IVOD_ID |
159380 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/159380 |
日期 |
2025-03-19 |
會議資料.會議代碼 |
委員會-11-3-19-3 |
會議資料.會議代碼:str |
第11屆第3會期經濟委員會第3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 |
3 |
會議資料.種類 |
委員會 |
會議資料.委員會代碼[0] |
19 |
會議資料.委員會代碼:str[0] |
經濟委員會 |
會議資料.標題 |
第11屆第3會期經濟委員會第3次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2025-03-19T11:42:19+08:00 |
結束時間 |
2025-03-19T11:51:16+08:00 |
影片長度 |
00:08:57 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/8d8da86eec6b25b87c1b5aa32a2c6a1bcea595bacfac0e479ba850061ce7750993c5041e5e26a2c65ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
賴瑞隆 |
委員發言時間 |
11:42:19 - 11:51:16 |
會議時間 |
2025-03-19T09:00:00+08:00 |
會議名稱 |
立法院第11屆第3會期經濟委員會第3次全體委員會議(事由:邀請國家發展委員會主任委員列席報告業務概況,並備質詢。【3月19日及20日二天一次會】) |
transcript.pyannote[0].speaker |
SPEAKER_01 |
transcript.pyannote[0].start |
1.70159375 |
transcript.pyannote[0].end |
3.27096875 |
transcript.pyannote[1].speaker |
SPEAKER_01 |
transcript.pyannote[1].start |
11.84346875 |
transcript.pyannote[1].end |
11.86034375 |
transcript.pyannote[2].speaker |
SPEAKER_00 |
transcript.pyannote[2].start |
11.86034375 |
transcript.pyannote[2].end |
12.13034375 |
transcript.pyannote[3].speaker |
SPEAKER_01 |
transcript.pyannote[3].start |
12.13034375 |
transcript.pyannote[3].end |
20.28096875 |
transcript.pyannote[4].speaker |
SPEAKER_00 |
transcript.pyannote[4].start |
12.14721875 |
transcript.pyannote[4].end |
12.51846875 |
transcript.pyannote[5].speaker |
SPEAKER_01 |
transcript.pyannote[5].start |
20.50034375 |
transcript.pyannote[5].end |
27.03096875 |
transcript.pyannote[6].speaker |
SPEAKER_00 |
transcript.pyannote[6].start |
27.03096875 |
transcript.pyannote[6].end |
55.76909375 |
transcript.pyannote[7].speaker |
SPEAKER_01 |
transcript.pyannote[7].start |
49.25534375 |
transcript.pyannote[7].end |
49.33971875 |
transcript.pyannote[8].speaker |
SPEAKER_01 |
transcript.pyannote[8].start |
49.52534375 |
transcript.pyannote[8].end |
49.55909375 |
transcript.pyannote[9].speaker |
SPEAKER_01 |
transcript.pyannote[9].start |
55.31346875 |
transcript.pyannote[9].end |
68.20596875 |
transcript.pyannote[10].speaker |
SPEAKER_00 |
transcript.pyannote[10].start |
68.20596875 |
transcript.pyannote[10].end |
68.52659375 |
transcript.pyannote[11].speaker |
SPEAKER_01 |
transcript.pyannote[11].start |
68.81346875 |
transcript.pyannote[11].end |
68.88096875 |
transcript.pyannote[12].speaker |
SPEAKER_00 |
transcript.pyannote[12].start |
68.88096875 |
transcript.pyannote[12].end |
95.91471875 |
transcript.pyannote[13].speaker |
SPEAKER_01 |
transcript.pyannote[13].start |
77.92596875 |
transcript.pyannote[13].end |
78.34784375 |
transcript.pyannote[14].speaker |
SPEAKER_01 |
transcript.pyannote[14].start |
95.91471875 |
transcript.pyannote[14].end |
97.02846875 |
transcript.pyannote[15].speaker |
