BCKV , West Bengal, INDIA. BCKV , West Bengal, INDIA. BCKV , West Bengal, INDIA

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2 Extent of Technological Change in Paddy Cultivation over Eastern Region of India during last four decades S. Chatterjee a *, S. Banerjee b, L. K. Murmu b and P. Bandopadhyay c a Assistant Professor in Agricultural Economics, AICRP-IFS, Directorate of Research, BCKV , West Bengal, INDIA b M.Sc. Research Scholar, Department of Agricultural Economics, BCKV , West Bengal, INDIA b Ph.D. Research Scholar, Department of Agricultural Economics, BCKV , West Bengal, INDIA c Professor in Agronomy, Department of Agronomy, BCKV , West Bengal, INDIA *Corresponding author: Tel.: , address: soumitra.soum123123@gmail.com (S. Chatterjee) Introduction: Rice is the major cereal crop grown in India. It covers nearly a one-fourth of the gross irrigated area in India (Chatterjee et. al. 2013), with vastly diverse conditions from below the sea-level in parts of Kerala state to, on the hills up to an elevation of almost 3000 m above mean sea level in Himachal Pradesh, Jammu and Kashmir states (Nirmala et. al. 2009). In India, this diverse rice growing conditions are mainly classified into five major ecologies namely, Irrigated, Uplands, Rainfed Lowlands, Deep water and Coastal wetlands with a wide level of variation in input use as well as cost structure. However, a serious concern has been raised on the long run sustainability of the productivity effects of Green Revolution technologies under irrigated ecosystem due to degradation of natural resource-base. However the majority of agricultural and food policy initiatives over Research and Development (R&D) wing has given a top priority for the rice improvement in terms of resource allocation both capital and human resources (Adlas et.al., 2006). The crop breeders have released nearly 650 varieties of rice over the past 35 years in India. The varieties released till mid 70 s were largely higher yielder while subsequent generations of those varieties were mainly either with improved resistance to pests and diseases or with grain quality (Janaiah, 2004). These improvements in the successive generations of HYV seeds are expected to reflect in the productivity growth in three ways viz., lowering the cost of production, higher market price per unit output, and lowering yield instability. However, a serious concern has been raised on the long run sustainability of the productivity effects of Green Revolution technologies under irrigated ecosystem due to degradation of natural resource-base. Many studies (Flinn and De Datta 1984; Cassman and Pingali, 1995, Nambiar, 1988, Pingali et. al. 1997, Greenlands, 1997; Yadav, et al., 2000, Dawe et. al. 2000; Kumar and Yadav, 2001) *Corresponding author: Tel.: , address: soumitra.soum123123@gmail.com (S. Chatterjee)

3 reported that rice yields were either declining or stagnant after the 1980s under the intensive irrigated rice systems due to various resource-degradation problems. Most of these studies were however largely based on experimental data designed with a specific objective under controlled environments (fixed nutrient doses, variety, other management practices, etc.) in the research farms and adaptive research trials. These studies provide an impression that productivity impact of technological progress has been vanishing in the irrigated systems. But, the yield trends of those HYVs from the controlled environment may not be matched with those of the farmers fields (real farm environment) because farmers access and adopt new variety seeds, and adjust their farm practices over the period to cope up with the changing production and micro policy environments. It is also essential to recognize a fact that the yield growth is not a true measure of technology impact, as it does not net out the effect of input growth from output growth. Thus, total factor productivity (TFP) growth is a correct measure of productivity impact of technical change (Evenson and Pray, 1991). Keeping the above views in mind, the present study attempts to evaluate the extent of technological change in paddy cultivation across the eastern states of India during last four decades () in order to judge the effect of Green Revolution on the productivity change of Rice cultivation over the periods. For this, the authors have computed Total Output Indices (TOI), Total Input Indices (TII) and Total Factor Productivity Indices (TFPI) for paddy across four Eastern states (Assam, Bihar, Orissa and West Bengal) of India over. Subsequently, correlation matrix and multiple linear stepwise regression analysis between changes in output over changes in various inputs used in the production process to identify the most contributable factor over the decade studied. Materials and Methods: Divisia Tornqvist-Theil index model, a modified translog homogeneous production function has been used to calculate the TOI, TII and TFPI as proposed by Diewert (1976) with its usual functional form: Total Output Index (TOI): Total Input Index (TII):

