It is evident from the above discussion that for 8 states namely Chhattisgarh, Madhya Pradesh, Rajasthan, Haryana, Jharkhand, Uttar Pradesh, West Bengal, and Odisha none of the subsectors has emerged as significant. But it cannot be directly deduced from this that the structure of Services Sector is similar in all these states. Therefore, on further analysis it was tried to ascertain whether the various subsectors were significantly different across these 8 states or not. For this purpose the regression equations were tested for all the 6 subsectors for each of the 8 states by using t-test and F-test. For testing the Interstate variations in the structure of services no significant values of differential intercept for any subsectors is evident. The regression analysis or ANOVA for 8 states was conducted to verify the results. The significance of differential coefficient would be established by using the t test and overall significance was established through F test. The F test here was calculated through t 2 . The preliminary results indicated that the structure of these states is likely to be identical or similar. But we cannot conclude this to be true econometrically true. With that, further exploring and confirming these results analysis is extended further.
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As is well known, the trickle down effect implies that the increase in GDP will reduce inequality i.e. the redistributive policies of the government will reduce income inequality by keeping up growth rate. Is the proposition effective among major Indian states? In the context of the above result it may be said that as majority of Indian population are poor, the issue of economic growth is important but not at the cost of depletion in human development issues. If economic growth is attained at the cost of increasing inequality among the individuals of the economy, then the situation is not at all viable. Economic growth should always be coupled with uniform wealth distribution. If under any situation there occurs any conflict between the economic growth and the distribution of income, then the government should construct its policy in such a way that this conflict gets resolved. So, the policy of attaining inclusive growth for Indian states should be formalized in such a way that equality in income distribution and economic growth should be attained simultaneously. Redistribution of income by fiscal methods must be ensured so that poverty and income inequality might be reduced. So, the set of established procedures of politically motivated policy certainty of government in Indian states should be executed in such a way that there must be a balance between economic growth and human development in all those states .
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As the preceding section establishes the presence of high degree of concentration of credit in a few states particularly during the phase of economic liberalization it is natural to have disparity in distribution of industrial credit across the states of India. We primarily quantify such a disparity in terms of the measure of Coefficient of Variations (C.V). Figure 14 presents the year wise trend of C.V for all the four subsectors and the aggregate industrial sector with one year gap between the years. Like the trends of concentration ratios of all the industrial sectors we here also observe that the trends of C.V of the aggregate industrial sector and the manufacturing sector follow the similar falling and rising paths respectively in the pre reform and post reform periods. The two trends look like saucer U type. Other three sectors' trends of C.V also look like U shaped but with some degrees of fluctuations. The maximum disparity in credit is observed for the mining and construction sectors. There is a departure of the electricity sector from the other sectors in the sense that the sector experienced a declining C.V like that of its trend in the concentration ratios. Hence, we summarize that, except the electricity sector, all the subsectors of the industrial sector and the aggregate industrial sector as a whole produced rising disparity in delivery of credit across the states. The electricity sector has to some extent contributed to minimizing the extent of disparity so that the aggregate industrial sector's C.V shows a smooth function.
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DOI: 10.4236/tel.2017.76124 1822 Theoretical Economics Letters both together (states and industries) and portray its findings in a simplified manner was largely ignored. This paper is an honest attempt to simplify the complex area of comparative productivity analysis for a geographically multifa- ceted country—India. The intent of this paper is multifold: first: it uses a simple technique growth accounting (Solow Residual) to estimate productivity and simplify its findings. Second: it takes 19 major Indian states and their 15 manu- facturing industries into account; this therefore, performs a comparative analysis of TFP (total factor productivity) at good disaggregated level. Third: it takes good care of data, measurement and variable issues which have generated good amount of debate in the past two decades and showed by Kathuria et al . . Fourth, it makes policy recommendations and contributes towards productivity literature in the context of India.
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We have attempted to make a comparative study of marginal farms at the inter-state level and compared it with the all India level. We have compared West Bengal and India as in West Bengal more than 80% farms are marginal. We have also undertaken similar study in the intra-state level for West Bengal. The data on land holdings, operated area and average size of land holding of marginal farms across 19 major Indian states have been collected from Agricultural Census, Agriculture Census Division, Department of Agriculture, Cooperation & Farmers Welfare, Government of India, 2000-01, 2005-06 and 2010-11. On the other hand, district- wise data on land holdings, operated area and average size of land holding of marginal farms have been collected from Land and Land Reforms Department and Evaluation Wing, Directorate of Agriculture, Government of West Bengal.