SPEAKER_00 |
transcript.pyannote[15].start |
97.02846875 |
transcript.pyannote[15].end |
97.06221875 |
transcript.pyannote[16].speaker |
SPEAKER_01 |
transcript.pyannote[16].start |
97.06221875 |
transcript.pyannote[16].end |
97.14659375 |
transcript.pyannote[17].speaker |
SPEAKER_00 |
transcript.pyannote[17].start |
97.14659375 |
transcript.pyannote[17].end |
135.31784375 |
transcript.pyannote[18].speaker |
SPEAKER_01 |
transcript.pyannote[18].start |
97.16346875 |
transcript.pyannote[18].end |
97.97346875 |
transcript.pyannote[19].speaker |
SPEAKER_01 |
transcript.pyannote[19].start |
98.81721875 |
transcript.pyannote[19].end |
100.09971875 |
transcript.pyannote[20].speaker |
SPEAKER_01 |
transcript.pyannote[20].start |
101.09534375 |
transcript.pyannote[20].end |
102.25971875 |
transcript.pyannote[21].speaker |
SPEAKER_01 |
transcript.pyannote[21].start |
102.49596875 |
transcript.pyannote[21].end |
104.82471875 |
transcript.pyannote[22].speaker |
SPEAKER_01 |
transcript.pyannote[22].start |
107.33909375 |
transcript.pyannote[22].end |
107.64284375 |
transcript.pyannote[23].speaker |
SPEAKER_01 |
transcript.pyannote[23].start |
120.61971875 |
transcript.pyannote[23].end |
120.97409375 |
transcript.pyannote[24].speaker |
SPEAKER_01 |
transcript.pyannote[24].start |
122.54346875 |
transcript.pyannote[24].end |
123.25221875 |
transcript.pyannote[25].speaker |
SPEAKER_01 |
transcript.pyannote[25].start |
124.70346875 |
transcript.pyannote[25].end |
125.51346875 |
transcript.pyannote[26].speaker |
SPEAKER_01 |
transcript.pyannote[26].start |
126.54284375 |
transcript.pyannote[26].end |
126.99846875 |
transcript.pyannote[27].speaker |
SPEAKER_01 |
transcript.pyannote[27].start |
127.90971875 |
transcript.pyannote[27].end |
129.15846875 |
transcript.pyannote[28].speaker |
SPEAKER_00 |
transcript.pyannote[28].start |
135.65534375 |
transcript.pyannote[28].end |
144.68346875 |
transcript.pyannote[29].speaker |
SPEAKER_01 |
transcript.pyannote[29].start |
137.12346875 |
transcript.pyannote[29].end |
137.44409375 |
transcript.pyannote[30].speaker |
SPEAKER_00 |
transcript.pyannote[30].start |
145.18971875 |
transcript.pyannote[30].end |
150.97784375 |
transcript.pyannote[31].speaker |
SPEAKER_01 |
transcript.pyannote[31].start |
150.04971875 |
transcript.pyannote[31].end |
159.06096875 |
transcript.pyannote[32].speaker |
SPEAKER_00 |
transcript.pyannote[32].start |
154.04909375 |
transcript.pyannote[32].end |
156.61409375 |
transcript.pyannote[33].speaker |
SPEAKER_00 |
transcript.pyannote[33].start |
158.25096875 |
transcript.pyannote[33].end |
167.36346875 |
transcript.pyannote[34].speaker |
SPEAKER_01 |
transcript.pyannote[34].start |
159.97221875 |
transcript.pyannote[34].end |
160.25909375 |
transcript.pyannote[35].speaker |
SPEAKER_00 |
transcript.pyannote[35].start |
167.88659375 |
