Estimating the efficiency of healthcare facilities providing HIV/AIDS treatment in Zambia:a data envelopment approach

Zambia and many other countries in Sub-Saharan Africa face a key challenge of sustaining high levels of coverage of AIDS treatment under prospects of dwindling global resources for HIV/AIDS treatment. Policy debate in HIV/AIDS is increasingly paying more focus to efficiency in the use of available resources. In this chapter, we apply Data Envelopment Analysis (DEA) to estimate short term technical efficiency of 34 HIV/AIDS treatment facilities in Zambia. The data consists of input variables such as human resources, medical equipment, building space, drugs, medical supplies, and other materials used in providing HIV/AIDS treatment. Two main outputs namely, numbers of ART-years (Anti-Retroviral Therapy-years) and pre-ART-years are included in the model. Results show the mean technical efficiency score to be 83%, with great variability in efficiency scores across the facilities. Scale inefficiency is also shown to be significant. About half of the facilities were on the efficiency frontier. We also construct bootstrap confidence intervals around the efficiency scores.

A note on a semiparametric approach to estimating financing constraints in firms

In this paper, we present a novel approach to modeling financing constraints of firms. Specifically, we adopt an approach in which firm-level investment is a nonparametric function of some relevant firm characteristics, cash flow in particular. This enables us to generate firm-year specific measures of cash flow sensitivity of investment. We are therefore able to draw conclusions about financing constraints of individual firms as well as cohorts of firms without having to split our sample on an ad hoc basis. This is a significant improvement over the stylized approach that is based on comparison of point estimates of cash flow sensitivity of investment of the average firm of ad hoc sub-samples of firms. We use firm-level data from India to highlight the advantages of our approach. Our results suggest that the estimates generated by this approach are meaningful from an economic point of view and are consistent with the literature. © 2014 © 2014 Taylor & Francis.

Estimating the impact of R&D on productivity using the BERD-ARD data

The UK has a relatively low ratio of business R&D to GDP (the BERD ratio) compared to other leading economies. There has also been a small decline in UK’s BERD ratio in the 1990s, whereas other leading economies have experienced small rises. The relatively low BERD ratio cannot be explained solely by sectoral or industry-level differences between the UK and other countries. There is, therefore, considerable interest in understanding the firm-level determinants of investment in R&D. This report was commissioned by the DTI to analyse the link between R&D and productivity for a sample of firms derived from merging the ONS’s Business Research and Development Database (BERD) and the Annual Respondents Database (ARD). The analysis estimates the private rates of returns to R&D, and not the social rates of return, since it is the private returns that should drive firms’ decisions. A key objective of this research is to analyse the productivity of R&D in small and medium sized enterprises (SME). The analysis is intended to allow comparisons to the results in Rogers (2005), which uses publicly available data on R&D in medium to large UK firms in the 1990s.

Estimating direct and indirect effects of foreign direct investment on firm productivity in the presence of interactions between firms

We implement a method to estimate the direct effects of foreign-ownership on foreign firms' productivity and the indirect effects (or spillovers) from the presence of foreign-owned firms on other foreign and domestic firms' productivity in a unifying framework, taking interactions between firms into account. To do so, we relax a fundamental assumption made in empirical studies examining a direct causal effect of foreign ownership on firm productivity, namely that of no interactions between firms. Based on our approach, we are able to combine direct and indirect effects of foreign ownership and calculate the total effect of foreign firms on local productivity. Our results show that all these effects vary with the level of foreign presence within a cluster, an important finding for the academic literature and policy debate on the benefits of attracting foreign owned firms.