Soybean Trade Report: Trend and Risk Analysis (EC1992, Dec. 2020)
Availability: Web only
Center for Agricultural Policy and Trade Studies
Agribusiness and Applied Economics
North Dakota State University
Fargo, N.D., 58108
Glossary
Average/mean -- This is the sum of a collection of numbers divided by the count of numbers in the collection.
For past historical data as in this report, this gives an idea of what the producer or decision maker should expect.
Coefficient of variation -- This is also known as the relative standard deviation. It is a statistical measure of the dispersion of data points around the mean. While it performs a similar function to the standard deviation, it is advantageous because it can be used to compare dispersion of data between distinct series of data. Furthermore, it is a unitless measure. Generally, a decision maker seeks a lower value because it provides an optimal risk-to-reward ratio with low volatility but high returns.
Descriptive statistics -- These are brief descriptive coefficients that summarize given data sets. These are classified into the measures of central tendency (mean/average) and measures of variability (minimum, variance/standard deviation and maximum variables).
Ex-ante -- These are inferences based on forecasts.
Export -- Goods or services that are sent out of a specific geographical location to another spatially demarcated jurisdiction. This is represented as nominal dollars.
Ex-post -- These are inferences based on actual results.
Harmonized system code -- Commonly represented as harmonized system (HS) code. This is a standardized numerical method of classifying traded products. Primarily, it is used by customs authorities around the world to identify products when assessing duties/taxes and for collecting data for statistical analysis.
Import -- Goods or services that are brought into a specific geographical location from another spatially demarcated jurisdiction. This is represented as nominal dollars.
Net farm income -- Net farm income refers to the return to farm operators for their labor, management and capital after all production expenses have been paid. This is the gross farm income minus production expenses.
Period -- A period is defined as a five-year interval in this report.
Prices -- Price is computed as the ratio of export value and quantity. This is represented as nominal dollars per metric ton ($/MT).
Production efficiency -- Production efficiency is concerned with producing goods and services with the optimal combination of inputs to produce maximum output for the minimum cost.
Production -- Quantity of commodity produced. This is measured as bushels for both commodities (corn and soybeans).
Productivity -- Productivity is the measure of output from a production process per unit of input.
Risk -- A risk is the possibility of loss or gain of an event with known probabilities.
Shares -- Representative proportion of the total of a variable/indicator.
Standard deviation -- This is a quantification of the amount of variation or dispersion of a set of data values. This is most often a complementary information to the mean. Given any mean, there are chances of gain or a loss. Hence, knowing the possible variation can allow the decision maker or producer to plan with bounds.
Trade -- This is basically computed as the sum of imports and exports. However, in this report, trade is used generically to represent either imports or exports.
Trend -- A general course or prevailing tendency to take a particular direction or move in some indicated direction. In this report, the trend defines the direction of growth of the respective variable.
Uncertainty -- Uncertainty refers to the occurrence of an event for which probabilities cannot be assigned.
Executive Summary
This report presents organized and structured information on soybean trade indicators across geographical space and through time. The indicators considered are exports, imports and prices. These also are presented at the byproduct level.
The levels of aggregation are global, U.S. and North Dakota. The information is presented in the form of trends and descriptive statistics. The former reveals the direction of the growth, while the latter reveals the magnitude of expectations. The descriptive statistics are represented by the mean, standard deviation, coefficient of variation and share contribution to the total.
The report is presented in six sections: (I) global temporal soybean trade, (II) global spatial soybean export, (III) global spatial soybean import, (IV) U.S. temporal soybean export, (V) U.S. spatial soybean export and (VI) U.S. state level soybean export. At the global level, the trends of the indicators are presented in addition to the descriptive statistics of the top 15 exporting and importing countries. The trends and descriptive statistics for the top 15 exporting states also are provided at the U.S. level.
This report is important because it serves as an informational guide on exports, our competitors for exports and potential markets for soybeans to our producers. In the current environment, the success (productivity and net farm income stability) of agricultural business depends on accurate prediction of potential demand for soybeans and their products to help producers in making decisions for domestic or foreign markets. Hence, having a comprehensive and accurate database on exports and imports at the global, national and state levels will enable producers in decision-making with confidence.
To formulate trade policies related to the international market, the trends and the descriptive statistics are useful to producers in identifying variations in demand for soybeans and their products. For decision makers, this information is helpful in the development of risk management tools for potential export losses due to risky events such as politically driven tariffs and uncertain events such as COVID-19. Finally, in the years of decline, identifying sources of variation or risk in changing consumer preferences, genetically modified restrictive index, trade facilitation and prosperity indexes is important. The study reveals that:
Global Trade
- The soybean market has shifted to processed products.
- Soybean grain, residue and crude oil are primary with an increase in flour.
- Brazil, Argentina, Paraguay and Canada are the major competitors with the U.S. for soybean grains.
- China, Japan, Netherlands, Spain and Germany are the major destinations for soybean grain.
- Soybean grain prices have been on the decline in recent years.
U.S. Trade
- China, Mexico, Japan, Indonesia and Netherlands are the major destinations for U.S. soybean grains.
- Turkey, Russia, Argentina and Italy are among the top 15 importers of soybean grains but not part of the top 15 U.S. export destinations.
U.S. State Trade
- Our state-level estimates of trade are consistent with U.S. Department of Agriculture (USDA) Economic Research Service (ERS) exports. In contrast, the USDA Foreign Agricultural Service (FAS) under- and overestimates state exports because they are based on the location of the port.
- Our production-adjusted state export estimates suggest the major exporters of soybeans are Illinois, Iowa, Minnesota, Nebraska, Indiana, Ohio, Missouri, South Dakota, North Dakota and Kansas.
North Dakota Trade
- North Dakota soybean exports are underestimated by the USDA FAS.
– For instance, the production adjusted export value predicts a value of $885,365,842 in 2018, while the ERS method predicted $887,896,380 for North Dakota. On the other hand, the FAS presents a value of $62,543,314.
Future Research
Exports are particularly important for every economy. In the case of North Dakota, where production mostly exceeds domestic consumption, the need to explore foreign market potentials is essential. From this report, we observed that the current trends of soybean trade for North Dakota have been increasing. We must not only evaluate the determinants of North Dakota soybean exports but also explore potential markets.
