P UBLI C - P RIV A TE P A RTNERS H I P S IN SOUT H A SI A
Annex 1D. Imputing the Missing Values for Predictions Physical Investment The missing values for investments in physical infrastructure for small hydro projects in Nepal and Sri Lanka and for the wind and solar energy projects in India were imputed by estimating the amount of investment needed per megawatt for the same type of energy projects in the same country. Hence, the imputations are obtained from the following regression: Physical Investmenti = β × Capacityi + ui, where i stands for project; β is the regression coefficient; and ui is the residual. • In the case of Sri Lankan small hydro projects, 41 observations were used to impute 3 missing values. • In the case of Nepalese small hydro projects, 22 observations were used to impute 4 missing values. • In the case of Indian wind projects, 91 observation were used to impute 4 missing values. • In the case of Indian solar projects, 97 observations were used to impute 1 missing value.
Debt-to-Physical-Investment Ratio To obtain the estimates for the missing financing variables—debt and equity—the debt-to-physical-investment ratio has been predicted using type, sector, country, and financial closure year dummies, using the following regression: Debt to Physical Investment Ratioi = β0 + Typei + Sectori + Countryi + Financial Closure Yeari + ui , where i represents each project in South Asia. A total of 737 observations have been used to impute 344 missing values. The physical investment has been apportioned according to the predicted ratio between debt and equity.
Contract Period Four kind of projects have been identified as missing contract period information: energy projects, airport projects, seaport projects, and toll road projects in India. The missing contract period data were imputed using the following regressions and were rounded to the nearest integer. The regression for energy projects in South Asia is Periodi = β0 + Typei + Countryi + Financial Closure Yeari + ui , where i represents each energy project in South Asia. A total of 391 observations were used to impute 194 missing values. The regression for airport projects in South Asia is Periodi = β0 + ui , where i represents each airport project in South Asia. This regression essentially finds the average contract length for airport projects without any predictors. The choice of the model is due to sample limitations. Eight observations were used to impute three missing values. The regression for seaport projects in South Asia is Periodi = β0 + Typei + Financial Closure Yeari + ui , where i represents each toll road project in India. A total of 53 observations were used to impute one missing value. The regression for toll road projects in India is Periodi = β0 + Typei + Financial Closure Yeari + Subnationali + ui , where i represents each toll road project in India. The inclusion of the subnational contract indicator is due to the differences in the handling of contracts between the National Highways Authority of India and the state highways authorities. A total of 393 observations were used to impute 14 missing values.
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