iVOD / 160084

Field Value
IVOD_ID 160084
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/160084
日期 2025-04-10
會議資料.會議代碼 委員會-11-3-20-7
會議資料.會議代碼:str 第11屆第3會期財政委員會第7次全體委員會議
會議資料.屆 11
會議資料.會期 3
會議資料.會次 7
會議資料.種類 委員會
會議資料.委員會代碼[0] 20
會議資料.委員會代碼:str[0] 財政委員會
會議資料.標題 第11屆第3會期財政委員會第7次全體委員會議
影片種類 Clip
開始時間 2025-04-10T11:17:41+08:00
結束時間 2025-04-10T11:29:42+08:00
影片長度 00:12:01
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/127fafa562dc97122aaa0d9a87ccc9d939fb4699fde532611a30f584bceeba990b4769cd08d8a1da5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 李坤城
委員發言時間 11:17:41 - 11:29:42
會議時間 2025-04-10T09:00:00+08:00
會議名稱 立法院第11屆第3會期財政委員會第7次全體委員會議(事由:一、邀請中央銀行楊總裁金龍、金融監督管理委員會彭主任委員金隆、行政院主計總處陳主計長淑姿、財政部莊部長翠雲、經濟部郭部長智輝、農業部陳部長駿季就「川普對等關稅政策實施,對我國股匯市、經濟成長、物價、房市等項所造成之衝擊與因應措施」進行專題報告,並備質詢。 二、審查「納稅者權利保護法」4案: (一)本院委員賴士葆等22人擬具「納稅者權利保護法部分條文修正草案」案。 (二)本院委員羅廷瑋等18人擬具「納稅者權利保護法第四條條文修正草案」案。 (三)本院委員林思銘等20人擬具「納稅者權利保護法第七條及第二十一條條文修正草案」案。 (四)本院委員林思銘等18人擬具「納稅者權利保護法第二十一條條文修正草案」案。 三、審查「加值型及非加值型營業稅法」9案: (一) 本院委員鍾佳濱等18人、委員鍾佳濱等23人、委員郭國文等17人、委員吳沛憶等18人分別擬具「加值型及非加值型營業稅法部分條文修正草案」等4案。【本院委員吳沛憶等18人提案如經院會復議,則不予審查】 (二) 本院委員陳超明等18人、委員邱志偉等16人分別擬具「加值型及非加值型營業稅法第八條條文修正草案」等2案。 (三) 本院委員賴士葆等25人、委員顏寬恒等16人分別擬具「加值型及非加值型營業稅法第十三條條文修正草案」等2案。 (四) 本院委員賴士葆等22人擬具「加值型及非加值型營業稅法第五十八條條文修正草案」案。)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 5.39721875
transcript.pyannote[0].end 6.91596875
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 6.93284375
transcript.pyannote[1].end 9.58221875
transcript.pyannote[2].speaker SPEAKER_03
transcript.pyannote[2].start 9.78471875
transcript.pyannote[2].end 10.67909375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 18.20534375
transcript.pyannote[3].end 22.84596875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 19.30221875
transcript.pyannote[4].end 25.09034375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 25.44471875
transcript.pyannote[5].end 37.30784375
transcript.pyannote[6].speaker SPEAKER_03
transcript.pyannote[6].start 37.30784375
transcript.pyannote[6].end 37.62846875
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 37.62846875
transcript.pyannote[7].end 40.64909375
transcript.pyannote[8].speaker SPEAKER_03
transcript.pyannote[8].start 40.64909375
transcript.pyannote[8].end 40.66596875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 40.66596875
transcript.pyannote[9].end 46.31909375
transcript.pyannote[10].speaker SPEAKER_03
transcript.pyannote[10].start 40.76721875
transcript.pyannote[10].end 41.17221875
transcript.pyannote[11].speaker SPEAKER_03
transcript.pyannote[11].start 46.31909375
transcript.pyannote[11].end 46.45409375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 46.45409375
transcript.pyannote[12].end 66.60284375
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 46.47096875
transcript.pyannote[13].end 46.50471875
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 57.45659375
transcript.pyannote[14].end 57.47346875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 57.60846875
transcript.pyannote[15].end 57.70971875
transcript.pyannote[16].speaker SPEAKER_03
transcript.pyannote[16].start 63.71721875
transcript.pyannote[16].end 64.08846875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 66.82221875
transcript.pyannote[17].end 72.64409375
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 72.81284375
transcript.pyannote[18].end 73.20096875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 73.79159375
transcript.pyannote[19].end 77.68971875
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 77.94284375
transcript.pyannote[20].end 81.80721875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 82.02659375
transcript.pyannote[21].end 82.56659375
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 83.22471875
transcript.pyannote[22].end 99.34034375
