The long run impact of climate change on the productivity of major crops in the districts of Punjab is analyzed for the time period of 1970 to 2010. This study used deviations from average maximum annual temperature and deviations from average rainfall are used as indicators for climate change. While other variables include sale price, fertilizer use and number of tube wells. In order to incorporate long timer periods, this study used Panel ARDL model. The results show that cotton productivity is more positively sensitive to price changes; an increase in temperature, tube wells and fertilizers while wheat productivity is more positively sensitive to the rainfall in the long run. Consequently, in the short run, wheat productivity equilibrium is faster converging. Hence deviations from average rainfall are harmful to cotton crop in the long run and cotton & wheat in the short run, while deviations in maximum temperature is only harmful for cotton crop in the short run.
Even though Ethiopia had undertaken different policy measures since 1991 to boost agricultural production and increase the spillover effects of agriculture, there is no available study done to know the effects of such policies. This study aimed to fill this gap by analyzing the supply response of the commodity chosen haricot bean in Sidama Zone of Southern Ethiopia. The study applies the modified Nerlovian model and uses price data and non price data from 1991-2012.The result of the estimates of the time series data shows that acreage is positively and significantly influenced by change in its own price in the long run. Acreage and yield are highly influenced by price and non price factors both in the long run and short run. Generally farmers respond to price incentives by reallocating land and increase yield. The error correction term shows that deviation of acreage from the equilibrium corrected in the current period and it takes less than five years to come to the equilibrium. On the other hand any deviation of yield from the equilibrium corrected in the current period and takes less than two years to come to the equilibrium. The empirical results illustrate that there is still great potential to increase production through improvement of price and non price inputs. Hence the ongoing measures should be directed towards assuring appropriate remunerative prices and increase investment and supply of other non price factors like, increase investment in irrigation.
Indian Agricultural Concerns and Future Prospects of Agriculture in IndiaDevina Seram
Challenges faced in Present Indian Agriculture.
Future Prospects of Agriculture in India (Expected)
"Everything Else Can Wait But Not Agriculture".
- Jawaharlal Nehru
Changes in climate affects the land and farming immensely. Due to this,the crop growth is affected and results in inadequacy of seasonal crop outcome which does not meet the demands of the living beings. Hence, Climatic change has become a chief issue to be looked forth in order to prevent further threatenings to the livelihood. I have made a gist of the existing issue on climate changes and the insecurities of food resources in India.
Even though Ethiopia had undertaken different policy measures since 1991 to boost agricultural production and increase the spillover effects of agriculture, there is no available study done to know the effects of such policies. This study aimed to fill this gap by analyzing the supply response of the commodity chosen haricot bean in Sidama Zone of Southern Ethiopia. The study applies the modified Nerlovian model and uses price data and non price data from 1991-2012.The result of the estimates of the time series data shows that acreage is positively and significantly influenced by change in its own price in the long run. Acreage and yield are highly influenced by price and non price factors both in the long run and short run. Generally farmers respond to price incentives by reallocating land and increase yield. The error correction term shows that deviation of acreage from the equilibrium corrected in the current period and it takes less than five years to come to the equilibrium. On the other hand any deviation of yield from the equilibrium corrected in the current period and takes less than two years to come to the equilibrium. The empirical results illustrate that there is still great potential to increase production through improvement of price and non price inputs. Hence the ongoing measures should be directed towards assuring appropriate remunerative prices and increase investment and supply of other non price factors like, increase investment in irrigation.
Indian Agricultural Concerns and Future Prospects of Agriculture in IndiaDevina Seram
Challenges faced in Present Indian Agriculture.
Future Prospects of Agriculture in India (Expected)
"Everything Else Can Wait But Not Agriculture".
- Jawaharlal Nehru
Changes in climate affects the land and farming immensely. Due to this,the crop growth is affected and results in inadequacy of seasonal crop outcome which does not meet the demands of the living beings. Hence, Climatic change has become a chief issue to be looked forth in order to prevent further threatenings to the livelihood. I have made a gist of the existing issue on climate changes and the insecurities of food resources in India.