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We first propose a measure of effective SBRs for the 15 major Indian states for the period 1994-2005. We then exploit the differences in institutional quality across Indian states (as measured by our SBR index) to examine the effects of the SBR measure on total factor productivity growth across industries and states and over time. India provides a rich empirical context to study the impact of effective state- business relations on manufacturing productivity for three reasons. Firstly, differences in regional industrial performance persist, in spite of the dismantling of the License Raj regime in 1991 and significant trade liberalization since the 1990s. 2 These policy reforms should have led to a convergence of industrial productivity growth across Indian States, but this has not happened. Secondly, India’s federal structure and the significant political autonomy and independence in legislative powers enjoyed by state governments, along with regional variations in the collective
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Politicians have worn out the expression of “Secularism” like anything for their petty political gains. They trade “religion” for their vote banks under the Purdah (Veil) of Secularism. Under the garb of Secularism, they feed Communalism. They misused the slogan Sarva Dharma Samabhava to woo voters. Result is that Secularism got politicized and reduced to “political vendetta”. It lost all credibility that it‟d got when it was accepted by Indian nation after independence. The vision with which it was adopted by Indian Republic shrank to mere political rhetoric. It was trampled like anything by political stooges who know no low for their mere political gains. Glaring examples of which are Sikh riots of 1984, Gujarat riots of 2002 and Muzaffarnagar riots, lately.
This trend in credit deposit ratio is found to be similar to that of the real SDP for both the time points 1991-92 and 2005-06 (see figure- 4 and 5). A simple correlation estimates show that the relation between credit-deposit ratio and SDP shows an increased positive correlation from 0.41 to 0.65 between two time points (1991-92 and 2005-06). This indicates that in states where the credit-deposit ratio is high the output in the corresponding state is also high and vice-versa (see figure-4 and 5). Similarly the plot of the number of bank branches and SDP shows that development of financial sector is important for output growth (see figure 6 and 7). To understand the cause and effect relationship, we estimate the cross-sectional regression to see the impact of credit deposit ratio and number of bank branches on real SDP at both the points (1991-92 and 2005-06). Regression result shows that credit deposit ratio has a positive and significant effect on the SDP and also a substantial improvement in the effect of the credit deposit ratio on SDP (the coefficient changed from in 1991-92 5.87 to 14.56 in 2005-06). Although the effect of number of bank branches is positive but its coefficient is very small as compared to that of credit deposit ratio. Increase in the value of coefficient of number of bank branches from 0.017 in 1991-92 to 0.8 in 2005-06 shows that increased reach of banks are important for the economic growth. Thus, cross-sectional estimation also testifies the well established and argued effect of development in the financial sector on output.
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The RFID has wide range of use in the present time. The origin of the RFID can be traced from the World War-2 when the Germans, Americans, Japanese and British Army utilized the radars to monitor the activities of their aircraft . Later the department of agriculture in the United states used the RFID’s in 1950’s to study the movement of cows for the health purposes . The RFID system came into use in the late 1970’s when a group of scientists in the USA worked on a system to track down the nuclear material . This marked the era of RFID, which eventually gained popularity in the business world . RFID is the leading edge with an immense growth potential and a vivid spectrum of use in the prevailing world . In 2008 Gartner Inc. forecasts that the RFID market achieved the worldwide revenue of 1.2 billion which was 31% more than the revenue of the past year . Ever since RFID has seen sky-high expansion and has gained tremendous popularity in the corporate world . In the field of animal detection, the growth is such that any sudden change in the diet of the animals, any bacteria or virus the animals can be automatically detected .In the efficient management of warehouse, logistics based management is done so as to increase the productivity and reduce the cost of operation as the RFID can visualize the supply chain processes .The further implementation of this smart reader is visualized in the library management which provides better operational efficiency and precision but is a limitation because of the low budget. A method for measurement of the backscattered signal from the tag has
The outcome of any production process is mainly explained by the resource use efficiency of that production unit. To get the resource use efficiency of any production process, benchmarking finds wide applicability. The two main techniques used for benchmarking analysis are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). In general, certain non medical inputs have a significant impact on the health status of the population particularly in developing economies (Khursheed, 2017). The channel through which such factors influence health is quite diverse. For example, literacy by increasing access to information enhances the utilization of existing medical services and, hence, affects health. Of all the medical inputs, public health expenditure, which signifies the commitment of the State towards improving community health status, undoubtedly has a beneficial impact on health. In India due to NRHM the public health spending has improved and it has reversed the trend of falling public health expenditure (Khursheed, 2017). On the basis of Stochastic Frontier Analysis (SFA), Japan with efficiency score of 0.994 ranked at the top followed by China with the efficiency score of 0.993 India, with the efficiency score of .919 ranked 66th ahead of USA with its efficiency score of 0.914 (Ogloblin, 2011). On the basis of SFA the mean efficiency of the fourteen States during 1986-1995 in India was 0.692. Kerala with a widely recognized commitment towards the development of its social sector and Maharashtra with the fastest growing per capita real income were the two best performers in terms of efficiency in production of health. The economically poor States of Rajasthan, Uttar Pradesh, Madhya Pradesh, and Odhissa were the worst performing States with their efficiency scores of 0.64, 0.40, 0.339 and 0.23 respectively. Bihar despite its backwardness was ranked as the fifth most efficient State. However, Bihar's relatively higher rank in terms of efficiency in health production does not get reflected in its health outcome indicators (Chakrabatty and Rao, 2005).
