Purpose

The purpose of this paper is to determine the effects of the 2018–2020 China–US trade war on US farm bankruptcies as filed under Chapter 12. The key task is to identify the economic factors affecting farm bankruptcies generally, and to then control for the trade war impacts including the Market Facilitation Program (MFP), floods, agricultural conditions and the health of agricultural finance leading into the trade war.

Design/methodology/approach

Results were obtained using ordinary least square regression and panel fixed effect model using bankruptcy rates and number as the dependent variable. Independent variables included market effects, credit conditions, yield variation, trade impacts, 2019 flooding, macroeconomic conditions and regional fixed effects. The authors use cubic splines to interpolate annual and quarterly data to a monthly base.

Findings

Based on a fixed effect model, the authors find that all other things being equal the China–USA trade war would have had a significant impact on Chapter 12 farm bankruptcies, increasing the bankruptcy rate by 25.7%. The flooding in 2009 had minor effects of increasing the rate by only 0.05%. The overall impact will, however be substantially lower than the 25.7% because of the MFP. The MFP variables (binary) had mixed effects and its true impact is unknowable at this time; however, the authors also find that a 1% increase in the producer price index decreases bankruptcy rates by 2.62% and farm bankruptcy numbers by 3.70%. Likewise a 1% increase in GDP reduces bankruptcies by 3.25%. These suggest that the MFP program will have likely reduced farm bankruptcies considerably than what would have occurred in their absence. The authors also find that states heavily dependent on trade faced lower market uncertainty. Broader economic factors (net charge-offs of farm loans held by insured commercial banks, US real GDP, the average effective interest rate on nonreal estate farm loans) affect farm bankruptcy.

Research limitations/implications

The authors use monthly bankruptcy statistics, however not all data were available in monthly measures requiring interpolation using cubic spline functions to approximate monthly changes in some variables. Although the MFP had mixed effects in the model, the mid- to longer-term effects may be more impactful. These longer-term effects (and even shorter-term effects through 2020) are complicated by the coronavirus disease 2019 (COVID-19) pandemic, which will require a different identification strategy than that employed in this paper.

Originality/value

The analysis and results of this paper are, to the authors' knowledge, the first to investigate the impact of the China–US trade war on Chapter 12 farm bankruptcy filings. The use of cubic splines in the interpolation of agricultural data is also a technical innovation.

中文翻译：

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中美贸易战对美国第12章农场破产的影响

目的

本文的目的是确定 2018-2020 年中美贸易战对根据第 12 章提交的美国农场破产的影响。关键任务是确定一般影响农场破产的经济因素，然后控制贸易战影响包括市场促进计划 (MFP)、洪水、农业状况和导致贸易战的农业金融健康状况。

设计/方法/方法

结果是使用普通最小二乘回归和面板固定效应模型获得的，使用破产率和数量作为因变量。自变量包括市场影响、信贷状况、收益率变化、贸易影响、2019 年洪水、宏观经济状况和区域固定效应。作者使用三次样条将年度和季度数据插入到月基数中。

发现

作者基于固定效应模型发现，在所有其他条件相同的情况下，中美贸易战将对第 12 章农场破产产生重大影响，使破产率提高 25.7%。2009 年的洪水对增长率的影响很小，仅增加了 0.05%。然而，由于 MFP，整体影响将大大低于 25.7%。MFP 变量（二进制）具有混合效应，其真正影响目前尚不可知；然而，作者还发现，生产者价格指数每增加 1%，破产率就会降低 2.62%，农场破产数量会降低 3.70%。同样，GDP 增长 1% 可减少 3.25% 的破产。这些表明 MFP 计划可能会比没有它们时发生的情况大大减少农场破产。作者还发现，严重依赖贸易的国家面临的市场不确定性较低。更广泛的经济因素（受保商业银行持有的农业贷款的净冲销、美国实际 GDP、非房地产农业贷款的平均实际利率）影响农场破产。

研究限制/影响

作者使用月度破产统计数据，但并非所有数据都可用于需要使用三次样条函数进行插值的月度度量，以近似某些变量的月度变化。尽管 MFP 在模型中具有混合效应，但中长期效应可能更具影响力。这些长期影响（甚至到 2020 年的短期影响）因 2019 年冠状病毒病 (COVID-19) 大流行而变得复杂，这将需要与本文中采用的识别策略不同的识别策略。

原创性/价值

据作者所知，本文的分析和结果是第一次调查中美贸易战对第 12 章农场破产申请的影响。在农业数据插值中使用三次样条也是一项技术创新。