India is considered as one of the fastest growing economies in the world. Agriculture is the mother of any economy, whether it is rich or poor. Much of its influence is on the other sectors of economy - industry and service. India is the second largest in farm output. Hence, India’s economic security continues to be predicated upon the agriculture sector, and the situation is not likely to change in the near future. Even today, the share of agriculture in employment is about 49% of the population, as against around 75% at the time of independence. In the same period, the contribution of agriculture and allied sector to the Gross Domestic Product (GDP) has fallen from 61% to 17% in 2015-16. Around 51% of India’s geographical area is already under cultivation as compared to 11% of the world average. China with lesser cultivable land produces double the food grains, i.e. 607 million tons in 2015 -16 as compared with India’s 252 million tons in 2015-16. The present cropping intensity of 136% has registered an increase of only 25% since independence. Further, rain fed dry lands constitute 65% of the total net sown area. There is also an unprecedented degradation of land (107 million ha) and groundwater resource, and also fall in the rate of growth of total factor productivity. This deceleration needs to be arrested and agricultural productivity has to be doubled to meet growing demands of the population by 2050. Natural resource base of agriculture, which provides for sustainable production, is shrinking and degrading, and is adversely affecting production capacity of the ecosystem. However, demand for agriculture is rising rapidly with increase in population and per capita income and growing demand from industry sector. There is, thus, an urgent need to identify severity of problem confronting agriculture sector to restore its vitality and put it back on higher growth trajectory. The problems, however, are surmountable, particularly when new tools of science and technology have started offering tremendous opportunities for application in agriculture. However, the country recorded impressive achievements in agriculture during three decades since the onset of green revolution in late sixties. This enabled the country to overcome widespread hunger and starvation; achieve self-sufficiency in food; reduce poverty and bring economic transformation in millions of rural families. The situation, however, started turning adverse for the sector around mid-nineties, with slowdown in growth rate of output, which then resulted in stagnation or even decline in farmers’ income leading to agrarian distress, which is spreading and turning more and more serious. This Paper attempts to focus attention on Issues, Challenges and Government policies of Indian Agriculture in the context of Globalization.
Efficiency and Yield Gap Analysis in Potato Production: The Case of Potato Fa...Premier Publishers
The study examined efficiency, yield gap and level of responsiveness of output to the factors of production in potato production in central highlands of Ethiopia. The study used household level cross sectional data collected in 2015/16 from 196 sample farmers selected through multistage sampling technique. A stochastic frontier model was employed for the efficiency analysis. The scale coefficient for production function was calculated to be 1.1, indicating a 1% increase in all inputs proportionally increases total production by 1.1%. The mean technical efficiency and actual yield gap of sample households are 62.6% and 15.2 t/ha respectively. Eighty six percent of the yield variation in potato production is due to technical inefficiency and accounts for 13.07 t/ha yield gap. Therefore, efforts designed to improve efficiency would be more cost effective than introducing new technologies such as developing new varieties as a means of increasing potato production and productivity.
The Impact of Climate Change on Teff Production in Southeast Tigray, EthiopiaPremier Publishers
The paper reports results of a study on investigating impacts of climate change on teff (Eragrostis tef) production in three agro-ecological zones (highlands, midlands and lowlands) of Endamehoni and Raya Azebo weredas of Tigray. The impact of climate change on teff farming was estimated taking into account farm households’ characteristics, socio-economic, climate, adaptations, production factors and agro-ecological settings in a low-income developing country. Ricardian model was used to analyze data obtained from teff farming households. From the fourteen predictor variables fitted in the model, six variables e.g. climate factors, adaptation strategies, production factors, weather and climate information, socio-economic factors and agro-ecology were found to have significance influence on net revenues with model coefficients at p=0.05 and less. Climate factors (temperature and rainfall) and adaptation to climate change were found to play key roles on net revenues. Increasing (decreasing) temperature reduces (increases) teff revenues. Therefore, policies of government on adaptation ought to be given enough attention to reduce vulnerability and improve food security among teff farming communities in rural areas.
Climate Change & Its Relationship with Agriculture by Yogendra KatuwalYogendra Katuwal
Prepared by Yogendra Katuwal M.Sc. Ag (Agronomy) student of AFU, Rampur, Nepal. What is actually the relationship between climate change and agriculture is included needs a better understanding.
Modelling the impact of climate change on cereal yield in MoroccoIJEAB
To assess the impact of climate change different studies were conducted in several regions of Morocco. The assessment of climate change and its impacts involves the simulation of a range of different socio-economic and physical processes. Some of these processes are well known such temperature, rainfall, storms, etc.., others not. Hence for each modeling step researchers need to consider what is known, what is not known, and how climate change can be expressed.This paper is a contribution to research on climate change impact on cereal yield in the last 50 years. The application of the multiple linear regression model to a set of time series of yield, rainfall, temperature and storm has generated significant coefficients that can explain the relation between yield and the three climate variables. The model output confirms the results of the previous studies of yield variability. The positive effect of rainfall and the negative one of storm and temperature ware recorded. Above the three factors, temperature and storms have a negative effect on cereal yield. So more efforts on germplasm, crop management and agricultural policy measures are needed to alleviate the impact of climate change. An estimate coefficient of -4.943 for temperature is very indicating the high impact of temperature on yield. The R² is around 0.45indicates that more than 55% of total yield variability is explained by other factors than rain, temperature and storm.
Cereals are synonyms of Indian food production, obviously due to its lion share (~ 90 %) in total
Indian food basket. Since time immemorial, fate of Indian agriculture heavily depends upon the
success of cereals production. Agriculture glory of India must be strengthened all the way through
achieving self sufficiency in food production first; secondly by improving our agriculture image at
global arena, by get redden off from net importer to net exporter, obviously through strong
presence in global agriculture market. We are marching in the right direction; cereals are the leaders
in the food commodity export especially rice “The Basmati Rice”. Since, as of now, Indian share in
the world trade is meagre (~1.0%), there are needs to scale up to the tune of 6% in very quick
succession. No doubt, Cereals and coarse cereals should be a front leader in this endeavourer. Since
a lot more has to be done; we have to have adhered on do more policy. This article discuss at length
on past glory, present status and future prospect of the great Indian food basket famously known as
“The Cereals”.
