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Open AccessArticle

What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection

College of Economics and Management, China Agricultural University, Beijing 100083, China
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Author to whom correspondence should be addressed.
Sustainability 2019, 11(23), 6692; https://doi.org/10.3390/su11236692
Received: 23 October 2019 / Revised: 11 November 2019 / Accepted: 17 November 2019 / Published: 26 November 2019
(This article belongs to the Special Issue Sustainable Grazing Systems)
To understand key factors that drive China’s green fodder supply, this study estimates a Nerlovian partial-adjustment model, using provincial-level panel data spanning two decades (1997–2016). Based on a set of explanatory variables selected by the LASSO (Least Absolute Shrinkage and Selection Operator) method, estimation of the Nerlovian model by the system-GMM (Generalized Method of Moments) method yields three key findings. First, while farmers’ previous cultivation decisions on green fodder supply strongly predict their current decisions, without the influence of other drivers, China’s green fodder supply tends to decline over time. Second, among the identified drivers, government policy plays the most significant role—the availability of subsidies for cultivation of green fodder crops raises the sown area of green fodder crops by more than 30 percent. In contrast, farmer’s sown-area decision is only modestly responsive to price incentives. Finally, while the stock of fixed capital inputs (e.g., number of combine harvesters) and natural disasters (e.g., floods) both affect green fodder supply, their impacts are small. View Full-Text
Keywords: green fodder; supply response; LASSO; China; panel data green fodder; supply response; LASSO; China; panel data
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MDPI and ACS Style

Zhai, S.; Chen, Q.; Wang, W. What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection. Sustainability 2019, 11, 6692.

AMA Style

Zhai S, Chen Q, Wang W. What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection. Sustainability. 2019; 11(23):6692.

Chicago/Turabian Style

Zhai, Shengying; Chen, Qihui; Wang, Wenxin. 2019. "What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection" Sustainability 11, no. 23: 6692.

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