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 87.51096875
transcript.pyannote[23].end 87.78096875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 95.71221875
transcript.pyannote[24].end 96.11721875
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 99.25596875
transcript.pyannote[25].end 101.21346875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 100.63971875
transcript.pyannote[26].end 114.91596875
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 102.58034375
transcript.pyannote[27].end 102.83346875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 108.45284375
transcript.pyannote[28].end 108.50346875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 113.02596875
transcript.pyannote[29].end 113.16096875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 114.91596875
transcript.pyannote[30].end 117.98721875
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 117.31221875
transcript.pyannote[31].end 126.72846875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 118.15596875
transcript.pyannote[32].end 120.60284375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 127.30221875
transcript.pyannote[33].end 141.69659375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 141.69659375
transcript.pyannote[34].end 147.01221875
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 147.01221875
transcript.pyannote[35].end 169.16909375
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 150.60659375
transcript.pyannote[36].end 150.97784375
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 153.96471875
transcript.pyannote[37].end 154.03221875
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 154.03221875
transcript.pyannote[38].end 154.99409375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 155.41596875
transcript.pyannote[39].end 155.50034375
transcript.pyannote[40].speaker SPEAKER_03
transcript.pyannote[40].start 155.60159375
transcript.pyannote[40].end 155.71971875
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 161.38971875
transcript.pyannote[41].end 161.42346875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 161.42346875
transcript.pyannote[42].end 162.04784375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 164.95034375
transcript.pyannote[43].end 165.08534375
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 168.49409375
transcript.pyannote[44].end 172.22346875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 170.35034375
transcript.pyannote[45].end 170.53596875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 172.39221875
transcript.pyannote[46].end 180.96471875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 175.14284375
transcript.pyannote[47].end 175.48034375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 178.21409375
transcript.pyannote[48].end 178.23096875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 178.56846875
transcript.pyannote[49].end 178.58534375
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 181.23471875
transcript.pyannote[50].end 183.34409375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 181.58909375
transcript.pyannote[51].end 182.12909375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 183.20909375
transcript.pyannote[52].end 197.85659375
transcript.pyannote[53].speaker SPEAKER_03
transcript.pyannote[53].start 185.40284375
transcript.pyannote[53].end 185.41971875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 185.41971875
transcript.pyannote[54].end 185.47034375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 185.55471875
transcript.pyannote[55].end 185.58846875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 198.17721875
transcript.pyannote[56].end 204.77534375
transcript.pyannote[57].speaker SPEAKER_03
transcript.pyannote[57].start 199.42596875
transcript.pyannote[57].end 199.51034375
