∂φ<sup>∗</sup> results as is independent of _b_ . Our empirical findings cast doubt on the importance of this mechanism ∂D however: volatility is a positive (generally insignificant) determinant of leverage and more profitable firms have lower leverage.

An alternative possibility is that high-powered regulation increases the cost of equity, leading such firms to choose higher leverage. In the Capital Asset Pricing Model (CAPM), the cost of equity is determined by the covariance of the company’s returns with the market portfolio. Alexander et al (1996) find that this covariance is higher in price cap contracts than rate-of-return contracts in regulated infrastructure projects, implying a higher cost of equity.<sup>6</sup> Unlike the previous mechanism, this offsets the predictions of the model. The magnitude of this effect in our sample may not be significant however as almost all contracts include annual tariff adjustments for inflation, and many allow adjustments for exchange rate shocks. Such clauses reduce the extent to which the project’s returns are dictated by economy-wide cost shocks. Furthermore, Gaggero (2007) replicates the methodology of Alexander et al (1996) and does not find that the cost of equity is higher under higher-powered regulation.

# **3. Data**

We construct an original dataset of 124 transport concessions in Brazil, Chile, Colombia and Peru over the period 1992-2011. The complete panel – tracking all projects since the year of contract signing – covers 1,360 observations and financial data covers 1,037 observations. Details on the design of price regulation come from project contracts, sector legislation and renegotiation agreements. In addition we have information on the specifics of the projects (investment size, duration, etc.), on the institutional and regulatory environment, the timing and content of renegotiation agreements, as well as the evolution of key economic variables. Table 1 provides summary statistics of the main variables. Table A1 in the Appendix provides a full list of variables and sources.

Our principal measure of leverage is the ratio of total liabilities to total assets. The unit of observation is the project company, as opposed to the project sponsor(s). As argued by Esty (2004), project companies are “strategic research sites” and “provide a new and, potentially, very powerful laboratory to analyse structural decisions and to show why they matter”. The fact that project companies are created for a specific and well-defined purpose is greatly beneficial from a research perspective.

Firm-level financial data comes directly from regulatory agencies and from commercial databases. OSITRAN, the Peruvian federal regulator, provided the data for all Peruvian projects and ANI, the Agencia Nacional de Infraestructura provided data for Colombian road projects. The two commercial databases we use are the ISI Emerging Markets Database of Euromoney Institutional Investor and the Orbis Database of Bureau van Dijk.

In Chile, Colombia and Peru all concessions are regulated at the federal level. In Colombia the federal regulator varies across subsectors and across time, whereas in Chile all projects are regulated by the Ministerio de Obras Publicas (MOP) and all Peruvian projects are regulated by Ositran. In Brazil

> 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.

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