19 Table 4: Change in Turnover in the WIR Exchange Network, as Explained by GDP, 1951-2003 † t-statistics in [ ]; P-Values in { };***: p-val < 0.01, ** : p-val < 0.05, *: p-val <0.10, ○: p-val <0.15 Dependent Variable: lnWirTurn Cointegrat. Eq: LnWirTurn(-1) LnGDP(-1) ‡
(A1) 1951-1972 N = 22
(A2) 1973-2003 N = 31
(B1) 1951-1972 N = 22
(B2) 1973-2003 N = 31
(C1) ‡ 1973-2003 N = 31
(C2) ‡ 1973-2003 N = 31
1.0000 -1.2139 [-3.368]***
1.0000 -4.2392 [-8.794]***
0.8129
17.7226
1.0000 -9.3769 [-2.142]* 0.3631 [1.846]* 37.8888
1.0000 7.2798 [1.779]* -0.1734 [-2.798]** -42.3819
1.0000 -5.466 [-3.629]*** 0.1915 [2.805]*** 19.8842
1.0000 17.3717 [2.983]*** -0.3225 [-3.662]*** -95.0266
TIME Trend Constant Indep. Variables: Cointegrating Eq D(LnWirTurn(-1)) D(LnWirTurn(-2)) D(LnGDP(-1)) ‡ D(LnGDP(-2)) ‡ Constant R-squared Adj. R-squared F-statistic Log likelihood Akaike AIC Schwarz SC (a) Johansen P-Values (b) Serial LM P-Value (c) Granger P-Value (d) Chow Breakpoint (e) Chow Forecast
-0.15867 -0.1316 [-3.804]*** [-3.595]*** 0.2867 0.5922 [1.354] [3.865]*** 0.1469 0.4826 [0.913] [2.750]** -1.1049 -1.5442 [-2.298]** [-3.435]*** -0.2617 0.6911 [1.575]○ [-0.608] 0.1267 0.0077 [3.260]*** [0.646] 0.9456 0.8284 0.9287 0.7941 55.6648 0.0586 38.6343 0.0484 -2.9668 -3.0455 -2.6692 -2.7680 {0.0249} {0.1006} {0.6951} {0.0171} {0.0019} {0.0646} {0.0898} {0.0241}
-0.1147 -0.0633 [-3.305]*** [-3.029]*** 0.3844 0.6262 [1.788]* [3.914]*** 0.1583 0.3235 [0.921] [1.927] -1.4836 -1.2074 [-2.720]** [-2.598]** -0.6750 1.4179 [-1.414] [3.090]*** 0.1421 -0.0033 [3.133]*** [-0.263] 0.9385 0.8096 0.9193 0.7715 48.8141 21.2592 37.2733 51.5936 -2.8430 -2.9415 -2.5455 -2.6640 {0.0609} {0.0976} {0.7571} {0.0629} {0.0155} {0.0016} {0.0223} {0.0084}
-0.0485 -0.2218 [-2.856]*** [-5.277]*** 0.4473 0.2687 ○ [2.368]** [1.504] 0.4492 0.0745 [2.254]** [0.537] -1.4894 -1.9444 [-1.884]* [-3.241]*** 2.5289 -0.5876 [3.116]*** [-1.035] -0.0154 0.1845 [-1.017] [4.078]*** 0.7692 0.9512 0.7231 0.9350 16.6667 58.5213 48.6138 40.6703 -2.7493 -3.3019 -2.4717 -3.0035 {8.971e-06} {0.0310} {0.2892} {0.0038} {0.0021} {0.0077} {0.0628} {0.0065}
(†) See Note for Table 3.
(‡) For Columns 4(C1) and (C2), substitute the 2-year moving average terms for GDP, LnGDP_ma2(-t), and D(LnGDP_ma2(-t)).
GDP Granger-causes WIR in both periods, and this causation can be shown to usually be reciprocal; i.e., Granger causality is also significant in the ‘reverse’ WIR-to-GDP direction, with P-values (not shown) significant in 4(A1), (B1), (B2), (C1), and (C2). To repeat, however, WIR is too small to be an important determinant of Swiss GDP.