Browsing by Author "Yawe, Bruno Lule"

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    Coffee Production in Uganda: the role of Non-Price Factors; 1970/71-1994/95
    (University of Dar es Salaam, 1996) Yawe, Bruno Lule
    Uganda’s traditional export crops are coffee, cotton, tea, tobacco and cocoa. On these only coffee survived as a major export crop. The production of the rest declined due to the socio-economic and political break down over the years. The study presents the responsiveness of coffee output to price and non-price factors over 1970/71-1994/95 period. The nerlovian partial adjustment model was used to investigate the response of coffee output to price and non-price factors. This was due to its successful use by earlier studies and the fact that it forms the foundation of studies on supply response. Real producer price, time trend as a proxy for other non-price variables, lagged output and weather conditions were independent variables. The cobb-douglas production function was estimated to investigate the role of non- price factors. The (log of) coffee output was regressed on the (log of): area harvested, weather research investment and time trend. Regressions for the entire sample period and for periods within the study period are presented. Contrasting results were obtained over the different periods for the two models. Results for the nerlovian model showed that for much of the study period, real producer price impacted negatively on coffee output which may due to, among others, late payment to farmers. Weather, lagged output and other non-price factors generally impacted positively on coffee output. Results of thee cobb-douglas production function showed that area harvested, research investment and weather positively influenced coffee production. Time trend negatively affected coffee output, which points to the need for improved infrastructural facilities. These may include among others, rural feed road network and others that do not directly affect coffee production but are crucial to the functioning of the rural economy. It thence suggests that policy makes would do well to devote as much attention and effort to the provision of non-price factors like technology, infrastructure and human capital as to price movements for stimulating coffee output in Uganda.
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    Technical efficiency and total factor productivity growth in Uganda’s district referral hospitals
    (University of Dar es Salaam, 2006) Yawe, Bruno Lule
    The study measures the technical efficiency and total factor productivity growth of 25 district referral hospitals from three regions of Uganda over the 1999-2003 period. This study is motivated by a desire to evaluate the ongoing health sector reforms in Uganda which in part are seeking to improve the efficiency of health services. Nonparametric Data Envelopment Analysis (DEA) is used in the measurement of hospital technical efficiency whilst the DEA-Malmquist index is used in the measurement of hospital total factor productivity change. The Hospital Management Information System launched in 1997 is the source of the data for this study. The results indicate the existence of different degrees of technical and scale inefficiency in Uganda’s district referral hospitals over the sample period. There were productivity losses for the sample hospitals which are largely due to technological regress rather than technical inefficiency. Thus, changes in technology are needed if the hospitals are to become more productive, for instance through improved diagnosis tests, hospital information management. The findings illustrate one of the advantages of the frontier efficiency technique, namely the ability to identify the degree of emphasis that should be placed on improving technical efficiency vis-a-vis technological change. The study adds to the existing literature on health facility efficiency but additionally incorporates patient deaths in the measurement of hospital technical efficiency. Additionally, heterogeneity in the patient load is controlled for via a length of stay-based case-mix index. Quality of care was incorporated into the analysis by means of patient deaths. Super-efficiency was conducted to further distinguish between the technically efficient hospitals. To construct confidence intervals for individual hospitals technical efficiency scores, nonparametric bootstrapping was conducted. The efficiency vectors yielded have ready uses by policymakers in the hospital sector. Indicators of the relative efficiency of hospitals are needed to gauge whether hospital cost-containment efforts are succeeding, amongst other uses.