4 The equation can be simplified as: Tornqvist Aggregate Output Index is given by: Similarly Tornqvist Aggregate Input Index is given by: Where t = year, Q jt = Output of j th crop at t th year, Q jt-1 = Output of j th crop at (t 1) th year, S jt = Proportional value share of j th crop to total value of output at t th year. S jt-1 = Proportional value share of j th crop to total value of output at (t 1) th year. X it = Quantity of i th input at t th year, X it-1 = Quantity of i th input at (t 1) th year. S it = Share of i th input to total cost of inputs at t th year. S it-1 = Proportional of cost share of i th input to total cost of inputs at (t 1) th year, P jt-1 = Harvest price of j th crop at (t 1) th year, P jt = Harvest price of j th crop at t th year, C it-1 = Cost of i th input at (t 1) th year, C it = Cost of i th input at t th year. Total Factor Productivity Index (TFPI): Further, O Donnell (2012) defines TFP as the ratio between aggregate output to aggregate input. However TFP growth is a measurement of output growth divided by a measure of input growth, which is how the productivity growth is usually defined [e.g. Griliches (1961); Jorgenson and Griliches (1967)]. In general, Total Factor Productivity at t th year is measured by: Here, a multiplicatively-complete [O Donnell 2008] Tornqvist TFP indexes has been used as: For the productivity measurement over a long period of time, Output, Input & TFP indices are computed on the basis of Chain Base Index expressed as percentages. With chain-linking, an

5 index is calculated for two successive periods t and (t-1) over the whole period t 0 to T, (sample from t=0 to t=t) and the separate indexes are then multiplied together: TOI* (t) = TOI (1). TOI (2) TOI (t-1) Similarly, TII* (t) = TII (1). TII (2) TII (t-1) Total Factor Productivity Index (TFPI): The growth rates of TOI, TII and TFPI for paddy in the Eastern states of India over the year has been calculated using simple Logest estimates with the following exponential form as proposed by Lewin (1970) earlier on his article on compound interest and again that has been modified by Lewin (1981) himself. Where the dependent Y-value is a function of the independent time period (t), b is the growth factor over time t, a is the intercept term (constant). The significance t-test of growth rate at 5% level has been calculated from the following equation as: t cal (0.05) = b / se (b) Where b is the growth coefficient and se (b) represents standard error of the growth coefficient b. t cal (0.05) > t tab (0.05) denotes the significance of growth factor at 5% level. Stepwise multiple regression analysis followed the model function: where, Y = total output, X 1 : quantity of seeds used, X 2 : quantity of fertilizer used, X 3 : quantity of organic manure used, X 4 : quantity of irrigation charges, X 5 : total machine hour required, X 6 : plant protection cost, X 7 : bullock labour used (pair hours), X 8 : total human labour used (man hours) X 9 : interest on working capital, β 0 : constant, β 1.. β 9 : regression coefficients of respective variables for t th over (t-1) th year. The step-wise regression analysis has been done here to identify the most contributory factors responsible for the TFP change over decade and to exclude the irrelevant factors from the regression model. In this regard, it has to mentioned that

