Income modeling using Quantile Functions

Department of Statistics, Cochin University of Science and Technology

Influence Of Forecasting, Planning And Controlling On The Performance Of Small And Medium Enterprises

Production Planning and Control (PPC) systems have grown and changed because of the developments in planning tools and models as well as the use of computers and information systems in this area. Though so much is available in research journals, practice of PPC is lagging behind and does not use much from published research. The practices of PPC in SMEs lag behind because of many reasons, which need to be explored This research work deals with the effect of identified variables such as forecasting, planning and control methods adopted, demographics of the key person, standardization practices followed, effect of training, learning and IT usage on firm performance. A model and framework has been developed based on literature. Empirical testing of the model has been done after collecting data using a questionnaire schedule administered among the selected respondents from Small and Medium Enterprises (SMEs) in India. Final data included 382 responses. Hypotheses linking SME performance with the use of forecasting, planning and controlling were formed and tested. Exploratory factor analysis was used for data reduction and for identifying the factor structure. High and low performing firms were classified using a Logistic Regression model. A confirmatory factor analysis was used to study the structural relationship between firm performance and dependent variables.

“Income, Livelihood and Education of Tribal Communities in Kerala – Exploring Inter Community Disparities

The overall objective of the study is to examine whether the tribal communities in Kerala can be considered a coherent group in terms of select indicators of development by focusing on nine major tribal communities. The study also aims to bring out the intercommunity differences if any in aspects of livelihood options and education level of the tribal communities in Kerala

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

A Quantile based analysis of income data

Dept. of Statistics, CUSAT

Study on Microcredit in Kerala with Special Reference to Employment and Income Generation through Microenterprises and Livelihood Projects

This study aimed to study the evolution and substance of microfinance as a major tool for combating poverty at the global and national level. The development of micro finance in Kerala is briefly discussed. It also indicates the importance and role of microcredit in bringing the poor up in the society through entrepreneurial initiatives. The current trends in the field are also discussed, leading to the need of the present research.

Effects of red brick production on land use, household income, and greenhouse gas emissions in Khartoum, Sudan

In Khartoum (Sudan) a particular factor shaping urban land use is the rapid expansion of red brick making (BM) for the construction of houses which occurs on the most fertile agricultural Gerif soils along the Nile banks. The objectives of this study were to assess the profitability of BM, to explore the income distribution among farmers and kiln owners, to measure the dry matter (DM), nitrogen (N), phosphorus (P), potassium (K) and organic carbon (C_org) in cow dung used for BM, and to estimate the greenhouse gas (GHG) emissions from burned biomass fuel (cow dung and fuel wood). About 49 kiln owners were interviewed in 2009 using a semi-structured questionnaire that allowed to record socio-economic and variable cost data for budget calculations, and determination of Gini coefficients. Samples of cow dung were collected directly from the kilns and analyzed for their nutrients concentrations. To estimate GHG emissions a modified approach of the Intergovernmental Panel on Climate Change (IPCC) was used. The land rental value from red brick kilns was estimated at 5-fold the rental value from agriculture and the land rent to total cost ratio was 29% for urban farms compared to 6% for BM. The Gini coefficients indicated that income distribution among kiln owners was more equal than among urban farmers. Using IPCC default values the 475, 381, and 36 t DM of loose dung, compacted dung, and fuel wood used for BM emit annually 688, 548, and 60 t of GHGs, respectively.

Employment and Income of Workers on Indonesian Oil Palm Plantations: Food Crisis at the Micro Level

The importance of oil palm sector for Indonesia is inevitable as the country currently serves as the world’s largest producer of crude palm oil. This paper focuses on the situation of workers on Indonesian oil palm plantations. It attempts to investigate whether the remarkable development of the sector is followed by employment opportunities and income generation for workers. This question is posed within the theoretical framework on the link between trade liberalisation and labour rights, particularly in a labour-intensive and low-skilled sector. Based on extensive field research in Riau, this paper confirms that despite the rapid development of the oil palm plantation sector in Indonesia, the situations of workers in the sector remain deplorable, particularly their employment status and income. This also attests that trade liberalisation in the sector adversely affects labour rights. The poor working conditions also have ramifications for food security at the micro level.

