57 73.8673 153.0439 -226.0932 373.8279

58 75.2471 161.9420 -242.1534 392.6475

59 70.0053 189.8525 -302.0987 442.1094

60 120.4639 214.1559 -299.2739 540.2017

61 184.8801 235.9693 -277.6112 647.3714

62 275.8466 255.9302 -225.7674 777.4606

掠食者预测值为：

Forecasts for variable y

Obs Forecast Std Error 95% Confidence Limits

49 32.7697 14.7279 3.9036 61.6358

50 40.1790 16.3381 8.1570 72.2011

51 42.3346 21.8052 -0.4028 85.0721

52 58.2993 25.9832 7.3732 109.2254

53 78.9707 29.5421 21.0692 136.8722

54 106.5963 32.7090 42.4879 170.7047

55 66.4836 35.5936 -3.2787 136.2458

56 41.9681 38.6392 -33.7634 117.6996

57 46.7548 41.4617 -34.5085 128.0182

58 39.7201 44.1038 -46.7218 126.1619

59 44.9342 46.5964 -46.3930 136.2614

60 45.3286 48.9622 -50.6356 141.2928

61 43.8411 56.4739 -66.8456 154.5279

62 58.1725 63.0975 -65.4964 181.8413

6.4 （1）进出口总额序列均不平稳，但对数变换后的一阶差分后序列平稳。所以对这两个序列取对数后进行单个序列拟合和协整检验。

（2）出口序列拟合的模型为ln ~(1,1,0)t x ARIMA ,具体口径为：

1ln =0.14689+1-0.38845t t x B

ε∇ 进口序列拟合的模型为ln ~(1,1,0)t y ARIMA ,具体口径为：

1ln =0.14672+

1-0.36364t t y B

ε∇ （3）ln t y 和ln t x 具有协整关系 （4）协整模型为：-1ln =0.99179ln +-0.69938t t t t y x εε

（5）误差修正模型为：-1ln =0.97861ln -0.22395ECM t t t y x ∇∇