International Journal of Innovative Science and Technology, 2020
In this paper, the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models for active... more In this paper, the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models for active and exponential smoothing HOLT for removed rates has been estimated using daily time series data from 1st April to 14 th September 2020.The active and removed rates are computed from cumulative confirmed, active, recovered and deceased cases. It has been found that ARIMA (0, 1, 1) and Holt exponential smoothing Models are best fit for active and removed rates respectively. Normalized BIC is 0.577and 0.898 for active and removed rates respectively and is minimum among all the six models considered. Lack of fit of models is tested by Ljung-BoX Q statistic. The pvalue is 0.925 and 0.840 for active and removed rates respectively Since for both the rates p-value is greater than 0.05, hence conclude that our model does not show a lack of fit. On the basis of our analysis, active rate will be nullified latest by 5th January 2020, if everything goes best, as P M of India has assured on eve of Independence Day that vaccine for corona will be available very soon. Otherwise by 9 th February 2021 if the past trend continued and in worst situation it will tends to zero on 26th March 2021. We expect the removed rates will reach 100 percent by 20 TH October 2020 if everything goes best and by 5th January 2021 if the past trend continued. On the assumptions that Pandemic will come to an end when removed rate in the population tends to 100 percent and active rate to zero percent. Thus on the basis our analysis we expect that COVID-19 Pandemic may come to end latest either by 9 th February 2021 or 26th March 2021 subject to condition that the social distance and safely measures remains vigilance to stabilize and control the pandemic and in achieving India's recovery from COVID-19.
International journal of innovative science and technology, 2024
The risk of indebtedness across region level is higher among the households having less human and... more The risk of indebtedness across region level is higher among the households having less human and physical assets and human resources. However, because of their better borrowing capacities, the extent of indebtedness among them is significantly higher than other segment of the rural society. The same is true about the households self-employed in various agricultural and non-agricultural activities in the rural areas. The region level analysis also rejects the contention that the higher consumptive expenditure of the rural people as a cause of their risk of indebtedness whereas the extent of indebtedness confirms that consumptive expenditure plays a major role in their indebtedness. Similarly, the hypothesis of agricultural prosperity and indebtedness going together lacks wider generalization for household located in all the regions except NorthWest states in Logistic regression and in NorthWestern , Eastern and Southern region in Tobit regression. Exposure of rural households to higher risk and uncertain situations like droughts, floods, crop failure due to pest attack pushes rural households deeper into debt. I.
International Journal of Economics, Commerce and Management Research Studies, 2019
Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model has been estimated using month... more Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model has been estimated using monthly time series data on Consumer Price Index for Industrial workers(CPIIW) for a period from January 1990 to January 2019 and two years forecast of CPIIW was made It has been found that the best fitted model is ARIMA (0, 1, 1) X (0, 1, 1) 12, Normalized Bayesian Information Criteria (BIC) was 0.057, stationary R 2 = 0.44 and R 2 = 0.98.The model was further validated by Ljung-Box test (Q = 23.67 and p>0.09) with no significant autocorrelation between residuals at different lag times. The study shows that CPIIW will remains more or less steady during the winter season (October to March) and jumped approximately 18 to 20 points during summer/rainy season (April to September) for each of the year from 2019 to 2020. The dearness allowance/relief to the Central Government Employee/ pensioners shall be of the order of 12.8 percent in January 2019 which may rise to 26.5 percent in July 2020.
Increased endowment of physical and human resources reduces the dependence of rural households on... more Increased endowment of physical and human resources reduces the dependence of rural households on external loans but augments their capacity to borrow. Higher risk and uncertainty seriously impede the rural credit by discouraging both borrowing and lending in rural credit. Also, high level of agricultural development augments both propensity and capacity of borrowings to meet their money requirement for various purposes.
Rural Households with better physical and human resource base or comparatively more self sufficie... more Rural Households with better physical and human resource base or comparatively more self sufficient to satisfy their needs are less prone to the problem of indebtedness. However, because of their better borrowing capacities, the extent of indebtedness is significantly higher among them than the other segment of the rural population. Exposure to higher risk due to natural calamities push increasing proportion of rural households depress to debt.
