ratio is found to be statistically insignificant according to the state-space model, however, expected returns are found to contribute significantly to movements in the price-dividend ratio when one employs the VAR model. We offer some important econometric insights about the reasons for why state-space models and VAR models may give different results.