Estimating the impacts of rising food prices on nutrient intake in urban China

Zheng, Zhihao; Henneberry, Shida Rastegari

doi:10.1016/j.chieco.2012.07.001

Cited by 39 publications

(35 citation statements)

References 18 publications

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“…Endnotes a Among the much debated implications of food price increases are malnutrition and poverty (Ivanic et al, 2012, Zheng and Henneberry, 2012, Anriquez et al, 2013, Fujii, 2013, Wood et al 2012). The list of studies on oil and commodity price links is extensive and we mention only few representative studies here.…”

Section: Resultsmentioning

confidence: 99%

Oil and food prices in Malaysia: a nonlinear ARDL analysis

2015

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The present paper analyses the relations between food and oil prices for Malaysia using a nonlinear autoregressive distributed lags (NARDL) model. The bounds test of the NARDL specification suggests the presence of cointegration among the variables, which include the food price, oil price and real GDP. The estimated NARDL model affirms the presence of asymmetries in the food price behavior. Namely, in the long run, we find a significant relation between oil price increases and food price. Meanwhile, the long run relation between oil price reduction and the food price is absent. Furthermore, in the short run, only changes in the positive oil price exert significant influences on the food price inflation. With the absence of significant influence of oil price reduction on the food price both in the long run and in the short run, the role of market power in shaping the behavior of Malaysia's food price is likely to be significant.

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Section: Resultsmentioning

confidence: 99%

Oil and food prices in Malaysia: a nonlinear ARDL analysis

2015

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“…Inspired by the concept of nutrient elasticities applied in studies on human nutritional intake [34,35], we propose the concept of air pollution emission elasticities, which reflect how the changes in different types of vehicle activities impact the air pollution emissions. Specifically, in this study, the air pollution emissions refer to the emissions of three major pollutants from various vehicle types, including

CO

{NO}_{x}

and

{PM}_{2.5}

(For example, through the nutrient elasticities, Zheng and Henneberry [35] study the nutrient demand of three major nutrient substances (i.e., calorie, protein and fat), which were obtained from the foods (such as grain, oil, meat, eggs, etc.) consumed by a household.…”

Section: The Modeling Frameworkmentioning

confidence: 99%

Oil Price Uncertainty, Transport Fuel Demand and Public Health

Yang

Chang

2017

IJERPH

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Based on the panel data of 306 cities in China from 2002 to 2012, this paper investigates China’s road transport fuel (i.e., gasoline and diesel) demand system by using the Almost Ideal Demand System (AIDS) and the Quadratic AIDS (QUAIDS) models. The results indicate that own-price elasticities for different vehicle categories range from −1.215 to −0.459 (by AIDS) and from −1.399 to −0.369 (by QUAIDS). Then, this study estimates the air pollution emissions (CO, NOx and PM2.5) and public health damages from the road transport sector under different oil price shocks. Compared to the base year 2012, results show that a fuel price rise of 30% can avoid 1,147,270 tonnes of pollution emissions; besides, premature deaths and economic losses decrease by 16,149 cases and 13,817.953 million RMB yuan respectively; while based on the non-linear health effect model, the premature deaths and total economic losses decrease by 15,534 and 13,291.4 million RMB yuan respectively. Our study combines the fuel demand and health evaluation models and is the first attempt to address how oil price changes influence public health through the fuel demand system in China. Given its serious air pollution emission and substantial health damages, this paper provides important insights for policy makers in terms of persistent increasing in fuel consumption and the associated health and economic losses.

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“…It is a fact that the food consumed is affected by changes in a particular food's price and/-or the per capita food expenditure through the interdependent demand relationship. The relative changes in food demand are associated with the relative changes in food prices and income, and can be formulated as (Shan, 1988;Zheng & Henneberry, 2012):…”

Section: Model Specification and Estimation Proceduresmentioning

confidence: 99%