This paper analyses the characteristics of enterprises engaged in Hospitality Industry using Nati... more This paper analyses the characteristics of enterprises engaged in Hospitality Industry using National Sample survey data for four surveys conducted during the period 1983-84 to 2006-07. Number of enterprises have an increasing trend over a span of 20 years from 1983-84 to 2003-04 and average annual growth rate of the enterprises varies between 2.5 % to 4.7 % registering a highest growth rate of 4.7% during the period from 1993-94 to 2001-02 (Post Economic Reforms) .It has been found that 20.6 lakh enterprises were engaged in Hotels & Restaurants activity, generating an employment of order of 51.3 lakh persons, thereby, contributing to gross value addition to the tune of Rs. 14415.91 crore with Rs. 30974.07 crore investment in fixed assets in 2006-07. Gross Value Added per enterprise was Rs.789176 for Hotel activity, which happened to be highest among all enterprises in entire services sector (excluding Trade) in 2006-07.Labour productivity in Hotels has increased significantly whereas in restaurant it reduces marginally in a period from 2001-02 to 2006-07. It has been estimated that a total of 20.0 lakh enterprises may be engaged in hotels and restaurant industry generating an employment of order of 56.0 lakh by the end of first decade this century. The correlation coefficient between number of enterprises and number of tourist, (domestic as well as foreign visiting India) for the post economic reforms period 1991-2009 was found to be 0.81 and is highly significant (t stat = 5.69. p< 0.001). The elasticity of employment with respect to value added was found to be 0.292 and is statistically Significant (t stat =13.59, p < 0.0001). The estimates indicates that 3.0%. 3.25% and 3.50% growth in employment in Hospitality industry is achievable with an economic growth rate of approximately 10.2%, 11.1% and 12.0 % provided the average employment elasticity of 0.292 continues during the period 2009-10 to 2014-15.
Indebtedness is a multi-faceted problem. It is very interesting to understand this problem among ... more Indebtedness is a multi-faceted problem. It is very interesting to understand this problem among different occupations of rural households. In this paper, an attempt has been made to study the incidence and extent of indebtedness among rural households of different occupations. For this, we have used the sixth decennial All-India Rural Debt and Investment Survey (AIDIS) carried out by the National Sample Survey Organization (NSSO) during the 59th NSS round. It is found that there is low risk and high extent of indebtedness among the households having self-employed in agricultural and non-agricultural occupations in the country. These two occupational groups are on top of the asset and income distribution ladders in rural India. Scheduled caste household self-employed as cultivators, artisans, trading, etc. seems to have drawn substantial benefit from affirmative actions that resulted in their lesser risk of sinking into indebtedness. On the contrary, there may be some location disadvantage of being settled in remote areas and ownership of low quality land may be responsible for pushing scheduled tribe cultivators more into the risk of indebtedness. The occupational group wise analysis also rejects the oft-cited reason of consumptive nature as one of the main reasons for indebtedness in the rural household but holds true regarding the extent of indebtedness. Similarly, the occupation wise analysis confirms the thesis of debt and prosperity going together but it seems to be more relevant for the cultivator group of household
The present paper analyses employment scenario in India on the basis of quinquennial NSS surveys.... more The present paper analyses employment scenario in India on the basis of quinquennial NSS surveys. It has been observed that there has been a remarkable change in the labour forces, work forces and employment trend in India during the period 2004-05 to 2009-10. The labour forces participation rate (LFPR) fell to 40 per cent in 2009-10 from 43 per cent in 2004-05 on usual UPSS basis and in case of female it fell sharply to 23.3 per cent from 29.4 per cent. The declines in the LFPR brought down the growth rate of labour force to 0.18 percent in 2009-10 from 2.93 percent in 2004-05 but in case of female decline is very rapid from 3.87 percent to (-) 2.93 percent. Low LFPR may be hiding a large "shadow army" of labour, waiting to join the labour force in future The growth of workforce has decelerated from 2.78 per cent per year in the period 2004-05 to 0.25 per cent in 2009-10.There is distinct downward swing (eleven time fall in the workforce growth rate), with only 5.69 million jobs have been added during this period. In case of females worker, it has come down from 3.78 per cent per year to ( -) 2.88 percent. This may be due to the fact that the number of young people in education, therefore out of the workforce, has increased dramatically causing a drop in the labour participation rate. The total number of young working-age (15-24) people who continued in educational institutions doubled from about 30 million in 2004-05 to over 60 million in 2009-10. Cutting across the rural urban divide, the share of self employed