The regional production for each scenario is shown in Figure 8
. U.S. production ranges from 58 million (M) kg to 60 M kg for the Base Case
scenario (which imposes the highest duty on U.S. imports to China) and the No Tariff
scenario, respectively. China’s production ranges from 107 M kg to 127 M kg for the No Tariff
and All High Tariff
scenarios, respectively. ROW production ranges from 104 M kg to 108 M kg, for the Reverse
(which imposes the highest duties on ROW imports to China) and No Tariff
scenarios, respectively. Though China’s Base Case
modeled polysilicon production is the largest of the three regions under investigation, the region’s production is also the most responsive to the choice of trade scenario. China’s modeled production varies by as much as 15.7% of 2016’s maximum modeled production, whereas the ROW’s modeled production varies only by 3.7% of the maximum and the US’s varies by 3.3%. Though modeled production is subject to the model’s production limitations as previously discussed, all else equal, China’s modeled production absorbs the majority of the impacts of trade case variation on polysilicon production within the model.
Because the goal of this study is to understand and analyze the dynamics of polysilicon flow within and between regions, the results discussion is generally focused on the demand share, influx, and outflux results for each scenario. In the PolyMAT model, “influx” into one region includes imports from the other two regions and domestically produced polysilicon. “Outflux” from one region includes exports to the other two regions and domestically consumed polysilicon. “Demand shares” is the fraction of demand supplied by each of the three regions to meet one region’s demand.
3.1. Trade Action Severity: Impact on Global Polysilicon Flows
Our first set of scenarios aims to build an understanding of how the relative severity
of trade actions impacts trade flows. Using the PolyMAT model, we compare five scenarios (summarized in Table 3
), each with a varying degree of tariff severity, with the Base Case
scenario. These results are summarized in Figure 9
. Because China is the world’s largest producer and consumer of polysilicon for PV module production, the impact of China’s duties on U.S. and ROW imports to China is the focus of the results presented here. The first row of Figure 9
, “Import Duty”, displays China’s modeled import duty on both the USA and ROW across the analysis’s time horizon. In the No Tariff
, All High Tariff
, and All Low Tariff
cases, the import tariffs are set at the same value for both the U.S. and the ROW. The next row of Figure 9
, “Demand Shares”, displays how each of the three regions, U.S., ROW, and China, combine to meet China’s demand. In the Base Case
, when a relatively steep tariff is imposed on U.S. imports, and a less steep tariff is imposed on ROW imports, the ROW’s share of Chinese demand is reduced, but not as much as is the USA’s share of Chinese demand. The final row of Figure 9
, “Influx (kg/yr)”, displays how each region’s imports to China are changing over the time period while also displaying the year-on-year growth in China’s demand.
In the Base Case
scenario, as shown in the first column of Figure 9
, when the duties are first assumed to shift the global dynamics of trade flow in 2012, U.S. imports to China decrease from 34.9 M kg to 15.4 M kg (44%) from the prior year. Similarly, ROW imports to China decrease from 42.7 M kg to 33.6 M kg (21%) between 2011 and 2012. Modeled results show that with the Base Case’s
ultimate 57% duty rate, the United States’ deliveries to China do not recover, even with increasing demand, until 2016 when U.S. imports to China reach an estimated 39.6 M kg. In addition, U.S. demand share never achieves pre-duty levels, dropping from 0.26 in 2010 to 0.16 in 2016. The model shows that ROW imports, which were assessed at a lower duty rate (28%), recovered in 2013 with 42.3 M kg of imports to China. China supplied additional polysilicon to fill the gap, with China’s demand shares increasing from 0.43 to 0.62 and total volume increasing from 55.5 M kg to 81.1 M kg (an increase of 40.1%) in 2011 and 2012, respectively. In 2016, the model shows that U.S. and ROW imports to China totaled 39.6 M kg and 69.5 M kg, respectively.
For comparison among the seven scenarios exploring the impact of import duty severity, the 2016 production for each of the scenarios is presented in Figure 10
In the No Tariff scenario, we investigate what the global landscape for polysilicon would look like if China had not imposed import tariffs. We use 2016 as a representative year (i.e., after the duty has been in place for a few years and initial dynamics have stabilized) for this discussion. With no tariffs, U.S. and ROW production increases (58.2 M to 60.2 M [3.5%] and 106.0 M kg to 108.0 M kg [1.9%], respectively) and China’s production decreases (120.3 M kg to 107.2 M kg [10.9%]).
The 2016 outflux from the United States to China is 39.7 M kg in the Base Case (with 57% tariff) and increases to 62.4 M kg with no tariff (57.2% increase). The 2016 outflux from ROW to China increases from 69.5 M kg (with 27.8% tariff) to 76.3 M kg with no tariff (9.8% increase). In terms of meeting China’s demand, in 2016 the U.S. contribution increases from 0.16 to 0.26 and the ROW contribution increases from 0.29 to 0.32, for the Base Case and no tariff scenarios, respectively. China’s 2016 self-supply (influx) drops 22.3%, from 132.5 M kg (with Base Case tariffs) to 103.0 M kg in the No Tariff scenario. China domestic contribution drops to 0.43 in the No Tariff scenario, down from 0.55 (Base Case scenario) in 2016. The United States sees a larger increase in exports to China than the ROW in the No Tariff scenario because the larger duty reduction (57% → 0% vs. 27.8% → 0) has a greater impact on the price of polysilicon coming from the United States vs. the ROW.