Agriculture is one of those activities of man that is greatly affected by climate. Therefore, a change in climate would in no small measure impact on agriculture, location notwithstanding. This work as a result examined the impact of climate change on maize and cassava yields in Southeastern Nigeria. Expost-facto research method in the context of quasi experimental research design was adopted for the study. Data for rainfall and temperature were obtained from Nigerian Meteorological Agency (NIMET); and those for crop yields came from Federal Ministry of Agriculture of Nigeria and Agricultural Development Programme (ADP) of selected states. The data were analyzed using descriptive statistics, multiple linear regressions and analysis of variance. Results showed that, there are evidences of climate change in Southeastern Nigeria, with notable fluctuations in the identified trends. Employing the trend analysis represented by the least square line, Abia State rainfall is increasing at 0.1026mm per annum, while Imo State is decreasing at -1.1255 mm per annum. All the states recorded positive slopes in mean temperature which shows an increase in their trends. The multiple regression model showed R2 values that ranged between 0.25 – 0.29 revealing that only 25 %- 29 % of cassava and maize yields could be explained by rainfall and temperature across the states and the result was significant at p<0.05 revealing that cassava and maize yields significantly depended on rainfall and temperature. Crop yields were also significantly different spatially. As a result of the findings the study strongly advocates, development of better and sustained environmental policies that will be beneficial to climate systems while creating sustainable food security.
M.Sc. (Ag.) in Agricultural Marketing & Cooperation
This includes the inception, present status and future aspects of the Mission as a comprehensive manner.
Energy consumption pattern in wheat production in sindhsanaullah noonari
Wheat (Triticum aestivium L.) is the main staple food for most of the population and largest grain source o the
country. It occupies the central position in formulating agricultural policies. It contributes 13.1 percent to the
value added in agriculture and 2.7 percent to GDP. Area and production target of wheat for the year 2012-13 had
been set at 9045 thousand hectares and 25 million tons, respectively. Wheat was cultivated on an area of 8805
thousands hectares, showing a decrease of 3.6 percent over last year’s area of 9132 thousand hectares. However,
a bumper wheat crop of 24.2 million tons has been estimated with 3.9 percent increase over the last year’s crop
of 23.3 million tons. The prospects for wheat harvest improved with healthy fertilizer off-take and reasonable
rainfall during pre-harvesting period. Energy is a necessary of life for human beings all over the world due to its
function in strengthening the security and contentment of the people. Energy demand is growing with the
passage of time due to infrastructural and industrial development. Energy is required to perform all the human
activities. It is need for food preparation, water heating and cooling, for lighting, for production of goods etc.
The study was focused on all types of energy (fossil fuels, chemicals, animals dung, animate etc). A sample of
60 farmers was selected from study area. A pre tested questioner was used to collect data from selected
respondents through personal interviews. Descriptive statistics and Cobb-Douglas production function was
applied to analyze the data. Result shows that wheat farmer achieved highest amount of net energy which was
calculated as small, medium and large farmers is 1368336.88, 1698003.79 and1702527.75 MJ/acre respectively.
In production of wheat large, medium and small farmers achieve amount of net energy which was calculated
41525.06, 38590.99, 39095.33 MJ/acre. The impact of various energy inputs on yield was studied. The share of
various energy types in total cost of production was estimated. Commercial energy (diesel and electricity)
consumed highest amount of energy in production of wheat.
India is considered as one of the fastest growing economies in the world. Agriculture is the mother of any economy, whether it is rich or poor. Much of its influence is on the other sectors of economy - industry and service. India is the second largest in farm output. Hence, India’s economic security continues to be predicated upon the agriculture sector, and the situation is not likely to change in the near future. Even today, the share of agriculture in employment is about 49% of the population, as against around 75% at the time of independence. In the same period, the contribution of agriculture and allied sector to the Gross Domestic Product (GDP) has fallen from 61% to 17% in 2015-16. Around 51% of India’s geographical area is already under cultivation as compared to 11% of the world average. China with lesser cultivable land produces double the food grains, i.e. 607 million tons in 2015 -16 as compared with India’s 252 million tons in 2015-16. The present cropping intensity of 136% has registered an increase of only 25% since independence. Further, rain fed dry lands constitute 65% of the total net sown area. There is also an unprecedented degradation of land (107 million ha) and groundwater resource, and also fall in the rate of growth of total factor productivity. This deceleration needs to be arrested and agricultural productivity has to be doubled to meet growing demands of the population by 2050. Natural resource base of agriculture, which provides for sustainable production, is shrinking and degrading, and is adversely affecting production capacity of the ecosystem. However, demand for agriculture is rising rapidly with increase in population and per capita income and growing demand from industry sector. There is, thus, an urgent need to identify severity of problem confronting agriculture sector to restore its vitality and put it back on higher growth trajectory. The problems, however, are surmountable, particularly when new tools of science and technology have started offering tremendous opportunities for application in agriculture. However, the country recorded impressive achievements in agriculture during three decades since the onset of green revolution in late sixties. This enabled the country to overcome widespread hunger and starvation; achieve self-sufficiency in food; reduce poverty and bring economic transformation in millions of rural families. The situation, however, started turning adverse for the sector around mid-nineties, with slowdown in growth rate of output, which then resulted in stagnation or even decline in farmers’ income leading to agrarian distress, which is spreading and turning more and more serious. This Paper attempts to focus attention on Issues, Challenges and Government policies of Indian Agriculture in the context of Globalization.