Before 1991, Indian business success was a function of ambition, licenses, government contacts, and an understanding of the bureaucratic system. Decisions were based on connections, rather than the market or competition. Business goals reflected a continuation of the “Swadeshi” moment, which promoted import substitution to attain economic freedom the west. Pre-1991 polices were inward looking and geared towards the attainment of self-reliance. During this era, entrepreneurship was subdued, capital was limited and India had very few success stories.
Abstract : It is a well-known fact that Article-1 of the Indian Constitution says that India is a „Union of States.‟ Thus, the Indian Constitution does not declare itself as a „Federation‟. In fact, nowhere in the Constitution the term „Federation‟ has been used. Instead of it the term „Union‟ has been used. The dictionary meaning of „Union‟ is uniting or being united. Thus, the emphasis is on unity while the federation is a system of government in which unity and diversity are both taken into consideration and a balance between the two is sought. While moving, the „Draft Constitution‟ on November 4, 1948 in the Constituent Assembly Dr. B.R. Ambedkar explained why the term „Union‟ instead of federation was used. He stated that the Drafting Committee wanted to make it clear that though India was to be a federation, the federation was not the result of an agreement by the States to join in a federation, and that the federation not being the result of an agreement, no State has a right to separate from it. The federation is a union because it is indestructible. Though the country and the people may be divided into different States for convenience of administration, the country is one integral whole, its people a single people living under a single emporium derived from a single source. The Drafting Committee thought that it was better to make it clear at the outset rather than to leave it to speculation or to dispute. The present research paper highlights the tendency of regionalism in Indian Federalism in the present scenario.
All is not rosy with expatriates. The anxiety and the hassles in getting an H-IB visa continues to be legendary. The experience of many shows that working under H-IB is a nightmarish experience. Apart from the procedural difficulties, some migrants also speak about their difficulties faced with agents who pay discriminatory wages and insist on long hours of work. Migrants also speak about instances where brokers have illegally taken a cut from their wages and also occasions where agents have put restrictions on an employee who quits or switches jobs. This kind of shady deals have been brought to light in a report published by The Center for Investigative Reporting (CIR),a non-profit American organization. Center for Investigative Reporting (CIR) reporters Matt Smith and journalist Jennifer Gollan have raised several issues associated with the high-tech 'in-sourcing' software industry of US software industry, which thrives on the inflow of highly-skilled Indian tech workers on H-1B visas. These reporters pierced through the wall of silence of the Indian expatriates in the US software industries and brought to light several dubious roles of agents who recruit software engineers .It is learnt that often agents withhold salaries and demand cash for visas .Unfortunately , according to Center for Investigative Reporting, few victims are willing to challenge staffing companies or agents in the court because judgments against Indian workers who have violated their contracts by switching jobs or quitting before time can incur penalties in Excess of $50,000. One software engineer from Madurai ,Gobi Muthuperiasamy ,took a risk and spent three years in court when his labour broker sued him for switching jobs. Although Muthuperiasamy won the case, and didn't have to pay his broker a penny, he was still poorer by $25,000 in legal costs. Muthuperiasamy is among the few who have fought back. There are many anonymous H-IB visa holders who suffer in silence . 'Client charged 87.5/hr. I am paid 30/hr. 10,000 USD bond in India. I hate my life' is one of the several postings on the CIR site. Rajiv Dhabadkar, founder of the advisory National Organisation for Software & Technology Professionals (NO STOPS) claims that the website receives about 300-400 posts every day, often anonymous, detailing work-related horrors. Dhabadkar says that he often advises clients to look elsewhere for migration other than US.