Poverty targeting and income impact of subsidised credit on accessed households in the Northern Mountainous Region of Vietnam

This paper uses the data of 1338 rural households in the Northern Mountainous Region of Vietnam to examine the extent to which subsidised credit targets the poor and its impacts. Principal Component Analysis and Propensity Score Matching were used to evaluate the depth of outreach and the income impact of credit. To address the problem of model uncertainty, the approach of Bayesian Model Average applied to the probit model was used. Results showed that subsidised credit successfully targeted the poor households with 24.10% and 69.20% of clients falling into the poorest group and the three bottom groups respectively. Moreover, those who received subsidised credit make up 83% of ethnic minority households. These results indicate that governmental subsidies are necessary to reach the poor and low income households, who need capital but are normally bypassed by commercial banks. Analyses also showed that ethnicity and age of household heads, number of helpers, savings, as well as how affected households are by shocks were all factors that further explained the probability at which subsidised credit has been assessed. Furthermore, recipients obtained a 2.61% higher total income and a 5.93% higher farm income compared to non-recipients. However, these small magnitudes of effects are statistically insignificant at a 5% level. Although the subsidised credit is insufficient to significantly improve the income of the poor households, it possibly prevents these households of becoming even poorer.

Forecasting Global Temperature Variations by Neural Networks

Global temperature variations between 1861 and 1984 are forecast usingsregularization networks, multilayer perceptrons and linearsautoregression. The regularization network, optimized by stochasticsgradient descent associated with colored noise, gives the bestsforecasts. For all the models, prediction errors noticeably increasesafter 1965. These results are consistent with the hypothesis that thesclimate dynamics is characterized by low-dimensional chaos and thatsthe it may have changed at some point after 1965, which is alsosconsistent with the recent idea of climate change.s

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult to achieve because the relative values of the forecast components often fail to behave in a way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It has been shown that cause-specic mortality forecasts are pessimistic when compared with all-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approach of using log mortality rates and forecasts the density of deaths in the life table. Since these values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbing state), they are intrinsically relative rather than absolute values across decrements as well as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison (1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that the unit sum constraint is honoured. The structure of the best-known, single-decrement mortality-rate forecasting model, devised by Lee and Carter (1992), is expressed in compositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortality by cause of death for Japan

Salud y crecimiento económico: un modelo de generaciones traslapadas, expectativa de vida endógena y capital humano

Este trabajo desarrolla un modelo de generaciones traslapadas con expectativa de vida endógena y capital humano. Recoge parte de la evidencia empírica acerca de la transición demográfica explicada por Notestein en 1945, donde variaciones en la longevidad de los individuos afectan positivamente el crecimiento económico de un país. El modelo establece que la falta de incentivos para invertir en salud estanca a una economía en una trampa de pobreza y muestra que incrementos en la productividad en el sector de producción de capital humano, al igual que cambios tecnológicos sesgados al uso intensivo del mismo, incrementan el producto de estado estacionario y pueden sacar a una economía de una trampa de pobreza.

An approximation to the digital divide among low income people in Colombia, Mexico and Perú: two composite indexes

El estudio analiza los determinantes de uso y acceso a las tecnologías de información y comunicación en personas de bajos ingresos en pasases como Colombia, México y Perú. El punto central está en analizar las diferencias entre países de acuerdo a diferentes variables socioeconómicas. Se encuentra que la variable que más explica el nivel de acceso digital es la escolaridad. De otro lado no se encuentra una brecha por género sino en Perú. Los resultados también indican que cuando solo se tienen en cuenta las tecnologías más ‘avanzadas’, las diferencias entre la población son más notorias

The impact of a permanent Income shock on the situation of women in the household: the case of a pension reform in Argentina

Transfers to women may affect their bargaining power within the household and consequently their well-being. We analyze the effects of the 2004/2005 pension reform in Argentina, that resulted in an unexpected and substantial increase in permanent income for around 1.8 million women, on outcomes arguably related to women’s bargaining power within the household. We estimate the effects of the reform in the probability of divorce/separation, the distribution of household chores, and the probability of women being the head of the household, using a Difference-in-Differences approach. Our results show that despite the low divorce probability among seniors, transfers to senior women have substantial effects on their situation in the household. More specifically, we find that the reform had statistically significant effects on the probability of divorce/separation increasing it by 1.8 − 2.7 percentage points implying an increase of around 18 − 19% on the divorce/separation rate of 60 − 65 year old women. Moreover, the probability of being the head of the household also increased by 2.8−3.3 percentage points representing an increase of 7−19% in the probability amongst women of 60 − 65 years of age. In the case of married women, the probability of being the head of the household increased by 1.3 − 1.5 percentage points, which represents an increase of 20 − 22%. Results show that the distribution of household chores within the couples was also affected by the reform. More precisely, the probability that the wife is the only person in charge of the housework decreased by 5 percentage points, an 11% decrease. The participation of husbands in housework, however, did not change significantly.