6 for convenience of analysis and interpretation, the author has included only nine variables (the paid out and operational cost components) in computing the TFP and multiple regression analysis and not the entire input level (excluding fixed factors). The entire analysis has been performed using statistical package SAS 9.3 version and SPSS 13.0 version. Data: Relevant secondary data on area, production and productivity of rice for the period to , across the Eastern states (Assam, Bihar, Orissa and West Bengal) of India as well as input use and cost of cultivation data have been collected and compiled from the official website of Directorate of Economics and Statistics, Ministry of Agriculture, Government of India (eands.dacnet.nic.in) as well as the various periodical issues of Cost of Cultivation of Principal Crops in India (Anonymous 1991, 1996, 2000, 2003, 2007 and 2009a). Results and Discussion: The present study comprises of two major sections. Firstly, the authors have tried to estimate the overall as well as decadal change in output, input and total factor productivity for paddy in the Eastern states of India in the form of chain based index over and find out their behavioural change in form of exponential equation and growth rates over the period. In the second part, the authors have identified the key factor contributors for the change in productivity of paddy over time through computation of correlation and regression between changes in output over change in various factors used in paddy cultivation over the year. 1. Extent of Technological Change in Paddy Cultivation in Eastern states of India over 1.1. Estimation of Exponential Growth Rate of Total Output Indices (TOI), Total Input Indices (TII) and Total Factor Productivity Indices (TFPI) for paddy: Table 1.1 represents the decade-wise growth rates of Total Output Indices (TOI), Total Input Indices (TII) and Total Factor Productivity Indices (TFPI) for paddy in the Eastern states of India over. It has been visualized from the table that TFP for paddy in the Eastern states has been stagnant and in declining trend over the year barring some few decades. However, the overall TFP change in Assam has been recorded 0.85% while it is 0.67% in Bihar, 0.40% in Orissa, 0.78% in the state of West Bengal and 0.67% too in the entire Eastern region of India. The study finds a similarity with the work of Jha and Kumar (1998), while measuring the changes in TFP for rice across the states of India came into conclusion that the Eastern states

7 tend to drag the national average of TFP growth rates down. TFP gains its significance prominence in the second decade in Assam (1.93%), Orissa (3.14%), West Bengal (4.08%) and in the entire Eastern region of India (3.03%) while it is dominant in the third decade in the state of Bihar (4.18%). The change in output has been found to be maximum in the second decade in West Bengal (7.70%) surpassing well with the input growth rate (3.37%). The entire Eastern region has shown the similarity in output growth rate (5.72%) over input change (2.51%) in the second decade too ensures that the technological change in paddy cultivation has occurred in the Eastern India in 80s. Nowadays, due to profuse use of inorganic fertilizer and plant protection chemicals in paddy field, the inherent fertility status of the soil has been destroyed resulting technological stagnancy or even declination in productivity of crop. 2. Determination of source of productivity change of Paddy in the Eastern states of India 2.1. & 2.2. Correlation and Multiple Regression analysis for identification of factor contribution of paddy in the Eastern states of India over the period Table 2.1 and Table 2.2 have featured the correlation and multiple linear regressions between changes in output over change in various factors used in paddy cultivation over the decades. It has been found from Table 2.1 that productivity change in paddy for the state of Assam has significantly strong correlation with seed use (0.517), irrigation charges (0.345), bullock labour use (0.417), human labour use (0.566) and interest on working capital (0.489). Barring interest on working capital, no significant correlation was observed in the first decade ( to ). In the second decade ( to ), seed use and human labour use came into the picture along with a combination of bullock labour and machine labour use (correlation coefficient and respectively) indicating introduction of farm mechanization in Assam which can substitute the bullock labour use. The effect of machine labour along with bullock labour use supported by human labour has been gaining strong prominence with the productivity change in the third decade (correlation coefficient 0.847, and respectively) with the entry of inorganic fertilizer use (correlation coefficient 0.782) in Assam. Finally, it is the quality seed use along with the human labour use that came into the party at the last decade of paddy cultivation in the state of Assam. Productivity change in paddy has been dominated by the change in human labour use in Bihar in almost all the decades. Like Assam, the productivity change in the second decade has been strongly guided by seed use (0.842). Farm machinery use (-0.701) along with plant protection measures (-0.681) has the