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 204.77534375
transcript.pyannote[58].end 204.91034375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 204.91034375
transcript.pyannote[59].end 217.31346875
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 204.92721875
transcript.pyannote[60].end 205.04534375
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 217.31346875
transcript.pyannote[61].end 224.80596875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 223.30409375
transcript.pyannote[62].end 248.00909375
transcript.pyannote[63].speaker SPEAKER_03
transcript.pyannote[63].start 245.68034375
transcript.pyannote[63].end 246.03471875
transcript.pyannote[64].speaker SPEAKER_03
transcript.pyannote[64].start 248.00909375
transcript.pyannote[64].end 248.22846875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 248.22846875
transcript.pyannote[65].end 254.38784375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 253.72971875
transcript.pyannote[66].end 253.84784375
transcript.pyannote[67].speaker SPEAKER_03
transcript.pyannote[67].start 253.84784375
transcript.pyannote[67].end 253.89846875
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 254.38784375
transcript.pyannote[68].end 254.77596875
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 254.77596875
transcript.pyannote[69].end 257.62784375
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 254.80971875
transcript.pyannote[70].end 254.97846875
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 257.62784375
transcript.pyannote[71].end 257.64471875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 257.71221875
transcript.pyannote[72].end 259.82159375
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 259.92284375
transcript.pyannote[73].end 263.14596875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 263.14596875
transcript.pyannote[74].end 288.45846875
transcript.pyannote[75].speaker SPEAKER_03
transcript.pyannote[75].start 272.35971875
transcript.pyannote[75].end 272.39346875
transcript.pyannote[76].speaker SPEAKER_03
transcript.pyannote[76].start 272.41034375
transcript.pyannote[76].end 272.42721875
transcript.pyannote[77].speaker SPEAKER_03
transcript.pyannote[77].start 280.20659375
transcript.pyannote[77].end 280.22346875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 280.22346875
transcript.pyannote[78].end 281.77596875
transcript.pyannote[79].speaker SPEAKER_03
transcript.pyannote[79].start 287.07471875
transcript.pyannote[79].end 288.76221875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 288.71159375
transcript.pyannote[80].end 324.03096875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 303.62909375
transcript.pyannote[81].end 308.87721875
transcript.pyannote[82].speaker SPEAKER_03
transcript.pyannote[82].start 322.00596875
transcript.pyannote[82].end 322.44471875
transcript.pyannote[83].speaker SPEAKER_03
transcript.pyannote[83].start 324.03096875
transcript.pyannote[83].end 324.57096875
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 324.41909375
transcript.pyannote[84].end 342.71159375
transcript.pyannote[85].speaker SPEAKER_03
transcript.pyannote[85].start 325.11096875
transcript.pyannote[85].end 325.26284375
transcript.pyannote[86].speaker SPEAKER_03
transcript.pyannote[86].start 336.01221875
transcript.pyannote[86].end 336.13034375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 336.13034375
transcript.pyannote[87].end 336.16409375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 342.94784375
transcript.pyannote[88].end 345.96846875
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 345.96846875
transcript.pyannote[89].end 346.37346875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 346.49159375
transcript.pyannote[90].end 357.91596875
transcript.pyannote[91].speaker SPEAKER_03
