Using companies from an industry defined by $2-$digit SIC codes, you estimated the following accruals regression model:

Y $=$ A $+$ B$1$X$1+$ B$2$X$2+$ error,

where Y is total accruals in the current year $($i$.$e$.,$ current$-$year income before extraordinary items minus current$-$year cash flow from operations$),$

X$1$ is the change in revenue from last year to the current year,

and X$2$ is the gross amount of PP&E at the end of the current year.

All of these variables are scaled by total assets at the end of last year. The analysis provided the following information:

Regression Statistics CoefficientsStandard Error t Stat P$-$value

Multiple R $0\mathrm{.}071473$ Intercept $-0\mathrm{.}0290\mathrm{.}019-1\mathrm{.}5170\mathrm{.}132$

R Square $0\mathrm{.}005108$ X$10\mathrm{.}0090\mathrm{.}0200\mathrm{.}4780\mathrm{.}634$

Adjusted R Square$-0\mathrm{.}01134$ X$2-0\mathrm{.}0170\mathrm{.}025-0\mathrm{.}6690\mathrm{.}505$

Standard Error$0\mathrm{.}089906$

You also ran a model for the industry defined by $3-$digit SIC codes and obtained the following:

Regression Statistics CoefficientsStandard Error t Stat P$-$value

Multiple R $0\mathrm{.}239403$ Intercept $-0\mathrm{.}0560\mathrm{.}016-3\mathrm{.}4400\mathrm{.}001$

R Square $0\mathrm{.}057314$ X$1-0\mathrm{.}0470\mathrm{.}018-2\mathrm{.}5740\mathrm{.}011$

Adjusted R Square$0\mathrm{.}041336$ X$20\mathrm{.}0270\mathrm{.}0221\mathrm{.}2270\mathrm{.}222$

Standard Error$0\mathrm{.}075114$

The company you are investigating for fraud has the following data:

Income cash

Total before flow from

assets Revenue EI operations Gross PPE Receivables

last year $21331227$

current year $2026-1035$

Required:

$($Q$1)$ Accruals are generally the easiest portion of earnings to manipulate. Why?

$($Q$2)$ Is the $2-$digit or $3-$digit model more appropriate to use for a Discretionay Accruals analysis? Explain.

$($Q$3)$ Using the $2-$digit model, calculate Discretionary Accruals for the company being investigated. Does your analysis indicate Fraudulant Financial Reporting $($FFR$)?$ Explain.