Discusión de la Encuesta

Table 5.5 presents the regression results of the relationship between tranche spread and the political and legal institutions. Model 1 reports the main specification with investment profile (political risk variable), loan characteristics and country controls. Model 2 and 3 add creditor rights and governance measure respectively to the specification in Model 1. In Model 4 and 5, the investment profile interacts with legal and governance measures respectively.48

Consistent with the first hypothesis (H1) and the findings of Girardone and Snaith (2011)

and Qi et al. (2010), the present chapter finds that loan spread reduces with improvement (stronger) in political institutions. These results hold for all regression specifications in Table 5.5. Taking results in Model 1 for instance, a percentage increase in investment profile lead to 5.6% decrease in spread. Given mean (median) spread for the sample is 183.96 (140) bps (in Table 5.2), one percentage improvement in investment profile will lead to 10.3 bps (7.84 bps) reduction in the spread. This result suggests that loans signed in countries with strong politcal institutions benefits from lower financing cost. This result is in line with Girardone and Snaith (2011) and Qi et al. (2010) who also report lower spread (cost of debt) for countries with stronger political institutions. However, the coefficients (-0.045 to -0.092 from

48 _{Unreported coefficients on industry, loan-type, sovereign credit rating and year dummies are provided in}

Model 1 to 5) are much lower than 0.216 to 0.668 obtained in Qi et al. (2010). A potential explanation for the smaller coefficients is that (together with Girardone and Snaith (2011)) PF has peculiarities-political risk-mitigants and certification benefits of development banks (Kingsley, 2009; Hainz and Kleimeier, 2012). Thus, loan spreads on PF are less likely to respond to political risks relative to corporate debt, bonds, and equity.

For legal institutions, the results in Table 5.5 indicate that stronger creditor rights lead to reduction in the spread. Model 4, for instance, show that one percent improvement in legal institution reduces loan spread by 19.6% and statistically significant at the 5% significance level. This result also provides support for the role legal institutions on financial contracts, and in line with previous studies by Qi et al. (2010). On the other hand, the coefficient on legal institutions in Model 2 is positive and statistically insignificantly. This finding is interesting considering Subramanian and Tung (2016) study that show that PF act as a private response to weak creditor protection. Thus, separate incorporation of the project company and ring fencing its project cash flow through network of contracts (NFCs), lenders can provide an alternative to weaker creditor protection. If this is true, the loan spread on these transactions should also be less responsive to legal institutions.

Governance in Model 3 shows a positive relationship on loan spread. A one percent increase in governance is associated with 4.7 percent increase in the loan spread. The result is, however, counter-intuitive, but likely due to governance’s high correlation with investment profile (0.67 from Table 5.3). As a result, it is possible investment profile captures most of the effects from governance.

Table 5.5: OLS regression of tranche spread on political and legal institution

Model 1 Model 2 Model 3 Model 4 Model 5 Constant term 5.136*** 5.793*** 5.712*** 6.132*** 5.608*** (32.79) (25.45) (31.63) (22.79) (29.04) Investment profile -0.056*** -0.058*** -0.055*** -0.092*** -0.045*** (-5.18) (-4.80) (-4.65) (-5.12) (-3.42) Creditor right 0.026 -0.196** (1.63) (-2.43) Governance 0.047*** 0.000 (3.00) (0.000)

Investment profile x Creditor rights 0.022*** (2.90)

Investment profile x Governance 0.004

(1.17) NFC dummy -0.146*** -0.140*** -0.149*** -0.138*** -0.149***

(-3.68) (-3.70) (-4.11) (-3.68) (-4.08) Concession dummy 0.022 0.043 -0.020 0.038 -0.019 (0.46) (0.85) (-0.38) (0.76) (-0.37) Public finance initiatives/PPP dummy -0.113** -0.118** -0.151*** -0.130*** -0.155***

(-2.41) (-2.46) (-3.12) (-2.74) (-3.18) Bilateral agreement dummy 0.031 0.033 0.008 0.029 0.008

(0.50) (0.65) (0.17) (0.59) (0.16) Log of maturity 0.064*** 0.060*** 0.077*** 0.060*** 0.077***

(3.95) (3.66) (4.62) (3.65) (4.64) Log of tranche amount -0.052*** -0.052*** -0.054*** -0.052*** -0.053***

(-5.42) (-5.29) (-5.25) (-5.28) (-5.20) Currency dummy -0.105** -0.094** -0.0502 -0.087* -0.043 (-2.34) (-1.98) (-1.02) (-1.83) (-0.89) Refinance dummy 0.011 0.0169 -0.035 0.011 -0.033 (0.29) (0.40) (-0.85) (0.27) (-0.80)

Industrial dummies YES YES YES YES YES

Loan type dummies YES YES YES YES YES

Sovereign Rating dummies YES YES YES YES YES

Year dummies YES YES YES YES YES

Obs. 3284 3167 2717 3167 2717

Adjusted R2 _{0.28 0.27 0.33 0.28 0.33}

Table 5.5 shows regression estimates of the log of loan spread on political and legal institutions, loan characteristics and country controls for project finance loans. The variables: Investment profile x creditor right and Investment profile x governance are interaction terms of political institutions with legal and governance institutions respectively. Model 1 shows the estimates of loan spread on political institutions, loan, and country controls. Model 2 adds legal institutions while in Model 3 governance is the substituted for legal institutions. Model 4 and 5 add interaction terms of political institution and legal and governance institutions respectively. The sample period is 1998-2012. The models are estimated using OLS with robust standard errors clustered at the deal level. T-statistics are reported in parenthesis. ***, ** and * denotes significance at the 1%, 5% and 10% level respectively.

Turning to interaction terms in Model 4 and 5 reveal some interesting findings. Model 4 provides evidence on the interaction between political risk and creditor right. The estimated coefficient on interacting political and legal institution is positive and statistically significant at the 1% level. This result indicates that as countries’ political institutions improve, the impact of creditor right on PF loan spread reduces, all things being equal. Similarly, as countries’ legal institutions improve, the impact of political institutions on spread reduces. The finding suggests some degree of substitutability between political and legal institutions. The coefficient on the interaction between political institutions and governance is positive but statistically insignificant.

The coefficients on the control variables are consistent and in line with previous studies. NFC dummy, which proxies for risk-shifting contracts show a negative relationship with loan spread throughout Model 1 to 5. The estimated coefficients on the NFC dummy range between 0.138 and 0.149. These results are consistent with the findings of Corielli et al. (2010) who also report a negative relationship between loan spread and NFCs. NFCs provide contractual mechanisms for lenders to control the project company and its sponsors. In addition, following Byoun and Xu (2014) concession and PFI/PPP dummies are included to account projects with a higher tendency of government control. The results on concession report show both positive and negative results. However, they are insignificant throughout Model 1 and 5. On the other hand, PFI/PPP loans report negative and significant relationship with PF loan spread. Tranche maturity and amount show a positive and negative relationship with loan spread respectively.