In august 2016, richard purchased and placed in service an office building costing $753,000, including $134,000 for the land. the amount of depreciation richard may claim in 2016 is

1tanner invested $135,000 cash along with office equipment valued at $32,400 in the company in exchange for common stock. 2 the company prepaid $7,200 cash for 12 months’ rent for office space. (hint: debit prepaid rent for $7,200.) 3 the company made credit purchases for $16,200 in office equipment and $3,240 in office supplies. payment is due within 10 days. 6 the company completed services for a client and immediately received $2,000 cash. 9 the company completed a $10,800 project for a client, who must pay within 30 days. 13 the company paid $19,440 cash to settle the account payable created on april 3. 19 the company paid $6,000 cash for the premium on a 12-month insurance policy. (hint: debit prepaid insurance for $6,000.) 22 the company received $8,640 cash as partial payment for the work completed on april 9. 25 the company completed work for another client for $2,640 on credit. 28 the company paid $6,200 cash in dividends. 29 the company purchased $1,080 of additional office supplies on credit. 30 the company paid $700 cash for this month’s utility bill. prepare general journal entries to record these transactions. 2. post the journal entries from part 1 to the ledger accounts.

In 2015, lori assigned a paid-up whole life insurance policy to an irrevocable life insurance trust (ilit) for the benefit of her three children. the ilit contained a crummey provision for the benefit of each child. at the time of the transfer, the whole life insurance policy was valued at $200,000, and since lori had not made any other taxable gifts during her lifetime, she did not owe any gift tax. lori died in 2016, and the face value of the whole life insurance policy of $2,000,000 was paid to the ilit. regarding this transfer, how much is included in lori’s gross estate at her death?

Asupermarket has been experiencing long lines during peak periods of the day. the problem is noticeably worse on certain days of the week, and the peak periods are sometimes different according to the day of the week. there are usually enough workers on the job to open all cash registers. the problem is knowing when to call some of the workers stocking shelves up to the front to work the checkout counters. how might decision models the supermarket? what data would be needed to develop these models?