scholarly journals Growth and Decomposition analysis of Rabi Pulse Crops in Rajasthan

2021 ◽  
Vol 66 (3) ◽  
Author(s):  
Harkesh Kumar *, Balai
Keyword(s):  
Growth Rate ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Output Growth ◽  
Series Data ◽  
Pulse Crops ◽  
Relative Contribution ◽  
Positive Growth ◽  
Decomposition Models ◽  
Mixed Pattern

The present study was conducted to analyze the growth rate and source of output growth in area, production and productivity of rabi pulse crops viz., gram and lentil crops in Rajasthan. The study was solely based on secondary time series data. The study period (1988-89 to 2017-18) has been divided into four periods namely period-I (1988-89 to 1997-98), period-II (1998-99 to 2007-08), period- III (2008-09 to 2017-18) and overall period (1988-89 to 2017-18). Exponential growth and principal decomposition models were used to measure the growth rates and relative contribution of factors in production of gram and lentil crops. The area, production and productivity of gram showed mixed pattern of growth at the rate of -0.46, 1.86 and 2.33 per cent, respectively during overall period. However, the area, production and productivity of lentil were reported positive growth with the magnitude of 11.94, 12.72 and 0.93 per cent, respectively in the state. The study revealed that the mixed growth rate was observed in area, production and productivity of gram while increasing growth was observed in area, production and productivity of lentil. During all the study periods, the expansion in area was effective to increase the production of lentil in Rajasthan. During period-I and II, the production of gram was mainly contributed by expansion in area while in the case of period-III and overall, the interaction effect was more dominant

scholarly journals Variability and Sources of Output Growth in Major Oilseeds of Rajasthan

2021 ◽  
Vol 66 (1) ◽  
Author(s):  
Kailash Chand Bairwa
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Time Series Data ◽  
Output Growth ◽  
The State ◽  
Series Data ◽  
Oilseed Crops ◽  
Significant Growth ◽  
Area Effect ◽  
Relative Contribution

Rajasthan state is the second largest oilseeds producer and land coverage in the country. The share of oilseed crops is scheduled the significant growth in area and output in latest 20 years. Nevertheless, compare to wheat and gram, the growth rate of area and production of several oilseeds is less significant and there exist wide instability in their productivity in scattered part of the state. This study investigates to growth, its contributors and variability in area, production and productivity of major oilseed crops. The study period from 1990-91 to 2019-20 was divided into three sub-periods viz., period-I (1990-91 to 2004-05); period-II (2005-06 to 2019-20) and Overall study Period (1990-91 to 2018-19). Time series data were collected from various public E-sources to compute the growth, instability and decomposition in oilseeds production. It was revealed from the analysis that growth of kharif oilseeds was higher than rabi oilseeds. The highest instability (31.78) in production and productivity was reported in period-I for kharif oilseeds. In case of relative contribution, the area effect (416.85) and yield effects (211.10) were more effective in production of taramira and sesame crops, respectively. This analysis suggested that during period –I and II area effect was dominant in changing output of taramira and rapeseed-mustard.

A Study on the performance of Agricultural Sector in India

2017 ◽  
Vol 51 (03) ◽  
Author(s):  
Laishram Priscilla ◽  
Arsha Balakrishnan ◽  
Lalrinsangpuii Lalrinsangpuii ◽  
A. K. Chauhan
Keyword(s):  
Growth Rate ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Series Data ◽  
Meat Production ◽  
Area Effect ◽  
Agriculture Sector ◽  
Per Capita ◽  
Vegetables And Fruits

<span>The time series data at all India level on area, production and productivity of foodgrains, production and per capita availability of milk and eggs and production of meat were compiled and a decade wise analysis of growth rate, instability index and decomposition analysis was done to study the performance of agriculture sector. During the overall period, the area under food grains showed negative growth whereas production and productivity growth was positive. For milk and egg, both production and per capita availability showed positive growth. Meat production showed a positively significant growth rate. Growth rate in area, production and productivity of both vegetables and fruits was positive. In general, for foodgrains, the yield effect was higher than the area effect which could be attributed to increased use of high yielding varieties. For vegetables and fruits, the contribution of area effect was more than that of yield and the interaction effect suggesting that measures should be taken to improve their productivity. </span>

scholarly journals State-wise Production Performance of Basmati and Non-Basmati Rice in India

2021 ◽  
pp. 17-31
Author(s):  
M. Udhayakumar ◽  
K. R. Karunakaran ◽  
M. Thilagavathi ◽  
K. R. Ashok
Keyword(s):  
Growth Rate ◽  
Time Series Data ◽  
Production Performance ◽  
Basmati Rice ◽  
Series Data ◽  
High Productivity ◽  
Positive Growth ◽  
Cent Level ◽  
Positive Growth Rate ◽  
Level Of Significance

