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China’s Changing Population Structure and its Implications for US Agricultural Exports

Xi He and Wendong Zhang

On May 11, 2021, China released the findings from its seventh national population census, which shows that its population totaled 1.41 billion in 2020 with an average annual growth rate of 0.053% since 2010, the lowest ten-year growth rate since its first population census in 1953.1 China’s population structure is also changing—a growing share of residents are older than 65 and the birth rate is declining. Specifically, China’s total new births sharply declined by around 18%, from 14.65 million in 2019 to 12 million in 2020, despite some skepticism that the birth rates might be overreported and the death rates may be underreported. On May 31, 2021, China announced that it will allow couples to have up to three children and will provide supportive measures to improve its population structure and to actively cope with an aging population after scrapping its decades-old one-child policy and adopting a two-child policy in 2016 (BBC 2021).

As one of the major destinations of US agricultural exports,2 China’s changing population structure and growing economic development have important implications for its agricultural and food import demand from the United States.

China’s evolving population policies and landscape

China’s population policies have gone through several dramatic changes since the 1950s. In the early 1950s, China adopted various policies to encourage fertility to meet the human power needed for its industrialization. However, the substantial social and economic burdens associated with the fast-growing population made China adopt a one-child policy in 1980. With the gradually declining fertility rate and aging population, China relaxed the one-child policy to allow couples to have two children starting January 2016. In May 2021, China announced a policy allowing couples to have three children after the seventh national population census showed a steep decline in births.

Figure 1 shows China’s population in three age groups, 0–14, 15–64, and 65+, from 1990 to 2020. Over this period, China’s total population increased by around 23%. However, the population aged 65+ was the primary force behind this growth, with population aged 0–14 decreasing by around 20% and population aged 15–64 increasing by around 27%.

Figure 1
Figure 1. China’s population by age groups, 1990–2020.
Source: National Bureau of Statistics of China (NBSC 2021).

US major trading partners’ incomes and population structures

Table 1 shows major US agricultural export destination countries’ incomes and population structures. A notable pattern is that developed countries, such as Canada, Japan, Korea, and the Netherlands, have a higher share of population aged 65 and above and a lower share of population aged 0–14 than developing countries, such as China, Mexico, Vietnam, the Philippines, and Indonesia. This pattern and the trend in figure 1 indicate that China’s population structure is growing more like a developing country.

Table 1. Major US Agricultural Export Destination Countries’ Incomes and Population Structures in 2019
Partner 2020 Agricultural export value (Billion dollars) 2019 GDP per capita (Thousand dollars) 2019 Population (Million) Share of population aged 0–14 Share of population aged 15–64 Share of population aged 65+
China28.810.21397.717.8%70.7%11.5%
Canada25.246.237.615.8%66.5%17.6%
Mexico19.09.9127.626.2%66.4%7.4%
Japan12.940.2126.312.6%59.4%28.0%
Korea, South8.331.851.712.7%72.2%15.1%
Vietnam3.82.796.523.2%69.2%7.6%
Netherlands3.752.317.315.9%64.5%19.6%
Philippines3.23.5108.130.5%64.2%5.3%
Indonesia2.94.1270.626.2%67.7%6.1%
World Total162.317.8311.527.4%63.5%9.0%
Source: USDA GATS (2021) and World Bank (2021). Note that trade data is from 2020, while the population and GDP per capita data are from 2019 as that is the most recent year with data available on the share of population among different age groups.

US trading partners’ evolving agricultural imports

To understand how China’s population dynamics will affect its agricultural imports from the United States, we look at US agricultural trading partners’ population structure and composition of food imports from the United States. Figure 2 illustrates US exports of four agricultural categories—bulk (e.g., corn, soybeans, wheat), intermediate (e.g., soybean meal and soybean oil), consumer-oriented (e.g., pork and beef products), and agriculture-related products (e.g., seafood and forestry products)—to high-income, upper-middle-income, lower-middle-income, and low-income countries from 1990 to 2020.

Figure 2
Figure 2. US exports of agricultural commodities to countries with different income levels.
Note: Based on data from USDA GATS (2021). We use World Bank’s classification to classify countries into different income groups and use USDA’s definition of agricultural products and classification of agricultural product categories.

There are several patterns worthy of attention. First, US agricultural exports to upper-middle-income countries increased quickly since 2000 and gradually surpassed exports of the same to high-income countries. The main reason being that China is an upper-middle-income country and largely drives US exports to upper-middle-income countries. Second, the composition of US exports to high- and middle-income countries is quite different. While consumer-oriented products accounted for the largest, and a growing share of, high-income countries’ imports from the United States, bulk products consisted of the lion’s share of middle-income countries’ imports from the United States. If China’s GDP per capita continues to grow, China’s demand for US agricultural products might shift from bulk products to consumer-oriented products.

A gravity model analysis of population and income on US agricultural exports

We use the gravity model to quantify the impacts of population and income levels on US agricultural exports based on US exports of 761 agricultural products at the six-digit HS code level to 136 countries from 1990 to 2019. Table 2 presents the Poisson pseudo-maximum likelihood estimation results. We separately present the estimation results for bulk, intermediate, and consumer-oriented products.3 Column (2) shows that a 1% increase in tariffs decreases US export quantity by 0.05%, and GDP per capita in the destination country has an inverted-U relationship with US export quantity. Column (2) also shows that while a 1% increase in population aged 15–64 increases exports by 0.77%, a 1% increase in the population aged 0–14 and 65+ decreases exports by 0.74% and 0.33%, respectively, indicating that China’s aging population might decrease its food demand from the United States. In addition, excessive heat and strong exchange rates increase food demand from the United States. Export elasticity with regard to GDP is largest for consumer-oriented products, which indicates that income growth will increase demand for consumer-oriented products more than bulk and intermediate products.