- The next stage of this research seeks to evaluate the efficiency of U.S. state agricultural exports and its determinants. Of particular interest are the impact of the genetically modified restrictive index, tariffs and other transportation costs. The expected outcome of the estimation is to provide the requisite knowledge that will give North Dakota soybean farmers a comparative advantage in the international markets, given that these variables have become very instrumental drivers of international trade in recent years.
- The second objective will be to examine the determinants of commodity price volatilities and their impact on North Dakota production and exports.
About the Center
Center for Agricultural Policy and Trade Studies
The vision of the Center for Agricultural Policy and Trade Studies (CAPTS) is to enhance the sustainability of the net farm income of North Dakota producers through in-depth trade and agricultural policy research. After carefully considering stakeholder inputs, interests, risks and uncertainties, the concept of efficiency, technology assessment and productivity growth1 also are embedded into the center’s research.
To address this vision, the center aims to develop a “model of farm economy” to conduct ex-post and ex-ante evaluations for North Dakota. The model will evaluate agricultural and trade policies with its implications on North Dakota producers’ net farm income. Additionally, the implications of policy on North Dakota producers’ efficiency, technology assessment and productivity growth also will be evaluated.
The model of farm economy based on multiple theoretical frameworks will not only evaluate the implications of existing agricultural and trade policies (Title I, II, III and XI) but also future policies to meet efficiency, productivity and net farm income sustainability goals of North Dakota producers. Our perception of the challenges and the choices made at this juncture in history will determine how to protect farmers in our state and secure our future. The center keeps detailed records of all activities and publishes the information that will be of value to the clientele, including commodity groups and decision makers of the state and region.
Center and Current Project
The center, in collaboration with North Dakota Soybean and Corn councils, is evaluating measures of improving net farm income sustainability for producers in the state. The project is in three dimensions; these are the production indicator report, trade report and policy report.
The phase 1 outcomes of the project include detailed and comprehensive development of databases and the presentation of trends and risks in the production indicator, trade and policy reports. These reports are useful to the producers, commodity groups and decision makers.
Also, this information will form the basis for the development of the “model of farm economy” to evaluate the implications of agricultural and trade policies on North Dakota producers’ net farm income. Additionally, the implications of technology and policies on North Dakota producers’ efficiency and productivity growth will be evaluated.
About the North Dakota Soybean Council
The North Dakota Soybean Council (NDSC) was established in 1985 by the North Dakota Legislature. In 1991, the NDSC became a qualified state soybean board (QSSB) under the federal Soybean Promotion, Research and Consumer Information Act, when the United Soybean Board (USB) was established. Today, the NDSC serves more than 10,000 soybean farmers in North Dakota.
The NDSC is charged as the administrator of the North Dakota soybean checkoff. The checkoff is one-half of 1% of the price of each bushel of soybeans contributed at the first point of sale. Fifty percent of the funds collected remains in North Dakota for initiatives in the state. The remaining 50% is sent to the USB for national programs for the betterment of U.S. soybean farmers.
The NDSC consists of a board of 12 soybean producers elected by their peers. Board members are charged with determining how to invest the soybean checkoff into programs that support and expand research, market development, promotion and education to the benefit of the North Dakota soybean producers. In addition to the 12-member board, the office is managed by a team of six professionals to help oversee the investments as directed by the board.
Soybean production in North Dakota has grown tremendously since the mid-1980s, and soybeans are grown on farm operations statewide. Thanks to the investment in research, farmers have access to varieties that do well in our northern climate.
Because of our soy checkoff investments in transportation infrastructure and market development around the globe, North Dakota soybeans are a high-value export crop. The NDSC board strives to foster and grow strong market demand in traditional and new expanding markets, invest in research to meet the changing needs of farmers each year to ensure a quality crop, and work to ensure the tools and resources are available to help farmers remain profitable.
The soybean industry is a key piece of the North Dakota economy, helping support communities, rural and urban, creating job opportunities and sustaining healthy land that has been part of North Dakota’s heritage for generations.
The North Dakota Soybean Council is committed to growing a legacy of successful farmers. To learn more about the NDSC, visit www.ndsoybean.org, or follow it on social media.
Trade Report
Rationale for This Report
In recent years, discussions on global trade have become a delicate topic among world leaders. Each country seems to seek out its interest at the expense of others. However, a theoretically established fact is that international trade is a positive-sum game rather than a zero-sum game for partner countries involved. What also is well known is that governments are more likely to form free trade areas if the benefits outweigh the costs.
The U.S. has been at the center of many of these trade disputes in recent times. This can be primarily attributed to its efficiency of production. The U.S. agricultural sector consistently has produced more than its domestic needs. Hence, international trade and food aid supplies have been the two major outlets for excess agricultural produce of the U.S.
Considering this, the recent turn of geopolitical events has been unfavorable for farmers in the U.S. To remedy this issue, we have a need to understand the factors that hinder or promote U.S. agricultural exports. Several studies have been conducted on the determinants of U.S. agricultural exports. Meanwhile, crop production is spatially specialized in the U.S. For instance, the Midwestern states are the major producers of U.S. grains and oilseeds.
To formulate policies concerning current trade events, the understanding of the determinants of U.S. agricultural exports alone may not be sufficient. We have a need to dissect the determinants of state-level agricultural exports. However, research on U.S. state-level agricultural exports is limited, attributed to the nature of available data.
The current data on state-level exports do not reflect the major production states. This is because of the dual problem of the absence of ports of exit in these states and the USDA Foreign Agricultural Service’s method of reporting state-level exports based on the ports of exit rather than state of origin.
As part of its commitment to help mitigate the effects of these challenges faced by producers in North Dakota on the international markets, the CAPTS frequently performs research. This report is the output of a collaboration between the CAPTS and NDSC with the aim of overcoming challenges of soybean trade in North Dakota.
To evaluate the possible effects of these challenges and propose plausible solutions, the need exists for accurate and up-to-date data at different levels of aggregation. The objective of this study is to develop a statistical-based method to estimate the soybean exports by the individual states within the U.S.
Obtaining this estimate will be useful to examine the actual determinants of the soybean exports at the state level. Knowing this can help Congress formulate policies with emphasis on states that are major producers of soybeans.
This report, as part of a series of research in line with the collaborative objective, presents data on soybean trade indicators. This trade indicator report presents data on the following variables through time (temporal) and across geographical space (spatial):
- Export value
- Import value
- Price
Why is This Report Important?