transcript.pyannote[35].end |
170.97471875 |
transcript.pyannote[36].speaker |
SPEAKER_01 |
transcript.pyannote[36].start |
170.97471875 |
transcript.pyannote[36].end |
171.02534375 |
transcript.pyannote[37].speaker |
SPEAKER_00 |
transcript.pyannote[37].start |
171.02534375 |
transcript.pyannote[37].end |
171.04221875 |
transcript.pyannote[38].speaker |
SPEAKER_01 |
transcript.pyannote[38].start |
171.04221875 |
transcript.pyannote[38].end |
177.11721875 |
transcript.pyannote[39].speaker |
SPEAKER_00 |
transcript.pyannote[39].start |
174.77159375 |
transcript.pyannote[39].end |
175.86846875 |
transcript.pyannote[40].speaker |
SPEAKER_00 |
transcript.pyannote[40].start |
176.59409375 |
transcript.pyannote[40].end |
178.39971875 |
transcript.pyannote[41].speaker |
SPEAKER_00 |
transcript.pyannote[41].start |
178.75409375 |
transcript.pyannote[41].end |
184.82909375 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
185.31846875 |
transcript.pyannote[42].end |
190.70159375 |
transcript.pyannote[43].speaker |
SPEAKER_01 |
transcript.pyannote[43].start |
186.02721875 |
transcript.pyannote[43].end |
186.55034375 |
transcript.pyannote[44].speaker |
SPEAKER_00 |
transcript.pyannote[44].start |
190.93784375 |
transcript.pyannote[44].end |
197.75534375 |
transcript.pyannote[45].speaker |
SPEAKER_01 |
transcript.pyannote[45].start |
197.67096875 |
transcript.pyannote[45].end |
205.77096875 |
transcript.pyannote[46].speaker |
SPEAKER_01 |
transcript.pyannote[46].start |
205.80471875 |
transcript.pyannote[46].end |
205.85534375 |
transcript.pyannote[47].speaker |
SPEAKER_00 |
transcript.pyannote[47].start |
205.85534375 |
transcript.pyannote[47].end |
206.76659375 |
transcript.pyannote[48].speaker |
SPEAKER_01 |
transcript.pyannote[48].start |
205.87221875 |
transcript.pyannote[48].end |
206.37846875 |
transcript.pyannote[49].speaker |
SPEAKER_00 |
transcript.pyannote[49].start |
207.45846875 |
transcript.pyannote[49].end |
209.11221875 |
transcript.pyannote[50].speaker |
SPEAKER_00 |
transcript.pyannote[50].start |
209.39909375 |
transcript.pyannote[50].end |
215.18721875 |
transcript.pyannote[51].speaker |
SPEAKER_00 |
transcript.pyannote[51].start |
215.45721875 |
transcript.pyannote[51].end |
224.16471875 |
transcript.pyannote[52].speaker |
SPEAKER_01 |
transcript.pyannote[52].start |
223.81034375 |
transcript.pyannote[52].end |
226.59471875 |
transcript.pyannote[53].speaker |
SPEAKER_00 |
transcript.pyannote[53].start |
225.00846875 |
transcript.pyannote[53].end |
225.05909375 |
transcript.pyannote[54].speaker |
SPEAKER_00 |
transcript.pyannote[54].start |
226.08846875 |
transcript.pyannote[54].end |
230.91471875 |
transcript.pyannote[55].speaker |
SPEAKER_01 |
transcript.pyannote[55].start |
227.70846875 |
transcript.pyannote[55].end |
228.72096875 |
transcript.pyannote[56].speaker |
SPEAKER_00 |
