Effect of Grain Price Support Policy in China : A Grey Relational Analysis

Qian, Jiarong; Shoichi, Imasaka; Mu, Yueying; Isoda, Hiroshi

doi:10.5109/27382

Cited by 4 publications

(5 citation statements)

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“…Previous studies using the panel data sets to examine the driving forces of sown areas and agrochemical use, Nie et al [25], Wu et al [27], Yi et al [42], and Gao et al [43], applied fixed effect regressions to control for potential endogeneity problems caused by unobserved time-invariant household-specific variables. Likewise, we apply fixed effect regression in this study to estimate Equations ( 13) and (15). The dynamic nature of Equation ( 14), caused by the lagged A variable leads to biased and inconsistent OLS estimators [48].…”

Section: Estimation Methodsmentioning

confidence: 99%

“…We use a large-scale household-level panel data set, the Rural Fixed Observation Points (RFOP) survey data set, covering the period 1997-2010, to estimate the model presented in Equations ( 13)- (15). The RFOP is a nationwide longitudinal data set collected by the Research Center for Rural Economy (RCRE) of the Ministry of Agriculture [25,42,43].…”

Section: Datamentioning

confidence: 99%

“…Fixed effects regression results for agrochemical use, based on Equation (15), are summarized in Table 5. Column (1) presents the results for fertilizer and column (2) for pesticides; columns (3) and (4) present the results when the sown land areas are replaced by the shares of land sown with wheat and rice.…”

Section: Agrochemical Usementioning

confidence: 99%

“…Minimum support price may strongly affects the use of agricultural production inputs [9][10][11]. According to standard economic theory, minimum support price is expected to raise the grain price (see e.g., Li et al [7], Kozicka et al [9], Qian et al [12], Kim and Chavas [13], Lyu and Li [14], Qian et al [15], and Tripathi [16]), and thereby stimulate the use of agrochemicals and other variable inputs [5,[17][18][19]. However, only a limited number of studies, such as Li et al [7], Qian et al [12], Ali et al [20], Aditya et al [21], Krishnaswamy [22], Chintapalli and Tang [23], and Ritu et al [24], provided empirical evidence of this.…”

Section: Introductionmentioning

confidence: 99%

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Impacts of China’s Minimum Grain Procurement Price Program on Agrochemical Use: A Household-Level Analysis

Heerink

Oosterveer

et al. 2021

Agriculture

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China’s minimum grain procurement price program aims to boost grain production and ensure food self-sufficiency. It may also affect the already very high levels of chemical fertilizer and pesticides consumption, but little is known about these potential side-effects. In this paper, we apply panel data regression techniques to a large rural household-level data set for the period 1997–2010 to examine whether and how the minimum grain procurement price program affected households’ agrochemical use. We find that the minimum grain procurement price program negatively affected both chemical fertilizer and pesticides use, with pesticides use being more responsive than the use of fertilizer. The higher wheat and rice prices that resulted from the program stimulated the use of agrochemicals, but they also stimulated area expansion which contributed to lower agrochemical use per unit of land. These counteracting indirect effects were overshadowed by the large negative direct effect of the minimum procurement price of rice on the use of fertilizer and pesticides.

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Section: Estimation Methodsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Agrochemical Usementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impacts of China’s Minimum Grain Procurement Price Program on Agrochemical Use: A Household-Level Analysis

Heerink

Oosterveer

et al. 2021

Agriculture

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“…The price stabilization and enhancement effects of the price support policy have drawn the attention of economists and policymakers as well (Gouel, 2013;Li et al, 2021). The effect of price stabilization aids in lowering the volatility of market prices (Jayne et al, 2008;Kim & Chavas, 2002;Li et al, 2021;Miranda & Helmberger, 1988;Qian et al, 2013;Wang & Li, 2012). Anderson et al (2013) note that price enhancement encourages commodity surpluses and may adversely affect economic efficiency and agricultural trade.…”

Section: Introductionmentioning

confidence: 99%

Price support policy and market price dynamics: The case of Indian wheat

Tripathi

2024

Agricultural Economics

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The study investigates the effect of price support policies on market price distribution and its dynamics in the Indian wheat market. The analysis uses a quantile autoregression model that provides a flexible representation of price dynamics and the 2001–2020 monthly wholesale market price data. The analysis is conducted conditional on the net stock level held in the previous period. The results reveal that the net purchase by the government prevented very low market prices for wheat but resulted in price spikes. It has a price‐enhancing effect as well. The associated moments of price distribution show that public stockholding reduced variation in market price distribution. However, the government's release of stock did not prevent price rises. Findings show that dynamic adjustments tend to be qualitatively different across regimes. Government intervention in the grain market reduced stability through dynamic adjustments in wheat market prices. The results have policy implications for India and other countries in Southeast Asia in the context of the WTO's negotiations on public stockholdings and using public stockholdings as an instrument in addressing price volatility and food shortages.

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Grain price support policy and the distortion of market price

Tan,

Yue,

Chen

et al. 2024

CAER

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PurposeThis paper aims to examine whether China's grain price support policy has distorted the grain market price.Design/methodology/approachThe time-varying differences-in-differences (DID) model is used to study the impact of support policies on grain prices, and it is combined with the event study method to explore the dynamic effects of price support policy. Panel data model is used to study the effect of the price support policy on price formation for national grain market prices. In addition, we apply the smooth transformation (STR) model to verify whether there is a distortion in the transmission of grain prices among different markets in China and from the international market to China’s market.FindingsChina’s grain price support policy plays a significant role in rising grain market prices, weakens the decisive role of the market mechanism in the formation of grain prices, hinders the spatial transmission of market price signals and decreases the effect of price transmission from the world market to China’s market.Research limitations/implicationsIn order to ensure both the stability of grain production as well as the market stability, and also to ensure that intervention policies do not distort the food market, the minimum purchase price of grain and market regulation policies should be adjusted as follows: (1) price support policy should be shifted to an income support policy and (2) reasonably determine the scale of reserves and implement a grain minimum purchase price policy in limited areas.Originality/valueOur findings are relevant for understanding the effect of China's grain price support policies on the implementation regions and the price transmission effect, which provide reference experience for developing countries to implement food price policies.

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Effect of Grain Price Support Policy in China : A Grey Relational Analysis

Cited by 4 publications

References 0 publications

Impacts of China’s Minimum Grain Procurement Price Program on Agrochemical Use: A Household-Level Analysis

Impacts of China’s Minimum Grain Procurement Price Program on Agrochemical Use: A Household-Level Analysis

Price support policy and market price dynamics: The case of Indian wheat

Grain price support policy and the distortion of market price

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