8 significant detrimental effect on change in paddy productivity in Bihar at the second decade. Productivity change of paddy in Orissa has been widely correlated with the change in seed use pattern (0.489), organic manure use (0.390), bullock labour use (0.431) and human labour (0.551) followed by a significant negative effect on farm mechanization (-0.431). Farm mechanization has negative impact on change in productivity in all the decades in Orissa indicating dominance of traditional cultivation practices even after four decades of Green Revolution in India. Seed use along with human labour utilization and interest on working capital became the prime factor contributor over the productivity change in West Bengal throughout the period. Inclusion of plant protection chemicals in the third decade (correlation coefficient 0.718) has shown a strong positive impact on productivity change of paddy in this decade. Overall, the change in paddy productivity over the entire region has shown strong positive correlation with quality seed material use, utilization of human labour in all the decades under study. While inclusion of plant protection measures has been exerted significant positive impact on productivity change in later phases. Table 2.2 identifies the key factor contributor due to overall change in paddy productivity across the states of Eastern India over the period. Human labour use along with use of quality seed material became the prime contributor over the change in productivity of paddy in Assam over the entire period. Inclusion of organic manure as a third factor has ensured organic traditional rice cultivation in Assam as a whole. However with a critical view over the decade, interest on working capital was the sole contributor in the first decade. Inorganic fertilizer use has been included as a dominant factor in the next decade in Assam. Use of human labour, bullock labour along with irrigation and farm machineries became the prime factor contributor in Bihar as a whole. However, the quality seed material has been included in the next decade as a sole factor contributor for the change in paddy productivity. Barring interest on working capital, all the factors are responsible for overall change in productivity of paddy in Orissa as a whole. Farm machineries along with inorganic fertilizer use have the negative impact on productivity change ensures traditional farming situation in the state. Inclusion of organic manure use has been visualized in the final decade indicating organic paddy cultivation in the state which is highly welcomed for long term sustainability in the agricultural crop sector. Quality seed material along with human labour contribution became the prime contributor for overall change in productivity of paddy in West Bengal. Irrigation charges has been inserted in the third decade

9 ( to ) with a significant effect on productivity change. Overall seed use and human labour contribution exhibits major share in productivity change over Eastern region as a whole. Essence of farm mechanization cannot be visualized in the later decades as the factor has exerted negative impact on productivity change of paddy in the region. Conclusion: The entire study attempts to evaluate the extent of technological change in rice cultivation over the Eastern states of India during last four decades and to identify the key factor contributor for the overall change in paddy cultivation in Eastern India. The study concludes that there is an overall stagnancy in TFP for paddy in Eastern Region as a whole over the period studied whereas the maximum TFP has been gained in the second decade. The region still follows traditional rice cultivation package of practices even after four decades of Green Revolution in India with utilization of bullock labour instead of farm machineries and efficient use of seed and human labour which contributes maximum for the change in productivity over time. A combination of traditional as well as modern package of practices is highly welcomed in the region that could raise the overall productivity level of paddy in the region as a whole. References: Anonymous, Comprehensive Scheme for studying the cost of cultivation of Principal Crops in India. Directorate of Economics & Statistics, Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India, Krishi Bhawan, New Delhi, Anonymous,1996. Comprehensive Scheme for studying the cost of cultivation of Principal Crops in India. Directorate of Economics & Statistics, Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India, Krishi Bhawan, New Delhi, Anonymous, Comprehensive Scheme for studying the cost of cultivation of Principal Crops in India. Directorate of Economics & Statistics, Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India, Krishi Bhawan, New Delhi, Anonymous, 2003, Cost of Cultivation of Principal Crops in India. Directorate of Economics and Statistics, Department of Agriculture and Co-operation, Ministry of Agriculture Govt. of India, Anonymous, Reports of the Commission for Agricultural Cost and Prices for the Crops Sown during Season. Department of Agriculture and Cooperation, Ministry of Agriculture, Government of India, New Delhi. Anonymous, 2009a. Annual Report, Department of Agriculture, Government of West Bengal, Writers Buildings, Kolkata , 174. Adlas, J., Achoth, L., Is the Green Revolution Vanishing? Empirical Evidence from TFP analysis for Rice. Poster paper prepared for presentation at the International Association of Agricultural Economics Conference. Gold Coast, Australia, Aug 12-18, 2006.