transcript.pyannote[56].start |
231.08346875 |
transcript.pyannote[56].end |
234.08721875 |
transcript.pyannote[57].speaker |
SPEAKER_01 |
transcript.pyannote[57].start |
231.13409375 |
transcript.pyannote[57].end |
232.33221875 |
transcript.pyannote[58].speaker |
SPEAKER_00 |
transcript.pyannote[58].start |
234.62721875 |
transcript.pyannote[58].end |
250.70909375 |
transcript.pyannote[59].speaker |
SPEAKER_01 |
transcript.pyannote[59].start |
237.42846875 |
transcript.pyannote[59].end |
238.17096875 |
transcript.pyannote[60].speaker |
SPEAKER_01 |
transcript.pyannote[60].start |
238.62659375 |
transcript.pyannote[60].end |
240.82034375 |
transcript.pyannote[61].speaker |
SPEAKER_00 |
transcript.pyannote[61].start |
251.13096875 |
transcript.pyannote[61].end |
255.50159375 |
transcript.pyannote[62].speaker |
SPEAKER_00 |
transcript.pyannote[62].start |
255.97409375 |
transcript.pyannote[62].end |
256.61534375 |
transcript.pyannote[63].speaker |
SPEAKER_00 |
transcript.pyannote[63].start |
257.29034375 |
transcript.pyannote[63].end |
270.84096875 |
transcript.pyannote[64].speaker |
SPEAKER_01 |
transcript.pyannote[64].start |
259.09596875 |
transcript.pyannote[64].end |
259.41659375 |
transcript.pyannote[65].speaker |
SPEAKER_01 |
transcript.pyannote[65].start |
269.28846875 |
transcript.pyannote[65].end |
269.60909375 |
transcript.pyannote[66].speaker |
SPEAKER_01 |
transcript.pyannote[66].start |
270.03096875 |
transcript.pyannote[66].end |
270.23346875 |
transcript.pyannote[67].speaker |
SPEAKER_01 |
transcript.pyannote[67].start |
270.41909375 |
transcript.pyannote[67].end |
270.82409375 |
transcript.pyannote[68].speaker |
SPEAKER_01 |
transcript.pyannote[68].start |
270.84096875 |
transcript.pyannote[68].end |
271.65096875 |
transcript.pyannote[69].speaker |
SPEAKER_00 |
transcript.pyannote[69].start |
271.65096875 |
transcript.pyannote[69].end |
272.30909375 |
transcript.pyannote[70].speaker |
SPEAKER_01 |
transcript.pyannote[70].start |
272.30909375 |
transcript.pyannote[70].end |
272.34284375 |
transcript.pyannote[71].speaker |
SPEAKER_00 |
transcript.pyannote[71].start |
272.34284375 |
transcript.pyannote[71].end |
272.62971875 |
transcript.pyannote[72].speaker |
SPEAKER_01 |
transcript.pyannote[72].start |
272.62971875 |
transcript.pyannote[72].end |
272.71409375 |
transcript.pyannote[73].speaker |
SPEAKER_00 |
transcript.pyannote[73].start |
272.71409375 |
transcript.pyannote[73].end |
272.86596875 |
transcript.pyannote[74].speaker |
SPEAKER_01 |
transcript.pyannote[74].start |
272.86596875 |
transcript.pyannote[74].end |
290.02784375 |
transcript.pyannote[75].speaker |
SPEAKER_01 |
transcript.pyannote[75].start |
290.58471875 |
transcript.pyannote[75].end |
291.02346875 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
291.02346875 |
transcript.pyannote[76].end |
