PurposeThe 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/approachResults 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.FindingsBased 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/implicationsThe 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/valueThe 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.
Pengaruh Tingkat Edukasi dan Spesialisasi Pendidikan CEO terhadap Performa Perusahaan di Indonesia