10 Cassman, K.G., Pingali, P.L., Extrapolating trends from Long-term Experiments to Farmers Fields: The case of Irrigated Rice System in Asia, In (Barnett, Payne and Steiner) Agricultural Sustainability; economic, Environmental and Statistical Considerations. Johwiley & Sons Ltd., U. K, Chatterjee, S., An Economic Analysis of Total Factor Productivity (TFP) in Agriculture with reference to West Bengal: A thesis submitted to the Bidhan Chandra Krishi Viswavidyalaya in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Agriculture) in Agricultural Economics; Chatterjee, S., Gupta, S., Extent of technological change in rice cultivation over four decades in West Bengal, India. Agric. Econ. Czech, 59(6): Dawe, D. A.., Dobermann, P., Moya, S., Abdulrachman, P., Lal, S.Y., Li, B., Lin, G., Panaullah, O., Sariam, Y., Singh, A., Swarup, P.S., Tan, Q.X. Zhen., How widespread are yield declines in long-term rice experiments in Asia? Field Crops Res., 66, Diewert, W. E., Exact and Superlative Index Numbers. Journal of Econometrics. 4, eands. dacnet.nic.in Evenson, R.E., Carl, E. P Research and Productivity in Asian Agriculture. Ithaca, NY, Cornell University Press. Flinn, J.C., De Datta S.K., Trends in irrigated rice yields under intensive cropping at Philippines research stations. Field Crops Research. 5: Greenlands, D. L., The Sustainability of Rice farming, CAB International (UK) and International Rice Research Institute, Manila (Philippine); 115. Griliches, Z., An Appraisal of Long-Term Capital Estimates: Comment. Working paper, Priceton University Press. Janaiah, Aldas and Mahabub Hossain Partnership in the Public Sector Agricultural R & D: Evidence from India. Economic and Political Weekly, Vol. 39 (50), pp Jha, D., Kumar, P Rice Production and Impact of Rice Research in India: ed. Prabhu L. Pingali and Mahabub Houssain, TDRI; IRRI. Jorgenson, D., Griliches, Z., The Explanation of Productivity Change. The Review of Economic Studies. 34: Kumar, A.., Yadav, D.S., Long-term effects of fertilizers on the soil fertility and productivity of a rice-wheat system. J. Agron. Crop Sci. 186, Lewin, C.G., An Early Book on Compound Interest-Richard Witt s Arithmetical Questions. Journal of the Institute of Actuaries. 96(1): Lewin, C.G., Compound Interest in the Seventeenth Century. Journal of the Institute of Actuaries. 108(3): Nambiar, K.K.M., Annual reports, long-term fertilizer experiments in India ( ), IARI; New Delhi; India. Nirmala, B., Muthuraman, P., Economic and constraint analysis of rice cultivation in kaithal District of Haryana. Indian Res. J. Ext. Edu. 9(1): O Donell, C., An Aggregate Quantity-Price Framework for Measuring and Decomposing Productivity and Profitability Change. Centre for Efficiency and Productivity Analysis, Working Papers No. WP07/2008, University of Queensland, O Donell, C., Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture. Amer. J. Agr. Econ. 94(4):

11 Pingali, P.L., Hossain, M., Gerpacio, R., 1997.Asian Rice Bowls: The Returning Crisis? CAB International IRRI; Los Banos; Philippines. Yadav,R.L., Dwivedi, B.S., Pandey,P.S.,2000.Rice-wheat cropping system: assessment of sustainability under green manuring and chemical fertilizer inputs. Field Crops Res., 65,

