利用Eviews对以下数据进行构建var模型，进行协整检验，格兰杰因果检验，单位根检验 利用Eviews对建立的VAR模型进行数据分析
\u8c01\u5e2e\u6211\u7528eviews\u5bf9\u4ee5\u4e0b\u6570\u636e\u505a\u4e0bADF\u68c0\u9a8c \u534f\u6574\u68c0\u9a8c\u548c\u683c\u5170\u6770\u56e0\u679c\u68c0\u9a8c\uff08\u4e00\uff09\u3001ADF\u662f\u5355\u4f4d\u6839\u68c0\u9a8c\uff0c\u7b2c\u4e00\u5217\u6570\u636ey\u505aADF\u68c0\u9a8c\uff0c\u7ed3\u679c\u5982\u4e0b
Null Hypothesis: Y has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.820038 0.0213
Test critical values: 1% level -4.098741
5% level -3.477275
10% level -3.166190
\u57281%\u6c34\u5e73\u4e0a\u62d2\u7edd\u539f\u5047\u8bbe\uff0c\u5e8f\u5217y\u5b58\u5728\u5355\u4f4d\u6839\uff0c\u4e3a\u4e0d\u5e73\u7a33\u5e8f\u5217\u3002\u4f46\u57285%\u300110%\u6c34\u5e73\u4e0a\u5747\u63a5\u53d7\u539f\u5047\u8bbe\uff0c\u8ba4\u4e3ay\u5e73\u7a33\u3002
\u5bf9y\u8fdb\u884c\u4e00\u9636\u5dee\u5206\uff0c\u5dee\u5206\u540e\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: Y has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -9.328245 0.0000
Test critical values: 1% level -2.599934
5% level -1.945745
10% level -1.613633
\u53ef\u89c1\uff0c\u5728\u5404\u6c34\u5e73\u4e0ay\u90fd\u662f\u5e73\u7a33\u7684\u3002\u56e0\u6b64\uff0c\u53ef\u4ee5\u628a\u539f\u5e8f\u5217y\u770b\u505a\u4e00\u9636\u5355\u6574\u3002
\u7b2c\u4e8c\u5217xADF\u68c0\u9a8c\u5982\u4e0b\uff1a
Null Hypothesis: X has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.216737 0.0898
Test critical values: 1% level -4.098741
5% level -3.477275
10% level -3.166190
\u57281%\u30015%\u6c34\u5e73\u4e0a\u62d2\u7edd\u539f\u5047\u8bbe\uff0c\u5e8f\u5217x\u5b58\u5728\u5355\u4f4d\u6839\uff0c\u4e3a\u4e0d\u5e73\u7a33\u5e8f\u5217\u3002\u4f46\u572810%\u6c34\u5e73\u4e0a\u5747\u63a5\u53d7\u539f\u5047\u8bbe\uff0c\u8ba4\u4e3ax\u662f\u5e73\u7a33\u7684\u3002
\u5bf9y\u8fdb\u884c\u4e00\u9636\u5dee\u5206\uff0c\u5dee\u5206\u540e\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: X has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -7.627041 0.0000
Test critical values: 1% level -2.599934
5% level -1.945745
10% level -1.613633
\u53ef\u89c1\uff0c\u5728\u5404\u6c34\u5e73\u4e0ax\u90fd\u662f\u5e73\u7a33\u7684\u3002\u56e0\u6b64\uff0c\u53ef\u4ee5\u628a\u539f\u5e8f\u5217x\u770b\u505a\u4e00\u9636\u5355\u6574\u3002
\uff08\u4e8c\uff09\u3001\u53ea\u6709\u4e00\u9636\u5355\u6574\u7684\u5e8f\u5217\u624d\u53ef\u4ee5\u8fdb\u884c\u534f\u6574\u68c0\u9a8c\uff1a
\u5229\u7528engle\u548cgranger\u63d0\u51fa\u7684\u4e24\u6b65\u68c0\u9a8c\u6cd5\uff1a
\u9996\u5148\u5efa\u7acb\u6a21\u578b\uff1ay=ax+c+e\uff0c\u7ed3\u679c\u4e3aY = 0.720902361403*X + 788.046309221
\u518d\u5bf9\u65b9\u7a0b\u7684\u6b8b\u5dee\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: E has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.093534 0.0001
Test critical values: 1% level -2.599413
5% level -1.945669
10% level -1.613677
\u4ece\u68c0\u9a8c\u7ed3\u679c\u53ef\u4ee5\u770b\u51fa\u6b8b\u5dee\u5e8f\u5217\u662f\u5e73\u7a33\u7684\uff0c\u56e0\u6b64x\u548cy\u4e4b\u95f4\u5b58\u5728\u534f\u6574\u5173\u7cfb\u3002
\uff08\u4e09\uff09\u3001granger\u56e0\u679c\u68c0\u9a8c\uff1a
Pairwise Granger Causality Tests
Date: 03/13/11 Time: 14:15
Sample: 1 69
Lags: 2
Null Hypothesis: Obs F-Statistic Prob.