Table 8 presents the estimated coefficients for six specifications of the reduced-form equations for wages in registered manufacturing, as suggested by equation (9). All spec- ifications contain similar explanatory variables and definitions as the reduced-form em- ployment equations presented earlier in table 7. One slight modification is that we now include, as an extra variable, the lagged value of the number of workers in registered manufacturing divided by state population (labour participation): increases in the par- ticipation rate should reduce the wages paid by firms in Indian states. Specification (i) presents the basic equation with Solow residuals. The estimated parameters are signed in accordance with the theoretical model and common intuition, with the number of facto- ries per capita having the largest effect: As more firms opt to locate in a particular state, the demand for labour increases and, for a given population, the wage for workers is bid up.
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One of the book publishers who claimed he was likely to purchase print from India over the next three years had some interesting information to share during the phone interview. The firm mentioned that Indian print service providers were more likely to print color books but would also be interested in printing commercial sheet fed jobs should an opportunity arise. The firm spent the bulk of its money on printing color books offshore. The firm found it viable and much cheaper to print color books offshore. The publishing firm’s average print run that was offshored was 8,000 to 10,000 copies, and the average cost savings was between 40% and 60%.
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Dhara Shah in 2011, states the success in international assignment can be achieved with effective preparation of the employee. Cross – cultural training is very important for the success of an expatriate in foreign assignment. The previous research by Lakha 2005, Meijering & Van Hoven 2009, Upadhya & Vasavi 2006, Upadhya 2009, Mathew & Obgonna 2009, and Xiang 2001) suggests the Indian IT expatriates also experience some issues with communication society and racial discrimination.
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The results of forecast of prices of cotton in the market are shown in the Table 2. The forecasts indicate that there are narrow variations in between the actual and forecasted values of prices of cotton in the selected states. In Kharif season the cotton crop is harvested during December to January. Forecast shows that market prices of cotton, would be ruling in the range of ` 4,500 – 4,900 per quintal in kharif harvesting season, 2017-18. The prices of cotton in the market during harvesting period would be high in Karnataka, Andhra Pradesh and Maharashtra i.e. ` 4,500, 4,450 and 4,400 per q respectively. The prices would be low i.e. ` 4,350 and 4,300 per q in Gujarat and Haryana respectively. Forecasted prices of cotton by using ARIMA (0,1,0) model in India is shown in Fig. 3. This forecast is based on past data and model and that actual market price may not turn out to be the same as forecasted.
South Indian cuisine is equally popular in other parts of India. In other parts of this country, ask anyone for which other Indian cuisine they would prefer for a change. Most would reply 'South Indian'. Four different states, like: Andhra, Tamil Nadu, Karnataka and Kerala constitute of the southern part of India. There are four different schools too in south Indian cuisine. So south Indian cuisine is a vegetarian's delight. Another striking feature in south Indian cuisine is the use of coconut oil. Coconut oil lends the south Indian food a very special flavor. In most of the delicacies, coconut is also used profusely. Rice is staple food here too. Idly, Dosa, Vadas and Uttapams, made from rice ground with lentil, are popular south Indian specialties, mostly in Tamil Nadu. Also try spicy, oily and aromatic Chettinad cuisine while you are in Tamil Nadu. In some parts of South India like Andhra Pradesh, Biriyani prepared from rice and mixed with
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The Class Progression Index between the two decades of 2001 and 2011 show a falling trend in most states except Uttarakhand, where a positive trend is seen. Subsequently, the growth rates of the CPI from 2001-11 for these states are negative. This shows an unhealthy nature of urbanisation, with higher negative growth witnessed in the states where the convergence of the CPR between the two periods across class sizes as desired is not witnessed. For instance, West Bengal is a case where the progression from Class VI to V has actually worsened from 0.93 to 0.90 from 2001 to 2011, while there is only a minute fall in CPR from Class II to I from 2001-11 (0.67 to 0.63). The largest inequalities in these terms are seen in the states with the most negative growth rates in the CPI, namely West Bengal, Odisha, Chattisgarh and Jharkhand leading the rest. It is therefore important to interpret these ratios and indices carefully, so as to arrive at the true picture of the spread of the urbanisation in these states.
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Indigenous children of Canada (First Nations, Inuit, and Métis) and the United States (American Indian, Alaska Natives) face many health dispari- ties compared with the general American and Canadian populations. Oral health disparities for Indigenous children exemplify many of the inequities and the major need for health promotion, disease prevention, and early care services in these communities. Various organizations have provided guidelines on health promotion, disease prevention, and early visits for dental care; however, the severity of dental disease and the barriers to care in Indigenous communities require special consideration.
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