296.01846875 |
transcript.pyannote[77].speaker |
SPEAKER_00 |
transcript.pyannote[77].start |
296.22096875 |
transcript.pyannote[77].end |
304.13534375 |
transcript.pyannote[78].speaker |
SPEAKER_01 |
transcript.pyannote[78].start |
300.65909375 |
transcript.pyannote[78].end |
301.11471875 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
304.47284375 |
transcript.pyannote[79].end |
316.13346875 |
transcript.pyannote[80].speaker |
SPEAKER_01 |
transcript.pyannote[80].start |
310.48034375 |
transcript.pyannote[80].end |
311.59409375 |
transcript.pyannote[81].speaker |
SPEAKER_00 |
transcript.pyannote[81].start |
316.36971875 |
transcript.pyannote[81].end |
326.02221875 |
transcript.pyannote[82].speaker |
SPEAKER_00 |
transcript.pyannote[82].start |
326.51159375 |
transcript.pyannote[82].end |
331.45596875 |
transcript.pyannote[83].speaker |
SPEAKER_01 |
transcript.pyannote[83].start |
326.66346875 |
transcript.pyannote[83].end |
326.96721875 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
331.99596875 |
transcript.pyannote[84].end |
340.29846875 |
transcript.pyannote[85].speaker |
SPEAKER_00 |
transcript.pyannote[85].start |
340.46721875 |
transcript.pyannote[85].end |
342.39096875 |
transcript.pyannote[86].speaker |
SPEAKER_01 |
transcript.pyannote[86].start |
342.23909375 |
transcript.pyannote[86].end |
344.39909375 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
343.31909375 |
transcript.pyannote[87].end |
349.61346875 |
transcript.pyannote[88].speaker |
SPEAKER_00 |
transcript.pyannote[88].start |
350.01846875 |
transcript.pyannote[88].end |
351.97596875 |
transcript.pyannote[89].speaker |
SPEAKER_01 |
transcript.pyannote[89].start |
351.97596875 |
transcript.pyannote[89].end |
365.03721875 |
transcript.pyannote[90].speaker |
SPEAKER_00 |
transcript.pyannote[90].start |
358.94534375 |
transcript.pyannote[90].end |
359.11409375 |
transcript.pyannote[91].speaker |
SPEAKER_00 |
transcript.pyannote[91].start |
360.16034375 |
transcript.pyannote[91].end |
360.53159375 |
transcript.pyannote[92].speaker |
SPEAKER_00 |
transcript.pyannote[92].start |
365.03721875 |
transcript.pyannote[92].end |
380.57909375 |
transcript.pyannote[93].speaker |
SPEAKER_00 |
transcript.pyannote[93].start |
380.69721875 |
transcript.pyannote[93].end |
384.05534375 |
transcript.pyannote[94].speaker |
SPEAKER_00 |
transcript.pyannote[94].start |
384.52784375 |
transcript.pyannote[94].end |
385.43909375 |
transcript.pyannote[95].speaker |
SPEAKER_01 |
transcript.pyannote[95].start |
385.43909375 |
transcript.pyannote[95].end |
394.53471875 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
387.54846875 |
transcript.pyannote[96].end |
389.05034375 |
transcript.pyannote[97].speaker |
SPEAKER_00 |
transcript.pyannote[97].start |
393.16784375 |
transcript.pyannote[97].end |
394.43346875 |
transcript.pyannote[98].speaker |