workers has decreased from 56.4 per cent in 2004-05 to 50.6 per cent in 2009-10, resulting a reduction of 5.8 percentage point. The share of regular wage-salaried workers has, however, stagnated at around 16 percent per cent, while that of casual workers has increased from 28.3 to 32.8 per cent. The gender bias in casual wage payment for labours engaged in works other than public works is low in rural areas (0.68) than in urban areas (0.58 But it is low for the casual labour engaged in public works and lowest for casual workers engaged in MGNREG public works. The share agriculture & allied activities in employment has declined from 58.4 percent to 53.20 percent during the period 2004-05 to 2009-10. In absolute figures, the workforce has shrink to 247.62 million in 2009-10 from 268.7 million in 2004-05, registering annual rate of deceleration of ( -) 1.62 percent per annum, resulting withdrawal of 21.07 millions work force. The share of work force in industrial sector has increased to 22.50 percent in 2009-10 from 18.18 percent in 2004-05, registering annual acceleration of 3.67 percent per annum. The rate of growth workforce in construction sector has jumped to 11.7 percent in 2009-10 from 7.64 in 2004-05 percent. The share of work force in service sector has marginally increased to 25.30 percent in 2009-10 from 23.4 percent in 2004-05, registering annual acceleration of 1.84 percent. Financing, insurance, real estate & business has registered highest rate7.21 percent per annum in work force. The Trade, hotels and restaurants & communication is the largest employment provider, absorbing 43 per cent of total work force in service sector.he elasticity of employment with respect to value added was found to be 0.26 with 95 percent confidence interval (0.22 -0.29) and is statistically Significant (t stat =14.9106, p < 0.001). Assuming an overall elasticity 0.26, the projection showed that with annual growth rate of 8.6 percent in GDP and 40.9 percent LFPR, it will take up to 2016-17 to reach the point when work force equal labour that is, there would be no unemployment.
International Journal of Innovative Science and Technology, 2020
In this paper, the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models for active... more In this paper, the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models for active and exponential smoothing HOLT for removed rates has been estimated using daily time series data from 1st April to 14 th September 2020.The active and removed rates are computed from cumulative confirmed, active, recovered and deceased cases. It has been found that ARIMA (0, 1, 1) and Holt exponential smoothing Models are best fit for active and removed rates respectively. Normalized BIC is 0.577and 0.898 for active and removed rates respectively and is minimum among all the six models considered. Lack of fit of models is tested by Ljung-BoX Q statistic. The pvalue is 0.925 and 0.840 for active and removed rates respectively Since for both the rates p-value is greater than 0.05, hence conclude that our model does not show a lack of fit. On the basis of our analysis, active rate will be nullified latest by 5th January 2020, if everything goes best, as P M of India has assured on eve of Independence Day that vaccine for corona will be available very soon. Otherwise by 9 th February 2021 if the past trend continued and in worst situation it will tends to zero on 26th March 2021. We expect the removed rates will reach 100 percent by 20 TH October 2020 if everything goes best and by 5th January 2021 if the past trend continued. On the assumptions that Pandemic will come to an end when removed rate in the population tends to 100 percent and active rate to zero percent. Thus on the basis our analysis we expect that COVID-19 Pandemic may come to end latest either by 9 th February 2021 or 26th March 2021 subject to condition that the social distance and safely measures remains vigilance to stabilize and control the pandemic and in achieving India's recovery from COVID-19.
International journal of innovative science and technology, 2024
The risk of indebtedness across region level is higher among the households having less human and... more The risk of indebtedness across region level is higher among the households having less human and physical assets and human resources. However, because of their better borrowing capacities, the extent of indebtedness among them is significantly higher than other segment of the rural society. The same is true about the households self-employed in various agricultural and non-agricultural activities in the rural areas. The region level analysis also rejects the contention that the higher consumptive expenditure of the rural people as a cause of their risk of indebtedness whereas the extent of indebtedness confirms that consumptive expenditure plays a major role in their indebtedness. Similarly, the hypothesis of agricultural prosperity and indebtedness going together lacks wider generalization for household located in all the regions except NorthWest states in Logistic regression and in NorthWestern , Eastern and Southern region in Tobit regression. Exposure of rural households to higher risk and uncertain situations like droughts, floods, crop failure due to pest attack pushes rural households deeper into debt. I.