Efficiency and Yield Gap Analysis in Potato Production: The Case of Potato Fa...Premier Publishers
The study examined efficiency, yield gap and level of responsiveness of output to the factors of production in potato production in central highlands of Ethiopia. The study used household level cross sectional data collected in 2015/16 from 196 sample farmers selected through multistage sampling technique. A stochastic frontier model was employed for the efficiency analysis. The scale coefficient for production function was calculated to be 1.1, indicating a 1% increase in all inputs proportionally increases total production by 1.1%. The mean technical efficiency and actual yield gap of sample households are 62.6% and 15.2 t/ha respectively. Eighty six percent of the yield variation in potato production is due to technical inefficiency and accounts for 13.07 t/ha yield gap. Therefore, efforts designed to improve efficiency would be more cost effective than introducing new technologies such as developing new varieties as a means of increasing potato production and productivity.
The Impact of Climate Change on Teff Production in Southeast Tigray, EthiopiaPremier Publishers
The paper reports results of a study on investigating impacts of climate change on teff (Eragrostis tef) production in three agro-ecological zones (highlands, midlands and lowlands) of Endamehoni and Raya Azebo weredas of Tigray. The impact of climate change on teff farming was estimated taking into account farm households’ characteristics, socio-economic, climate, adaptations, production factors and agro-ecological settings in a low-income developing country. Ricardian model was used to analyze data obtained from teff farming households. From the fourteen predictor variables fitted in the model, six variables e.g. climate factors, adaptation strategies, production factors, weather and climate information, socio-economic factors and agro-ecology were found to have significance influence on net revenues with model coefficients at p=0.05 and less. Climate factors (temperature and rainfall) and adaptation to climate change were found to play key roles on net revenues. Increasing (decreasing) temperature reduces (increases) teff revenues. Therefore, policies of government on adaptation ought to be given enough attention to reduce vulnerability and improve food security among teff farming communities in rural areas.
Climate Change & Its Relationship with Agriculture by Yogendra KatuwalYogendra Katuwal
Prepared by Yogendra Katuwal M.Sc. Ag (Agronomy) student of AFU, Rampur, Nepal. What is actually the relationship between climate change and agriculture is included needs a better understanding.
Modelling the impact of climate change on cereal yield in MoroccoIJEAB
To assess the impact of climate change different studies were conducted in several regions of Morocco. The assessment of climate change and its impacts involves the simulation of a range of different socio-economic and physical processes. Some of these processes are well known such temperature, rainfall, storms, etc.., others not. Hence for each modeling step researchers need to consider what is known, what is not known, and how climate change can be expressed.This paper is a contribution to research on climate change impact on cereal yield in the last 50 years. The application of the multiple linear regression model to a set of time series of yield, rainfall, temperature and storm has generated significant coefficients that can explain the relation between yield and the three climate variables. The model output confirms the results of the previous studies of yield variability. The positive effect of rainfall and the negative one of storm and temperature ware recorded. Above the three factors, temperature and storms have a negative effect on cereal yield. So more efforts on germplasm, crop management and agricultural policy measures are needed to alleviate the impact of climate change. An estimate coefficient of -4.943 for temperature is very indicating the high impact of temperature on yield. The R² is around 0.45indicates that more than 55% of total yield variability is explained by other factors than rain, temperature and storm.
Cereals are synonyms of Indian food production, obviously due to its lion share (~ 90 %) in total
Indian food basket. Since time immemorial, fate of Indian agriculture heavily depends upon the
success of cereals production. Agriculture glory of India must be strengthened all the way through
achieving self sufficiency in food production first; secondly by improving our agriculture image at
global arena, by get redden off from net importer to net exporter, obviously through strong
presence in global agriculture market. We are marching in the right direction; cereals are the leaders
in the food commodity export especially rice “The Basmati Rice”. Since, as of now, Indian share in
the world trade is meagre (~1.0%), there are needs to scale up to the tune of 6% in very quick
succession. No doubt, Cereals and coarse cereals should be a front leader in this endeavourer. Since
a lot more has to be done; we have to have adhered on do more policy. This article discuss at length
on past glory, present status and future prospect of the great Indian food basket famously known as
“The Cereals”.
