Management of common property resources : intertemporal exploitation of village dams in Sri Lanka

Village dams in Sri Lanka are owned in common by the villagers and the water in them is used for in-situ public good purposes and for the irrigation of their private rice lands. The water resource of the dam is replenished every year by the runoff from its catchment during the monsoons. Within a year, the water storage is dynamic, being influenced by periodic inflows and evaporative losses. The advent of the new rice technology, consisting of high-yielding and short-aged varieties of rice, has increased the scarcity value of water. However, there are inherent inefficiencies in its exploitation due to commonality. Making use of a two-period model and the concept of user cost, the common ownership of the dam and its contents have been shown to lead to inefficiently heavy extractions of water during the Wet Season with the result that the scarcity in the Dry Season is exacerbated. This inefficiency has been shown by comparing the net social benefits under the commonality allocation and that under the efficient allocation. The analysis incorporates explicitly the substitution possibilities between land and water so that the optimal land area is chosen for each level of application of water. The empirical approach developed in the thesis involves two aspects. First, the water storage is characterized by a transfer function model. A monte carlo simulation model, developed on the basis of this, is used to simulate the water storage behaviour for a number of years. Second, the marginal net social benefits for water use in the Wet Season and the associated user costs are derived. This utilizes a simulation model of the crop irrigation system, which is placed within a discrete dynamic programming framework. The water storage and the soil moisture are included as the state variables. This model implements the efficient intraseasonal distribution of a given amount of water. Crop response functions derived via this for different areas of rice are used to define a crop response frontier and a user cost frontier. At an efficient interseasonal allocation, the marginal net social benefit and the marginal social cost are equated. The commonality allocation of water and the associated net benefits are derived by a simulation of the traditional irrigation and growth of rice. The analysis is repeated for several rainfall years. This analysis enables the efficiency gain due to the resolution of commonality and the gain due to the adoption of the new technology of rice production to be estimated separately. On an average, the efficiency gain has been estimated to be approximately 25 per cent of the overall gains* The analysis also determines the optimal use tax and the allocation of land and water in each of the two seasons

A network science approach to analysing manufacturing sector supply chain networks: Insights on topology

Due to the increasingly complex nature of the modern supply chain networks (SCNs), a recent research trend has focussed on modelling SCNs as complex adaptive systems. Despite the substantial number of studies devoted to such hypothetical modelling efforts, studies analysing the topological properties of real world SCNs have been relatively rare, mainly due to the scarcity of data. This paper aims to analyse the topological properties of twenty-six SCNs from the manufacturing sector. Moreover, this study aims to establish a general set of topological characteristics that can be observed in real world SCNs from the manufacturing sector, so that future theoretical work modelling the growth of SCNs in this sector can mimic these observations. It is found that the manufacturing sector SCNs tend to be scale free with degree exponents below two, tending towards hub and spoke configuration, as opposed to most other scale-free networks which have degree exponents above two. This observation becomes significant, since the importance of the degree exponent threshold of two in shaping the growth process of networks is well understood in network science. Other observed topological characteristics of the SCNs include disassortative mixing (in terms of node degree as well as node characteristics) and high modularity. In some networks, we find that node centrality is strongly correlated with the value added by each node to the supply chain. Since the growth mechanism that is most widely used to model the evolution of SCNs, the Barabasi - Albert model, does not generate scale-free topologies with degree exponent below two, it is concluded that a novel mechanism to model the growth of SCNs is required to be developed

Topological Structure of Manufacturing Industry Supply Chain Networks

Empirical analyses of supply chain networks (SCNs) in extant literature have been rare due to scarcity of data. As a result, theoretical research have relied on arbitrary growth models to generate network topologies supposedly representative of real-world SCNs. Our study is aimed at filling the above gap by systematically analysing a set of manufacturing sector SCNs to establish their topological characteristics. In particular, we compare the differences in topologies of undirected contractual relationships (UCR) and directed material flow (DMF) SCNs. The DMF SCNs are different from the typical UCR SCNs since they are characterised by a strictly tiered and an acyclic structure which does not permit clustering. Additionally, we investigate the SCNs for any self-organized topological features. We find that most SCNs indicate disassortative mixing and power law distribution in terms of interfirm connections. Furthermore, compared to randomised ensembles, self-organized topological features were evident in some SCNs in the form of either overrepresented regimes of moderate betweenness firms or underrepresented regimes of low betweenness firms. Finally, we introduce a simple and intuitive method for estimating the robustness of DMF SCNs, considering the loss of demand due to firm disruptions. Our work could be used as a benchmark for any future analyses of SCNs

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Water resource optimisation in small dams in the dry zone of Sri Lanka : a time series analysis and stochastic simulation approach

ThesisThesis, 1981Thesis (M.A.), Australian National University, 198