I belive this is Undervaluing asserts.
hope this helps!
The ability to meet short-term obligations and efficiently generate revenues is called Liquidity and efficiency.
When a financial asset or security may be quickly and easily converted into cash without depreciating in value, this is referred to as having liquidity.
In other words, the degree to which an asset may be swiftly purchased or sold on the market at a price representing its underlying value is referred to as liquidity. Due to its ease and speed of conversion into other assets, cash is regarded as the most liquid asset.
Business efficiency is the amount of output a firm or organization can create given the time, money, and resources available. In other words, a company's efficiency refers to how well it can turn resources like labor, capital, and raw materials into services and goods that generate income.
To learn more about Liquidity and Efficiency refer to:
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Answer:
Bad debt expense $ 14.850
Explanation:
Initial Balance
Accounts Receivable $ 309.000
Allowance for Uncollectible Accounts $ 600
Should be 5% of the Accounts Receivables
Allowance for Uncollectible Accounts $ 15.450
We must calculate the difference between the actual balance and the must be balance.
Adjustment entry
Bad debt expense $ 14.850
Allowance for Uncollectible Accounts $ 14.850
END Balance
Accounts Receivable $ 309.000
Allowance for Uncollectible Accounts $ 15.450
Answer:
a) H0: u = presence of a unit root
HA: u ≠ presence of a unit root ( i.e. stationary series )
b) t stat = -0.064
c) We will reject the Null hypothesis and the next step will be to accept the alternative hypothesis
d) It is not valid to compare the estimated t stat with the corresponding critical value because a random walk is non-stationary while the difference is stationary because it is white noise
Explanation:
<u>a) stating the null and alternative hypothesis</u>
H0: u = presence of a unit root
HA: u ≠ presence of a unit root ( i.e. stationary series )
<u>b) performing the test </u>
critical value = -2.88
T stat = coefficient / std error
= -0.02 / 0.31 = -0.064
c) From the test, the value of T stat > critical value we will reject the Null hypothesis hence the next step will be to accept the alternative hypothesis
d) It is not valid to compare the estimated t stat with the corresponding critical value because a random walk is non-stationary while the difference is stationary because it is white noise
