Gender-differentiated stochastic meta-frontier analysis of production technology heterogeneity among smallholder cassava farmers in Ghana

This paper assesses the differences in technical efficiency of, and the cassava production systems employed by, male-managed (MMF) and female-managed (FMF) cassava farms in the Fanteakwa District of Ghana. The study employs the translog stochastic meta-frontier model to analyse data obtained from 300 randomly selected smallholder cassava farmers and finds an average metafrontier technical efficiency (MTE) of 0.06 and 0.03 among MMF and FMF respectively. The technology gap ratios (TGR) are 0.25 and 0.04 for the MMF and FMF respectively. The results suggest that both MMFs and FMFs are technically inefficient. However, the production technology operated on MMFs is relatively superior to that operated on FMFs, as shown by the relatively higher TGR for MMFs. The results also reveal that proximity to markets, extension access, off-farm economic activities and formal education are the major contributors to the technical efficiency of the farmers.

Clinical pharmacology strategies in supporting drug development and approval of antibody–drug conjugates in oncology

Antibody–drug conjugates (ADCs) are important molecular entities in the treatment of cancer. These conjugates combine the target specificity of monoclonal antibodies with the potent anti-cancer activity of small-molecule therapeutics. The complex structure of ADCs poses unique challenges to characterize the drug’s pharmacokinetics (PKs) and pharmacodynamics (PDs) since it requires a quantitative understanding of the PK and PD properties of multiple different molecular species (e.g., ADC conjugate, total antibody and unconjugated cytotoxic drug). As a result, clinical pharmacology strategy of an ADC is rather unique and dependent on the linker/cytotoxic drug technology, heterogeneity of the ADC, PK and safety/efficacy profile of the specific ADC in clinical development. In this review, we summarize the clinical pharmacology strategies in supporting development and approval of ADCs using the approved ADCs as specific examples to illustrate the customized approach to clinical pharmacology assessments in their clinical development.

Accounting for TFP Growth in Global Agriculture - a Common-Factor-Approach-Based TFP Estimation

There is no consensus about trends in agricultural productivity among agricultural economists. The aim of this paper is to contribute to the investigation of this issue by estimating a Total Factor Productivity (TFP) index for global agriculture and global agricultural regions. One of the biggest challenges with analysing global productivity trends is the lack of price data or cost shares, especially in developing countries. We apply recently introduced econometric models that permit accounting for technology heterogeneity and the time-series properties of data to estimate cost shares. Aggregate sectoral data from the USDA ERS database are investigated for the period 1990 to 2013. Although we used a different method, our results are in line with earlier findings that used USDA or FAO database. TFP growth has accelerated in world agriculture, largely due to better performance in transition countries. Although TFP growth has accelerated in world agriculture, it has slowed down in industrialized countries. TFP growth in the EU has increased, but at slower rate in recent years. In the Old Member States the growth rate has decreased, whereas in the New Member States it has increased. The results highlight that insufficient spending on productivity-enhancing agricultural R&D in industrialized countries may put future agricultural productivity growth at risk.

Measuring Logistics Efficiency in China Considering Technology Heterogeneity and Carbon Emission through a Meta-Frontier Model

Due to the differences in the economic and social environment, production technology heterogeneity exists in the logistics industry among provinces in China. If this fact is ignored, the evaluation result of logistics efficiency may be biased. To this end, this study developed a new analysis framework for evaluating logistics efficiency with the consideration of technology heterogeneity and carbon emission through a metafrontier data envelopment analysis (DEA) method. Furthermore, the source of logistics inefficiency were identified. The proposed method was employed in the regional logistics industry in China from 2011 to 2017. The following empirical findings could be drawn: (1) The overall logistics efficiency is low in China, and great potential exists in improving logistics efficiency. (2) Significant disparities exist in logistics efficiency and the technology gap among the three areas. The east area has higher logistics efficiency with advanced technology, while the central area and the west area have lower logistics efficiencies. (3) The technology gap and management issues in the utilization of logistics resources are the two primary reasons resulting in the logistics efficiency loss in China. The effect of the management factor is significant in the east area, while the impact of the technology gap is dominant in the central area and the west area. Some policy suggestions for enhancing logistics efficiency are provided.

Role of Capital Productivity in Economic Growth

The main aim of this study is to measure the value of the capital in labour productivity growth at Turkish manufacturing industry within the years of 1980-2011 by applying an econometric model that account for cross-section dependence and heterogeneity of production technology in a panel setting, which is not done before. That is the common correlated effects (CCE) type estimator of Pesaran is applied. The cross-sectional averages of the dependent and explanatory variables are used at the CCE estimator. The main findings of the study are; first, individual industry regression results convey apparent technology heterogeneity across the industries. Second, imposing slope homogeneity restriction in the pooled models lends a lot of precision to the capital productivity estimate. When tested, the industries are not poolable. But, interestingly, the mean-group and pooled estimates of technology coefficients are close. The technology estimates are sensitive to the presence of observed and unobserved common factors, justifying the use of CCE estimators.