transcript.pyannote[91].start 351.82409375
transcript.pyannote[91].end 352.34721875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 358.13534375
transcript.pyannote[92].end 361.81409375
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 361.81409375
transcript.pyannote[93].end 377.03534375
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 376.00596875
transcript.pyannote[94].end 380.64659375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 377.25471875
transcript.pyannote[95].end 407.42721875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 383.00909375
transcript.pyannote[96].end 383.19471875
transcript.pyannote[97].speaker SPEAKER_03
transcript.pyannote[97].start 407.37659375
transcript.pyannote[97].end 407.79846875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 407.79846875
transcript.pyannote[98].end 417.60284375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 417.60284375
transcript.pyannote[99].end 422.69909375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 423.13784375
transcript.pyannote[100].end 437.70096875
transcript.pyannote[101].speaker SPEAKER_03
transcript.pyannote[101].start 432.08159375
transcript.pyannote[101].end 432.40221875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 436.82346875
transcript.pyannote[102].end 439.00034375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 439.00034375
transcript.pyannote[103].end 440.01284375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 440.01284375
transcript.pyannote[104].end 449.34471875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 449.66534375
transcript.pyannote[105].end 449.80034375
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 449.80034375
transcript.pyannote[106].end 449.95221875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 449.95221875
transcript.pyannote[107].end 450.01971875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 450.01971875
transcript.pyannote[108].end 454.27221875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 454.55909375
transcript.pyannote[109].end 458.76096875
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 458.49096875
transcript.pyannote[110].end 469.35846875
transcript.pyannote[111].speaker SPEAKER_03
transcript.pyannote[111].start 467.87346875
transcript.pyannote[111].end 469.32471875
transcript.pyannote[112].speaker SPEAKER_03
transcript.pyannote[112].start 469.35846875
transcript.pyannote[112].end 469.39221875
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 469.39221875
transcript.pyannote[113].end 469.40909375
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 469.64534375
transcript.pyannote[114].end 477.44159375
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 474.92721875
transcript.pyannote[115].end 474.94409375
transcript.pyannote[116].speaker SPEAKER_03
transcript.pyannote[116].start 474.94409375
transcript.pyannote[116].end 475.16346875
transcript.pyannote[117].speaker SPEAKER_03
transcript.pyannote[117].start 477.44159375
transcript.pyannote[117].end 477.91409375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 477.91409375
transcript.pyannote[118].end 489.30471875
transcript.pyannote[119].speaker SPEAKER_03
transcript.pyannote[119].start 489.30471875
transcript.pyannote[119].end 489.43971875
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 489.43971875
transcript.pyannote[120].end 493.57409375
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 493.57409375
transcript.pyannote[121].end 494.01284375
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 493.94534375
transcript.pyannote[122].end 505.52159375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 505.89284375
transcript.pyannote[123].end 508.96409375
transcript.pyannote[124].speaker SPEAKER_03
transcript.pyannote[124].start 508.96409375
