{"pre_text": ["the goldman sachs group , inc .", "and subsidiaries management 2019s discussion and analysis in the table above , total aus net inflows/ ( outflows ) for 2017 included $ 23 billion of inflows ( $ 20 billion in long- term aus and $ 3 billion in liquidity products ) in connection with the acquisition of a portion of verus investors 2019 outsourced chief investment officer business ( verus acquisition ) and $ 5 billion of equity asset outflows in connection with the divestiture of our local australian- focused investment capabilities and fund platform ( australian divestiture ) .", "the table below presents average monthly assets under supervision by asset class .", "average for the year ended december $ in billions 2018 2017 2016 ."], "post_text": ["operating environment .", "during 2018 , our assets under supervision increased reflecting net inflows in liquidity products , fixed income assets and equity assets .", "this increase was partially offset by depreciation in our client assets , primarily in equity assets , as global equity prices generally decreased in 2018 , particularly towards the end of the year .", "the mix of our average assets under supervision between long-term assets under supervision and liquidity products during 2018 was essentially unchanged compared with 2017 .", "in the future , if asset prices continue to decline , or investors continue to favor assets that typically generate lower fees or investors withdraw their assets , net revenues in investment management would likely be negatively impacted .", "during 2017 , investment management operated in an environment characterized by generally higher asset prices , resulting in appreciation in both equity and fixed income assets .", "our long-term assets under supervision increased from net inflows primarily in fixed income and alternative investment assets .", "these increases were partially offset by net outflows in liquidity products .", "as a result , the mix of our average assets under supervision during 2017 shifted slightly from liquidity products to long-term assets under supervision compared to the mix at the end of 2016 .", "2018 versus 2017 .", "net revenues in investment management were $ 7.02 billion for 2018 , 13% ( 13 % ) higher than 2017 , primarily due to significantly higher incentive fees , as a result of harvesting .", "management and other fees were also higher , reflecting higher average assets under supervision and the impact of the recently adopted revenue recognition standard , partially offset by shifts in the mix of client assets and strategies .", "in addition , transaction revenues were higher .", "see note 3 to the consolidated financial statements for further information about asu no .", "2014-09 , 201crevenue from contracts with customers ( topic 606 ) . 201d during 2018 , total assets under supervision increased $ 48 billion to $ 1.54 trillion .", "long-term assets under supervision decreased $ 4 billion , including net market depreciation of $ 41 billion primarily in equity assets , largely offset by net inflows of $ 37 billion , primarily in fixed income and equity assets .", "liquidity products increased $ 52 billion .", "operating expenses were $ 5.27 billion for 2018 , 10% ( 10 % ) higher than 2017 , primarily due to the impact of the recently adopted revenue recognition standard and increased compensation and benefits expenses , reflecting higher net revenues .", "pre-tax earnings were $ 1.76 billion in 2018 , 24% ( 24 % ) higher than 2017 .", "see note 3 to the consolidated financial statements for further information about asu no .", "2014-09 , 201crevenue from contracts with customers ( topic 606 ) . 201d 2017 versus 2016 .", "net revenues in investment management were $ 6.22 billion for 2017 , 7% ( 7 % ) higher than 2016 , due to higher management and other fees , reflecting higher average assets under supervision , and higher transaction revenues .", "during 2017 , total assets under supervision increased $ 115 billion to $ 1.49 trillion .", "long-term assets under supervision increased $ 128 billion , including net market appreciation of $ 86 billion , primarily in equity and fixed income assets , and net inflows of $ 42 billion ( which includes $ 20 billion of inflows in connection with the verus acquisition and $ 5 billion of equity asset outflows in connection with the australian divestiture ) , primarily in fixed income and alternative investment assets .", "liquidity products decreased $ 13 billion ( which includes $ 3 billion of inflows in connection with the verus acquisition ) .", "operating expenses were $ 4.80 billion for 2017 , 3% ( 3 % ) higher than 2016 , primarily due to increased compensation and benefits expenses , reflecting higher net revenues .", "pre-tax earnings were $ 1.42 billion in 2017 , 25% ( 25 % ) higher than geographic data see note 25 to the consolidated financial statements for a summary of our total net revenues , pre-tax earnings and net earnings by geographic region .", "62 goldman sachs 2018 form 10-k ."], "table": [["$ in billions", "average for theyear ended december 2018", "average for theyear ended december 2017", "average for theyear ended december 2016"], ["alternative investments", "$ 171", "$ 162", "$ 149"], ["equity", "329", "292", "256"], ["fixed income", "665", "633", "578"], ["total long-term aus", "1165", "1087", "983"], ["liquidity products", "352", "330", "326"], ["total aus", "$ 1517", "$ 1417", "$ 1309"]], "table_ori": [["", "Average for theYear Ended December"], ["<i>$ in billions</i>", "2018", "2017", "2016"], ["Alternative investments", "$ 171", "$ 162", "$ 149"], ["Equity", "329", "292", "256"], ["Fixed income", "665", "633", "578"], ["Total long-term AUS", "1,165", "1,087", "983"], ["Liquidity products", "352", "330", "326"], ["Total AUS", "$1,517", "$1,417", "$1,309"]]}

Question: what are the pre-tax earnings in 2016 , in billions?
Evidence:
text_30: pre-tax earnings were $ 1.42 billion in 2017 , 25% ( 25 % ) higher than geographic data see note 25 to the consolidated financial statements for a summary of our total net revenues , pre-tax earnings and net earnings by geographic region .
Program: add(const_1, 25%), divide(1.42, #0)
Answer:
str_answer: 1.1
exe_answer: 1.136