This report presents systematically aggregated trade information for soybean producers. First, it is important because it contains details of exports and imports based on soybean byproducts through time. This information reveals the shifting demand for these byproducts through time.
For U.S. soybean producers, this information is relevant for them to identify major competitors and potential new markets. Identifying the competitors will aid in policy formulation to increase market dominance, while identifying new markets will help increase total market share (and subsequently revenue) through exploring these new destinations.
Secondly, the report presents information on soybean prices during the period in addition to statistical risk. The financial markets (prices) form the bedrock of profit maximization and income sustainability. These trends and statistical risks are important because they reveal the volatilities and possible losses or gains. For North Dakota soybean producers, this report presents a set of accurate state-level exports that eliminates the port bias problem.
Typically, the demand for state production incentives can be boosted with higher historic exports. However, under situations where the exports for certain states are underestimated due to the port bias problem, the representatives have difficulty in obtaining the necessary incentives for their producers. These accurate state-level exports can be used for negotiations by state representatives or commodity groups for incentives for soybean producers in North Dakota.
Data and Methods
The U.S. national and state-level exports and imports from the world and individual countries are available from Global Agricultural Trade System (GATS), U.S. Department of Agriculture, Foreign Agricultural Service (USDA-FAS). These trade data are presented at bulk and byproduct levels identified by their harmonized system (HS) codes. The soybean trade data were obtained from this website at the byproduct level. The groups (with their HS codes) obtained are:
- Whole soybeans (120100 and 120190)
- Soybean seeds (120110)
- Soybean flour (120810)
- Soybean residue (230400)
- Soybean crude oil (150710)
- Soybean refined oil (150790)
To compute the production-adjusted state-level exports, production data were obtained from the USDA National Agricultural Statistical Services (NASS). The Statistical Analysis System (SAS) software is used in the generation of tables and graphs. These are presented at:
- World (aggregate and countries)
- U.S. (aggregate and states)
The empirical framework for this report includes annual trends, five-year changes and summary statistics (mean, risk/deviations and coefficient of variation) and intensity of trade (market share) among countries and states. The results presented at various levels would help the soybean producers not only evaluate their options for the present but also develop strategies for the future based on the market trends and risks.
- Annual trends: The annual trends of global exports, imports and prices of soybeans are presented in the report. The export and import values also are presented by trends for the top 15 countries. At the U.S. level, the trends of these indicators are presented for the whole country and top 15 states. At the North Dakota level, the trends are presented and compared for our computed production-adjusted exports, USDA FAS exports and ERS exports. Presenting these trends in the report will provide a framework to gauge the changes through time across countries and states. Furthermore, it will help reveal the extent of bias accumulation attributed to the current USDA FAS method of computing state exports. Knowing these trends can serve as a basis for estimating the volatilities and their sources. This can help forecast future possibilities for desired horizons for advance decision-making.
- Five-year changes: This report further presents histograms of the five-year sums of the trade indicators at the various levels of aggregation and product group level. Having the indicators for five-year periods in the report will provide a framework to evaluate the increase/decrease or shifts across periods.
- Summary statistics: The summary statistics are provided for the various levels of aggregation for all the trade indicators enumerated. This will provide a framework to evaluate the magnitude of the variables using totals, averages, risks, coefficient of variation and intensity of the trade variables in the form of market share.
Key Findings
Global Trend and Risk
Global soybean export quantity and value increased steadily during the period (Figure 1). Between 2014 and 2018, whole soybeans accounted for 60.2% of the global export share of soybean products. Soybean residue accounted for 28.5% of the share in this period. The third important byproduct in this period was crude soybean oil (8%).
Figure 7 presents the global export share of soybean products from 2014 to 2018. The trends of export value, quantity and price for the six byproducts are presented in Figures 8, 9 and 10.
The top 15 exporters of whole soybeans (export value share) based on the period between 2014 and 2018 are:
- Brazil (45.1%)
- U.S. (38.3%)
- Argentina (5.63%)
- Paraguay (2.89%)
- Canada (2%)
- Uruguay (1.95%)
- Ukraine (1.61%)
- Netherlands (0.75%)
- India (0.25%)
- Russia (0.21%)
- China (0.19%)
- Belgium (0.16%)
- Croatia (0.12%)
- Romania (0.11%)
- France (0.08%)
The trends of the export values for the top 15 countries are presented from Figure 11 to Figure 13. Figures 14 to 28 present trends for the top 15 exporters for the other byproducts. The details for the descriptive statistics can be found in the appendix.
The top 15 importers of whole soybeans (import value share) based on the period between 2014 and 2018 are;
- China (60.7%)
- Japan (3.33%)
- Netherlands (2.99%)
- Spain (2.97%)
- Germany (2.50%)
- Indonesia (2.22%)
- Turkey (2.06%)
- Mexico (2.86%)
- Taiwan (1.88%)
- Thailand (1.86%)
- Russia (1.66%)
- Argentina (1.44%)
- South Korea (1.31%)
- Italy (1.24%)
- Vietnam (1.23%)
The trends of the import values for the top 15 countries are presented from Figure 29 to Figure 31. Figures 32 to 46 present trends for the top 15 importers for the other byproducts. The details for the descriptive statistics can be found in the appendix.
U.S. States Trend and Risk
The trends of the share of U.S. soybean exports relative to the world is presented in Figure 47. This figure shows that the U.S. global share of whole soybean exports has declined through time. The implication of this phenomenon suggests that U.S. soybean exports are shifting to processed soybean products in recent times.
The top 15 U.S. export destinations are:
- China (25.4%)
- Mexico (3.97%)
- Japan (2.41%)
- Indonesia (2.29%)
- Netherlands (1.84%)
- Taiwan (1.64%)
- Germany (1.38%)
- Egypt (1.12%)
- Spain (1.03%)
- Thailand (0.95%)
- Vietnam (0.84%)
- Bangladesh (0.76%)
- South Korea (0.70%)
- Pakistan (0.69%)
- Colombia (0.50%)
The trends of the import values for the top 15 U.S. export destination countries are presented from Figure 48 to 50. Figures 51 to 65 present trends for the top 15 U.S. exporting destinations for the other byproducts. The details for the descriptive statistics can be found in the appendix.
