Nonlinear investigations of China's agricultural transformation based on the structural break regime switching model

2012 ◽  
Vol 4 (1) ◽  
pp. 52-68 ◽  
Author(s):  
Jie Lu ◽  
Angang Hu ◽  
Yilong Yan
Keyword(s):  
Regime Switching ◽  
Structural Break ◽  
Regime Switching Model ◽  
Switching Model ◽  
Agricultural Transformation

scholarly journals Effectiveness and Sustainability of Grain Price Support Policies in China

2019 ◽  
Vol 11 (9) ◽  
pp. 2478 ◽  
Author(s):  
Jie Lyu ◽  
Xiaolei Li
Keyword(s):  
Regime Switching ◽  
Structural Break ◽  
Economic Costs ◽  
Price Support ◽  
Stock Level ◽  
Regime Switching Model ◽  
Switching Model ◽  
Pricing Policies ◽  
Price Patterns ◽  
High Support

We evaluated the effectiveness and sustainability of the grain price support policies in China using the structural break regime switching model. Based on the rice, wheat, and corn monthly price data from 1987 to 2017, we provide strong evidence that the Chinese grain price support policies have been effective in stabilizing the domestic grain price. A structural change occurred in grain price patterns in 2004 when the price support policies were established. Since then, Chinese grain prices have followed a regime with significantly lower volatility. We documented several problems challenging the sustainability of the Chinese grain price support policies in the future, including high economic costs that can trigger high support prices, high public stock level, and high grain import pressure. Our findings shed new light on the functioning of the grain pricing policies and provide useful implications for the market-oriented reforms in the Chinese grain market.

Impact of volatility and equity market uncertainty on herd behaviour: evidence from UK REITs

2018 ◽  
Vol 11 (2) ◽  
pp. 169-186 ◽  
Author(s):  
Omokolade Akinsomi ◽  
Yener Coskun ◽  
Rangan Gupta ◽  
Chi Keung Marco Lau
Keyword(s):  
Asset Allocation ◽  
Regime Switching ◽  
Stock Exchange ◽  
Equity Market ◽  
Market Uncertainty ◽  
Content Type ◽  
Regime Switching Model ◽  
Switching Model ◽  
Market Sentiment ◽  
The Impact

PurposeThis paper aims to examine herding behaviour among investors and traders in UK-listed Real Estate Investment Trusts (REITs) within three market regimes (low, high and extreme volatility periods) from the period June 2004 to April 2016.Design/methodology/approachObservations of investors in 36 REITs that trade on the London Stock Exchange as at April 2016 were used to analyse herding behaviour among investors and traders of shares of UK REITs, using a Markov regime-switching model.FindingsAlthough a static herding model rejects the existence of herding in REITs markets, estimates from the regime-switching model reveal substantial evidence of herding behaviour within the low volatility regime. Most interestingly, the authors observed a shift from anti-herding behaviour within the high volatility regime to herding behaviour within the low volatility regime, with this having been caused by the FTSE 100 Volatility Index (UK VIX).Originality/valueThe results have various implications for decisions regarding asset allocation, diversification and value management within UK REITs. Market participants and analysts may consider that collective movements and market sentiment/psychology are determinative factors of risk-return in UK REITs. In addition, general uncertainty in the equity market, proxied by the impact of the UK VIX, may also provide a signal for increasing herding-related risks among UK REITs.

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