Are Stock Returns Predictable? A Test Using Markov Chains

This paper uses a Markov chain model to test the random walk hypothesis of stock prices. Given a time series of returns, a Markov chain is defined by letting one state represent high returns and the other represent low returns. The random walk hypothesis restricts the transition probabilities of the Markov chain to be equal irrespective of the prior years. Annual real returns are shown to exhibit significant nonrandom walk behavior in the sense that low (high) returns tend to follow runs of high (low) returns in the postwar period.     

THE FISCAL DIVIDEND MYTH OF AN INCOME/GST TAX SWITCH*

Reaping a windfall fiscal dividend from the taxation of the ‘underground’ economy's expenditures on ‘legitimate’ commodities is often seen as a significant advantage for a goods and services tax (GST) over an income tax. This claim ignores the changes in prices in the underground economy which would arise from the introduction of a GST. Employing a general equilibrium model which allows for tax evasion, we show that any ‘dividend’ arising from a change in the income tax/GST mix is equivalent to a rise in the income tax rate without a GST.     

A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output

We compare a number of widely used trend‐cycle decompositions of output in a formal Bayesian model comparison exercise. This is motivated by the often markedly different results from these decompositions—different decompositions have broad implications for the relative importance of real versus nominal shocks in explaining variations in output. Using U.S. quarterly real GDP, we find that the overall best model is an unobserved components model with two features: (i) a nonzero correlation between trend and cycle innovations and (ii) a break in trend output growth in 2007. The annualized trend output growth decreases from about 3.4% to 1.2%–1.5% after the break. The results also indicate that real shocks are more important than nominal shocks. The slowdown in trend output growth is robust when we expand the set of models to include bivariate unobserved components models.