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Regulation, renegotiation and capital structure: theory and evidence from Latin American transport concessions

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Abstract

We examine the capital structure of regulated infrastructure firms. We develop a model showing that leverage, the ratio of liabilities to assets, is lower under high-powered regulation and that firms operating under high-powered regulation make proportionally larger reductions in leverage when the cost of debt increases. We test the predictions of the model using an original panel dataset of 124 transport concessions in Brazil, Chile, Colombia and Peru over 1992–2011. For each concession we have data on the regulatory regime, annual financial performance and contract renegotiations. We begin by demonstrating that, although pervasive, contract renegotiations do not fundamentally alter the regulatory regime. Importantly, firms are not systematically able to renegotiate when in financial difficulty, implying that price cap contracts remain high-powered in practice. We use this result for our main empirical work, where we find broad support for our theoretical predictions: when the cost of debt increases, firms operating under high-powered regulation make proportionally larger reductions in leverage.

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Notes

  1. We define leverage as the ratio of liabilities to assets.

  2. Similar arguments have been made by others in the field. Klein (2012, p. 27) states that “without market risk, investors are often willing to provide high levels of debt... when there is market risk, financiers tend to require significantly higher equity cushions”. Engel et al. (2010, p. 49) argue that “leverage depends on the volatility of revenues and when these are very volatile, the project may not be bankable. Governments sometimes provide revenue insurance to improve the bankability of a project. Better alternatives allowing for high levels of leverage are, for example, PVR and availability contracts”.

  3. Cambini and Spiegel (2011) provide examples from US electricity and UK water regulation to support this view.

  4. See a detailed discussion on this mechanism in Tirole (2006), pp. 296–298.

  5. In a model that would incorporate a moral hazard component to the firm’s cost function, a similar debt-increasing effect would arise from moral hazard biting stronger. This can be seen simply in Tirole (2006, Chap. 7), if \(\Delta p\), the probability gap of success between the high and low effort states, increases.

  6. Their results show higher equity betas amongst price cap firms. In the standard CAPM model this implies a higher cost of equity, all else equal.

  7. Officially known as the Mecanismo de Distribución de Ingresos (MDI). This renegotiation did not affect all Chilean projects.

  8. This category also includes renegotiations to change the maintenance works/schedule.

  9. Values no longer sum to 1 as most renegotiations have numerous outcomes.

  10. We distinguish between tariff revisions and adjustments. Revisions determine the type of price regulation in effect (price cap, cost-plus, etc.). Tariff adjustments typically occur annually to adjust for inflation and sometimes exchange rate movements.

  11. RPI-X regulation consists of periodic price reviews (typically every 5 years) in which a tariff is set that increases at the rate of inflation (RPI) minus a factor X to account for productivity gains.

  12. The working capital ratio is defined as current assets divided by current liabilities. A ratio below 1 is typically used as an indicator of liquidity problems. Given the highly leveraged nature of project finance transactions however, a ratio below 1 is extremely common. We therefore choose a more extreme ratio of 0.5. Even at this level, over a third of observations classify as being in “distress”.

    Table 2 Random effect probit estimations—determinants of renegotiation
  13. The distress variable is significant at the 10 % level, but if the threshold is changed from 1 standard deviation above country mean to 1.5 or 2, this significance disappears.

  14. We do not include taxes in our main specifications. As noted by Rajan and Zingales (1995), the tax advantage of debt is highly sensitive to assumptions regarding the tax rates of the marginal investor. Rajan and Zingales (1995) do not include taxes in their core regression and Frank and Goyal (2009) do not find taxes to be one of their “core factors” explaining capital structure. When we include the top corporate tax rate in Eq. (6) it is insignificant and none of the main results are affected. In Eq. (7) the tax variable is generally significant, although again the main results remain largely unaffected. This significance is likely to be spurious as the time-series variation in corporate tax rates is extremely limited.

  15. Total shares traded may be a more informative variable than stock market capitalization for an emerging country sample (see Booth et al. 2001). Replacing this variable with the ratio of stock market capitalization to GDP does not affect our main hypotheses. The capitalization variable itself is less significant than our preferred measure.