Agriculture is one of those activities of man that is greatly affected by climate. Therefore, a change in climate would in no small measure impact on agriculture, location notwithstanding. This work as a result examined the impact of climate change on maize and cassava yields in Southeastern Nigeria. Expost-facto research method in the context of quasi experimental research design was adopted for the study. Data for rainfall and temperature were obtained from Nigerian Meteorological Agency (NIMET); and those for crop yields came from Federal Ministry of Agriculture of Nigeria and Agricultural Development Programme (ADP) of selected states. The data were analyzed using descriptive statistics, multiple linear regressions and analysis of variance. Results showed that, there are evidences of climate change in Southeastern Nigeria, with notable fluctuations in the identified trends. Employing the trend analysis represented by the least square line, Abia State rainfall is increasing at 0.1026mm per annum, while Imo State is decreasing at -1.1255 mm per annum. All the states recorded positive slopes in mean temperature which shows an increase in their trends. The multiple regression model showed R2 values that ranged between 0.25 – 0.29 revealing that only 25 %- 29 % of cassava and maize yields could be explained by rainfall and temperature across the states and the result was significant at p<0.05 revealing that cassava and maize yields significantly depended on rainfall and temperature. Crop yields were also significantly different spatially. As a result of the findings the study strongly advocates, development of better and sustained environmental policies that will be beneficial to climate systems while creating sustainable food security.
M.Sc. (Ag.) in Agricultural Marketing & Cooperation
This includes the inception, present status and future aspects of the Mission as a comprehensive manner.
Energy consumption pattern in wheat production in sindhsanaullah noonari
Wheat (Triticum aestivium L.) is the main staple food for most of the population and largest grain source o the
country. It occupies the central position in formulating agricultural policies. It contributes 13.1 percent to the
value added in agriculture and 2.7 percent to GDP. Area and production target of wheat for the year 2012-13 had
been set at 9045 thousand hectares and 25 million tons, respectively. Wheat was cultivated on an area of 8805
thousands hectares, showing a decrease of 3.6 percent over last year’s area of 9132 thousand hectares. However,
a bumper wheat crop of 24.2 million tons has been estimated with 3.9 percent increase over the last year’s crop
of 23.3 million tons. The prospects for wheat harvest improved with healthy fertilizer off-take and reasonable
rainfall during pre-harvesting period. Energy is a necessary of life for human beings all over the world due to its
function in strengthening the security and contentment of the people. Energy demand is growing with the
passage of time due to infrastructural and industrial development. Energy is required to perform all the human
activities. It is need for food preparation, water heating and cooling, for lighting, for production of goods etc.
The study was focused on all types of energy (fossil fuels, chemicals, animals dung, animate etc). A sample of
60 farmers was selected from study area. A pre tested questioner was used to collect data from selected
respondents through personal interviews. Descriptive statistics and Cobb-Douglas production function was
applied to analyze the data. Result shows that wheat farmer achieved highest amount of net energy which was
calculated as small, medium and large farmers is 1368336.88, 1698003.79 and1702527.75 MJ/acre respectively.
In production of wheat large, medium and small farmers achieve amount of net energy which was calculated
41525.06, 38590.99, 39095.33 MJ/acre. The impact of various energy inputs on yield was studied. The share of
various energy types in total cost of production was estimated. Commercial energy (diesel and electricity)
consumed highest amount of energy in production of wheat.
Evaluation of Fertilizer Management on Yield and Yield Components and Product...Premier Publishers
This fertilizer management trial on maize was conducted to offer research evidence to the universal dispute on the economic viability and productivity of divergent fertility management strategies. We compared six treatments including a control or no fertilizer (T1), T2 NPK (15-15-15), T3 chemical and granular organic fertilizer with hormone mixed formula 1 (HO-1), T4 formula 2 (HO-2), T5 formula 3 (HO-3), T6 granular organic fertilizer (GOF). The trial was replicated thrice in a Randomized Complete Block Design with a plot size of 6 m x 5 m. The maize cultivar (Pacific 999 Super) and a fertilizer dose of 0.9 kg plot-1 were used. The results revealed that HO-3 produced the highest yield components and a significant (p < 0.05) yield (8,276.69 kg ha-1), representing an increase of (50 %) over the control. Also, HO-2 and NPK treatments recorded equal effects on maize yield (7,420.00- and 7,266.69 kg ha-1, respectively). The production cost, revenue and profit of HO-3 were highest (31,317.37-, 72,896.82- and 41,579.45-baht rai-1, respectively). A significant 17.4 % rise in profit was realized with HO-3 application over NPK treatment. The Benefit: Cost ratio of HO-3 fertilizer was the best (2.33) and suitable for farmers to maximize returns.
