Dynamic connectedness of China’s green bonds and asset classes

This paper quantifies the co-movement and time-varying integration between China's green bonds and other asset classes across different time domains using the wavelet coherence and time-frequency connectedness model based on the time-varying parameter VAR (TVP-VAR). First, we predominantly detect a strong positive co-movement of green and conventional bonds, especially in the medium and long term. Second, strong bidirectional spillovers exist between green bonds and treasury, corporate, and financial bonds regardless of the time horizon. Lastly, cross-market spillovers between the green bonds and the stock, energy, low-carbon stock market were quite limited in the short-run but strengthened towards the long-term except during the 2015 China stock market crash and the COVID-19 recession when short-term integration rose sharply. The results document some practical enlightenment for investors and policymakers with various time horizons.     

The agribusiness cycle and its wavelets

Cyclical exposures of farm profit to the economic environment are a fact of life for farmers. By utilising the farmer terms of trade as a net profit margin metric, we show how wavelet analysis can be used to decompose the cycle and trend, analyse causal influences, and detect structural breaks. With the NZ dairy industry as case study, the wavelet decomposition reveals that shorter cycles are almost wholly the result of commodity prices. Longer cycles are produced by the interaction of commodity prices with the exchange rate, but with a strong natural buffering element. The buffer was upset following the Asian crisis of 1997–1998, but may have restored itself since. A favourable long-term trend has appeared from the mid nineties onwards. Implications for risk management are briefly examined.      

Measuring Core Inflation in South Africa

Measures of core inflation convey critical information about an economy. They have a direct effect on the policymaking process, particularly in inflation‐targeting countries, and are utilised in forecasting and modelling exercises. In South Africa, the price indices on which inflation is based have been subject to important structural breaks following changes to the underlying basket of goods and the methodology for constructing price indices. This paper seeks to identify a consistent measure of core inflation for South Africa using trimmed means estimates, measures that exclude changes in food and energy prices, dynamic factor models, and wavelet decompositions. After considering the forecasting ability of these measures, which provide an indication of expected second‐round inflationary effects, traditional in‐sample criteria were used for further comparative purposes. The results suggest that wavelet decompositions provide a useful measure of this critical variable.