International Journal of Economics, Commerce and Management Research Studies, 2019
Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model has been estimated using month... more Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model has been estimated using monthly time series data on Consumer Price Index for Industrial workers(CPIIW) for a period from January 1990 to January 2019 and two years forecast of CPIIW was made It has been found that the best fitted model is ARIMA (0, 1, 1) X (0, 1, 1) 12, Normalized Bayesian Information Criteria (BIC) was 0.057, stationary R 2 = 0.44 and R 2 = 0.98.The model was further validated by Ljung-Box test (Q = 23.67 and p>0.09) with no significant autocorrelation between residuals at different lag times. The study shows that CPIIW will remains more or less steady during the winter season (October to March) and jumped approximately 18 to 20 points during summer/rainy season (April to September) for each of the year from 2019 to 2020. The dearness allowance/relief to the Central Government Employee/ pensioners shall be of the order of 12.8 percent in January 2019 which may rise to 26.5 percent in July 2020.
Increased endowment of physical and human resources reduces the dependence of rural households on... more Increased endowment of physical and human resources reduces the dependence of rural households on external loans but augments their capacity to borrow. Higher risk and uncertainty seriously impede the rural credit by discouraging both borrowing and lending in rural credit. Also, high level of agricultural development augments both propensity and capacity of borrowings to meet their money requirement for various purposes.
Rural Households with better physical and human resource base or comparatively more self sufficie... more Rural Households with better physical and human resource base or comparatively more self sufficient to satisfy their needs are less prone to the problem of indebtedness. However, because of their better borrowing capacities, the extent of indebtedness is significantly higher among them than the other segment of the rural population. Exposure to higher risk due to natural calamities push increasing proportion of rural households depress to debt.
This paper analyses the characteristics of enterprises engaged in Hospitality Industry using Nati... more This paper analyses the characteristics of enterprises engaged in Hospitality Industry using National Sample survey data for four surveys conducted during the period 1983-84 to 2006-07. Number of enterprises have an increasing trend over a span of 20 years from 1983-84 to 2003-04 and average annual growth rate of the enterprises varies between 2.5 % to 4.7 % registering a highest growth rate of 4.7% during the period from 1993-94 to 2001-02 (Post Economic Reforms) .It has been found that 20.6 lakh enterprises were engaged in Hotels & Restaurants activity, generating an employment of order of 51.3 lakh persons, thereby, contributing to gross value addition to the tune of Rs. 14415.91 crore with Rs. 30974.07 crore investment in fixed assets in 2006-07. Gross Value Added per enterprise was Rs.789176 for Hotel activity, which happened to be highest among all enterprises in entire services sector (excluding Trade) in 2006-07.Labour productivity in Hotels has increased significantly whereas in restaurant it reduces marginally in a period from 2001-02 to 2006-07. It has been estimated that a total of 20.0 lakh enterprises may be engaged in hotels and restaurant industry generating an employment of order of 56.0 lakh by the end of first decade this century. The correlation coefficient between number of enterprises and number of tourist, (domestic as well as foreign visiting India) for the post economic reforms period 1991-2009 was found to be 0.81 and is highly significant (t stat = 5.69. p< 0.001). The elasticity of employment with respect to value added was found to be 0.292 and is statistically Significant (t stat =13.59, p < 0.0001). The estimates indicates that 3.0%. 3.25% and 3.50% growth in employment in Hospitality industry is achievable with an economic growth rate of approximately 10.2%, 11.1% and 12.0 % provided the average employment elasticity of 0.292 continues during the period 2009-10 to 2014-15.