transcript.pyannote[124].end 509.41971875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 509.41971875
transcript.pyannote[125].end 517.11471875
transcript.pyannote[126].speaker SPEAKER_03
transcript.pyannote[126].start 517.11471875
transcript.pyannote[126].end 517.41846875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 517.70534375
transcript.pyannote[127].end 526.17659375
transcript.pyannote[128].speaker SPEAKER_03
transcript.pyannote[128].start 526.17659375
transcript.pyannote[128].end 526.29471875
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 526.29471875
transcript.pyannote[129].end 532.43721875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 532.58909375
transcript.pyannote[130].end 534.02346875
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 534.02346875
transcript.pyannote[131].end 534.10784375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 534.10784375
transcript.pyannote[132].end 534.90096875
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 534.90096875
transcript.pyannote[133].end 549.76784375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 540.13221875
transcript.pyannote[134].end 540.14909375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 540.25034375
transcript.pyannote[135].end 542.84909375
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 544.23284375
transcript.pyannote[136].end 551.18534375
transcript.pyannote[137].speaker SPEAKER_03
transcript.pyannote[137].start 551.18534375
transcript.pyannote[137].end 551.53971875
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 551.20221875
transcript.pyannote[138].end 551.25284375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 551.53971875
transcript.pyannote[139].end 556.61909375
transcript.pyannote[140].speaker SPEAKER_03
transcript.pyannote[140].start 556.83846875
transcript.pyannote[140].end 557.09159375
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 557.34471875
transcript.pyannote[141].end 559.87596875
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 558.37409375
transcript.pyannote[142].end 558.57659375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 560.17971875
transcript.pyannote[143].end 562.87971875
transcript.pyannote[144].speaker SPEAKER_01
transcript.pyannote[144].start 562.30596875
transcript.pyannote[144].end 571.03034375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 571.03034375
transcript.pyannote[145].end 573.71346875
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 571.95846875
transcript.pyannote[146].end 572.46471875
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 573.59534375
transcript.pyannote[147].end 577.84784375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 575.67096875
transcript.pyannote[148].end 575.99159375
transcript.pyannote[149].speaker SPEAKER_03
transcript.pyannote[149].start 577.99971875
transcript.pyannote[149].end 578.01659375
transcript.pyannote[150].speaker SPEAKER_02
transcript.pyannote[150].start 578.01659375
transcript.pyannote[150].end 578.03346875
transcript.pyannote[151].speaker SPEAKER_03
transcript.pyannote[151].start 578.03346875
transcript.pyannote[151].end 578.21909375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 578.21909375
transcript.pyannote[152].end 581.52659375
transcript.pyannote[153].speaker SPEAKER_03
transcript.pyannote[153].start 578.25284375
transcript.pyannote[153].end 578.28659375
transcript.pyannote[154].speaker SPEAKER_03
transcript.pyannote[154].start 581.47596875
transcript.pyannote[154].end 581.64471875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 581.64471875
transcript.pyannote[155].end 583.66971875
transcript.pyannote[156].speaker SPEAKER_03
transcript.pyannote[156].start 583.58534375
transcript.pyannote[156].end 584.17596875
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 583.93971875