  16. The fixed effects also remove the volatility variable as this is constant within each firm.

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Acknowledgments

We thank Lorena Lizarazo for excellent research assistance. We thank Organismo Supervisor de la Inversión en Infraestructura de Transporte de Uso Público (OSITRAN) in Peru, Agencia Nacional de Infraestructura (ANI) in Colombia, Luis Guasch and Alexander Galetovic for sharing data. We are grateful to Lincoln Flor and Camila Rodriguez for providing advice and contacts. We thank the editor, two anonymous referees, Jane Ansell, Tim Besley, Philippe Gagnepain, Marian Moszoro, Marcia Schafgans and participants at the Workshop on Procurement and Infrastructure in Toulouse, the Chaire EPPP Conference on Contracts, Procurement and Public–Private Arrangements in Florence and the Financing Infrastructure in Crisis Times workshop in Paris for helpful comments and suggestions.

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Appendix

Appendix

Proposition 1

The derivation follows closely Cambini and Spiegel (2011). Consider first the case \(D<D_1 \). Then \(\varphi ^{*}\left( {p,D} \right) =0,\frac{\partial p^{*}}{\partial D}=0,\) so that \(\frac{\partial Y(D)}{\partial D}=0\), using the fact that \(R_E =R_D\).

Consider now the case \(D_1 <D<D_2 \). Then \(\varphi ^{*}\left( {p,D} \right) =(1-\frac{p^{*}-D}{\bar{c}})\) and \(p^{*}\left( D \right) =a+\left( {1-b} \right) \left[ {\frac{\bar{c}}{2}+(1-\frac{p^{*}-D}{\bar{c}})T} \right] \). This implies that \(\frac{\partial \varphi ^{*}}{\partial D}=\frac{1}{\bar{c}},\frac{\partial \varphi ^{*}}{\partial p}=-\frac{1}{\bar{c}},\) and \(\frac{\partial p^{*}}{\partial D}=\left( {1-b} \right) T\frac{1}{\bar{c}}\). Using the fact that

$$\begin{aligned} \frac{\partial Y(D)}{\partial D}=\frac{\partial p^{*}}{\partial D}-\left( {\frac{\partial \varphi ^{*}\left( {p\left( D \right) ,D} \right) }{\partial p^{*}}\frac{\partial p^{*}(D)}{\partial D}+\frac{\partial \varphi ^{*}(p\left( D \right) ,D)}{\partial D}} \right) T \end{aligned}$$
(8)

straightforward computations lead to

$$\begin{aligned} \frac{\partial Y(D)}{\partial D}=\frac{T}{\bar{c}}\left[ {\left( {1-b} \right) \frac{T}{\bar{c}}-b} \right] \end{aligned}$$
(9)

Thus \(\frac{\partial Y(D)}{\partial D}>0\) if \(\frac{T}{\bar{c}}>\frac{b}{(1-b)}\). In this case, which occurs if \(b\) is small enough, the firm chooses \(D=D_2 \) for which its profit is maximum, while for \(\frac{\partial Y(D)}{\partial D}<0\), the firm’s profit is maximized at \(D=D_1 \).

Finally, when \(D>D_2 \), \(\varphi ^{*}\left( {p,D} \right) =1\), \(p^{*}\left( D \right) =a+\left( {1-b} \right) \left[ {\frac{\bar{c}}{2}+T} \right] \), so that \(\frac{\partial p^{*}}{\partial D}=\frac{\partial \varphi ^{*}}{\partial D}=\frac{\partial \varphi ^{*}}{\partial p}=\frac{\partial Y(D)}{\partial D}=0\).

Proposition 2

If \(R_E \ne R_D \) Eq. (9) becomes:

$$\begin{aligned} \frac{\partial Y(D)}{\partial D}=\frac{T}{\bar{c}}\left[ {\left( {1-b} \right) \frac{T}{\bar{c}}-b} \right] +R_E -R_D \end{aligned}$$
(10)

and denoting \(\frac{T}{\bar{c}}\equiv z\) we have that \(\frac{\partial Y(D)}{\partial D}>0\) if \(b<\frac{z-(R_D -R_E )/z}{1+z}\).

See Tables 5 and 6.

Table 5 Variable definitions and sources
Table 6 Regulation summary

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Moore, A., Straub, S. & Dethier, JJ. Regulation, renegotiation and capital structure: theory and evidence from Latin American transport concessions. J Regul Econ 45, 209–232 (2014). https://doi.org/10.1007/s11149-013-9243-6

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