The production-adjusted export trends of the top 15 states are:
- Illinois (14.5%)
- Iowa (13.%)
- Minnesota (8.56%)
- Nebraska (7.66%)
- Indiana (6.89%)
- Ohio (6.27%)
- Missouri (6.14%)
- South Dakota (5.51%)
- North Dakota (5.07%)
- Arkansas (4.01%)
- Kansas (3.98%)
- Mississippi (2.80%)
- Michigan (2.36%)
- Wisconsin (2.29%)
- Kentucky (2.29%)
The trends of the indicators for the top 15 exporting states are presented from Figure 66 to Figure 71. The details for other indicators at the global level can be found in the appendix.
North Dakota Whole Soybean Exports
The USDA FAS reports state export values are based on reported port values. Hence, the data obtained from the USDA FAS website do not reflect the actual performance of the individual states in terms of their export and production. To that effect, state representatives have difficulty negotiating for incentives and farm programs for domestic farmers. To solve this problem, this report employs a production accounts method to estimate North Dakota soybean exports.
For consistency, the cash-receipts based method that is employed by the USDA ERS to estimate state level exports also is obtained. The export value for these three methods is presented in Tables 1, 2 and 3. A comparison of the three data types is shown in Table 4 for the total export value during the period.
You can see that the production accounts method and cash-receipts method yield similar results. The data from USDA FAS underestimates North Dakota soybean exports by about 10 times relative to the production accounts method. For instance, the production adjusted export value predicts a value of $885,365,842 in 2018 while the ERS method predicted $887,896,380 for North Dakota. On the other hand, the FAS presents a value of $62,543,314.
Future Research Proposal
Exports are particularly important for every economy. Furthermore, in the case of North Dakota, where production mostly exceeds domestic consumption, the need to explore foreign market potentials is essential. From this report, we can observe that the current trends of soybean trade for North Dakota have been increasing. Evaluating the determinants of North Dakota soybean exports is essential.
- The next stage of this research seeks to evaluate the efficiency of U.S. state agricultural exports and its determinants. Of particular interest are the impact of genetically modified restrictive index, tariffs and other transportation costs. The expected outcome of the estimation is to provide the requisite knowledge that will give North Dakota soybean farmers a comparative advantage on the international markets, given that these variables have become very instrumental drivers of international trade in recent years characterized by geopolitical disputes.
- The second objective will be to examine the determinants of commodity price volatilities and their impact on North Dakota production and exports.
Section I: Global Temporal Soybean Trade
Figure 1: Global Soybean Exports, Annual Trends
Figure 2: Global Soybean, Seed Exports, Annual Trends
Figure 3: Global Soybean Oil Crude Exports, Annual Trends
Figure 4: Global Soybean Oil Refined Exports, Annual Trends
Figure 5: Global Soybean Residue Exports, Annual Trends
Figure 6: Global Soybean Flour Exports, Annual Trends
Figure 7: Global Export Share of Soybean Products, 2014-2018
Figure 8: Global Export Value of Soybean Products, Annual Trends
Figure 9: Global Export Quantity of Soybean Products, Annual Trends
Figure 10: Global Export Price of Soybean Products, Annual Trends
Section II: Global Spatial Soybean Export
Figure 11: Top 5 Countries Soybean Export Value, Annual Trends
Figure 12: Top 6 to 10 Countries Soybean Export Value, Annual Trends
Figure 13: Top 11 to 15 Countries Soybean Export Value, Annual Trends
Figure 14: Top 5 Countries Soybean, Seed Export Value, Annual Trends
Figure 15: Top 6 to 10 Countries Soybean, Seed Export Value, Annual Trends
Figure 16: Top 11 to 15 Countries Soybean, Seed Export Value, Annual Trends
Figure 17: Top 5 Countries Soybean Oil Crude Export Value, Annual Trends
Figure 18: Top 6 to 10 Countries Soybean Oil Crude Export Value, Annual Trends
Figure 19: Top 11 to 15 Countries Soybean Oil Crude Export Value, Annual Trends
Figure 20: Top 5 Countries Soybean Oil Refined Export Value, Annual Trends
Figure 21: Top 6 to 10 Countries Soybean Oil Refined Export Value, Annual Trends
Figure 22: Top 11 to 15 Countries Soybean Oil Refined Export Value, Annual Trends
Figure 23: Top 5 Countries Soybean Residue Export Value, Annual Trends