The present study was designed to evaluate the state wise Basmati and non-Basmati rice production performance in India. The study is based on the time series data on area production and yield which were compiled from various sources for a period of 39 years (1980-81 to 2018-19). The sate wise analysis considers for the major basmati and non-basmati production sates by merging the newly divide states to parents’ sates like Telangana to AP etc. While considering overall period in basmati area (6.01%) production (10.55%) and yield (4.28%) shows positive growth rate with 1 per cent level of significance. Allover India shows positive growth rate like area (0.24%), production (1.95%) and Productivity (1.70%) with 1 per cent level of significance. For India, in overall period it is more stable as Area (2.89), Production (6.07) and yield (4.5) give low instability percent. Special attention program is need to enhance the production of rice in Assam and Orissa were two states are in lowest category in terms of productivity, so effects may be taken to increase the productivity in Assam and further increase from medium to high productivity states in case of Andhra Pradesh.

Decomposition analysis and acreage response of pigeonpea in western Vidarbha

2016 ◽  
Author(s):  
M. Vikram Sandeep ◽  
S. S. Thakare ◽  
D. H. Ulemale
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Coefficient Of Variation ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Secondary Data ◽  
Pigeon Pea ◽  
Series Data ◽  
Response Analysis ◽  
Instability Index

In the present investigation, an attempt was made to study the decomposition and acreage response of pigeonpea in western Vidarbha. The study was based on time series secondary data on the rainfall, farm harvest prices and other data, which were obtained from various Government publications. Nerlovian lagged adjustment model (1958) was used in acreage response analysis based on time series data. The study revealed that the compound growth rate for area and production under pigeon pea was recorded high during period I in all the districts. During period II, the area, production and productivity of pigeonpea registered mostly negative growth rates in all the districts. During period III, the compound growth rate for area, production and productivity under pigeonpea has increased in all the districts of western Vidarbha region. At overall period, the coefficient of variation and Coppock's instability index for area, production and productivity were high for pigeonpea in Akola district compared to other districts and coefficient of variation and Coppock's instability index for production and productivity were lowest for pigeonpea in Amravati district. At overall period, in pigeonpea, the area effect (56.61%) was most responsible factor for increasing production in Amravati division with positive yield and interaction effect i.e. 18.91 per cent and 23.75 per cent respectively.

A Study on the performance of Agricultural Sector in India

2017 ◽  
Vol 51 (03) ◽  
Author(s):  
Laishram Priscilla ◽  
Arsha Balakrishnan ◽  
Lalrinsangpuii Lalrinsangpuii ◽  
A. K. Chauhan
Keyword(s):  
Growth Rate ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Series Data ◽  
Meat Production ◽  
Area Effect ◽  
Agriculture Sector ◽  
Per Capita ◽  
Vegetables And Fruits

The time series data at all India level on area, production and productivity of foodgrains, production and per capita availability of milk and eggs and production of meat were compiled and a decade wise analysis of growth rate, instability index and decomposition analysis was done to study the performance of agriculture sector. During the overall period, the area under food grains showed negative growth whereas production and productivity growth was positive. For milk and egg, both production and per capita availability showed positive growth. Meat production showed a positively significant growth rate. Growth rate in area, production and productivity of both vegetables and fruits was positive. In general, for foodgrains, the yield effect was higher than the area effect which could be attributed to increased use of high yielding varieties. For vegetables and fruits, the contribution of area effect was more than that of yield and the interaction effect suggesting that measures should be taken to improve their productivity.

The Effects of Oil Prices Changes on Output Growth and Inflation: Evidence from Turkey

2013 ◽  
Vol 5 (11) ◽  
pp. 730-739 ◽  
Author(s):  
Pelin ÖGE GÜNEY
Keyword(s):  
Time Series Data ◽  
Output Growth ◽  
Oil Price ◽  
Series Data ◽  
Negative Effects ◽  
Price Changes ◽  
Asymmetric Effects ◽  
Price Increases ◽  
Causality Tests ◽  
The Impact

This paper investigates the effects of oil price changes on output and inflation for the case of Turkey using monthly time series data for the period 1990:1–2012:3. Recent studies suggest that oil price changes may have asymmetric effects on the macroeconomic variables. To account for asymmetric effects, we decompose oil price changes into positive and negative parts following Hamilton (1996). Our results show that while oil price increases have clear negative effects on output growth, the impact of oil price decline is insignificant. Similarly, oil price increases have positive and significant effects on inflation. However, oil price declines have not a significant effect on inflation. The Granger causality tests also support these results.

