# 3.2 Forecasting Dividends

**Key points**

Historical

**time series of dividends are too erratic**for infrastructure companies to allow a direct dividend forecast.A more robust strategy is to use a model of the firm's free-cash flow to equity, which is always observable and to derive future dividends by combining this FCFE forecast with a FCF Retention Rate forecast.

A combination of systematic and idiosyncratic models allows

**using the entire history of dividend payout behaviour**available for 600+ tracked firms with the**unique cash flow trend of each company**.

Forecasting dividend payouts is challenging because for many firms equity and quasi-equity payouts are not statistically tractable directly. As is well documented in the corporate-finance literature, private firms tend to have a more erratic dividend-payout behaviour than listed firms (dividends are less “sticky”), and their equity payouts can vary considerably in size and frequency. In fact, the best model of broad equity payouts across the infrastructure universe is a random march.

**About realised infrastructure dividends **

While some infrastructure companies pay dividends regularly, others pay dividends in irregular and more unpredictable patterns. A non-negligible subset of companies in the *Scientific Infra & Private Assets* database (about 10%) has never paid out a single dividend, some in more than ten years of operation. Still, these “zero payout” firms can be assumed to have a positive present value (otherwise investors would not hold them). Hence, they should not be excluded from a broad market infrastructure equity index, since they represent a certain pattern of equity payout found in the market.

## Quantities of interest

Our approach to forecasting cash flows in unlisted infrastructure projects aims to minimise the multiplication of estimation errors by using the smallest number of variables possible. We focus on modelling the **free cash flow to equity of infrastructure companies** as a stochastic process described as a two-dimensional state vector (mean and variance). This is parsimonious.

The future free cash flow to equity of each firm is defined as:

where is the senior debt service owned at time and is the Cash Flow Available for Debt Service at that time.

The CFADS model is a dynamic model estimated as:

Where for each age *t* CFADS is a function of the Revenue, Equity to Assets ratio*, *Senior Leverage and CV are indicator variables for the industrial classifications that the company belong to.

This dynamic model illustrates the age-varying relationship between cash flows of a company at a given age as a function of financial characteristics of infrastructure companies. The CFADS model is estimated with Kalman Filtering to illustrate how the factor prices for each independent variables in the model vary with the age of the companies.

The dynamic model estimation by Kalman filter can be written as a system of two equations. The observed equation and the state equation can be written as follows:

Where is a vector of independent variables*, * is a vector of the model coefficients and an identity matrix.

This free-cash-flow process is the result of the firm’s business model and risk, the choice and evolution of its financial structure, and it ultimately determines the ability of the firm to repay its senior creditors and equity investors. Crucially, infrastructure companies are characterised by limited growth opportunities and numerous long-term commitments (to invest only in their core business, to deliver service, etc.) thus making future debt service and equity payouts a direct function of the firm’s free cash flow, which cannot be used for other purposes.

While we cannot model the payouts to equity investors directly, we can use the following indirect, two-step approach:

We first estimate the parameters of the firm’s

**free-cash-flow process**(free cash flow to equity or FCFE) as defined above. Unlike equity payouts, this first quantity can always be observed: as long as a firm is operational, it must have a free cash flow (even if it is negative).We then estimate the firm’s

**FCFE retention rate**(FCFE-RR), that is, its tendency to distribute FCFE in any given period. Likewise, this quantity is always observable and partly embodies the economic dynamic of the firm, including its ability and tendency to reinvest free cash, to keep it in various reserve accounts, or to distribute it as dividends or shareholder loan repayments.

The FCFE-RR is computed as

where is all cash held at bank at the end of each period and is the free cash flow to equity as defined above.

Hence, measures the tendency of each firm to retain free cash flow to equity instead of distributing it to shareholders. Particularly in infrastructure projects with a finite life, it can be expected to follow the firm's lifecycle and must take the value of 0 in the last year, when all remaining free cash must be paid out. Conversely, with 'infrastructure corporates' can be expected to follow different regimes depending on the firm's life and history, including the impact of any regulatory changes.

Thus, future equity payouts of each firm are simply written:

Likewise, the volatility of future equity payouts is the combination of the conditional variance of and .

Watch a 2-minute **video tutorial** highlighting our approach to dividend forecasting: