_-5 -_

# C. Basic statistical analysis

Average ERRs, disaggregated by sector and type of single policy distortion, are presented in table 1 6 The differences between investnment efficiency in undistorted and a distorted policy environments can be very large. The (Pearson) correlation coefficients between the policy index and ERRs (not shown) are highly significant, with few exceptions.<sup>7</sup> In most cases, when classifying by a single policy distortion indicator, average ERRs of projects implemented under a distorted policy regime are at least five percentage points lower than those of projects implemented under an undistorted regime.<sup>8</sup> In addition, each of the five policy distortion indices appears to impact significantly across sectors--although to different degrees. Further, the sensitivity of public sector projects to policy distortions is at least as significant as for private sector projects.

A country that mismanages its exchange rate is also likely to exhibit macroeconomic instability as well as trade and pricing distortions: it is therefore relevant to assess the combined effect of policy distortions on ERRs. Average ERRs, disaggregated by various combinations of policy distortions, are presented in appendix table 1. Multiple policy distortions, when compared with an undistorted policy environment, can make a difference of over 10 percentage points. These large differences between investment efficiency in undistorted and distorted environments (measured by multiple indicators) suggest an independent effect of different types of distortions<sup>9</sup> --a result which is explored in the econometric specifications below.

## IV. The Effect of Economic Policy Distortions on ERRs: Econometric Results

The correlations above do not control for other factors nor for mechanisms that mnight affect both ERRs and policies.<sup>10</sup> In order to account for other possible determinants of investment productivity and to explore the relative importance of policies, a set of multivariate econometric specifications was estimated. 1<sup>1</sup>

> 6 Sector-specific disaggregation was possible for the larger public sector data set; the smaller private sector data set, mostly comprising agricultural and industrial projects, was not disaggregated.

> 7 Such as the relationship between both the real interest rate and price of tradeable goods on the one hand, and the ERR of projects in non-tradeables, on the other.

8 Note that these reestimated ERRs are not a true _ex post_ rate of retum: the stream of project benefits is only flowing for a few years by the time of the reestimated calculation. We conducted an analysis of possible measurement biases with the available subsample of seventy public projects with true _ex posi_ evaluations, undertaken five-to-eight years after project completion. The reestimated ERR and the ex post ERR were found to be very highly correlated (r =.8), yet the average _expost_ ERR--I I to 12%--was 3-to-4 percentage points below the average reestimated ERR. Since the _expost_ ERR is a better approximation of the true economic value of the project, this suggests that, on average, a project implemented in a distorted policy framework will have a true ERR lower than 10 percent.

9 The types of policy variable combinations was circumscribed to those where indices measured different types of distortions--thus, for instance, indices of trade openness and of distortions in the price of tradables are not introduced simultaneously, and neither is the fiscal deficit and the real interest rate.

10 Nor, of course, do they control for reverse causation; but it seems quite unlikely that project returns would affect policy distortions.