Regional Development in Kerala A Study of Malappuram District

The study makes an attempt to examine the inter regional variations in Kerala in economic development with respect to the important indicators of development over the period 1971 to 2001. The study takes districts as the unit of analysis because this is an attempt to find out the status of districts in Kerala.The study proved that there exists inter district disparities in economic development measured in terms of different indices used for analysis.. statistical estimation of variation proves that there is high degree of variation in industrial sector followed by social and economic infrastructure. The composite index of industrial development shows that the highest index is 1.395 which is five times greater than that of the lowest index 0.273. More or less the same pattern of differences are noticed in most of the indicators of the development. A ranking of the district on the basis of the overall development indicators shows that Malappuram is the least developed district in Kerala. In case of almost all indicators of development Malappuram is lagging behind all other districts.

Farm Poverty in Kerala: A case study of Alappuzha, Trissur, Palakkad and Wayanad

The present study was an attempt to analytically approach the problem of farm poverty in Kerala from an entirely different angle by incorporating an independently developed and reformulated definition of poverty line in terms of physical units of operational holdings (say, acre). The entire discussion on farm poverty emerged out of proper co-ordination of two important factors popularly considered as the distinct features of Iregional variations in farm productivity tried to highlight various grave issues deserving thorough introspection.

Inter- State Variations in Productivity trends and Technological Change in Indian industry

The present study entitled ‘Inter-State Variations in Manufacturing Productivity and Technological Changes in India’ covers a period of 38 years from l960 tol998-99. The study is mainly based on ASI data. The study starts with a discussion of the major facilitating factors of industrialization, namely, historical forces, public policy and infrastructure facilities. These are discussed in greater details in the context of our discussion on Perrox’s (1998) ‘growth pole’ and ‘development pole’, Hirschman’s (1958) ‘industrial centers’ and Myrdal’s ‘spread effect’ Most of the existing literature more or less agrees that the process of industrialization has not been unifonn in all Indian states. There has been a decline in inter-state industrial disparities over time. This aspect is dealt at some length in the third chapter. An important element that deserves detailed attention is the intra-regional differences in industrialisation. Regional industrialisation implies the emergence of a few focal points and industrial regions. Calcutta, Bombay and Madras were the initial focal points. Later other centers like Bangalore, Amritsar, Ahemedabad etc. emerged as nodal points in other states. All major states account for focal points. The analysis made in the third chapter shows that industrial activities generally converge to one or two focal points and industrial regions have emerged out of the focal points in almost all states. One of the general features of these complexes and regions is that they approximately accommodate 50 to 75 percent of the total industrial units and workers in the state. Such convergence is seen hands in glow with urbanization. It was further seen that intra-regional industrial disparity comes down in industrial states like Maharashtra, Gujarat and Uttar Pradesh.

Regional climate model applications on sub-regional scales over the Indian monsoon region: The role of domain size on downscaling uncertainty

Regional climate models are becoming increasingly popular to provide high resolution climate change information for impacts assessments to inform adaptation options. Many countries and provinces requiring these assessments are as small as 200,000 km2 in size, significantly smaller than an ideal domain needed for successful applications of one-way nested regional climate models. Therefore assessments on sub-regional scales (e.g., river basins) are generally carried out using climate change simulations performed for relatively larger regions. Here we show that the seasonal mean hydrological cycle and the day-to-day precipitation variations of a sub-region within the model domain are sensitive to the domain size, even though the large scale circulation features over the region are largely insensitive. On seasonal timescales, the relatively smaller domains intensify the hydrological cycle by increasing the net transport of moisture into the study region and thereby enhancing the precipitation and local recycling of moisture. On daily timescales, the simulations run over smaller domains produce higher number of moderate precipitation days in the sub-region relative to the corresponding larger domain simulations. An assessment of daily variations of water vapor and the vertical velocity within the sub-region indicates that the smaller domains may favor more frequent moderate uplifting and subsequent precipitation in the region. The results remained largely insensitive to the horizontal resolution of the model, indicating the robustness of the domain size influence on the regional model solutions. These domain size dependent precipitation characteristics have the potential to add one more level of uncertainty to the downscaled projections.