SPEAKER_00 |
transcript.pyannote[98].start |
394.53471875 |
transcript.pyannote[98].end |
395.07471875 |
transcript.pyannote[99].speaker |
SPEAKER_01 |
transcript.pyannote[99].start |
395.07471875 |
transcript.pyannote[99].end |
407.44409375 |
transcript.pyannote[100].speaker |
SPEAKER_00 |
transcript.pyannote[100].start |
407.44409375 |
transcript.pyannote[100].end |
407.76471875 |
transcript.pyannote[101].speaker |
SPEAKER_01 |
transcript.pyannote[101].start |
407.76471875 |
transcript.pyannote[101].end |
407.86596875 |
transcript.pyannote[102].speaker |
SPEAKER_00 |
transcript.pyannote[102].start |
407.86596875 |
transcript.pyannote[102].end |
414.49784375 |
transcript.pyannote[103].speaker |
SPEAKER_00 |
transcript.pyannote[103].start |
415.66221875 |
transcript.pyannote[103].end |
416.97846875 |
transcript.pyannote[104].speaker |
SPEAKER_01 |
transcript.pyannote[104].start |
416.97846875 |
transcript.pyannote[104].end |
423.82971875 |
transcript.pyannote[105].speaker |
SPEAKER_00 |
transcript.pyannote[105].start |
423.59346875 |
transcript.pyannote[105].end |
433.87034375 |
transcript.pyannote[106].speaker |
SPEAKER_01 |
transcript.pyannote[106].start |
433.87034375 |
transcript.pyannote[106].end |
433.90409375 |
transcript.pyannote[107].speaker |
SPEAKER_01 |
transcript.pyannote[107].start |
433.93784375 |
transcript.pyannote[107].end |
474.03284375 |
transcript.pyannote[108].speaker |
SPEAKER_00 |
transcript.pyannote[108].start |
434.14034375 |
transcript.pyannote[108].end |
434.76471875 |
transcript.pyannote[109].speaker |
SPEAKER_00 |
transcript.pyannote[109].start |
441.83534375 |
transcript.pyannote[109].end |
442.62846875 |
transcript.pyannote[110].speaker |
SPEAKER_00 |
transcript.pyannote[110].start |
474.03284375 |
transcript.pyannote[110].end |
474.20159375 |
transcript.pyannote[111].speaker |
SPEAKER_01 |
transcript.pyannote[111].start |
474.20159375 |
transcript.pyannote[111].end |
474.38721875 |
transcript.pyannote[112].speaker |
SPEAKER_00 |
transcript.pyannote[112].start |
474.38721875 |
transcript.pyannote[112].end |
474.40409375 |
transcript.pyannote[113].speaker |
SPEAKER_01 |
transcript.pyannote[113].start |
475.01159375 |
transcript.pyannote[113].end |
475.02846875 |
transcript.pyannote[114].speaker |
SPEAKER_00 |
transcript.pyannote[114].start |
475.02846875 |
transcript.pyannote[114].end |
484.56284375 |
transcript.pyannote[115].speaker |
SPEAKER_00 |
transcript.pyannote[115].start |
484.81596875 |
transcript.pyannote[115].end |
492.03846875 |
transcript.pyannote[116].speaker |
SPEAKER_00 |
transcript.pyannote[116].start |
492.46034375 |
transcript.pyannote[116].end |
494.97471875 |
transcript.pyannote[117].speaker |
SPEAKER_01 |
transcript.pyannote[117].start |
494.97471875 |
transcript.pyannote[117].end |
537.58409375 |
transcript.pyannote[118].speaker |