12 Table 1.1: Decade-wise Growth Rates of Total Output Indices, Total Input Indices and Total Factor Productivity Indices of Eastern States of India during States Assam Bihar Orissa West Bengal Period to to to to to to to to to to to to to to to Exponential trend of total output indices (TOI) Y = 91.71e 0.02t R 2 = 0.84 Y = 95.58e 0.01t R 2 = 0.07 Y = 91.59e 0.02t R 2 = 0.45 Y = 94.95e 0.02t R 2 = 0.58 Y = 88.36e 0.02t R 2 = 0.22 Y = e 0.00t R 2 = 0.00 Y = e 0.01t R 2 = 0.02 Y = e 0.04t R 2 = 0.28 Y = e 0.02t R 2 = 0.08 Y = 90.32e -0.02t R 2 = 0.05 Y = 90.19e 0.02t R 2 = 0.51 Y = 99.68e 0.00t R 2 = 0.01 Y = e 0.06t R 2 = 0.46 Y = e -0.01t R 2 = 0.02 Y = e 0.05t R 2 = 0.35 Y = 98.56e 0.03t R 2 = 0.87 Y = e 0.01t R 2 = 0.07 Y = e 0.07t R 2 = 0.81 Y = 98.63e 0.02t R 2 = 0.68 Growth Rate (%) 1.95* * 2.00* * * * * 2.29* Exponential trend of total input indices (TII) Y = e 0.01t R 2 = 0.76 Y = e 0.01t R 2 = 0.11 Y = 96.09e 0.01t R 2 = 0.06 Y = 95.33e 0.02t R 2 = 0.54 Y = 96.65e 0.00t R 2 = 0.01 Y = e -0.01t R 2 = 0.27 Y = 96.54e 0.03t R 2 = 0.63 Y = e 0.01t R 2 = 0.25 Y = e -0.02t R 2 = 0.22 Y = 98.96e -0.01t R 2 = 0.11 Y = e 0.01t R 2 = 0.86 Y = e 0.01t R 2 = 0.18 Y = e 0.02t R 2 = 0.78 Y = 99.55e 0.01t R 2 = 0.64 Y = e 0.00t R 2 = 0.07 Y = 97.33e 0.02t R 2 = 0.85 Y = 88.12e 0.03t R 2 = 0.47 Y = 98.76e 0.03t R 2 = 0.77 Y = 96.03e 0.01t R 2 = 0.15 Growth Rate (%) 1.09* * * * * 1.40* * 3.18* 3.37* 1.16 Exponential trend of total factor productivity indices (TFPI) Y = 88.89e 0.01t R 2 = 0.65 Y = 90.86e 0.00t R 2 = 0.00 Y = 95.08e 0.02t R 2 = 0.53 Y = e 0.00t R 2 = 0.09 Y = 91.78e 0.02t R 2 = 0.40 Y = 87.18e 0.01t R 2 = 0.12 Y = e -0.03t R 2 = 0.26 Y = e 0.03t R 2 = 0.21 Y = e 0.04t R 2 = 0.51 Y = 91.63e -0.02t R 2 = 0.03 Y = 88.37e 0.00t R 2 = 0.06 Y = 99.35e R 2 = 0.07 Y = e 0.03t R 2 = 0.26 Y = e -0.02t R 2 = 0.17 Y = e 0.05t R 2 = 0.37 Y = e 0.01t R 2 = 0.37 Y = e -0.02t R 2 = 0.20 Y = e 0.04t R 2 = 0.56 Y = e 0.01t R 2 = 0.18 Growth Rate (%) 0.85* * * * * to Y = e -0.01t R 2 = Y = 98.93e 0.00t R 2 = Y = e -0.01t R 2 =

13 Eastern Region to to to to Y = 97.76e 0.02t R 2 = 0.77 Y = e 0.00t R 2 = 0.02 Y = e 0.06t R 2 = 0.72 Y = e 0.02t R 2 = 0.34 Y = e 0.01t R 2 = * * Y = e 0.01t R 2 = 0.78 Y = 95.01e 0.03t R 2 = 0.71 Y = e 0.02t R 2 = 0.86 Y = e 0.01t R 2 = 0.20 Y = e 0.00t R 2 = * 2.58* 2.51* Y = 91.86e 0.01t R 2 = 0.42 Y = e -0.02t R 2 = 0.31 Y = e 0.03t R 2 = 0.51 Y = e 0.01t R 2 = 0.14 Y = e 0.01t R 2 = * * Table 2.1: Correlation Matrix between change in output over change in various input use of paddy in Eastern India during to States Period Y X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 X ** * ** 0.566** 0.489** to * * Assam to * * * 0.708* to ** ** * 0.716** 0.932** 0.736** to ** * ** 0.764** ** 0.340* to Bihar to ** * * ** to * * to * * ** * ** ** 0.551** to ** Orissa to ** * 0.834** 0.767** to * to ** * ** 0.888** ** ** 0.409** to West Bengal to * * 0.713** to * ** ** 0.777** to * * ** 0.316* ** 0.570** 0.381* to * Eastern Region to ** * ** 0.798** to * * 0.619* 0.753** to * * 0.713* 0.582* Note: X 1: seed use X 2: fertilizer use X 3: organic manure use X 4: machine labour use X 5: irrigation charges X 6: plant protection chemicals X 7: bullock labour use X 8: human labour use X 9: interest on working capital *means significant at p 0.05 level **means significant at p 0.01 level (-) means negative value