transcript.pyannote[157].end 588.76596875
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 589.00221875
transcript.pyannote[158].end 589.76159375
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 589.06971875
transcript.pyannote[159].end 592.24221875
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 592.24221875
transcript.pyannote[160].end 592.25909375
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 592.34346875
transcript.pyannote[161].end 598.38471875
transcript.pyannote[162].speaker SPEAKER_03
transcript.pyannote[162].start 598.19909375
transcript.pyannote[162].end 598.57034375
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 598.46909375
transcript.pyannote[163].end 598.55346875
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 598.57034375
transcript.pyannote[164].end 602.09721875
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 602.35034375
transcript.pyannote[165].end 606.53534375
transcript.pyannote[166].speaker SPEAKER_03
transcript.pyannote[166].start 606.53534375
transcript.pyannote[166].end 607.24409375
transcript.pyannote[167].speaker SPEAKER_01
transcript.pyannote[167].start 607.24409375
transcript.pyannote[167].end 611.46284375
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 611.47971875
transcript.pyannote[168].end 611.51346875
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 611.51346875
transcript.pyannote[169].end 616.69409375
transcript.pyannote[170].speaker SPEAKER_02
transcript.pyannote[170].start 619.36034375
transcript.pyannote[170].end 620.32221875
transcript.pyannote[171].speaker SPEAKER_02
transcript.pyannote[171].start 620.57534375
transcript.pyannote[171].end 621.53721875
transcript.pyannote[172].speaker SPEAKER_02
transcript.pyannote[172].start 622.07721875
transcript.pyannote[172].end 622.70159375
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 622.97159375
transcript.pyannote[173].end 625.78971875
transcript.pyannote[174].speaker SPEAKER_04
transcript.pyannote[174].start 624.20346875
transcript.pyannote[174].end 625.01346875
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 625.92471875
transcript.pyannote[175].end 639.64409375
transcript.pyannote[176].speaker SPEAKER_04
transcript.pyannote[176].start 640.80846875
transcript.pyannote[176].end 665.85096875
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 646.46159375
transcript.pyannote[177].end 647.77784375
transcript.pyannote[178].speaker SPEAKER_00
transcript.pyannote[178].start 652.67159375
transcript.pyannote[178].end 652.72221875
transcript.pyannote[179].speaker SPEAKER_02
transcript.pyannote[179].start 664.87221875
transcript.pyannote[179].end 665.10846875
transcript.pyannote[180].speaker SPEAKER_02
transcript.pyannote[180].start 665.85096875
transcript.pyannote[180].end 671.95971875
transcript.pyannote[181].speaker SPEAKER_04
transcript.pyannote[181].start 666.34034375
transcript.pyannote[181].end 666.37409375
transcript.pyannote[182].speaker SPEAKER_04
transcript.pyannote[182].start 671.18346875
transcript.pyannote[182].end 677.56221875
transcript.pyannote[183].speaker SPEAKER_00
transcript.pyannote[183].start 677.29221875
transcript.pyannote[183].end 677.30909375
transcript.pyannote[184].speaker SPEAKER_02
transcript.pyannote[184].start 677.30909375
transcript.pyannote[184].end 678.03471875
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 678.03471875
transcript.pyannote[185].end 678.87846875
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 678.72659375
transcript.pyannote[186].end 678.76034375
transcript.pyannote[187].speaker SPEAKER_04
transcript.pyannote[187].start 678.76034375
transcript.pyannote[187].end 682.32096875
transcript.pyannote[188].speaker SPEAKER_00
transcript.pyannote[188].start 681.20721875
transcript.pyannote[188].end 681.69659375
