Time–frequency relationship between US output with commodity and asset prices

Abstract

Commodity and asset prices have a well-documented effect on economic growth, manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short-run. The aim of this paper is to disentangle the short-and long-run comovements between U.S. historical business cycles and commodity and asset prices, over the period . For this purpose we use a time-frequency approach and we test the historical influence of oil, gold, housing and stock prices, over the output growth. Different from other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that comovements between economic growth and commodity and assets prices manifest especially in the short-run. We also find that stock returns and housing prices have a more powerful effect on the U.S. economic growth rate than the oil and gold prices. The long-run comovements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, comovements become weaker in the short-run. In general the oil and housing prices lead the GDP growth, the U.S. output lead the gold prices, while there is no clear causality direction between business cycle and stock prices.

Money, Credit, House Prices and Quantitative Easing – The Wavelet Perspective From 1970 to 2016

“…For instance,Flor and Klarl (2017) studied the housing cycle synchronization across the largest US metropolitan statistical areas Su, Yao, and Chang (2016). investigated the relationship between output and asset prices, whileTiwari, Albulescu, and Gupta (2016) examined the link between business cycles, commodity and asset prices Bruzda (2017). applied real and complex wavelets in asset classification for the US stock market.…”

Dynamic Comovements Between Housing and Oil Markets in the US over 1859 to 2013: a Note

“…The result highlighted the importance of real oil and real housing prices as potential leading indicators of the U.S. economy. Note that, the preferences for a qual-VAR instead of a standard probit model used for predicting recessions is to account for the fact that macroeconomic variables and asset prices, respectively, affect recessions and are also affected by them, in turn(Dueker 2005, Tiwari et al 2016. Complete details of these results are available upon request from the authors.3 But, we have now controlled for the missing variables and especially the two channels as indicated by an anonymous referee, by using alternative investment-related variables (asset prices) and construction costs.…”

Forecasting oil and stock returns with a Qual VAR using over 150 years off data

“…While, the general belief is that oil and stock prices are leading indicators of the economy, there is ample evidence that economic activity too plays a crucial role in predicting both in and out-of-sample movements in oil (see for example, Kilian (2009), Kilian and Vigfusson (2013), Kilian (2014, 2015) and Baumeister et al, (2015)) and stock prices (see for example, Rapach, Wohar and Rangvid (2005), Goyal and Welch (2008), Rapach, Strauss and Zhou (2010), Rapach and Zhou (2013)). More importantly, as highlighted, amongst others, by Baumeister et al, (2010), Kilian and Vigfusson (2011), Baumeister and Peersman (2013), , Bjørnland and Larsen (2015) for the oil market, and Simo-Kengne et al, (2015), Tiwari et al, (2016) and Antonakakis et al, (forthcoming) for the stock market; these relationships with economic activity are in fact nonlinear.…”