Impact of climate change on wheat yield using remote sensing technique | JBES...Innspub Net
The present study demonstrates the ability of GIS and RS in capturing the spatial temporal data. The changing climatic conditions in the country effects the agriculture. The impacts of climate change are not only restricted to the agricultural productivity of the Pakistan but changing climate also impose destructive impacts on the Land use change practices. Three districts of Punjab i.e. Attock, Multan and Gujrat were selected for analysis of climatic effect on wheat production. The time span that is used for analyzing the change in these areas was from 1999-2014. Climatic changes are not always negative ones but sometimes climatic changes are favoring the increased agricultural production. As the change in temperature and rainfall pattern affects the crop conditions, which changes the net production. It is concluded that for real time prediction of crop yield satellite remote sensing could be used for timely management of food crisis in Pakistan as well as in the world.
Food is life and the global food sustainability is essential to human being survival. The global food system is highly
complex and is driven by various factors including environment, cultural, social and economic drive. It is vital to understand
these drivers and their interaction in order to help to improve the public food sustainability policies. Global polices and projects
desperately required in order improving the global food sustainability. Food sustainability is one of the unsolved global issues
and great commitment is required starting from global policy makers, national governments, and every individual home. This
research paper includes analysis and study of various elements such as global change science, policy, food crisis, factor affecting
and challenging food security, data on status and future projection and potential ways of solving problems. The goal of food
sustainability is to enable all people throughout the world to satisfy their basic needs and have a reasonable quality of life without
compromising the quality of life of future generations. Agriculture sustainability is the best solution which can feed the world
without compromising the environment or threatening human health. Scientific evidence that global environment has changed
is overwhelming and indisputable. These phenomena have a direct impact on agriculture which in turn affects food
sustainability. The food price is always toward upward trend which is validated by the periodic average global food price
monitoring report released by the Food and agricultural organizations. The factors affecting and challenging the food security
are many including increased food consumption due to population increase, uneven distribution, changes in living styles, limited
resources, environmental problems, economic problems and others. The potential ways to solve food sustainability need to be
established and implemented effectively across the world.
Wheat crop responds to climate change in rainfed areas of District Mansehra, ...Innspub Net
Agriculture in many ways is affected by climate change and has impact for productivity of crops particularly in rainfed areas. Climate change related research remained a poorly investigated area in KP and instant study filled that gap by investigating impacts of change in climate on farm productivity. The secondary data, spread over 30 years from 1984 to 2013 pertaining to temperature, precipitation, area under cultivation and yield of crops was collected. Analytical models used are ARDL Model. The results pertaining to impact of temperature and precipitation on wheat yield suggest long run relationship among the variables. Temperature is positively and significantly related in Mansehra. The precipitation is positively and significantly related. Short run relationship implies that around 100% deviations from long-term equilibrium are adjusted every year in case of Mansehra. The results wheat areas suggest long run relationship among the variables based on F Statistics value. Both temperature and precipitation are positively and significantly related to the area under wheat in the long run in case of Mansehra. Based on objectives of the research study and field findings recommendations offered include; farmers awareness drive, policies to promote adaptation measures, enhancing farmers’ adaptive capacity to strengthen local resilience, participation of farming community in formulation of policies, making meteorological information available to farmers, Design research plans to evolve crops varieties addressing changing climatic challenges, construct water harvesting structures for high efficiency irrigation and further research to estimate range of temperature and precipitation within which crops under study perform better.
Extreme weather events and their impact on urban crop production: A case of K...Innspub Net
Extreme weather events are anticipated to increase the existing challenges and generate new combination of vulnerabilities, especially in developing countries. The agricultural sector is the most vulnerable due to overreliance on unpredictable rainfall. This study examined the impact of extreme weather events on urban crop production and the adaptation strategies applied by the farmers. Secondary data were collected through a literature survey and primary data were collected using structured interviews, observations and focus group discussions. A total of 108 crop farmers were interviewed in two wards of Kinondoni District. The Statistical Package for Social Sciences (SPSS) version 20 was used to analyze the data and Pearson Chi-square was used to test the statistical significance between variables. The study observed that, farmers perceived extreme weather events including floods (39%), extreme temperatures (36%), and drought (25%). These extreme weather events affected negatively crop production leading damaging of crops and low yields (38%), outbreak of crop pests and disease (38%), drying of water sources (20%), and loss of soil fertility (4%). Crop farmers used various adaptation strategies such as crop diversification (28%), the use of pesticides (23%), changing of cropping patterns and planting calendar (16%), irrigation practices (18%) and replanting (10%). The study recommends for adoption of new farming systems such as vertical farming systems for better output with the use of limited water and land resources.