Indebtedness is a multi-faceted problem. It is very interesting to understand this problem among ... more Indebtedness is a multi-faceted problem. It is very interesting to understand this problem among different occupations of rural households. In this paper, an attempt has been made to study the incidence and extent of indebtedness among rural households of different occupations. For this, we have used the sixth decennial All-India Rural Debt and Investment Survey (AIDIS) carried out by the National Sample Survey Organization (NSSO) during the 59th NSS round. It is found that there is low risk and high extent of indebtedness among the households having self-employed in agricultural and non-agricultural occupations in the country. These two occupational groups are on top of the asset and income distribution ladders in rural India. Scheduled caste household self-employed as cultivators, artisans, trading, etc. seems to have drawn substantial benefit from affirmative actions that resulted in their lesser risk of sinking into indebtedness. On the contrary, there may be some location disadvantage of being settled in remote areas and ownership of low quality land may be responsible for pushing scheduled tribe cultivators more into the risk of indebtedness. The occupational group wise analysis also rejects the oft-cited reason of consumptive nature as one of the main reasons for indebtedness in the rural household but holds true regarding the extent of indebtedness. Similarly, the occupation wise analysis confirms the thesis of debt and prosperity going together but it seems to be more relevant for the cultivator group of household
The present paper analyses employment scenario in India on the basis of quinquennial NSS surveys.... more The present paper analyses employment scenario in India on the basis of quinquennial NSS surveys. It has been observed that there has been a remarkable change in the labour forces, work forces and employment trend in India during the period 2004-05 to 2009-10. The labour forces participation rate (LFPR) fell to 40 per cent in 2009-10 from 43 per cent in 2004-05 on usual UPSS basis and in case of female it fell sharply to 23.3 per cent from 29.4 per cent. The declines in the LFPR brought down the growth rate of labour force to 0.18 percent in 2009-10 from 2.93 percent in 2004-05 but in case of female decline is very rapid from 3.87 percent to (-) 2.93 percent. Low LFPR may be hiding a large "shadow army" of labour, waiting to join the labour force in future The growth of workforce has decelerated from 2.78 per cent per year in the period 2004-05 to 0.25 per cent in 2009-10.There is distinct downward swing (eleven time fall in the workforce growth rate), with only 5.69 million jobs have been added during this period. In case of females worker, it has come down from 3.78 per cent per year to ( -) 2.88 percent. This may be due to the fact that the number of young people in education, therefore out of the workforce, has increased dramatically causing a drop in the labour participation rate. The total number of young working-age (15-24) people who continued in educational institutions doubled from about 30 million in 2004-05 to over 60 million in 2009-10. Cutting across the rural urban divide, the share of self employed workers has decreased from 56.4 per cent in 2004-05 to 50.6 per cent in 2009-10, resulting a reduction of 5.8 percentage point. The share of regular wage-salaried workers has, however, stagnated at around 16 percent per cent, while that of casual workers has increased from 28.3 to 32.8 per cent. The gender bias in casual wage payment for labours engaged in works other than public works is low in rural areas (0.68) than in urban areas (0.58 But it is low for the casual labour engaged in public works and lowest for casual workers engaged in MGNREG public works. The share agriculture & allied activities in employment has declined from 58.4 percent to 53.20 percent during the period 2004-05 to 2009-10. In absolute figures, the workforce has shrink to 247.62 million in 2009-10 from 268.7 million in 2004-05, registering annual rate of deceleration of ( -) 1.62 percent per annum, resulting withdrawal of 21.07 millions work force. The share of work force in industrial sector has increased to 22.50 percent in 2009-10 from 18.18 percent in 2004-05, registering annual acceleration of 3.67 percent per annum. The rate of growth workforce in construction sector has jumped to 11.7 percent in 2009-10 from 7.64 in 2004-05 percent. The share of work force in service sector has marginally increased to 25.30 percent in 2009-10 from 23.4 percent in 2004-05, registering annual acceleration of 1.84 percent. Financing, insurance, real estate & business has registered highest rate7.21 percent per annum in work force. The Trade, hotels and restaurants & communication is the largest employment provider, absorbing 43 per cent of total work force in service sector.he elasticity of employment with respect to value added was found to be 0.26 with 95 percent confidence interval (0.22 -0.29) and is statistically Significant (t stat =14.9106, p < 0.001). Assuming an overall elasticity 0.26, the projection showed that with annual growth rate of 8.6 percent in GDP and 40.9 percent LFPR, it will take up to 2016-17 to reach the point when work force equal labour that is, there would be no unemployment.
Uploads
Papers by Kulwinder Kaur