SPEAKER_00 |
transcript.pyannote[118].start |
500.13846875 |
transcript.pyannote[118].end |
500.62784375 |
transcript.pyannote[119].speaker |
SPEAKER_00 |
transcript.pyannote[119].start |
534.96846875 |
transcript.pyannote[119].end |
535.32284375 |
transcript.whisperx[0].start |
1.718 |
transcript.whisperx[0].end |
3.014 |
transcript.whisperx[0].text |
好,謝謝召委,請留之為 |
transcript.whisperx[1].start |
12.385 |
transcript.whisperx[1].end |
28.204 |
transcript.whisperx[1].text |
我先請教一下那個台灣的景氣的燈號從1月份出來看來是從紅燈降為這個紅藍紅黃燈號對那主要怎麼看接下來的整個景氣狀況今年台灣的景氣狀況這個紅黃代表我們在一個溫和的成長狀態 |
transcript.whisperx[2].start |
32.569 |
transcript.whisperx[2].end |
56.576 |
transcript.whisperx[2].text |
那我目前從AI的需求包括半導體先進半導體AI相關的訂單來看的話它還是會帶動我們的外銷持續成長那第二個部分是國內的投資我們今年預估會到5.7兆會上創歷史新高那最近其實我們也看到很多產業會有集單進來所以目前我還是比較樂觀看所以樂觀看待整個景氣的狀況 |
transcript.whisperx[3].start |
58.356 |
transcript.whisperx[3].end |
78.181 |
transcript.whisperx[3].text |
那我們也看到其實美國的財長他其實對於他們的整個景氣部分他擔心是疲軟甚至於民間部門是衰退的主委怎麼看待這個其實我們有在觀察舉個例子他一月份的民間的銷售指數他是衰退了0.4是這四年比較高的 |
transcript.whisperx[4].start |
80.382 |
transcript.whisperx[4].end |
94.209 |
transcript.whisperx[4].text |
那我們也在看他的領那個就業基金的就業基金的人數那的確有比較偏高我們其實有持續在在觀察但是他最近通膨是有一點下滑所以還呈現一個不是那麼明確的狀態 |
transcript.whisperx[5].start |
95.49 |
transcript.whisperx[5].end |
117.508 |
transcript.whisperx[5].text |
所以你認為還要再觀察他有好消息有壞消息剛剛你講的這些好消息前面兩個是不好的所以我們還在觀察那包括他的PPI指數那這個會不會對台灣產生相關的一些聯動美國是我們的主要出國之一所以值得我們好好的去看他的變化 |
transcript.whisperx[6].start |
117.608 |
transcript.whisperx[6].end |
142.396 |
transcript.whisperx[6].text |
所以主委怎麼看 審慎樂觀的看待這整個狀況目前還是審慎樂觀 但是我們還是要非常非常的小心因為政策 這個是一個很敏感的時候尤其是四月份 五月份會是一個我們很重要的觀察期四月份 五月份四月份會是一個很重要的觀察期因為四月份他會提出他們對於各國關稅的一個狀態 |
transcript.whisperx[7].start |
145.236 |
transcript.whisperx[7].end |
169.001 |
transcript.whisperx[7].text |
那當然他有講到是說投資的多關稅就會少但是我們還得看一下是就等於是川普政府他在於關稅上面他最後的政策對我們還是得看他最後的政策因為他跟各國談判的結果就處理了所以影響到整個景氣的方向因為我們難以預測現在各國都難以預測啦所以我們才會我會用兩個非常小心就是我們的確是非常在意這件事情 |
transcript.whisperx[8].start |
169.781 |
transcript.whisperx[8].end |
183.8 |
transcript.whisperx[8].text |
那另外今年的經濟成長率大概各機關都評估3%以上主委應該也是樂觀的看待3%以上因為目前有些是訂單的狀態的確我想魏哲嘉先生在跟總統的記者會上也講他訂單滿到 |
transcript.whisperx[9].start |
185.402 |
transcript.whisperx[9].end |
203.468 |
transcript.whisperx[9].text |
不能再滿,那的確也因為這樣還有新廠需求可以已經到這個程度那這個整體的發展看起來AI的變化還是持續往上走這個需求的變化還是很明確那今年的可能的這些的像川普的現象還有包括台灣內部的一些政治紛爭會不會影響到台灣經濟生產率的這個影響 |
transcript.whisperx[10].start |
207.526 |
transcript.whisperx[10].end |
228.481 |
transcript.whisperx[10].text |
有些會影響啦有些我舉個例子好了我們政府投資會有縮減的現象那大概會有0.08%你講的就是說我們被大量的刪減跟大量凍結這些狀況嗎對包括我們前瞻預算並沒有審核嘛那這個都會造成這個會影響到多少的經濟成長率大概0.08%它會有一點0.08%的影響那如果解凍不順利的話呢 |
transcript.whisperx[11].start |
234.705 |
transcript.whisperx[11].end |
256.076 |
transcript.whisperx[11].text |
解凍不順利我們可能要再算現在算的是解凍順利在上半年解凍是刪除的部分那另外就是0.08是刪除的部分另外還有一個就是川普上來之後全球在看他的政策都是會認為對GDP會有傷害就是傷害的大與小大概大家都有一個高中低的劇本那 |
transcript.whisperx[12].start |
257.352 |
transcript.whisperx[12].end |