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 682.35471875
transcript.pyannote[189].end 694.99409375
transcript.pyannote[190].speaker SPEAKER_03
transcript.pyannote[190].start 694.99409375
transcript.pyannote[190].end 695.36534375
transcript.pyannote[191].speaker SPEAKER_00
transcript.pyannote[191].start 695.26409375
transcript.pyannote[191].end 709.82721875
transcript.pyannote[192].speaker SPEAKER_02
transcript.pyannote[192].start 709.82721875
transcript.pyannote[192].end 711.46409375
transcript.pyannote[193].speaker SPEAKER_00
transcript.pyannote[193].start 709.87784375
transcript.pyannote[193].end 710.41784375
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 711.81846875
transcript.pyannote[194].end 718.11284375
transcript.pyannote[195].speaker SPEAKER_04
transcript.pyannote[195].start 715.09221875
transcript.pyannote[195].end 715.76721875
transcript.pyannote[196].speaker SPEAKER_04
transcript.pyannote[196].start 717.53909375
transcript.pyannote[196].end 719.31096875
transcript.pyannote[197].speaker SPEAKER_02
transcript.pyannote[197].start 719.31096875
transcript.pyannote[197].end 719.47971875
transcript.pyannote[198].speaker SPEAKER_04
transcript.pyannote[198].start 719.47971875
transcript.pyannote[198].end 721.15034375
transcript.whisperx[0].start 5.384
transcript.whisperx[0].end 10.24
transcript.whisperx[0].text 好 謝謝主席我們請這個央行 央總裁央總裁請
transcript.whisperx[1].start 18.44
transcript.whisperx[1].end 45.436
transcript.whisperx[1].text 李委員早部長好辛苦了我還記得我們在3月27號的時候還有這個針對所謂的什麼川普政府對等關稅策略與我國被列入骯髒15國名單有來做一個專案報告結果發現不是骯髒15國一公佈的時候發現全世界都有不過我看了一下當時候的這個央行的這個報告
transcript.whisperx[2].start 47.417
transcript.whisperx[2].end 69.375
transcript.whisperx[2].text 其實你們那時候說到說台灣跟美國的關稅的差距啦這個如果按照這一個貿易加權平均的關稅來計算的話台灣是1.7%美國是2.2%其實台灣還低於美國0.5個百分點那如果按照簡單平均的關稅來算一算台灣呢是6.5那高於美國的這個3.2%多了3.3%
transcript.whisperx[3].start 73.998
transcript.whisperx[3].end 97.67
transcript.whisperx[3].text 就是說從當時候三月底的這一個報告來看的話總裁有想到說最後川普的算法是這樣子的嗎沒有因為我認為我當時我們的推論是說第一個我對等你講對等關稅因為對等我們加權平均都比你低當然雖然就是說簡單平均我們比他高沒有錯而且主要的就是來農產品
transcript.whisperx[4].start 99.391
transcript.whisperx[4].end 126.292
transcript.whisperx[4].text 但是也就是3.3而已啊對嘛 那這是第一點第二點呢 我們也認為就是說事實上呢台灣最近幾年對你的粗糙呢這些的產品都是你最需要的而且對你很有貢獻的對你的經濟發展很有貢獻所以那時候你是說其實是產業的互補對 是互補啊不是不公平貿易嘛我們的這些產品包括SERVER這些AI SERVER這些對它的那個生產力的提升
transcript.whisperx[5].start 127.546
transcript.whisperx[5].end 146.805
transcript.whisperx[5].text 還有就是對他國防安全航太領域這些都有貢獻的所以我們才會覺得就是說應該不至於對我們台灣的這個對等關稅會扣那麼高所以那時候一個最壞的這個預想的一個策略會被課到多少那時候
transcript.whisperx[6].start 147.105
transcript.whisperx[6].end 163.95
transcript.whisperx[6].text 那時候他也有提到基本是10%那時候頂多我們也是想大概是10%那你現在就是說他是用那個公式是非常不合理的就是說用第一個他是用你對他的逆差第二個除上你對他的一個出口所以這個方案是你們從來沒有想過沒有想到
transcript.whisperx[7].start 172.432
transcript.whisperx[7].end 197.543
transcript.whisperx[7].text 那現在又從32%又降到10%了又回到這個基礎關稅來了那總裁想說這中間的轉折是怎麼樣這美國自己也受不了了嗎我也覺得是這樣子因為剛剛我也在講就是說第一個他也沒有想到就是說他的這個對等關稅一公佈了之後呢事實上最先反映的是他本國的
transcript.whisperx[8].start 198.263
transcript.whisperx[8].end 214.538
transcript.whisperx[8].text 他的股市整個股市你看跌的那麼多那其他的國家的股市呢也就隨著多跌所以呢而且連續的他如果說不做這樣的一個踩煞車的時候呢就是說有這三個月的一個緩衝期的話那這樣的話呢股市下去的話是會崩盤的所以總裁認為說川普的轉折是跟自己國內的這一個股市
transcript.whisperx[9].start 224.907
transcript.whisperx[9].end 244.897
transcript.whisperx[9].text 還有剛剛也有委員談到就是說他的公債的利率這樣彈升上來他也會有一點怕為什麼呢美國財政部特別是美國財政部他都希望他的長期的公債的殖利率能夠下來那沒有想到就是說他下來到3.9幾的時候最近又爬到4.33所以他也太緊張了
transcript.whisperx[10].start 248.399
transcript.whisperx[10].end 250.702
transcript.whisperx[10].text 所以我是覺得4.33對美國財政部的財政負擔是蠻大的所以我覺得這就是一個轉折點無論如何也爭取到三個月時間了那三個月時間總裁有什麼樣的建議嗎
transcript.whisperx[11].start 263.356
transcript.whisperx[11].end 273.845
transcript.whisperx[11].text 所以我總覺得我剛剛也是在講就是說三個月的時間當然大家就整個市場就說鬆了一口氣鬆了一口氣你看看美國的股市都是每個都上漲
transcript.whisperx[12].start 280.59
transcript.whisperx[12].end 296.125
transcript.whisperx[12].text 他的reaction就是利多嘛包括我相信亞洲的大概也是台灣的也是嘛不過呢我剛剛也在講就是說事實上呢因為三個月只是這個時間而已三個月時間如果說大家要來談判的話三個月是足夠長