Y does not Granger Cause X 67 1.11304 0.3350
X does not Granger Cause Y 5.72061 0.0052
\u4ece\u7ed3\u679c\u53ef\u77e5\u62d2\u7eddy\u4e0d\u80fdgranger x\u7684\u5047\u8bbe\uff0c\u5373y granger\u5f15\u8d77x\uff1b\u4f46\u662f\u4e0d\u80fd\u62d2\u7eddx\u4e0d\u80fdg\u5f15\u8d77y\uff0c\u5373\u63a5\u53d7x\u4e0d\u80fdgranger\u5f15\u8d77y\u3002
\u8fd9\u4e9b\u90fd\u662f\u53ef\u4ee5\u505a\u7684
\u6570\u636e\u4f60\u63d0\u4f9b\u7ed9\u6211\u554a
\u6211\u66ff\u522b\u4eba\u505a\u8fd9\u7c7b\u7684\u6570\u636e\u5206\u6790\u86ee\u591a\u7684
绛旓細1銆侀鍏堟墦寮EViews10杞欢锛屽湪棣栫晫闈細寮瑰嚭涓涓璇濇锛岀偣鍑汇怌reate a new EViews workfile銆戯紝鍒涘缓涓涓柊鐨勬枃浠躲2銆佺劧鍚庡湪寮瑰嚭鐨勭晫闈㈤噷锛岃緭鍏ュ紑濮嬫椂闂村拰缁撴潫鏃堕棿锛屽紑濮嬫椂闂磋緭鍏1979锛岀粨鏉熸椂闂磋緭鍏ヤ负1997锛屽叾浣欎繚鎸侀粯璁や笉鍙橈紝鐒跺悗鐐瑰嚮銆怬K銆戙3銆佺劧鍚庡彲浠ョ湅鍒板嚭鐜颁簡涓涓┖鐧界晫闈紝鐒跺悗鍦ㄥ懡浠よ緭鍏ユ閲屸...
绛旓細杩庢帴鏁版嵁鎺㈢储涔嬫梾锛侀鍏堬紝浣犻渶瑕佸湪Eviews鐨勮垶鍙颁笂锛鐢‥xcel鐨勬暟鎹枃浠舵潵鍚姩銆傚湪宸︿笂瑙掔殑銆愭枃浠躲戣彍鍗曚腑锛岃交杞讳竴鐐癸紝閫夋嫨銆愬鍏ユ暟鎹戦夐」锛屽儚瀵诲疂涓鏍锋壘鍒伴偅浠界簿蹇冨噯澶囩殑Excel鏂囦欢锛岀偣鍑汇愭墦寮銆戯紝鐒跺悗璺熼殢姝ラ杩涘叆涓嬩竴姝ャ傚畬鎴愭暟鎹姞杞藉悗锛屽埆鎬ワ紝鎴戜滑瑕佸紑濮嬫暟鎹垎鏋愩傚湪鍛戒护绐楀彛锛岄敭鍏ュ己澶х殑鍛戒护琛岋細鈥...
绛旓細銆傛鏃讹紝浣犲皢鐪嬪埌妯″瀷缁撴灉鐨勫彲瑙嗗寲鐣岄潰锛岃繖灏嗗府鍔╀綘鏇村ソ鍦拌В璇诲拰鐞嗚В鍥炲綊鍒嗘瀽鐨勭粨鏋溿傛瘡涓姝ラ兘绮惧績璁捐锛屾瘡涓涓搷浣滈兘鑷冲叧閲嶈锛岀‘淇濅綘鐨Eviews鍥炲綊鍒嗘瀽涓ヨ皑涓旈珮鏁堛傚笇鏈涜繖涓缁嗙殑姝ラ鎸囧崡鑳藉府浣犻『鍒杩涜鍥炲綊鍒嗘瀽锛岃鏁版嵁璇磋瘽锛屾彮绀洪殣钘忕殑妯″紡銆傜幇鍦紝浣犲凡缁忔帉鎻′簡鍩虹锛屽噯澶囧紑濮嬩綘鐨勬暟鎹帰绱箣鏃呭惂锛
绛旓細涓銆乂ar浼拌缁撴灉锛歠di瀵硅锤鏄撻暱鏈熷瓨鍦ㄨ礋鍚戝啿鍑,璐告槗瀵筬di瀛樺湪闀挎湡鐨勬鍚戝啿鍑汇備簩銆丣ohansen鍗忔暣妫楠岋細1.杩圭粺璁￠噺:娌℃湁鍗忔暣鍏崇郴;2.鏋佸ぇ鐗瑰緛鏍圭粺璁￠噺:娌℃湁鍗忔暣鍏崇郴銆備笁銆丄DF鍗曚綅鏍规楠岋細FDI涓庤锤鏄撻兘鏄2闃跺崟浣嶈繃绋嬨傚洓銆丟ranger鍥犳灉妫楠岋細璐告槗鏄痜di鐨凣ranger鍥 杞欢锛EViews5.0 ...