The Decomposition Analysis of Carbon Emissions: Theoretical Basis, Methods and Their Evaluations

2020 ◽  
Vol 08 (04) ◽  
pp. 2050020
Author(s):  
Shenning QU
Keyword(s):  
Environmental Economics ◽  
Carbon Emissions ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Series Data ◽  
Process Time ◽  
Structural Decomposition Analysis ◽  
Systematic Analysis ◽  
Index Decomposition ◽  
Laspeyres Index

As an analytical framework for studying the characteristics of changes in things and their action mechanisms, the decomposition analysis of greenhouse gas emissions has been increasingly used in environmental economics research. The author introduces several decomposition methods commonly used at present and compares them. The index decomposition analysis (IDA) of carbon emissions usually uses energy identities to express carbon emissions as the product of several factor indexes, and decomposes them according to different weight-determining methods to clarify the incremental share of each index, in which way it is possible to decompose the models that contain less factors, process time series data, and conduct cross-country comparisons. It mainly includes the Laspeyres index decomposition and the Divisia index decomposition. Among them, the LMDI I method has been widely used for its advantages such as generating no residuals and easy to use. The structural decomposition analysis (SDA) can be used to conduct a more systematic analysis, decompose models with more influencing factors, and analyze the impacts of various factors on emissions, but this method has higher requirements for data collection. The biggest difference between the SDA method and the IDA methods of carbon emissions is that the former is based on an input–output system, while the latter only needs to use sectors’ aggregate data.

scholarly journals THE TESTING OF MONEY NEUTRALITY IN ECONOMIC GROWTH OF INDONESIA

2017 ◽  
Vol 1 (1) ◽  
pp. 12
Author(s):  
Muammil Sun’an ◽  
Amran Husen
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Output Growth ◽  
Broad Sense ◽  
Series Data ◽  
Analysis Tool ◽  
Real Sector ◽  
Short Term ◽  
Correction Model

<p>This study aim is to test the money neutrality in a narrow sense (M1) and a broad sense (M2) to the growth of output (GDP) in Indonesia, both in short term and long term. This research uses quarterly time series data at 2010 - 2016 periods. The analysis tool used is Error Correction Model (ECM). The results show that short-term money supply (M1 and M2) affect on output growth. However, in the long term, only money circulation in a broad sense (M2) affects on output growth, which also means that money is not neutral because it affects the real sector (GDP).</p><p> <strong>Keywords:</strong> M1, M2, Population, Capital, and Economic Growth.</p>

An intraregional economic analysis of production structure and factor demand in major Canadian softwood lumber producing regions

1988 ◽  
Vol 18 (8) ◽  
pp. 1036-1048 ◽  
Author(s):  
J. K. Meil ◽  
J. C. Nautiyal
Keyword(s):  
Technical Change ◽  
Time Series Data ◽  
Decomposition Analysis ◽  
Production Capacity ◽  
Series Data ◽  
Variable Cost ◽  
Production Structure ◽  
Cross Sectional ◽  
Behaviour Factor ◽  
Factor Demand

Cross-sectional time-series data were employed to estimate four intraregional models of production structure and factor demand over the time period 1968–1984. Lumber, tie, and pulp chip information was incorporated into the restricted, single-output, variable cost transcendental logarithmic function. Results indicate that aggregate sectoral studies do not adequately reflect regional production behaviour in the industry. Additional tests for aggregation bias demonstrated that different mill sizes within a region also portray differing production behaviour. Factor demand decomposition analysis indicated that demand for production inputs is not static, but is governed by offsetting dynamic effects. With few exceptions, all mills across regions exemplify material- and energy-using and labour-saving biases in technical change. Larger mills consistenly registered the greatest labour-saving technical change, which countered their lack of attaining significantly large cost-reducing scale economies. Mid-sized mills consistently exhibited the largest returns to scale. The data suggest that small mills are leaving the industry in some regions and production capacity is becoming concentrated in the larger mills.

scholarly journals The effects of fiscal operations on economic growth and stability in Nigeria: empirical evidence based on time series data

2018 ◽  
Vol 6 (1) ◽  
pp. 36
Author(s):  
Miftahu Idris ◽  
Rosni Bakar ◽  
Tunku Salha Tunku Ahmad
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Alternative Model ◽  
Time Series Data ◽  
Output Growth ◽  
Series Data ◽  
Economic Stability ◽  
Economic Management ◽  
Baseline Model ◽  
Desirable Outcome

This study examines the effects of fiscal operations on the economic growth and stability with the view to identifying its significance on real output growth and sustainable development. The study utilises an annual time series data covering the period of 1980 to 2015 and further adopts an ARDL model for estimation. The estimated model is sub-divided into two: the Baseline model and the Alternative model. While the former measures the effects of economic growth, the latter accounts for the effects of economic stability. The ARDL Bound testing show the existence of long-run relationship among the examined variables in both the two models, with corresponding F-statistic values of 7.62 and 6.67, respectively. The overall results indicate that fiscal operations lead to economic growth as shown by the Baseline model; and it also leads to economic stability as revealed by the Alternative model. It can therefore be concluded that any meaningful spending with corresponding taxation will improve the public sector performance and produce a desirable outcome on output growth and strengthen the capability of fiscal operations in terms of economic management. There is an urgent need to ensure that appropriate fiscal operations are conducted and do not result in excess liquidity beyond the absorptive capacity of the economy.

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