transcript.whisperx[13].start 299.688
transcript.whisperx[13].end 323.807
transcript.whisperx[13].text 可以讓他美國跟這些國家來談就台灣來講總裁也是很好啊但是問題還是有什麼優先來做的但是問題就是說這個三個月也是很長的三個月很長的話整個的金融市場還是因為他的uncertainty他的不確定性還是依然存在因為不曉得他的 outcome 是什麼
transcript.whisperx[14].start 325.188
transcript.whisperx[14].end 345.539
transcript.whisperx[14].text 所以也就是說在這段期間股市還有包括其他匯市債市也都是一樣的它還是會上上下下上上下下而且波動度也應該從上一次的波動非常大的之後它可能會減少波動但是它的波動度還是會大的好
transcript.whisperx[15].start 347.04
transcript.whisperx[15].end 374.043
transcript.whisperx[15].text 那我請教一下那這樣子對於台灣的經濟的成長率會不會有影響本來預估是大概是3.14那現在就是說會受到影響有可能最差會到1.4%那好一點的話2.6%那總裁這邊的想法咧我覺得所以也就是說在這一次的評估裡面我們就沒有把我們的評估把它揭露出來為什麼因為我們總覺得這是一個uncertainty
transcript.whisperx[16].start 374.743
transcript.whisperx[16].end 379.605
transcript.whisperx[16].text 但是總是有影響嘛所以我們才扣的這些投資因因為到目前為止IMF跟那個BIS還有就是ADB這些OECD都還沒有來估測說對整個全球經濟的影響是怎麼樣對個別國家的影響是怎麼樣到目前他們還沒有
transcript.whisperx[17].start 397.072
transcript.whisperx[17].end 422.367
transcript.whisperx[17].text 但是呢投資銀行他就有一些的評估所以我們就引用了這個評估但是呢我們有一個但書我們說這都是參考參考因為到目前為止呢整個的情勢都還沒有非常的明朗所以我們現在做這樣的一個評估的時候有些時候呢會嚇到自己那如果就是說最後如果是10%的關稅好了那總裁認為說寶山有可能嗎
transcript.whisperx[18].start 423.631
transcript.whisperx[18].end 448.882
transcript.whisperx[18].text 這個我們必須要再做評估我也沒辦法說在這裡就馬上跟委員說就可以保持這個3%的經濟成長力到目前為止我覺得我們必須要總裁認為不確定性太高了對對對對那請教一下這個關稅對等關稅它裡面除了貿易逆差之外它有提到說這個所謂的匯率的操縱
transcript.whisperx[19].start 451.263
transcript.whisperx[19].end 467.57
transcript.whisperx[19].text 匯率的操縱我跟委員報告一下匯率的操縱這個我看指標上面其實是有達到它的這個對 這個就是說匯率的這個問題基本上它當然它有說這個可能會涉及到它的逆差跟匯率有一些的關聯對啊 有出超碼
transcript.whisperx[20].start 469.731
transcript.whisperx[20].end 493.34
transcript.whisperx[20].text 但是我認為事實上匯率的這個部分是美國財政部的主權所以我上一次的報告裡面我也提到就是說美國財政部在4月是因為那時候一般來講他都會在4月中會提出他的匯率報告那他的匯率報告他就會提出他的看法
transcript.whisperx[21].start 494.781
transcript.whisperx[21].end 512.867
transcript.whisperx[21].text 他的看法所以呢我現在呢要跟委員報告的就是說事實上呢關稅關稅的這個議題呢是美國政府美國的總統有這個緊急的緊急的那個發布命令的那個權限但是呢財政部的這個會議報告他的會議報告我跟委員報告他的會議報告是國會通過的
transcript.whisperx[22].start 517.788
transcript.whisperx[22].end 521.612
transcript.whisperx[22].text 他的匯率報告是國會通過的他是1988年綜合貿易及競爭力法案還有2015年貿易變節化及貿易執行法案這個都是國會通過的
transcript.whisperx[23].start 532.705
transcript.whisperx[23].end 555.454
transcript.whisperx[23].text 他國會通過的他有一定的標準總裁我是說如果按照這一個美國財政部的標準來講的話其實我們有兩個指標包含這一個對美國貿易的粗糙經常這樣的順差其實都有達到那我是說這方面的話會不會被美國我們匯率沒有啊我們匯率我們還是賣啊我們還是在賣啊他的第三個標準是說你要單邊的買
transcript.whisperx[24].start 557.535
transcript.whisperx[24].end 578.26
transcript.whisperx[24].text 我們沒有啊我們反而是在賣啊所以總裁認為說不會因為這樣子被美國如果說根據美國國會所通過的這個法案的三個標準按照道理我們是不會列在裡面的所以總裁認為說不會就對了我們是覺得是不會的但是呢現在就是說態度他
transcript.whisperx[25].start 579.16
transcript.whisperx[25].end 601.66
transcript.whisperx[25].text 現在就是說財政部長的態度還有就川普總統的態度因為這個匯率報告畢竟還是要通過川普總統的看過看起來美國財政部長是對這個關稅是踩煞車的啦我想就是說因為這個標準是國會通過的所以國會通過的話你不能就是說是
transcript.whisperx[26].start 602.581
transcript.whisperx[26].end 610.854
transcript.whisperx[26].text 是對國會的這三個標準做某些的扭曲這個是跟他的關稅是不大一樣的總裁請回最後一點時間我請財政部莊部長
transcript.whisperx[27].start 619.597
transcript.whisperx[27].end 626.28
transcript.whisperx[27].text 關於對等關稅 它裡面有提到台灣裡面有一些非關稅的障礙那我們的經貿談判辦公室有指出有七項非關稅的障礙那其中跟財政部有相關的要怎麼去做處理
transcript.whisperx[28].start 640.871
transcript.whisperx[28].end 647.735
transcript.whisperx[28].text 是,對於非關稅障礙這個部分,經貿辦公室都逐一在談對,那我說跟財政部那在財政部那個部分當然也有提到所謂的違規轉運,就是息產地的部分那那個部分我們海關跟我們的經濟部其實在從107年中美貿易戰以後已經建立起一個非常好的一個機制來做事前的預防、事中的管理及事後的嚴懲這個部分
transcript.whisperx[29].start 666.327
transcript.whisperx[29].end 687.668
transcript.whisperx[29].text 那我是說在對等關稅成立之後有沒有新的措施來做法因為你要因應新的情勢啊我們又在希望能夠再精進那海關這邊已經檢討以後就更精進的一些作為署長有要做補充的嗎那個關務署署長可以再說明那個精進的措施報告委員我簡短報告一下我們已經立即成立了一個強力查核小組在各關
transcript.whisperx[30].start 688.328
transcript.whisperx[30].end 703.294
transcript.whisperx[30].text 都要組這個強力者查核小組違規轉運那由官務長或副官務長要親自帶隊那頻率會非常高查核的頻率會非常高另外我們會建立一個專一的風險管理系統專門針對違規轉運來做精準的一個打擊因為洗產業這個是很嚴重啦為什麼像越南這些國家
transcript.whisperx[31].start 712.179
transcript.whisperx[31].end 717.611
transcript.whisperx[31].text 開始被課那麼多關稅就是它涉及席產地啦所以這方面我要盡量避免好不好好謝謝主席謝謝謝謝委員謝謝