Institutional arrangements of outgrower sugarcane production in Southern Africa

ABSTRACT

Management models are needed that empower local communities to produce biofuel feedstock in a manner that drives rural development. Much can be learnt through the accumulated experiences of sugarcane outgrower schemes in southern Africa. Early schemes provided limited empowerment, but protected outgrowers from the risks of volatile sugar value chains. In later schemes, processing plants were responsible for all operations and simply paid dividends to participating farmers. More recent schemes offer full ownership, which comes with greater rewards and empowerment, but also exposure to risks. The underlying institutional structures of outgrower schemes largely dictate their performance, and thus the factors that affect their viability or collapse. To understand the different institutional arrangements of sugarcane outgrower schemes we undertake a comparative analysis of 13 schemes in southern Africa employing a political economy framework that uses the three key questions: ‘who owns what’, ‘who does what’, and ‘who gets what’.     

Economic Analysis for Ecosystem Service Assessments

The paper seeks to contribute to the expanding literature on ecosystem service assessment by considering its integration with economic analyses of such services. Focussing upon analyses for future orientated policy and decision making, we initially consider a single period during which ecological stocks are maintained at sustainable levels. The flow of ecosystems services and their contribution to welfare bearing goods is considered and methods for valuing resultant benefits are reviewed and illustrated via a case study of land use change. We then broaden our time horizon to discuss the treatment of future costs and benefits. Finally we relax our sustainability assumption and consider economic approaches to the incorporation of depleting ecological assets with a particular focus upon stocks which exhibit thresholds below which restoration is compromised.     

Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence

In this paper we develop flexible techniques for measuring the speed of output convergence between countries when such convergence may be of an unknown non-linear form. We then calculate these convergence speeds for various countries, in terms of half-lives, using a time-series data-set for 88 countries. These calculations are based on both nonparametric kernel regression and ‘fuzzy’ regression, and the results are compared with more restrictive estimates based on the assumption of linear convergence. The calculated half-lives are regressed, again in various flexible ways, on cross-section data for the degree of openness to trade. We find evidence that favors the hypothesis that increased trade openness is associated with a faster rate of convergence in output between countries.     

How well do children insure parents against low retirement income? An analysis using survey data from urban China

As population aging becomes more pronounced in the developing world, the uneven implementation of social safety nets raises important questions as to how well traditional family-based mechanisms insure elderly incomes when pension systems fail. Using a unique dataset from a recent household survey conducted in urban China, we find evidence that private transfers respond to low household income of retired workers when income falls below the poverty line. This finding is consistent with an altruistic motive for transfers at low levels of household income. At the same time, however, the transfer response to elderly pre-transfer income is not sufficient to fully cover shortfalls that arise with severe pension arrears and low retirement income.     

Analysing multi-level Monte Carlo for options with non-globally Lipschitz payoff

Giles (Oper. Res. 56:607–617, 2008) introduced a multi-level Monte Carlo method for approximating the expected value of a function of a stochastic differential equation solution. A key application is to compute the expected payoff of a financial option. This new method improves on the computational complexity of standard Monte Carlo. Giles analysed globally Lipschitz payoffs, but also found good performance in practice for non-globally Lipschitz cases. In this work, we show that the multi-level Monte Carlo method can be rigorously justified for non-globally Lipschitz payoffs. In particular, we consider digital, lookback and barrier options. This requires non-standard strong convergence analysis of the Euler–Maruyama method.      

Correcting for selectivity bias in the estimation of road crash costs

Police road crash data comprise a non-random sample of the true population of road crashes, the bias being due to the existence of crashes that are not notified to the Police. Heckman viewed similar problems as ‘omitted variables’ problems in that the exclusion of some observations in a systematic manner (so-called selectivity bias) has inadvertently introduced the need for an additional regressor in least squares procedures. In the case of Police road crash data, selectivity bias arises from factors affecting the notification of crashes to the Police, such as the number of vehicles in the crash and the type and location of the crash. Using Heckman's methodology for correcting for this selectivity bias, Police road crash data for Western Australia are reconciled with total road crash data in the estimation of the property damage costs of road crashes.     

ELECTION MANIFESTO POLICIES COMPARED

In this Forecast Release we compare the likely outcomes of the economic policies proposed by the three main contenders in the General Election. The results of some Dolicies. such as Labour's import controh and exchannge controls and the Allianie incomes policy, aie particularly dificult to evaluate using a conventional model; even for Conservative policies which are similar to those pursued so far, there remains considerable uncertainty about their consequences in future years. We have therefore prepared two forecasts for each of the three parties. One of these forecasts assumes that their policies are broadly successful, the other assumes they are unsuccessful.     

On the Inconsistency of Instrumental Variables Estimators for the Coefficients of Certain Dummy Variables

In this paper we consider the asymptotic properties of the Instrumental Variables (IV) estimator of the parameters in a linear regression model with some random regressors, and other regressors that are dummy variables. The latter have the special property that the number of non-zero values is fixed, and does not increase with the sample size. We prove that the IV estimator of the coefficient vector for the dummy variables is inconsistent, while that for the other regressors is weakly consistent under standard assumptions. However, the usual estimator for the asymptotic covariance matrix of the I.V. estimator for all of the coefficients retains its usual consistency. The t-test statistics for the dummy variable coefficients are still asymptotically standard normal, despite the inconsistency of the associated IV coefficient estimator. These results extend the earlier results of Hendry and Santos (Oxf Bull Econ Stat 67:571–595, 2005), which relate to a fixed-regressor model, in which the dummy variables are non-zero for just a single observation, and OLS estimation is used.