绛旓細1銆侀鍏堟墦寮EViews10杞欢锛屾柊寤轰竴涓獁orkfile锛岀劧鍚庡湪銆怱tart date銆戦噷杈撳叆銆1979銆戯紝鍦ㄣ怑nd date銆戦噷杈撳叆銆1997銆戯紝鍏朵綑淇濇寔榛樿鍗冲彲锛岀偣鍑汇怬K銆戯紝鍙互鐪嬪埌濡傚浘鎵绀虹殑鐣岄潰銆2銆佺劧鍚庡湪鍛戒护妗嗛噷杈撳叆鈥渄ata y x鈥濓紝鍐嶆寜鍥炶溅閿紝鍗冲彲鍦℅roup閲屾柊寤篩 X鍒椼3銆佺劧鍚庡鍒朵笅Excel閲岄潰鐨鏁版嵁锛岀洿鎺ョ矘璐村埌杞欢...
绛旓細1銆侀鍏鐢create鍛戒护寤虹珛workfile锛屽湪workfile structure type 涓夋嫨Dated- regular frequency 锛屽湪Frequency涓夋嫨Annual,鍦⊿tart date 鍜孍nd date 涓垎鍒緭鍏1980浠ュ強2009锛岀偣鍑婚敭鐩極K閿2銆佸湪涓荤獥鍙ｄ腑鐢ㄥ懡浠ata y x銆3銆佸皢鏁版嵁瀵煎叆Eviews涓锛宔xcel鐨勬暟鎹彲浠ョ洿鎺ュ鍒剁矘璐村埌group涓4銆佺敤鏈灏忎簩涔...
绛旓細浣跨敤Eviews杩涜骞崇ǔ鎬ф楠岀殑姝ラ锛1. 鍔犺浇鏁版嵁锛氭墦寮Eviews杞欢锛屽鍏ラ渶瑕佽繘琛屽钩绋虫ф楠岀殑鏃堕棿搴忓垪鏁版嵁銆2. 寤虹珛鏃堕棿搴忓垪鎴栨ā鍨嬶細鍦‥views涓紝鏍规嵁鏁版嵁鎬ц川寤虹珛鏃堕棿搴忓垪鎴栧洖褰掓ā鍨嬨3. 閫夋嫨妫楠屾柟娉曪細閫夋嫨骞崇ǔ鎬ф楠岀殑鏂规硶锛屽ADF妫楠屻4. 鎵ц妫楠屽苟鏌ョ湅缁撴灉锛氬湪Eviews鐨勫懡浠ょ獥鍙ｈ緭鍏ユ楠屽懡浠わ紝鎵ц妫楠屽悗...
绛旓細姒傚康锛欵views鏄疎conometrics Views鐨勭缉鍐欙紝鐩磋瘧涓鸿閲忕粡娴庡瑙傚療锛岄氬父绉颁负璁￠噺缁忔祹瀛﹁蒋浠跺寘銆傚畠鐨勬湰鎰忔槸瀵圭ぞ浼氱粡娴庡叧绯讳笌缁忔祹娲诲姩鐨勬暟閲忚寰嬶紝閲囩敤璁￠噺缁忔祹瀛︽柟娉曚笌鎶鏈杩涜鈥滆瀵熲濄傚彟澶朎views涔熸槸缇庡浗QMS鍏徃鐮斿埗鐨勫湪Windows涓嬩笓闂ㄤ粠浜鏁版嵁鍒嗘瀽銆佸洖褰掑垎鏋愬拰棰勬祴鐨勫伐鍏枫浣跨敤Eviews鍙互杩呴熷湴浠庢暟鎹腑瀵绘壘鍑...
绛旓細鍦ㄥ鍏鏁版嵁鏃讹紝璇锋敞鎰浠ヤ笅鍑犵偣锛氱‘淇濅綘鐨勬暟鎹槸鎸夋纭殑椤哄簭鎺掑垪鐨勩傜‘淇濅綘鐨勬暟鎹牸寮忎笌EViews鐨勬暟鎹牸寮忓尮閰嶃備緥濡傦紝EViews鐨勬暟鎹氬父浠ュ垪鐨勫舰寮忚〃绀猴紝鑰屼笉鏄銆傚鏋滀綘浠庡叾浠栬蒋浠讹紙濡侲xcel鎴朣PSS锛夊鍏ユ暟鎹紝鍙兘闇瑕佸厛杩涜涓浜涢澶勭悊姝ラ锛屽娓呯悊鏁版嵁鎴栬浆鎹㈡牸寮忋傚湪瀵煎叆澶у瀷鏁版嵁闆嗘椂锛屽彲鑳介渶瑕佽冭檻浣跨敤E...
绛旓細鍑忓幓鍧囨暟灏卞彲浠ュ幓涓績鍖
