Performance of land reform projects in the North West province of South Africa: Changes over time and possible causes

Anecdotal evidence as well as selected studies on the performance and progress of South Africa’s land reform programme generally present mixed to rather negative results. Few longitudinal studies exist on the progress of redistributed farms, resulting in an incomplete picture of the performance and progress of land reform projects. In this article, we report on the progress and performance of a group of land reform projects in the North West province of South Africa over five years. As part of a comprehensive audit of land reform projects in the North West province, 43 farms were studied in 2005 to assess their performance, based on their production status. Five years later, in 2010, 37 of these farms were visited again to review their progress. The results indicate that the production status (and thus performance) of land reform projects is not static. Although some projects either improved or maintained their initial production status, the overall trend shows deterioration in performance. Numerous factors are responsible for the decline, including group characteristics where farms are owned by groups of beneficiaries. This article is thus the first to use two surveys of a group of land reform projects to show the true status of farms in their post-transfer phase in South Africa.     

Projecting future crop productivity for global economic modeling

Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

The relationship between Arab values and work beliefs: An exploratory examination

In this study, 365 employees from three Middle Eastern countries (Saudi Arabia, Kuwait, and Oman) are queried about their cultural values and work‐related beliefs. This analysis is unique both in its sample and its focus on the relationship between individual cultural values and beliefs about work. Results suggest that the cultural value dimensions individualism (p < .001) and masculinity (p < .001) are related to both an individual's beliefs about organizational commitment and work ethic. Additional findings reveal patterns between cultural values and humanistic and political beliefs. Future research directions and managerial implications are also discussed. © 2002 Wiley Periodicals, Inc.     

Some strange properties of panel data estimators

We study the biases that are likely to arise in practice with panel data when parameters vary across individuals, but this is not allowed for in estimation. We consider both stationary and non-stationary regressors. We find that biases can be severe for relatively small parameter variation, and that this problem is hard to detect. We study in some detail by Monte-Carlo the performance of the Anderson-Hsiao estimator in the presence of this particular mis-specification.     

‘Control – What Control?’ Culture and Ambiguity Within a Knowledge Intensive Firm*

ABSTRACT This paper explores the distinctive culture that existed within a knowledge‐intensive firm (KIF) and also attempts to explain the emergence and effects of this culture. The findings are based on a detailed case study that was conducted over two years within a consultancy firm that created and applied scientific knowledge and expertise to the invention of solutions for clients. The firm employed highly educated scientists, considered ‘leading’ in their respective disciplines and project work was inherently fluid, complex, and uncertain. These kinds of ‘knowledge workers’, and this kind of work, are expected to demand high levels of autonomy. This creates complex managerial dilemmas around how to balance autonomy with control and uncertainty and flexibility with efficiency. The analysis shows how a strong culture based on an acceptance of ambiguity (e.g. in roles, power relations, organizational routines and practices) promoted the development of a loyal, committed, effective workforce and sustained a fluid and flexible form of project working over time. Critically, ambiguity allowed individuals to sustain multiple identities as both ‘expert’ and ‘consultant’. This, coupled with a corporate identity premised on ‘élitism’, helped to maximize commitment to the work and minimize tensions between control and autonomy. Thus the culture that embraced ambiguity (a consensus that there would be no consensus) engendered a form of normative control whereby consultants operated freely and at the same time willingly participated in the regulation of their own autonomy.