Cane Contracting and Renegotiation: A Fixed Effects Analysis of the Adoption of New Technologies in the Cuban Sugar Industry, 1899-1929

1994 ◽  
Vol 31 (2) ◽  
pp. 141-175 ◽  
Author(s):  
Alan Dye
Keyword(s):  
Fixed Effects ◽  
New Technologies ◽  
Sugar Industry ◽  
Cuban Sugar

Cuban Sugar Industry

2011 ◽  
Author(s):  
Jonathan Curry-Machado
Keyword(s):  
Sugar Industry ◽  
Cuban Sugar

scholarly journals Spatial Economics, Urban Informatics, and Transport Accessibility

2021 ◽  
pp. 115-132
Author(s):  
Ying Jin
Keyword(s):  
Spatial Econometrics ◽  
Fixed Effects ◽  
New Technologies ◽  
Ordinary Least Squares ◽  
Dynamic Panel Data ◽  
Urban Structure ◽  
Transport Accessibility ◽  
City Regions ◽  
Intellectual Context ◽  
Central Pillar

AbstractOne central pillar in the development of urban science which is key to the development of simulation of models of urban structure is spatial econometrics. In this chapter, we outline the way in which ideas pertaining to accessibility which we define conventionally, as in transport economics, as the relative nearness and size of locations to one another, can be embedded in a wider econometric framework. We are thus able to explore how GDP (gross domestic product) of different locations is influenced by different spatial investments. To illustrate this, we first outline the intellectual context, followed by a review of the most relevant econometric models. We examine the data required for such models and look at various quantifications in terms of elasticities of business productivity with respect to transport accessibility, using ordinary least squares, time-series fixed effects, and a range of dynamic panel-data models which narrow down the valid range of estimates. We then show how the model is applied to Guangdong province (with its connections to Hong Kong and Macau), which is one of the three major mega-city regions and a leading adopter of new technologies in China.

Avoiding Holdup: Asset Specificity and Technical Change in the Cuban Sugar Industry, 1899–1929

1994 ◽  
Vol 54 (3) ◽  
pp. 628-653 ◽  
Author(s):  
Alan Dye
Keyword(s):  
Technical Change ◽  
Sugar Industry ◽  
Economic Structure ◽  
Asset Specificity ◽  
Western Region ◽  
Site Specificity ◽  
Incentive Structure ◽  
Post Colonial ◽  
Cuban Sugar ◽  
Relative Decline

Asset specificity can have profound influences on the economic structure of a country. An example is post-colonial Cuba. This article demonstrates that the existence of site specificity in assets generated problems of holdup for sugar mill owners in their contractual relations with cane suppliers. Recognition of that incentive structure offers an institutional explanation for the post-1900 concentration of U.S. investment in the eastern provinces. To reduce transaction costs, mill managers avoided investing in the western part of the island where the sugar industry was well established. A consequence was the relative decline of the western region.

scholarly journals Experimental and statistical evaluation of the performance of Chitosan as a coagulant in the treatment of sugar refinery effluents

2015 ◽  
Author(s):  
◽  
Ritha-Lorette Luti Pambi
Keyword(s):  
New Technologies ◽  
Sugar Industry ◽  
Low Cost ◽  
Oxygen Demand ◽  
Good Method ◽  
Settling Time ◽  
Simultaneous Increase ◽  
Water Recovery ◽  
Dissolved Solids ◽  
Sugar Refinery

