Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals

Time and frequency connectedness among oil shocks, electricity and clean energy markets

Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

Dynamic volatility spillover effects between oil and agricultural products

Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

This study examines the nature and dynamics of volatility spillovers between crude oil and agricultural commodity markets since the 2008–09 financial crisis. We tested for volatility spillovers with a flexible bivariate heterogeneous autoregressive model to identify the short-, mid-, and long-term spillover effects. We observed bidirectional spillovers of short-term volatilities between crude oil and agricultural commodity markets in the crisis period, compared to mid-term and long-term volatilities of corn being transmitted to the crude oil volatility in the post-crisis period. These findings suggest that crude oil and agricultural commodity markets have become less integrated after the 2008–09 crisis.

https://www.mdpi.com/2071-1050/11/2/396/pdf

Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis

ABSTRACT The evaluation of the scientific and technological (S&T) innovation efficiency of universities is important for the ‘double first-class’ construction in China. However, related research often only considers desirable outputs while ignoring undesirable ones, which tends to produce biased evaluation results. For this reason, this study takes the ratio of unemployed graduates as undesirable output, and uses the global Malmquist – Luenberger index method to evaluate the S&T innovation efficiency of 31 relevant universities in China during 2013–2017, then develops a panel Tobit model to analyse its influencing factors. The results reveal that: first, during the sample period, the S&T innovation efficiency of those universities improved overall, and technical progress was the main driver. Second, excluding undesirable output will result in an overestimate of the S&T innovation efficiency of universities. Third, the S&T innovation efficiency of universities features regional distribution, with high efficiency in the west and low efficiency in the east. Moreover, different regions have different drivers for the improvement of S&T innovation efficiency of universities, with technical progress for the east and technical efficiency changes for the central and west. Finally, the ‘double first-class’ construction proposal in China has significantly promoted the improvement of S&T innovation efficiency in universities.

Yaxian Lu

Papers

Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis

Evaluating the scientific and technological innovation efficiency of universities in China: evidence from the global Malmquist–Luenberger index model