Figure 24: Top 6 to 10 Countries Soybean Residue Export Value, Annual Trends
Figure 25: Top 11 to 15 Countries Soybean Residue Export Value, Annual Trends
Figure 26: Top 5 Countries Soybean Flour Export Value, Annual Trends
Figure 27: Top 6 to 10 Countries Soybean Flour Export Value, Annual Trends
Figure 28: Top 11 to 15 Countries Soybean Flour Export Value, Annual Trends
Section III: Global Spatial Soybean Import
Figure 29: Top 5 Countries Soybean Import Value, Annual Trends
Figure 30: Top 6 to 10 Countries Soybean Import Value, Annual Trends
Figure 31: Top 11 to 15 Countries Soybean Import Value, Annual Trends
Figure 32: Top 5 Countries Soybean, Seed Import Value, Annual Trends
Figure 33: Top 6 to 10 Countries Soybean, Seed Import Value, Annual Trends
Figure 34: Top 11 to 15 Countries Soybean, Seed Import Value, Annual Trends
Figure 35: Top 5 Countries Soybean Oil Crude Import Value, Annual Trends
Figure 36: Top 6 to 10 Countries Soybean Oil Crude Import Value, Annual Trends
Figure 37: Top 11 to 15 Countries Soybean Oil Crude Import Value, Annual Trends
Figure 38: Top 5 Countries Soybean Oil Refined Import Value, Annual Trends
Figure 39: Top 6 to 10 Countries Soybean Oil Refined Import Value, Annual Trends
Figure 40: Top 11 to 15 Countries Soybean Oil Refined Import Value, Annual Trends
Figure 41: Top 5 Countries Soybean Residue Import Value, Annual Trends
Figure 42: Top 6 to 10 Countries Soybean Residue Import Value, Annual Trends
Figure 43: Top 11 to 15 Countries Soybean Residue Import Value, Annual Trends
Figure 44: Top 5 Countries Soybean Flour Import Value, Annual Trends
Figure 45: Top 6 to 10 Countries Soybean Flour Import Value, Annual Trends
Figure 46: Top 11 to 15 Countries Soybean Flour Import Value, Annual Trends
Section IV: U.S. Temporal Soybean Export
Figure 47: U.S. Share of Exports Relative to the World, Annual Trends
Section V: U.S. Spatial Soybean Export
Figure 48: U.S. Soybean Export Value to Top 5 Countries, Annual Trends
Figure 49: U.S. Soybean Export Value to Top 6 to 10 Countries, Annual Trends
Figure 50: U.S. Soybean Export Value to Top 11 to 15 Countries, Annual Trends
Figure 51: U.S. Soybean, Seed Export Value to Top 5 Countries, Annual Trends
Figure 52: U.S. Soybean, Seed Export Value to Top 6 to 10 Countries, Annual Trends
Figure 53: U.S. Soybean, Seed Export Value to Top 11 to 15 Countries, Annual Trends
Figure 54: U.S. Soybean Oil Crude Export Value to Top 5 Countries, Annual Trends
Figure 55: U.S. Soybean Oil Crude Export Value to Top 6 to 10 Countries, Annual Trends
Figure 56: U.S. Soybean Oil Crude Export Value to Top 11 to 15 Countries, Annual Trends
Figure 57: U.S. Soybean Oil Refined Export Value to Top 5 Countries, Annual Trends
Figure 58: U.S. Soybean Oil Refined Export Value to Top 6 to 10 Countries, Annual Trends
Figure 59: U.S. Soybean Oil Refined Export Value to Top 11 to 15 Countries, Annual Trends
Figure 60: U.S. Soybean Residue Export Value to Top 5 Countries, Annual Trends
Figure 61: U.S. Soybean Residue Export Value to Top 6 to 10 Countries, Annual Trends
Figure 62: U.S. Soybean Residue Export Value to Top 11 to 15 Countries, Annual Trends
Figure 63: U.S. Soybean Flour Export Value to Top 5 Countries, Annual Trends
Figure 64: U.S. Soybean Flour Export Value to Top 6 to 10 Countries, Annual Trends
Figure 65: U.S. Soybean Flour Export Value to Top 11 to 15 Countries, Annual Trends
Section VI: U.S. State Level Soybean Export
Figure 66: U.S. Soybean Export Value of Top 5 States, Annual Trends
Figure 67: U.S. Soybean Export Value of Top 6 to 10 States, Annual Trends
Figure 68: U.S. Soybean Export Value of Top 11 to 15 States, Annual Trends
Figure 69: U.S. Soybean Export Value of Top 16 to 20 States, Annual Trends
Figure 70: U.S. Soybean Export Value of Top 21 to 25 States, Annual Trends
Figure 71: U.S. Soybean Export Value of Top 26 to 30 States, Annual Trends
Table 1: NDSU Estimate of U.S. State Soybean Grain Export Value, Annual Trends.
Reporter |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
Alabama |
49,392,902 |
53,381,418 |
124,668,707 |
119,458,101 |
113,582,129 |
96,466,269 |
72,386,119 |
77,762,651 |
52,786,085 |
Arkansas |
596,148,177 |
709,761,752 |
1,109,898,433 |
914,056,087 |
1,014,409,247 |
788,347,767 |
801,265,558 |
906,182,168 |
661,862,886 |
Florida |
3,765,225 |
2,171,448 |
6,185,430 |
7,185,457 |
8,554,909 |
4,729,801 |
5,127,140 |
2,189,143 |
1,666,539 |
Georgia |
38,481,192 |
16,421,572 |
66,680,298 |
61,334,317 |
73,586,720 |
66,152,300 |
40,815,062 |
31,491,863 |
18,800,466 |
Illinois |
2,728,267,437 |
2,475,450,182 |