The implementation of new water regulations from the local government has been a motivation for most industries to treat the effluent before disposal or reuse within the plant, in order to save costs and avoid sanctions. Tongaat-Huletts sugar refinery has therefore invested in this collaborative research with the Durban University of Technology in order to investigate new technologies for wastewater treatment and water recovery using an organic coagulant called chitosan. Chitosan is a natural non-toxic polymer extracted from the exoskeleton of crustaceans. Chitosan has gained extensive attention as a coagulant in the treatment of wastewaters from various industries. However, no attention has been given to the coagulation of effluents from the sugar industry using this polymer. In this work, chitosan coagulant (CCo) was prepared by dissolution of known amounts of chitosan powder in aqueous acid at 50℃. The solution was diluted to desired concentrations using distilled water at room temperature. The removal of impurities using chitosan was investigated for two effluent streams from the sugar refinery, namely the final effluent (FE) and the resin effluent (RE) by applying the one-factor-at-a-time (OFAT) method. The optimum chitosan loading was found to be 138 mg/l for the RE and 7.41 mg/l for the FE, beyond which the efficiency of the coagulant decreased. The coagulation of FE removed 97% of the total suspended solids (TSS), 61% colour and 35% chemical oxygen demand (COD). The treatment of RE resulted in the removal of 68% TSS, 30% colour and 15% COD due to its high content of impurities. Therefore, RE was not considered for statistical studies. The Box-Behnken (BBD) design, which is a statistical response surface methodology (RSM) model was used to study the simultaneous effect of pH, coagulant loading and settling time on the removal of the COD, TSS and colour, with the help of an overlay plot for the FE. The optimum values from the overlay plot were 92% for TSS, 83% for colour and 29% for COD. The model equations generated by the BBD for individual responses involved all the manipulated variables contrary to the OFAT which only considered one manipulated parameter per response. Moreover, the BBD allowed the simultaneous analysis of all the parameters and the identification of interactions which occur when the effect of one factor is dependent on the level of another. The most important interaction for the removal of TSS was the combination of the variation in pH and coagulant dosage. The COD removal was mostly affected by the interaction between the coagulant loading and the settling time. The colour removal increased with the simultaneous increase of the pH and the settling time. A comparative study between the wastewaters from the sugar industry, the brewery industry and milk processing industry revealed that the performance of the chitosan was also affected by the amount of total dissolved solids (TDS) in the wastewater. A model was developed relating the TSS, COD and TDS from all these wastewaters, and was used to predict the TSS removal for the effluent from the olive oil mills and the wastewater from the winery. Chitosan can be considered as a good alternative to inorganic and synthetic coagulants for the pre-treatment of the FE due to its ability to efficiently remove the levels of TSS and colour. Furthermore, the production of chitosan from crustacean shells is a good method of reducing pollution from the fishery industry. Chitosan can be produced locally at low cost due to both the abundance of crustacean shells in the coastal regions of South Africa and the simplicity of its preparation process. It is recommended that a mathematical model be developed to accurately predict the influence of chitosan on all types of effluent. Such a model will provide an indication of the performance of the chitosan and guide experimenters. It is further recommended that the effect of the use of organic coagulants on the destabilization of dissolved solids in wastewater be given greater attention.

scholarly journals Application of Multiple Unsupervised Models to Validate Clusters Robustness in Characterizing Smallholder Dairy Farmers

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Devotha G. Nyambo ◽  
Edith T. Luhanga ◽  
Zaipuna O. Yonah ◽  
Fidalis D. N. Mujibi
Keyword(s):  
Milk Yield ◽  
Fixed Effects ◽  
Prediction Accuracy ◽  
New Technologies ◽  
Production Systems ◽  
Expert Knowledge ◽  
Self Organizing Maps ◽  
Similar Information ◽  
Smallholder Dairy ◽  
Self Organizing

The heterogeneity of smallholder dairy production systems complicates service provision, information sharing, and dissemination of new technologies, especially those needed to maximize productivity and profitability. In order to obtain homogenous groups within which interventions can be made, it is necessary to define clusters of farmers who undertake similar management activities. This paper explores robustness of production cluster definition using various unsupervised learning algorithms to assess the best approach to define clusters. Data were collected from 8179 smallholder dairy farms in Ethiopia and Tanzania. From a total of 500 variables, selection of the 35 variables used in defining production clusters and household membership to these clusters was determined by Principal Component Analysis and domain expert knowledge. Three clustering algorithms, K-means, fuzzy, and Self-Organizing Maps (SOM), were compared in terms of their grouping consistency and prediction accuracy. The model with the least household reallocation between clusters for training and testing data was deemed the most robust. Prediction accuracy was obtained by fitting a model with fixed effects model including production clusters on milk yield, sales, and choice of breeding method. Results indicated that, for the Ethiopian dataset, clusters derived from the fuzzy algorithm had the highest predictive power (77% for milk yield and 48% for milk sales), while for the Tanzania data, clusters derived from Self-Organizing Maps were the best performing. The average cluster membership reallocation was 15%, 12%, and 34% for K-means, SOM, and fuzzy, respectively, for households in Ethiopia. Based on the divergent performance of the various algorithms evaluated, it is evident that, despite similar information being available for the study populations, the uniqueness of the data from each country provided an over-riding influence on cluster robustness and prediction accuracy. The results obtained in this study demonstrate the difficulty of generalizing model application and use across countries and production systems, despite seemingly similar information being collected.

Sign in / Sign up

Export Citation Format

Share Document