14 Table 2.2: Multiple step-wise linear regressions between change in output over change in various inputs use in paddy cultivation across eastern states of India during States Period Regression equation Parameters Remarks Assam Bihar Y = X 8 ** Y = X 1 * X 8 ** Y = X 1 * (-) X X 8 ** to Y = (-) X 9 * to Y = X 8 * Y = X 8 ** (-) X 2 * to Y = X 8 ** to to Y = X 8 ** Y = X 8 ** X 1 ** Y = X 8 ** Y = X X 8 ** Y = X X 7 * X 8 ** Y = (-) X X X 7 * X 8 ** Y = X X X 3 (-) X X 5 (-) X X 7 (-) X X 9 X 8 : human labour use X 1 : seed use X 3 : organic manure use X 9 : interest on working capital X 8 : human labour use X 2 : inorganic fertilizer use X 8 : human labour use X 8 : human labour use X 1 : seed use X 8 : human labour use X 7 : bullock labour use X 5 : irrigation charges X 4 : machine labour use to Y = X 1 ** X 1 : seed use X 1 : seed use X 2 : fertilizer use X 3 : organic manure use X 4 : machine labour use X 5 : irrigation charges X 6 : plant protection chemicals X 7 : bullock labour use X 8 : human labour use X 9 : interest on working capital to Y = X 8 * X 8 : human labour use to Y = X 1 (-) X 2 (-) X X X X X 8 (-) X 9 X 1 : seed use X 2 : fertilizer use X 3 : organic manure use X 5 : irrigation charges X 6 : plant protection chemicals X 7 : bullock labour use X 8 : human labour use X 9 : interest on working capital Human labour use becomes the prime contributor over the overall productivity change in Rice followed by quality seed material. Organic manure has a significantly negative impact upon productivity change as a whole. Interest on working capital becomes the sole contributor for overall change in productivity of Rice in the first decade. Human labour use along with inorganic fertilizer use becomes the prime contributor over the change in productivity in the second decade. Third decade features human labour use as the sole contributor over productivity change in Rice. Human labour use and quality seed material use for paddy have the strong significant positive impact over the productivity change in the last phase. Human labour use has become the highest level of contribution followed by bullock labour use and irrigation charges. Farm mechanization has the significant negative impact on productivity change indicating the dominancy of bullock labour use at the first phase. No significant level of contribution was found from any factor however farm mechanization, plant protection measures and contribution of human labour has the negative impact over productivity change at the first decade. Quality seed material has been identified as the prime factor contributor with a significantly strong positive impact on change in productivity at second decade. Human labour contribution features maximum for overall productivity change during third phase. There is no significant relation between output and change in input pattern in the final decade. However fertilizer and manure use have shown negative impact over change in productivity.