3,175,558,000 |
3,097,558,770 |
3,371,591,259 |
2,683,744,235 |
3,254,794,085 |
3,052,350,584 |
2,700,661,679 |
Indiana |
1,474,741,783 |
1,396,830,689 |
1,875,803,109 |
1,746,689,864 |
1,860,562,277 |
1,351,448,409 |
1,760,623,814 |
1,601,719,182 |
1,386,513,407 |
Iowa |
2,757,085,048 |
2,736,858,741 |
3,417,212,339 |
2,729,554,351 |
2,998,307,820 |
2,646,814,660 |
2,969,181,259 |
2,723,238,639 |
2,158,279,331 |
Kansas |
800,110,250 |
571,713,986 |
711,663,210 |
830,007,923 |
817,903,101 |
682,485,202 |
1,000,375,934 |
896,143,182 |
741,156,947 |
Kentucky |
267,268,449 |
327,055,092 |
482,939,366 |
538,290,444 |
527,318,931 |
439,661,201 |
493,030,458 |
518,241,349 |
400,970,328 |
Louisiana |
217,832,388 |
193,456,234 |
431,714,713 |
360,356,070 |
519,043,748 |
297,803,111 |
321,665,569 |
339,166,519 |
254,198,597 |
Maryland |
94,115,735 |
100,271,342 |
179,567,233 |
116,393,117 |
137,820,435 |
100,683,175 |
111,921,500 |
120,682,953 |
92,058,190 |
Michigan |
488,642,826 |
477,331,416 |
678,573,424 |
545,655,117 |
529,045,017 |
468,368,347 |
555,271,743 |
470,720,365 |
433,760,729 |
Minnesota |
1,778,711,499 |
1,555,721,518 |
2,466,440,332 |
1,775,678,238 |
1,815,490,713 |
1,772,133,000 |
2,017,685,179 |
1,831,024,795 |
1,459,259,490 |
Mississippi |
393,285,906 |
384,938,425 |
720,713,084 |
598,207,869 |
756,819,477 |
544,529,091 |
540,935,397 |
582,072,569 |
485,039,235 |
Missouri |
1,221,212,188 |
1,086,209,507 |
1,298,515,539 |
1,309,796,844 |
1,568,853,765 |
889,670,988 |
1,462,660,953 |
1,441,065,787 |
1,020,369,381 |
Nebraska |
1,461,070,892 |
1,433,155,369 |
1,653,922,321 |
1,604,512,966 |
1,691,944,169 |
1,420,129,242 |
1,618,625,340 |
1,538,223,634 |
890,089,246 |
New Jersey |
12,815,654 |
18,069,350 |
28,863,642 |
21,338,540 |
26,969,714 |
15,277,966 |
18,989,780 |
21,528,741 |
15,632,374 |
New York |
75,735,585 |
66,946,111 |
110,560,035 |
84,559,572 |
85,192,034 |
63,189,736 |
70,471,088 |
57,379,144 |
63,843,819 |
North Carolina |
239,902,855 |
229,349,092 |
494,913,724 |
315,029,866 |
426,440,479 |
257,802,599 |
319,572,057 |
333,697,558 |
207,935,000 |
North Dakota |
748,253,829 |
624,472,118 |
1,294,063,389 |
866,901,586 |
1,161,115,671 |
846,756,197 |
1,251,508,675 |
1,122,286,931 |
885,365,842 |
Ohio |
1,256,900,466 |
1,294,533,668 |
1,708,147,360 |
1,430,415,391 |
1,532,221,716 |
1,164,702,811 |
1,430,163,251 |
1,259,449,514 |
1,132,158,630 |
Oklahoma |
67,156,429 |
18,733,304 |
31,810,784 |
65,256,268 |
61,127,727 |
54,884,149 |
71,910,167 |
87,761,107 |
61,430,211 |
Pennsylvania |
124,792,643 |
123,149,223 |
200,761,395 |
168,717,642 |
169,718,888 |
120,005,292 |
140,179,420 |
140,937,595 |
109,397,886 |
South Carolina |
61,259,065 |
50,338,102 |
103,322,742 |
58,173,785 |
95,831,901 |
45,502,340 |
68,211,443 |
73,310,579 |
40,359,805 |
South Dakota |
850,666,949 |
839,515,795 |
1,157,917,084 |
1,147,883,455 |
1,301,743,034 |
1,079,088,366 |
1,297,029,929 |
1,120,602,335 |
927,471,897 |
Tennessee |
240,687,153 |
224,777,720 |
386,535,016 |
463,868,931 |
474,287,556 |
394,342,345 |
402,629,473 |
418,343,046 |
308,128,457 |
Texas |
28,633,567 |
9,376,705 |
23,651,907 |
14,634,292 |
29,991,120 |
13,474,783 |
23,109,452 |
31,655,542 |
14,959,919 |
Virginia |
83,579,059 |
121,641,274 |
193,175,746 |
148,669,751 |
151,204,397 |
100,986,835 |
113,958,886 |
126,798,837 |
95,318,044 |
West Virginia |
3,214,579 |
4,629,405 |
7,937,969 |
6,533,449 |
8,011,165 |
5,891,864 |
6,995,585 |
6,857,895 |
5,637,313 |
Wisconsin |
441,013,478 |
428,764,012 |
566,204,774 |
383,065,956 |
475,836,623 |
433,542,933 |
563,429,704 |
493,329,387 |
411,719,410 |
Table 2: FAS Estimate of U.S. State Soybean Grain Export Value, Annual Trends.
Reporter |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
Alabama |
428,913,454 |
210,782,592 |
59,364,625 |
29,503,499 |
221,409,827 |
264,969,749 |
287,981,379 |
209,525,965 |
154,048,982 |
Alaska |
. |
. |
. |
. |
. |
. |
. |
. |
60,000 |
Arizona |
. |
5,944 |
. |
. |
304,842 |
221,509 |
. |
. |
. |
Arkansas |
38,577,159 |
58,469,109 |
36,998,625 |
45,311,903 |
26,953,714 |
8,637,979 |
7,101,822 |
22,123,753 |
15,149,539 |
California |
17,730,485 |
6,354,428 |
1,249,508 |
2,772,092 |
9,757,607 |
16,410,061 |
36,936,831 |
22,134,534 |
4,262,074 |
Colorado |
. |
. |
10,777 |
. |
. |
. |
553,055 |
4,836,963 |
. |
Connecticut |
244,936,851 |
132,411,400 |
14,435,138 |
2,508 |
. |
. |
. |
7,323 |
5,400 |
District of Columbia |
58,193,233 |
. |
. |
. |
369,651 |
. |
. |
. |
. |
Florida |
287,302 |
17,291 |
101,050 |
260,338 |
143,577 |
388,841 |
317,075 |
