Indigenous Credit Associations in Botswana: An Application of Elinor Ostrom\u27s Common-Pool Resource Analysis

In this paper I attempt to analyze and explain the important of certain indigenous credit agreements in Botswana. Rotating Savings and Credit Associations are agreements made by a group of people who create a communal fund which rotates around the group until each member had had access to the pooled resource. These agreements are informal and most commonly found in the poorer traditional sectors of Botswana’s economy. Furthermore, I attempt to explain why these agreements can be best understood using Elinor Ostrom’s common-pool resource analysis. This framework explains why these agreements are so successful in creating a source of capital, which is sustainable and long-enduring, for many entrepreneurs who belong to the poor sectors of the economy. Also, using this analysis, certain policy decisions can be critiqued as to how best to categorize and foster these indigenous institutions so that more people can have access to informal credit

Strike Three: Umpires' Demand for Discrimination

We explore umpires' racial/ethnic preferences in the evaluation of Major League Baseball pitchers. Controlling for umpire, pitcher, batter and catcher fixed effects and many other factors, strikes are more likely to be called if the umpire and pitcher match race/ethnicity. This effect only exists where there is little scrutiny of umpires' behavior -- in ballparks without computerized systems monitoring umpires' calls, at poorly attended games, and when the called pitch cannot determine the outcome of the at-bat. If a pitcher shares the home-plate umpire's race/ethnicity, he gives up fewer runs per game and improves his team's chance of winning. The results suggest that standard measures of salary discrimination that adjust for measured productivity may generally be flawed. We derive the magnitude of the bias generally and apply it to several examples.

Strike Three: Umpires' Demand for Discrimination

We explore how umpires' racial/ethnic preferences are expressed in their evaluation of Major League Baseball pitchers. Controlling for umpire, pitcher, batter and catcher fixed effects and many other factors, strikes are more likely to be called if the umpire and pitcher match race/ethnicity. This effect only exists where there is little scrutiny of umpires' behavior – in ballparks without computerized systems monitoring umpires' calls, at poorly attended games, and when the called pitch cannot determine the outcome of the at-bat. If a pitcher shares the home-plate umpire's race/ethnicity, he gives up fewer hits, strikes out more batters, and improves his team's chance of winning. The general implication is that standard measures of salary discrimination that adjust for measured productivity may be flawed. We derive the magnitude of the bias generally and apply it to several examples.strategic interactions, worker evaluation, wage equations, economics of sports

Extending the multi-level method for the simulation of stochastic biological systems

The multi-level method for discrete state systems, first introduced by Anderson and Higham [Multiscale Model. Simul. 10:146--179, 2012], is a highly efficient simulation technique that can be used to elucidate statistical characteristics of biochemical reaction networks. A single point estimator is produced in a cost-effective manner by combining a number of estimators of differing accuracy in a telescoping sum, and, as such, the method has the potential to revolutionise the field of stochastic simulation. The first term in the sum is calculated using an approximate simulation algorithm, and can be calculated quickly but is of significant bias. Subsequent terms successively correct this bias by combining estimators from approximate stochastic simulations algorithms of increasing accuracy, until a desired level of accuracy is reached. In this paper we present several refinements of the multi-level method which render it easier to understand and implement, and also more efficient. Given the substantial and complex nature of the multi-level method, the first part of this work (Sections 2 - 5) is written as a tutorial, with the aim of providing a practical guide to its use. The second part (Sections 6 - 8) takes on a form akin to a research article, thereby providing the means for a deft implementation of the technique, and concludes with a discussion of a number of open problems.Comment: 38 page

Factors controlling the net ecosystem production of cryoconite on Western Himalayan glaciers

Ikke OAIn situ experiments were conducted to determine the net ecosystem production (NEP) in cryoconite holes from the surface of two glaciers (Patsio glacier and Chhota Shigri glacier) in the Western Himalaya during the melt season from August to September 2019. The study aimed to gain an insight into the factors controlling microbial activity on glacier surfaces in this region. A wide range of parameters, including sediment thickness, TOC %, TN %, chlorophyll-a concentration, altitudinal position, and grain size of the cryoconite mineral particles were considered as potential controlling factors. From redundancy analysis, the rate of Respiration observed in cryoconite at Chhota Shigri glacier was predominantly explained by sediment thickness in cryoconite holes (37.1% of the total variance, p < 0.05) with Photosynthesis largely explained by the chlorophyll-a content of the sediment (39.6%, p < 0.05). NEP was explained primarily by the TOC content and sediment thickness in cryoconite holes (35.8% and 22.1% respectively, p < 0.05). The altitudinal position of the cryoconite is strongly correlated with biological activity, suggesting that the stability of cryoconite holes was an important factor driving primary productivity and respiration rate on the surface of Chhota Shigri glacier. We calculated that the number of melt seasons required to accumulate organic carbon in thin sediment layers (< 0.3 cm), based on our measured NEP rates, ranged from 11 to 70 years, indicating that the organic carbon in cryoconite holes largely derives from allochthonous inputs, such as elsewhere on the glacier surface. Phototrophic biomass in the same thin sediment layer of cryoconite was estimated to take atleast 4 months to be produced in situ (with mean estimated time upto 1.7 ± 1.5 years). Organic matter accumulated inside the cryoconite holes both through allochthonous deposition and via biological activity on the glacier surface in these areas may have the potential to export dissolved organic matter and associated nutrients to downstream ecosystems. Given the importance of Himalayan glaciers as a vital water source for millions of people downstream, this study highlights the need for further investigation in aspects of the quantification of in situ produced organic matter and its impact on supraglacial melting in the Himalay

Proton supplier role of binuclear gold complexes in promoting hydrofunctionalisation of nonactivated alkenes

Density functional theory (DFT) was used to investigate PR 3 AuOTf-catalyzed hydrofunctionalisation of nonactivated alkenes using acetic acid and phenol where OTf = triflate (CF 3 SO 3- ). The gold(i) complex itself is found to be unlikely to operate as the π-activator due to its relatively low electrophilicity. Instead, the concurrent coordination of two gold(i) complexes to a nucleophile (PhOH or AcOH) enhances the acidity of the latter\u27s proton and causes the ensuing binuclear complex to serve as a strong proton supplier for activating the alkene π-bonds. Alternatively, the binuclear complex is also susceptible to produce a hidden HOTf. This hidden acid is accessible for hydrofunctionalization to occur but it is not in sufficient concentration to decompose the final product

Robustly simulating biochemical reaction kinetics using multi-level Monte Carlo approaches

In this work, we consider the problem of estimating summary statistics to characterise biochemical reaction networks of interest. Such networks are often described using the framework of the Chemical Master Equation (CME). For physically-realistic models, the CME is widely considered to be analytically intractable. A variety of Monte Carlo algorithms have therefore been developed to explore the dynamics of such networks empirically. Amongst them is the multi-level method, which uses estimates from multiple ensembles of sample paths of different accuracies to estimate a summary statistic of interest. {In this work, we develop the multi-level method in two directions: (1) to increase the robustness, reliability and performance of the multi-level method, we implement an improved variance reduction method for generating the sample paths of each ensemble; and (2) to improve computational performance, we demonstrate the successful use of a different mechanism for choosing which ensembles should be included in the multi-level algorithm