15 Orissa West Bengal Y = X 8 ** Y = X 1 ** X 8 ** Y = X 1 ** X 3 * X 8 ** Y = X 1 ** X 3 * X X 8 Y = X 1 ** (-) X X 3 ** X X 8 * Y = X 1 * (-) X 2 * X 3 ** X X 7 * X 8 * Y = X 1 ** (-) X 2 ** X 3 ** X 5 * X X 7 ** X 8 * Y = X 1 ** (-) X 2 ** X 3 ** (-) X 4 * X 5 * X 6 ** X 7 ** X 8 * X 8 : human labour use X 1 : seed use X 3 : organic manure use X 7 : bullock labour use X 2 : fertilizer use X 5 : irrigation charges X 6 : plant protection chemicals X 4 : machine labour use to Y = (-) X 4 * X 4 : machine labour use to to to to Y = X 1 ** Y = X 1 ** (-) X 2 ** Y = (-) X X X 3 (-) X X 5 (-) X X 7 (-) X X 9 Y = X 8 ** Y = X 8 ** X 3 * Y = X 1 ** Y = (-) X 1 ** X 9 ** Y = X X 2 (-) X 3 (-) X X 5 (-) X 6 (-) X X X 9 X 1 : seed use X 2 : fertilizer use X 1 : seed use X 2 : fertilizer use X 3 : organic manure use X 4 : machine labour use X 5 : irrigation charges X 6 : plant protection chemicals X 7 : bullock labour use X 8 : human labour use X 9 : interest on working capital X 8 : human labour use X 3 : organic manure use X 1 : seed use X 9 : interest on working capital X 1 : seed use X 2 : fertilizer use X 3 : organic manure use X 4 : machine labour use X 5 : irrigation charges X 6 : plant protection chemicals X 7 : bullock labour use X 8 : human labour use X 9 : interest on working capital Human labour use became the sole factor contributor over the productivity change when only a single factor is concerned. Quality seed use entered next followed by organic manure use, bullock labour use, inorganic fertilizer use with a negative impact, irrigation charges, plant protection measures and last of all farm mechanization have a significant effect on the change in productivity over time. Farm mechanization has a significant negative impact on change in productivity as the use of bullock labour dominates. Quality seed use has the significant contributor in the second decade while a negative impact of inorganic fertilizer use indicating the detrimental effect of fertilizer over change in productivity. No significant relation has been made with change in input over change in productivity of paddy in third phase. Human labour became the prime contributor along with initiation of organic manure use establishing organic rice production in last decade. Quality HYV seed use as well as interest on working capital became the prime factor contributor over the change in productivity of rice. No significant relation has been made with change in input over change in productivity of paddy in first phase.

16 Eastern Region to Y = X 8 * X 8 : human labour use to to to to Y = X 8 ** Y = X 8 ** X 5 * Y = X X 2 (-) X 3 (-) X X X 6 (-) X 8 (-) X 9 Y = X 1 ** Y = X 1 ** X 8 ** Y = X 1 ** X X 8 ** Y = X 1 ** (-) X X X 8 ** Y = (-) X 1 * Y = (-) X 1 * X 9 Y = (-) X 1 ** (-) X X 9 Y = X 7 ** Y = X 7 ** X 2 * Y = X 7 ** X 2 ** (-) X 9 * X 8 : human labour use X 5 : irrigation charges X 1 : seed use X 2 : fertilizer use X 3 : organic manure use X 4 : machine labour use X 5 : irrigation charges X 6 : plant protection chemicals X 8 : human labour use X 9 : interest on working capital X 1 : seed use X 8 : human labour use X 6 : plant protection chemicals X 4 : machine labour use X 1 : seed use X 9 : interest on working capital X 4 : machine labour use X 7 : bullock labour use X 2 : fertilizer use X 9 : interest on working capital to Y = X 8 * X 8 : human labour use to Y = X 1 * X 1 : seed use Human labour became the prime factor contributing maximum for overall change in productivity at first decade. Human labour use along with assured irrigation facilities became the prime factor contributor for overall change in productivity. No significant relationship found with output change to all the factors while X 7 : Bullock labour use has been omitted from the regression function indicating farm mechanization in paddy cultivation. Quality seed material has become the prime contributor over productivity change when only one factor is concerned. Next to seed, contribution of human labour along with plant protection measures has been identified as the key factor contributor over the period. Finally farm mechanization has been contributed with a negative impact in the eastern region rice production ensures the effect of bullock labour in the region. Seed comes as the first factor contributor followed by interest on working capital and machine labour use with a negative impact on productivity at initial phase under study. Bullock labour became the prime contributor over the change in productivity in the second decade before the era of farm mechanization in the eastern region as a whole. Fertilizer use comes next in this decade. Interest on working capital has a negative impact on productivity change in this decade. Human labour use became the sole factor contributor for overall change in productivity of paddy in the third decade. Use of quality seed material i.e. HYV seeds for paddy became the prime contributing factor for the overall change in productivity at the fourth and final decade under study.

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