359,325 |
620,082 |
Georgia |
39,443,574 |
16,296,170 |
15,122,056 |
22,077,697 |
49,213,718 |
15,762,389 |
15,198,326 |
16,054,456 |
4,089,106 |
Idaho |
226,711 |
541,449 |
158,434 |
92,755 |
170,847 |
29,683 |
. |
261,338 |
717,598 |
Illinois |
814,243,258 |
1,625,854,587 |
1,362,897,365 |
2,214,293,471 |
1,817,716,871 |
1,545,176,493 |
2,332,596,018 |
2,066,582,523 |
1,085,258,241 |
Indiana |
14,686,144 |
28,699,888 |
6,213,448 |
7,537,154 |
14,734,668 |
17,513,467 |
13,326,299 |
49,528,290 |
19,149,433 |
Iowa |
540,983,969 |
320,972,852 |
407,828,629 |
233,301,810 |
514,585,104 |
384,733,628 |
254,397,650 |
181,208,717 |
446,017,735 |
Kansas |
129,478,630 |
109,464,637 |
610,325,254 |
850,842,098 |
395,292,804 |
167,803,856 |
241,910,523 |
403,491,950 |
489,182,199 |
Kentucky |
2,080,386 |
5,007,883 |
1,972,876 |
1,177,347 |
6,195,332 |
1,019,129 |
2,623,310 |
957,863 |
8,283,346 |
Louisiana |
8,764,338,491 |
8,291,470,163 |
12,843,402,733 |
9,511,056,196 |
10,670,343,934 |
8,989,056,848 |
10,929,406,459 |
10,612,210,335 |
8,586,069,559 |
Maine |
110,354 |
165,257 |
554,568 |
665,455 |
866,142 |
262,116 |
462,777 |
209,331 |
176,307 |
Maryland |
4,843,312 |
2,869,428 |
469,815 |
5,811,169 |
37,242,724 |
16,142,674 |
13,152,113 |
21,694,528 |
11,704,377 |
Massachusetts |
. |
. |
70,029 |
. |
33,603 |
13,264 |
39,032 |
20,739 |
. |
Michigan |
78,735,580 |
113,914,680 |
141,246,383 |
124,641,629 |
155,154,577 |
109,425,060 |
112,277,996 |
146,249,414 |
178,533,566 |
Minnesota |
262,182,677 |
209,823,377 |
115,791,483 |
141,262,415 |
227,452,759 |
174,401,674 |
188,308,175 |
162,289,202 |
160,168,898 |
Mississippi |
69,377,998 |
76,123,598 |
9,324,240 |
27,928,050 |
43,824,384 |
. |
7,997,369 |
109,695,163 |
24,833,770 |
Missouri |
175,253,679 |
120,381,361 |
155,468,801 |
138,178,418 |
161,337,031 |
164,373,988 |
215,189,400 |
190,678,016 |
150,160,873 |
Montana |
174,848 |
. |
. |
. |
. |
. |
7,046 |
. |
168,027 |
Nebraska |
359,487,907 |
560,407,597 |
639,226,332 |
422,040,296 |
518,221,910 |
314,912,665 |
337,945,415 |
335,468,101 |
505,992,006 |
Nevada |
8,223 |
. |
. |
6,276,392 |
. |
. |
. |
. |
. |
New Hampshire |
. |
. |
. |
. |
59,000 |
. |
. |
9,511 |
. |
New Jersey |
74,843,698 |
77,469,875 |
90,107,061 |
76,090,588 |
73,649,989 |
60,990,057 |
92,267,379 |
79,923,599 |
101,438,203 |
New York |
51,339,692 |
62,575,399 |
153,853,141 |
117,226,800 |
178,929,758 |
142,133,404 |
120,591,915 |
106,098,708 |
80,713,587 |
North Carolina |
78,469,848 |
33,453,452 |
60,915,957 |
87,611,219 |
70,583,803 |
41,636,904 |
23,954,134 |
43,863,346 |
38,068,885 |
North Dakota |
31,812,886 |
53,376,277 |
19,991,108 |
48,847,042 |
108,537,241 |
45,280,399 |
24,666,687 |
53,903,787 |
62,543,314 |
Ohio |
341,798,999 |
530,788,095 |
884,125,989 |
1,216,348,179 |
1,728,523,660 |
1,702,615,896 |
2,078,849,724 |
1,755,642,873 |
1,520,681,385 |
Oklahoma |
11,092,775 |
62,186,818 |
504,738 |
. |
. |
84,010 |
13,358,244 |
. |
11,702,737 |
Oregon |
388,110,204 |
182,637,110 |
402,945,102 |
381,553,051 |
278,127,532 |
35,292,036 |
166,150,223 |
54,831,859 |
100,464,378 |
Pennsylvania |
11,151,344 |
11,133,835 |
3,824,207 |
. |
69,929 |
. |
92,349 |
239,090 |
241,921 |
Puerto Rico |
. |
2,833 |
. |
. |
. |
. |
. |
. |
12,000 |
South Carolina |
4,412,186 |
10,266,898 |
12,730,788 |
17,710,192 |
30,981,211 |
34,984,700 |
22,038,202 |
41,847,137 |
44,359,662 |
South Dakota |
4,526,024 |
139,056 |
17,845 |
12,721,442 |
27,691,643 |
19,720,204 |
34,289 |
4,996,254 |
43,312,266 |
Tennessee |
41,219,134 |
24,745,148 |
9,321,634 |
5,057,994 |
3,254,442 |
6,833,051 |
10,898,192 |
2,361,000 |
649,837 |
Texas |
864,505,095 |
501,918,706 |
435,627,903 |
380,427,005 |
227,044,932 |
170,329,849 |
351,426,337 |
123,319,547 |
23,003,627 |
Utah |
. |
. |
. |
. |
. |
. |
12,081 |
. |
. |
Vermont |
1,403,564 |
1,028,806 |
594,035 |
264,175 |
269,353 |
254,319 |
437,689 |
429,682 |
454,567 |
Virgin Islands |
. |
. |
. |
242,054 |
133,217 |
. |
. |
. |
. |
Virginia |
427,597,503 |
327,187,228 |
699,793,313 |
726,250,755 |
784,315,854 |
586,236,529 |
698,594,949 |
595,598,525 |
699,439,644 |
Washington |
4,136,462,553 |
3,691,428,435 |
5,477,640,695 |
4,637,625,695 |
5,382,152,728 |
3,775,920,088 |
4,048,962,755 |
3,787,834,446 |
2,388,833,273 |
West Virginia |
. |
. |
. |
. |
203,220 |
. |
. |
6,826,399 |
. |
Wisconsin |
73,071,333 |
108,828,252 |
91,798,122 |
77,187,578 |
105,296,113 |
80,361,162 |
166,470,178 |
251,734,968 |
97,865,999 |
Table 3: ERS Estimate of U.S. State Soybean Grain Export Value, Annual Trends.