282.545 |
transcript.whisperx[12].text |
的確GDP會有一點影響但是我們已經考慮了這幾個因素進來我們唯一沒有考慮到的是前瞻預算跟現有預算的三減的部分但是川普的部分我們在去年估的時候有估進來了所以還是要努力的守住3%以上對 我們會去努力守住好 那我再請教一下這個對於我們的我看到國發會有些也被刪包括被刪了2.2億甚至被動了30% 3.1億左右 |
transcript.whisperx[13].start |
285.947 |
transcript.whisperx[13].end |
313.822 |
transcript.whisperx[13].text |
這個對於我們的亞系計畫人才的計畫跟資安的計畫會不會產生影響這個預算三減多少會有影響那有幾個部分會影響比較大的還是第一個就是資訊的部分那個會影響到我們對資安跟政府公報那這個是影響比較大雖然金額金額是一千萬但是影響是比較大一點就是我們等於行政院公報會資安的部分行政院跟各單位跟包括團體 |
transcript.whisperx[14].start |
315.262 |
transcript.whisperx[14].end |
331.131 |
transcript.whisperx[14].text |
200多個單位的溝通會有一點目前是稍微是有影響這個對我們影響是比較大所以雖然看起來他是1000萬可能他影響會超過5400萬的地方那另外就是各單位的電費其實我們在去年提出預算的時候沒有考慮到10月的 |
transcript.whisperx[15].start |
332.051 |
transcript.whisperx[15].end |
344.965 |
transcript.whisperx[15].text |
10月份再漲價之後呢其實再減15%統三下來其實就我了解不只我們各部會大概電費都會出現很大的挑戰好 因為10月份我趕快進到下一個了那5400億400萬這塊也是影響比較大對我們這個產業發展 |
transcript.whisperx[16].start |
350.892 |
transcript.whisperx[16].end |
371.763 |
transcript.whisperx[16].text |
主委一起努力啦我們來努力來改變這個那接下來是因為時間很有限那個亞洲資產管理中心這個是總統的政見這個也大力在推動當中那高雄已經有成立了第一個金融專區主委有在協助跟掌握吧有的有的有的我們目前有16家業者已經簽了MOU跟政府這16家都會進駐嗎 |
transcript.whisperx[17].start |
372.864 |
transcript.whisperx[17].end |
381.572 |
transcript.whisperx[17].text |
他們都是表達高度的意願那同時我們現在在開放很多的銀行申請私人銀行業務那我們希望能擴大這個這個亞洲資產中心的 |
transcript.whisperx[18].start |
384.605 |
transcript.whisperx[18].end |
412.684 |
transcript.whisperx[18].text |
的一些量能對因為第一個點是在高雄來做轉區的對那雅灣4月份開始進駐那7月份要正式來起動了嘛謝謝委員幫忙沒有這個這要全力來出力那現在的部分它的範圍會不只在幾棟建築嘛我看了現在最新的規劃會在周邊的雅灣周邊都會做一些的區域都會做整個它會逐步擴大啦我們一開始先以操作為主OBU的操作那慢慢會再擴大業務量業務範圍 |
transcript.whisperx[19].start |
415.665 |
transcript.whisperx[19].end |
432.352 |
transcript.whisperx[19].text |
好那除了16家銀行以外我看有些的我們的公股的部分像其他的像台銀、土銀這些未來會有機會來加入嗎因為我們現在就我了解來申請這個私人銀行業務的銀行是有增加的趨勢那這些都有可能會應該都會下去 |
transcript.whisperx[20].start |
434.413 |
transcript.whisperx[20].end |
455.191 |
transcript.whisperx[20].text |
對我希望這不是只有金管會的事啦我希望也不是只有在我希望國發會用國家的整體高度這也是總統的政見所以這件事情也一定要成功的啦那特別是在現在的不管是國內資金或國際的一些資金我們希望他在爭取未來不管是新加坡甚至於香港甚至於日本的這些競爭上面 |
transcript.whisperx[21].start |
456.652 |
transcript.whisperx[21].end |
474.086 |
transcript.whisperx[21].text |
在台灣在高雄取得一定的一個優勢那這有很多的配套措施必須要一併來處理我希望國發會用你們的高度來協助好的那另外是我要請教的是裡面其實還有一個重要的是稅負優惠的部分這個部分諸位有什麼看法怎麼推動 |
transcript.whisperx[22].start |
475.647 |
transcript.whisperx[22].end |
491.488 |
transcript.whisperx[22].text |
稅賦的優惠的部分我們現在會協助這個金管會跟相關的部會去溝通稅賦的部分那包括這個是目前是比較重要那會對的部分也在溝通中那看起來也算是比較順利 |
transcript.whisperx[23].start |
492.549 |
transcript.whisperx[23].end |
509.518 |
transcript.whisperx[23].text |
那稅賦還要加把劍這幾樣都是重要的一個成功的那個不然為什麼人家要來到台灣來到高雄我希望在這一塊用這個國防會的高度去協助你也是政委我希望用這個高度去協助去做處理讓整個金管會讓各部會間整個動起來 |
transcript.whisperx[24].start |
512.239 |
transcript.whisperx[24].end |
536.609 |
transcript.whisperx[24].text |
因為我覺得有些體系上相對是比較保守一點的那如果國發會用國家發展的高度去處理而且這也是總統的政見落實政見也是國發會一個重要的工作沒錯沒錯所以我希望用這樣的高度去協調處理更大的一個開放更大的一個彈性讓整個這個金融產業在台灣能夠更蓬勃的發展好的好不好那請主委再大力來推動好謝謝委員好謝謝 |