ℓ1 polynomial trend filtering, which is a filtering method described as an ℓ1-norm penalized least-squares problem, is promising because it enables the estimation of a piecewise polynomial trend in a univariate economic time series without prespecifying the number and location of knots. This...

This paper investigates the dynamic relationships between oil prices and the Japanese economy from a frequency domain perspective. Both the frequency domain causality test of Breitung and Candelon (2006) and the frequency dependent regression method developed by Ashley and Verbrugge (2009) are...

Using the monthly Japanese data from January 1970 to December 2011, this paper analyzes the predictive power of commodity prices and manufactured goods prices for inflation. We split the full sample into the two sub-periods 1970M1-1990M12 and 1991M1-2011M12. By testing the causality at various...

The Russian invasion of Ukraine on February 24, 2022 dramatically disrupted the global supply of crude oil and agricultural commodities. As a consequence, the prices of oil and agricultural commodities increase substantially and many countries face the problem of high food inflation. Against...

ℓ1 polynomial trend filtering, which is a filtering method described as an ℓ1-norm penalized least-squares problem, is promising because it enables the estimation of a piecewise polynomial trend in a univariate economic time series without prespecifying the number and location of knots. This...

Several common properties shared by cryptocurrencies and precious metals, such as safe haven, hedge and diversification for risk assets, have been wildly discussed since the day Bitcoin was created in 2008. However, no studies have explored whether cryptocurrency market uncertainties can help to...