Climate Change and Its Impact on Agricultural Production: An Empirical Review...Premier Publishers
Agriculture, which is the mainstay of the economies of many developing countries, is highly depends on climatic conditions. This paper aimed at reviewing the climate change and its impacts on agricultural production with the specific objectives of reviewing the farmer’s adaptation strategies and barriers to the climate change and the impacts of climate change on agricultural production and food security in sub Saharan Africa countries. Empirical evidence shows that most of the smallholder famers in Sub-Saharan Africa have experienced the adaptation strategy of switching from planting high water-requirement to low water-requirement crops, planting diversified crops, changed planting dates to correspond to the change in the precipitation pattern and mixed cropping. The farmers’ ability to adapt to climate change has faced by access to information, extension services and access to credit. The effect of long-term mean climate change has significance impacts on global food production and affects all dimensions of food security in several ways ranging from direct effects on crop production to changes in markets, food prices and supply chain infrastructure which may require ongoing adaptation. Finally, effective institutions on climate change at the global level help to facilitate the policy implementations and to combat the impact of climate change.
Since after the introduction of the potato in India in the early seventeenth century by the Portuguese traders, the potato has been widely grown and consumed in the country. These tuberous nutritious crops known as the king of vegetables is ranked as the fourth largest food crop in the world. A variety of processed products can be achieved that enhances the market value, marketability, and desirability of the product. In this review, we will discuss on the potato, current global and Indian scenario, scope and potential of processing market, health-related issues of potato. And discuss popular potato processed products and future outlook to improve the processing industry.
This study examined the influence of the characteristics of the audit committee on Palestinian firms’ value. The research explores precisely the effect on the Audit Committee characteristics’ efficiency, namely, independence, expertise, evaluating the relationship among dependent and independent variables. Secondary data collected from a list of companies were registered in the Palestine Stock Exchange from 2011 to 2018. Individual variables considered are the independence & expertise of the audit committee, whereas the ROA is employed as the dependent variable as an indicator of a firm’s value. The results showed that the Audit Committee’s independence & expertise substantially positive with ROA. The study concluded that the audit committee’s characteristics are enhancing firm performance. The implications of this study’s findings can be used by decisions and policymakers, the firm’s management, and other stockholders’ interests to create reliable ties between agents and the principals.
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict, and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates a strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends conflict management as an integral part of effective human resource management.
This paper examines the role of loan characteristics in mortgage default probability for different mortgage lenders in the UK. The accuracy of default prediction is tested with two statistical methods, a probit model and linear discriminant analysis, using a unique dataset of defaulted commercial loan portfolios provided by sixty-six financial institutions. Both models establish that the attributes of the underlying real estate asset and the lender are significant factors in determining default probability for commercial mortgages. In addition to traditional risk factors such as loan-to-value and debt servicing coverage ratio lenders and regulators should consider loan characteristics to assess more accurately probabilities of default.
This study examined the impact of financial innovation on money demand in Nigeria, using quarterly time series for the period 2009-2019. The dependent variable was money demand, represented by broad money, while the independent variable was financial innovation represented by modern payment channels such as volume of Automated Teller Machines (ATMs) transactions, volume of Point of Sales (POS) transactions, volume of Internet banking transactions, and volume of Mobile banking transactions. The study employed the ordinary least squares (OLS) regression technique as the estimation method within the cointegration, granger causality, and error correction modeling. The result obtained showed that financial innovation has mixed impact on money demand in Nigeria during the period of analysis. For instance, financial innovation has positive impact on money demand through volume of ATM transactions in the current period, two periods lagged of volume of mobile banking transactions, current period and one period lagged of volume of internet banking transactions, and current period’s volume of Point of Sales (POS) transactions in Nigeria. On the other hand, financial innovation has negative impact on money demand through one period lagged of volume of point of sales in Nigeria. On the stability of the demand for money function, the result of the stability tests based on the CUSUM test and CUSUM of squares test showed that the demand for money function was stable during the evaluation period. The study recommended that monetary policy strategy of the central bank of Nigeria (CBN) should be fine-tuned to ensure it is well suited to deal with the challenges posed by financial innovation by way of proliferation of sophisticated payment channels.
Equity financing is one of the sources of funding available to non-bank financial institutions which is quite prevalent in developed financial markets for small or start-up firms. This study empirically determined the effect of the Equity Financing Scheme on a sustainable increase in productivity of agro-allied small businesses in Nigeria. Data for this study were elicited through the use of a questionnaire structured in a five-point likert scale. The evaluation of the relationship between the dependent and independent variables was performed using the Ordinary Least Square regression technique. The study revealed that the equity financing scheme had a positive and significant effect on the sustainable productivity of agro-allied small businesses in South-South Nigeria. The study recommended that efforts should be made to educate the small business entrepreneurs on the benefits of equity financing as a viable option towards business growth and expansion and that the government through the various intervention agencies should restructure the long-term loan policies to give access to more growth-oriented agro-allied businesses, to increase their presently low capacity to procure heavy-duty technology to increase productivity and achieve food security in Nigeria. Small business owners should take advantage of the membership of cooperative societies and as well maintain good business relationships with suppliers; this will guarantee a continuous supply of needed materials and uninterrupted operations of the business.