Reporter |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
Alabama |
73,954,793 |
49,880,016 |
100,062,807 |
118,202,214 |
121,590,926 |
95,129,081 |
92,216,032 |
74,298,255 |
58,119,228 |
Arkansas |
656,092,494 |
667,771,548 |
1,152,546,130 |
940,414,269 |
916,393,282 |
785,441,985 |
865,448,375 |
870,569,562 |
647,443,142 |
Florida |
4,036,807 |
2,483,538 |
4,594,726 |
6,555,230 |
8,268,136 |
5,948,273 |
5,431,108 |
3,334,028 |
1,686,045 |
Georgia |
61,774,041 |
25,405,273 |
45,494,532 |
61,742,843 |
70,200,264 |
63,459,255 |
58,536,299 |
34,597,922 |
22,484,895 |
Illinois |
2,554,986,187 |
2,527,639,054 |
3,398,123,200 |
2,727,309,735 |
3,548,909,304 |
2,709,289,088 |
3,120,453,270 |
3,031,785,096 |
2,580,703,101 |
Indiana |
1,523,260,747 |
1,450,088,039 |
1,971,017,449 |
1,633,199,461 |
2,005,419,264 |
1,505,921,700 |
1,669,883,295 |
1,648,609,538 |
1,313,500,996 |
Iowa |
2,815,191,908 |
2,562,979,009 |
3,572,049,324 |
2,874,983,078 |
3,057,640,118 |
2,459,174,009 |
3,239,975,779 |
2,750,615,573 |
2,161,213,295 |
Kansas |
903,962,842 |
578,026,928 |
686,912,168 |
760,958,611 |
791,467,166 |
625,146,168 |
1,000,108,456 |
896,886,997 |
707,570,180 |
Kentucky |
322,737,838 |
306,157,628 |
396,887,192 |
508,286,156 |
544,727,467 |
449,025,120 |
481,443,407 |
458,572,572 |
401,368,894 |
Louisiana |
245,762,017 |
202,695,127 |
413,118,148 |
370,329,977 |
464,737,281 |
355,171,808 |
313,242,546 |
356,290,982 |
243,526,731 |
Maryland |
100,644,748 |
89,329,281 |
152,026,467 |
134,034,197 |
129,302,126 |
103,549,726 |
113,928,474 |
112,077,039 |
91,821,259 |
Michigan |
467,952,282 |
483,227,066 |
677,407,600 |
540,205,249 |
537,774,238 |
463,530,158 |
559,896,674 |
511,953,226 |
398,267,086 |
Minnesota |
1,679,340,585 |
1,561,243,877 |
2,344,476,592 |
2,010,695,810 |
1,912,360,654 |
1,566,283,798 |
2,071,758,552 |
1,839,744,706 |
1,468,819,668 |
Mississippi |
459,058,852 |
389,375,792 |
711,713,581 |
625,237,467 |
687,432,296 |
538,833,562 |
587,601,480 |
564,757,415 |
460,410,514 |
Missouri |
1,236,163,204 |
1,251,885,693 |
1,303,713,754 |
1,299,608,358 |
1,461,805,669 |
1,072,389,199 |
1,193,439,972 |
1,427,604,018 |
1,089,777,361 |
Nebraska |
1,248,904,459 |
1,601,787,258 |
1,789,207,269 |
1,480,422,594 |
1,712,132,436 |
1,367,513,294 |
1,717,768,259 |
1,548,854,368 |
1,218,671,884 |
New Jersey |
15,793,422 |
14,323,363 |
25,714,741 |
22,838,294 |
24,409,352 |
18,185,403 |
18,472,958 |
19,622,087 |
15,329,284 |
New York |
67,455,851 |
66,266,797 |
96,575,196 |
91,148,007 |
87,536,000 |
64,093,153 |
71,893,653 |
59,613,716 |
53,152,044 |
North Carolina |
311,485,890 |
248,756,891 |
384,247,762 |
391,873,231 |
380,345,371 |
337,575,309 |
273,837,455 |
354,968,176 |
229,042,615 |
North Dakota |
669,967,641 |
695,879,713 |
1,146,629,155 |
933,591,300 |
1,165,768,640 |
771,725,190 |
1,272,664,285 |
1,053,397,508 |
887,896,380 |
Ohio |
1,243,966,767 |
1,092,616,889 |
1,760,589,088 |
1,606,358,670 |
1,498,114,639 |
1,212,274,421 |
1,389,462,795 |
1,301,332,017 |
1,063,309,023 |
Oklahoma |
69,354,261 |
39,161,395 |
28,394,061 |
48,691,072 |
64,952,907 |
52,593,577 |
69,967,399 |
79,912,523 |
65,642,938 |
Pennsylvania |
118,894,400 |
114,019,661 |
177,057,054 |
175,045,246 |
172,166,347 |
126,586,469 |
138,611,215 |
135,445,312 |
105,340,083 |
South Carolina |
71,052,952 |
54,267,104 |
86,065,742 |
74,986,201 |
81,555,217 |
62,829,914 |
62,617,123 |
70,079,757 |
51,127,503 |
South Dakota |
836,118,289 |
766,202,177 |
1,176,848,188 |
1,087,858,191 |
1,300,941,680 |
1,041,864,717 |
1,363,891,852 |
1,172,612,686 |
899,135,824 |
Tennessee |
267,913,182 |
249,894,559 |
322,762,121 |
395,358,683 |
487,978,412 |
424,184,076 |
370,266,723 |
396,135,014 |
299,397,470 |
Texas |
28,720,975 |
16,132,372 |
19,080,472 |
17,368,085 |
24,156,890 |
18,162,622 |
20,623,714 |
28,042,931 |
18,797,904 |
Virginia |
97,855,652 |
94,783,928 |
173,307,690 |
156,845,329 |
151,542,174 |
109,733,219 |
115,564,291 |
116,139,028 |
96,696,633 |
West Virginia |
3,781,251 |
3,554,284 |
6,813,451 |
6,867,591 |
7,605,423 |
6,116,857 |
6,625,548 |
6,577,270 |
5,522,764 |
Wisconsin |
417,306,169 |
352,698,466 |
595,204,686 |
424,123,118 |
402,902,749 |
413,427,748 |
536,137,009 |
495,676,864 |
379,483,339 |
Table 4: NDSU, FAS and ERS Soybean Grain Export Value for North Dakota.
Year |
NDSU |
FAS |
ERS |
2004 |
176,417,880 |
16,537,825 |
172,576,480 |
2005 |
206,445,024 |
14,995,466 |
176,105,139 |
2006 |
246,560,080 |
15,204,638 |
249,537,724 |
2007 |
388,443,847 |
26,299,636 |
378,063,952 |
2008 |
539,176,689 |
31,871,809 |
557,316,513 |
2009 |
550,721,268 |
24,744,387 |
573,534,627 |
2010 |
748,253,829 |
31,812,886 |
669,967,641 |
2011 |
624,472,118 |
53,376,277 |
695,879,713 |
2012 |
1,294,063,389 |
19,991,108 |
1,146,629,155 |
2013 |
866,901,586 |
48,847,042 |
933,591,300 |
2014 |
1,161,115,671 |
108,537,241 |
1,165,768,640 |
2015 |
846,756,197 |
45,280,399 |
771,725,190 |
2016 |
1,251,508,675 |
24,666,687 |
1,272,664,285 |
2017 |
1,122,286,931 |
53,903,787 |
1,053,397,508 |
2018 |
885,365,842 |
62,543,314 |
887,896,380 |
1 The efficiency concept allows producers to evaluate input resources (cost) to produce output (revenue). The producers’ efficiency will improve through time with adoption of innovative technologies to minimize cost and maximize revenue.
Acknowledgments
The authors express their gratitude to the North Dakota Soybean Council and North Dakota Soybean Growers’ Association for their support, suggestions, comments and several days of discussion during the project. Thanks to Ellen Crawford for editorial changes, Deb Tanner for formatting and NDSU Extension publication team. All views expressed in this publication are those of the authors and do not reflect the opinions and interest of the supporting organizations or NDSU.