Travel Report from the first field trip within the SIDA supported project "Mini-grids supplied by renewable energy - improving technical and social feasibility : Including visits to Ihushi Development Center, Tweyambe Secondary School and Mavuno Project in Tanzania. Conducted in April 2011

This report describes the outcome of the first visit to Tanzania, within the project "Mini-grids supplied by renewable energy - improving technical and social feasibility". The trip included visits to three different organizations; Ihushi Development Center (IDC) near Mwanza, TIDESO near Bukoba, and Mavuno Project in Karagwe. At IDC, a brief evaluation of the current power system was done and measuring equipment for long term measurements were installed. At all three locations investigations regarding the current and future electricity demand were conducted and connections to people relevant to the study were established. The report is including as well some technical specifications as some observations regarding organization and management of the technical systems. The trip was including only short visits and therefore only brief introductions to the different organizations, based on observations done by the author. The report is hence describing the author’s understanding of the technical system and social structures after only short visits to each of the organizations, and may differ from observations done at another point in time, over a different time period, or by some other person.This report describes the outcome of the first visit to Tanzania, within the project "Mini-grids supplied by renewable energy - improving technical and social feasibility". The trip included visits to three different organizations; Ihushi Development Center (IDC) near Mwanza, TIDESO near Bukoba, and Mavuno Project in Karagwe. At IDC, a brief evaluation of the current power system was done and measuring equipment for long term measurements were installed. At all three locations investigations regarding the current and future electricity demand were conducted and connections to people relevant to the study were established. The report is including as well some technical specifications as some observations regarding organization and management of the technical systems. The trip was including only short visits and therefore only brief introductions to the different organizations, based on observations done by the author. The report is hence describing the author’s understanding of the technical system and social structures after only short visits to each of the organizations, and may differ from observations done at another point in time, over a different time period, or by some other person.

Modified Fixed Effects Estimation of Technical Inefficiency

We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.