Table 2. Gravity Model Estimation Results of US Agricultural Exports, 1990–2019
(1)

All agricultural products
(2)

All agricultural products
(3)

Bulk products
(4)

Intermediate products
(5)

Consumer-oriented products
Log of tariff-0.047***
(0.002)
-0.047***
(0.002)
-0.025***
(0.004)
-0.039***
(0.003)
-0.061***
(0.002)
Log of population in destination country0.245***
(0.016)
    
Log of population aged 0-14 in destination country -0.738***
(0.022)
-0.700***
(0.077)
-0.760***
(0.040)
-0.563***
(0.028)
Log of population aged 15-64 in destination country 0.765***
(0.022)
0.569***
(0.079)
0.829***
(0.040)
0.718***
(0.027)
Log of population aged 65+ in destination country -0.326***
(0.019)
-0.169**
(0.069)
-0.462***
(0.034)
-0.275***
(0.024)
Log of GDP per capita in destination country0.555***
(0.012)
0.508***
(0.012)
0.318***
(0.040)
0.456***
(0.020)
0.663***
(0.015)
Square of Log of GDP per capita in destination country-0.083***
(0.002)
-0.088***
(0.002)
-0.070***
(0.008)
-0.086***
(0.004)
-0.107***
(0.003)
Log of exchange rate-0.076***
(0.003)
-0.079***
(0.003)
-0.050***
(0.008)
-0.081***
(0.004)
-0.072***
(0.004)
Temperature-1.173***
(0.265)
-0.784***
(0.266)
-1.664*
(0.935)
-0.854*
(0.437)
-0.411
(0.337)
Square of temperature0.122***
(0.036)
0.084**
(0.036)
0.249*
(0.129)
0.069
(0.060)
0.045
(0.046)
Precipitation-0.065***
(0.011)
-0.039***
(0.011)
-0.007
(0.044)
-0.042**
(0.020)
-0.025**
(0.012)
Square of precipitation0.009***
(0.001)
0.008***
(0.002)
0.002
(0.006)
0.010***
(0.003)
0.004**
(0.002)
RTA partners with the U.S.0.013**
(0.005)
0.008
(0.006)
0.005
(0.019)
-0.043***
(0.010)
0.046***
(0.007)
Country fixed effectsYYYYY
HS-6 fixed effectsYYYYY
Year fixed effectsYYYYY
Number of observations1,007,9791,007,979101,119316,772519,170
Note: We use Poisson pseudo-maximum likelihood, which can address zero trade flows and heteroskedasticity in the estimation. The outcome is the logarithm of US export quantity. We use US agricultural export data of 761 agricultural commodities to 136 countries at the six-digit HS code level from 1990 to 2019 (USDA GATS 2021). Tariff data come from the TRAINS dataset at United National Conference on Trade and Development (UNCTAD 2021). Data on population, GDP, weather, and exchange rate come from the World Bank (World Bank 2021). Note that because we include country fixed effects, the impacts of country-invariant factors, such as distance from the United States, cannot be estimated.

Based on these estimates, China’s income growth will likely continue to increase its food imports from the United States, with the largest increase being in consumer-oriented products. China’s growing aging population and dwindling labor force aged 14–65 will reduce its food demand from the United States, possibly with a demand shift from bulk products to consumer-oriented products.

Conclusions

With an aging population and a declining fertility rate, China’s population pattern increasingly resembles developed countries. Based on the comparison of major US agricultural trading partners’ incomes, population structures, agricultural import compositions from the United States, and the results from a gravity model, we predict that China’s economic development will increase its demand for consumer-oriented products from the United States. We also predict that China’s aging population and gradually flattening population growth will slow its food demand and change its food demand composition from the United States. Given China’s priority in promoting self-sufficiency of staple foods, we anticipate seeing some import substitution from bulk products, such as corn, into consumer-oriented products, like meat, in the future.

References

British Broadcasting Corporation (BBC). 2021. “China allows three children in major policy shift.” BBC May 31, 2021.

National Bureau of Statistics of China (NBSC). 2021.

USDA Global Agriculture Trade System (USDA GATS). 2021.

United National Conference on Trade and Development (UNCTAD). 2021. Trade Analysis Information System (TRAINS).

World Bank. 2021. World Bank Indicators.

Footnotes

1. China conducted population censuses in 1953, 1964, 1982, 1990, 2000, 2010, and 2020.

2. The United States exported around 20% of its $162 billion in agricultural products to China in 2020 (USDA 2021).

3. Agricultural related products are excluded from the analysis due to small sample size.

Suggested citation

He, X. and W. Zhang. 2021. "China’s Changing Population Structure and its Implications for US Agricultural Exports." Agricultural Policy Review, Spring 2021. Center for Agricultural and Rural Development, Iowa State University. Available at www.card.iastate.edu/ag_policy_review/article/?a=122.