We next investigated the impact of a range of tariffs specific to China imports from the United States and ROW. The range of values is shown in Table 3
for the scenarios included: Reverse
, All High Tariff
, and All Low Tariff
relative to the Base Case
. The duty levels, demand shares, and influx to China are highlighted in Figure 9
Once again focusing on 2016 results, in the Reverse scenario, when the severity of the current China import tariff is reversed, i.e., U.S. imports are assessed a 28% duty and ROW imports are assessed a 57% duty, compared to the Base Case, U.S. influx increases by 45.6% to 57.8 M kg and ROW influx decreases by 29.0% to 49.2 M kg. Polysilicon self-supplied by China increases slightly to 134.6 M kg (1.2%). In the High Tariff scenario, when all importers are assessed a high tariff (i.e., 57% for both United States and ROW), compared to the Base Case, U.S. influx decreases by 10.0% to 43.7 M kg and ROW influx decreases by 23.2% to 53.4 M kg in 2016. Polysilicon domestically supplied by China increases by 9.1% to 144.6 M kg. In the Low Tariff scenario, when all importers are assessed a low tariff (i.e., 28% for both United States and ROW), compared to the Base Case, U.S. influx increases by 33.5% to 53.0 M kg and ROW influx decreases by 6.8% to 64.8 M kg. Polysilicon domestically supplied by China decreases by 6.5% to 123.9 M kg.
The magnitude of the import tariff in a region impacts the demand share distribution from the three regions. Specifically, as the tariff on a region increases, its contribution to the demand share decreases and the other regions’ demand shares increase to fill the gap. In all of these scenarios, in the first year of the duty’s initial impact (2012 for this study), there is a steep drop in the importers’ contribution to demand and a corresponding increase in the domestic contribution to demand. The higher the duty, the larger the initial drop in the importers’ contribution to demand share. For example, the U.S. and ROW contributions to China demand show the greatest 2011–2012 drop, between 48% and 54%, in the scenarios where a 57% duty is assessed and the lowest 2011–2012 drop, between 16% and 25% when the lower 28% duty is in place. For the time period evaluated, the U.S. and ROW contributions to China’s polysilicon demand do not recover to pre-tariff levels in the scenarios evaluated.
3.3. Retaliation: Impact of U.S. and ROW Tariffs on China Imports
To understand the impacts of retaliatory tariffs targeting a region that has implemented duties on another region’s imports, we assessed the impact of the United States and ROW imposing tariffs on China imports. The duty levels are shown in Table 3
for the Retaliation
scenario relative to the Base Case
scenario. Because the United States imports so little polysilicon from China, this discussion is focused on the impact of a ROW duty on imports into ROW from China. These results are highlighted in Figure 13
, which shows the level and timing of the “retaliatory” duty on China imports, China’s contribution to ROW demand, and volume of polysilicon imports from China into the ROW.
As with the other scenarios evaluated, in the first year the duty begins to influence trade flows, there is a steep drop in the demand shares along with a drop in the influx from the targeted region. In this scenario, imports from China to ROW drop 34.3%, from 0.35 to 0.23, from 2011 to 2012. Although not shown in Figure 13
, the bulk of this shortage is made up by an increase in the ROW self-supplied polysilicon (or ROW demand share) from 0.57 to 0.68 (an increase of 19%). The corresponding drop in imports is 19.4 M kg to 12.0 M kg from 2011 to 2012. In 2016, China influx to ROW decreases from 37.1 M kg to 29.3 M kg in the Retaliation
scenario, compared to the Base Case
scenario, a 21.0% reduction. As with the other scenarios evaluated, over the time period used, China’s contributions to the ROW polysilicon demand do not recover to pre-tariff levels in the scenarios evaluated.
This scenario shows that the model is responsive to changing duties from all included regions.
3.5. Impact of Differences in Relative Regional Attractiveness
Other measures to promote domestic production and trade with specific regions have been used in the renewable energy manufacturing sector. As described in Section 2.1
, the PolyMAT model estimates the “attractiveness” of polysilicon from each of the three regions using a logit function that considers (1) the relative price of polysilicon supplied from each region and (2) other non-price-driven, exogenous factors such as the impact of domestic content requirements or free trade agreements (the parameter, k). In aggregate, the k parameter embodies all inputs to polysilicon attractiveness except price and can be used to fine-tune the model to mirror historical data (particularly in times of relative price parity).
Results from the scenarios presented to this point were driven by the relative attractiveness of polysilicon from competing producers, based on its relative price and the logit function parameters required to generate model outputs that qualitatively capture historical data. To begin to understand the impact of changing relative attractiveness on the demand share and influx volumes, the k portion of the logit function was adjusted by ±50% from the Base Case
for each region while the other regions were held at Base Case
levels. Figure 15
shows the results for the changes to demand shares and influx to China by each potential source region for the +50% k scenarios.
shows the relationship between the k parameter in the attractiveness calculation and demand shares and influx from each regional trading partner (using 2016 results for China), when the k value is varied by ±50%. Higher values of k correspond to greater attractiveness of polysilicon coming from a particular region (due to exogenous factors, not the price of polysilicon itself) and hence a greater share of demand being fulfilled by that specific region. Differences in the slope of the relationships depicted in Figure 16
are a function of both the Base Case
value of k for a specific regional trading partner as well as the Base Case
values of k for the other competing regions. More rigorous estimates of the regional values for k, based on inter-regional data for shipments of polysilicon, would allow deeper analysis of these relationships in the future.