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Table 5 Non-linear ARDL estimation results

From: Nexus between financial innovation and economic growth in South Asia: evidence from ARDL and nonlinear ARDL approaches

  Country
Bangladesh India Pakistan Sri Lanka
coefficients t-stat coefficients t-stat coefficients t-stat coefficients t-stat
Panel – A: Long-run Estimation
 C −3.16a −1.41 −26.65 −2.39 18.52a 1.33 −3.79a −2.73
 Y(−1) −0.72a −0.18 −2.29 −2.52 −0.76a − 3.58 − 1.38a −4.37
 FI_P(− 1) 2.56b 2.60 5.38b −2.27 4.92a 1.58 0.92a 1.76
 FI_N(−1) −4.07b −3.51 −7.11a − 1.96 −6.73a − 1.61 −0.18a −1.41
 DCP(−1) −8.09a −5.74 16.73 2.16 −7.98a −2.57 1.43 0.97
 GCF(−1) −4.52b −5.42 −0.81 − 0.56 −0.83 −2.52 − 1.93 − 2.68
 TO(− 1) 7.86a 5.17 −7.35 −1.37 1.74a 0.35 7.27 2.90
Panel – B: Short-run Estimation
 ∆Y(−1) −0.53a −1.78 1.95a 3.39    0.78b 3.03
 ∆Y(−2) −0.35 − 1.63 1.55b 3.58 −0.65 −2.68 1.20b 3.94
 ∆Y(−3) − 0.55b −3.15 −0.22b − 0.04 −0.61a − 1.78   
 ∆Y(−4) −0.48a 4.16 −0.14b − 0.39 − 0.77b −2.63 −0.51b −2.42
 ∆FI_P(−1) 0.14a 3.84 .03a 1.93 0.78a   −2.10a −4.29
 ∆FI_P(−2) 0.39a 1.88 0.58a 1.19 0.9b 1.60 −1.77b −3.97
 ∆FI_P(− 3) 0.01a 0.87 1.74b 1.02 0.07b 0.91 −0.49b −1.67
 ∆FI_P(−4) 0.71a 2.24 1.54b 2.44 0.04a 2.19 −3.42a −2.33
 ∆FI_N(−1) 0.07a 1.54 −0.87b −1.89 − 0.58a − 0.82 1.41b 1.21
 ∆FI_N(−2) −0.96a −2.73 − 0.65b − 2.13 − 1.78a − 1.52 5.76b 2.98
 ∆FI_N(−3) − 1.04b − 2.72 − 0.67b − 0.94 − 0.33a − 0.92 1.14b 1.08
 ∆FI_N(−4) 0.96a 3.32 − 1.12a − 1.42 − 2.93a −2.06 − 14.88 −1.54
 ∆DCP(−1) 6.66b 3.42    17.21* 2.81 −5.43b −3.57
 ∆DCP(−2) 2.97b 1.98 −13.87b −2.22    −5.29b −3.86
 ∆DCP(−3)      12.70a 2.59 −1.67b − 1.37
 ∆DCP(−4) −6.29b −4.15 − 1.21b −2.48 17.21* 2.81 −3.97b −2.53
 ∆GCF(−1) 3.41b 5.34      1.35b 2.62
 ∆GCF(−2) 1.46b 3.35    0.40b 1.36 0.22b 0.68
 ∆GCF(−3) 1.04b 4.38 0.16b 1.11 0.81a 2.18 0.33a 1.29
 ∆GCF(−4)   0.57b 1.95 0.25 1.03 −1.45a −0.17
 ∆TO(−1) −4.12b −4.57 − 4.48 − 1.13 8.96b 2.28   
 ∆TO(−2) −2.61 −2.96 17.21 1.72 11.74b 3.72   
 ∆TO(−3) −3.11b −3.89 3.70 0.77 2.95b 0.93   
 ∆TO(−4) −3.46b −4.45 10.99 2.12 14.03b 3.57   
Panel – C: Symmetric Estimation
Fpss 19.43   15.79   13.72   9.15  
\( {L}_{EX}^{+} \) 3.47a   2.43a   6.47a   0.67a  
\( {L}_{EX}^{-} \) −5.65a   −3.10a   10.50a   −0.13b  
WLR 4.78(0.002)   1.33(0.003)   2.70(0.009)   1.17(0.001)  
WSR 12.17(0.004)   6.29(0.007)   6.18(0.004)   5.55(0.008)  
Panel – D: Residual Diagnostic and Model Stability Test
 R2 0.86   0.79   0.89   0.83  
 δ 0.27   0.32   0.21   0.44  
\( {\mathrm{F}}_{\mathrm{statistics}}^2 \) 10.42a   5.28a   3.07a   3.73b  
\( {\mathrm{x}}_{\mathrm{Autocorrelation}}^2 \) 2.20(0.18)   5.84(0.24)   4.84(0.45)   6.75(0.59)  
\( {\mathrm{x}}_{\mathrm{Heteroskedasticity}}^2 \) 1.96(0.26)   1.40(0.49)   1.19(0.18)   1.49(0.18)  
\( {\mathrm{x}}_{\mathrm{Normality}}^2 \) 1.61(0.41)   1.51(0.77)   1.14(0.56)   1.64(0.43)  
\( {\mathrm{x}}_{\mathrm{RESET}}^2 \) 1.19(0.34)   0.97(0.23)   6.29(0.18)   3.29(0.18)  
  1. Note 1. The superscript “+” and “-” indicate positive and negative changes, respectively
  2. Note 2. Fpss for F-statistics from Wald test for long-run cointegration
  3. Note 3. \( {L}_{FI}^{+} \) and \( {L}_{FI}^{-} \) for long-run coefficients for financial innovation positive and negative changes
  4. Note 4. WLR refers to the Wald test of long-run symmetry\
  5. Note 5. WSR refers to the Wald test of the additive short-run symmetry condition
  6. Note 6. a and b denote significance at the 1 and 5%, levels, respectively