The impact of US sugar prices on the financial performance of US sugar-using firms

Agricultural and Food Economics

Table 5 Regression with MTB_t + 1 as the dependent variable

Variable	Model 1	Model 2	Model 3
ln(SGA)	0.237***	0.226***	0.224***
ln(SGA)	(0.082)	(0.080)	(0.080)
t	2.90	2.81	2.81
ln(ATO)	0.545***	0.520***	0.513***
ln(ATO)	(0.097)	(0.093)	(0.092)
t	5.64	5.59	5.59
ln(Size)	0.275***	0.251***	0.237***
ln(Size)	(0.045)	(0.046)	(0.046)
t	6.14	5.48	5.18
ln(Growth)	0.005	0.005	0.006
ln(Growth)	(0.007)	(0.007)	(0.007)
t	0.65	0.66	0.84
ln(FRisk)	− 0.090***	− 0.095***	− 0.098***
ln(FRisk)	(0.015)	(0.016)	(0.017)
t	− 5.89	− 5.86	− 5.83
ln(UWpra)	0.153***
ln(UWpra)	(0.046)
t	3.28
ln(UWpre)		0.117*
ln(UWpre)		(0.062)
t		1.88
ln(UWprb)			0.056
ln(UWprb)			(0.047)
t			1.18
Constant	− 2.807***	− 2.563***	− 2.395***
Constant	(0.501)	(0.517)	(0.533)
t	− 5.60	− 4.95	− 4.49
Observations	977	977	977
# of firms	26	26	26
R-squared	0.647	0.624	0.617
F value	112.92	98.03	93.48

Notes: Robust standard errors in parentheses. ***p<0.01, **p<0.05, *p<0.1. Reported R² are “within” R² statistics. Variable definitions are in Table 1. The data were winsorized at the 1% and 99% percentiles (Adams et al. 2019; Tukey 1962). The AIC and BIC tests confirmed that winsorized data explain better the models