This study seeks to evaluate the impact of public borrowing on economic growth in Nigeria using time series data from 1980 to 2018. Specifically, the study seeks to analyze the effect of domestic debt (proxy by Federal Government Bonds-FGB) and external debt (proxy by International Monetary Fund Loan-IMFL) on Nigerian’s Gross Domestic Product (GDP). To achieve this objective, secondary data was collected from the Central Bank of Nigeria Statistical bulleting and the Debt Management Office of Nigeria. A multiple regression model involving the dependent variable (GDP) and the independent variables (FGB and IMFL) was formulated and subjected to econometric analysis. These variables were adjusted with the Jarque-bera test of normality while the correlation result was used to check the possibility of multi-collinearity among the variables. The t-test was used to answer the research questions and test the formulated hypotheses at the 5percent statistical level. Results from the analysis show that a positive relationship exists between IMF Loan and Nigeria’s gross domestic product, while a negative relationship exists between FG Bonds and Nigeria’s gross domestic product, which violates the Keynesian theory of public debt. The study concludes that both domestic and external debt significantly affect economic growth in Nigeria. Therefore, it was recommended that public borrowing should be efficiently used and contracted solely for economic reasons and not for social or political reasons as this will help to avoid accumulation of debt stock over time.
Equity investment financing is an innovative way of financing the real sector which has considerable developmental potential. The study empirically determined the effect of Equity investment financing on sustainable increase in productivity among agro-allied small businesses in South-South Nigeria. The instrument of data collection is the research questions structured in a five-point likert scale. The evaluation of the relationship between the dependent and independent variables was performed using the Ordinary Least Square regression technique. The study revealed that equity investment financing has a positive and significant effect on the sustainable productivity of businesses in Nigeria. The study recommended educating small business entrepreneurs on the benefits of equity financing as a viable option towards business growth and expansion and that the government through the various intervention agencies should restructure the long-term loan policies to give access to more growth-oriented agro-allied businesses, to increase their presently low capacity to procure heavy-duty technology to increase productivity and achieve food security in Nigeria. Small business owners should take advantage of the membership of cooperative societies and as well maintain good business relationships with suppliers; this will guarantee a continuous supply of needed materials and uninterrupted operations of the business.
This paper aims to explore the relationships of the performance of producer responsibility organizations (PROs) for waste oil, waste electrical and electronic equipment (WEEE), and end-of-life vehicles (ELV). The methodology consists in estimating the cointegration equations between the variables of lubricating oil production (SIG), electric and electronic equipment (EEE), and vehicle production (VP) using dynamic ordinary least squares (DOLS). Subsequently, elasticities are got based on estimates for Spain over the period 2007-2019 using quarterly data. The main results were that SIG and EEE were cointegrated variables. The elasticity of the SIG variable up to EEE was positive at 2, 4166. Additionally, the elasticity of the SIG variable up to VP was 2, 4050. However, SIG and VP are not cointegrated variables; subsequently, it was not a stable relationship between these variables. Results suggest it was because EPR was applied in WEEE PRO join with a deposit refund system (DRS); meanwhile, EPR in ELV PRO had been applied without subsidies to purchase cars.
In the process of R&D globalization, due to market demand and preferential policies, many multinational companies choose to invest in R&D in China. With the increase of labor costs in coastal areas and the rapid economic development of the central and western regions, multinational companies have already shifted from coastal areas to central and western regions when choosing R&D regions in China, especially in Shaanxi Province. Therefore, studying the character of R&D investment and operating performance of Multinational Corporation in Shaanxi Province has important practical significance. This article uses the data of the R&D investment of multinational corporation in the joint annual inspection of Shaanxi Province in 2018 as the sample and uses EXCEL software to conduct data analysis to gain an in-depth understanding of the character of R&D and investment of multinational corporation in Shaanxi Province, business characteristics and business performance. And it is concluded that the R&D investment of multinational corporation in Shaanxi Province has a series of characteristics such as concentration of distribution, concentration of enterprise scale, and overall good performance of operating performance.
In Bangladesh, migrant worker’s remittances constitute one of the most significant sources of external finance. This paper investigates the existence of relation between remittance inflow and GDP and the causal link between them in Bangladesh by employing the Granger causality test under a VECM framework. Using time series data over a 38 year period, we found that growth in remittances does lead to economic growth in Bangladesh. In addition to the relationship, this paper also points out some issues that are working as impediments in getting remittance and give some recommendations to overcome those impediments.
In the context of the 4.0 revolution, technology applications, especially cloud computing will have strong impacts on all areas, including accounting systems of enterprises. Cloud computing contributes to helping the enterprise accounting apparatus become compact, help automate the input process, improve the accuracy of the input data. Besides, the issur of accounting, reporting, risk control and information security also became better, contributing to improving the effectiveness of accounting. However, besides the positive impacts, businesses also face many difficulties in deploying and applying cloud computing. However, this application requirement will become an inevitable trend contributing to improving the operational efficiency of enterprises. To promote this process requires from the State as well as businesses themselves must have awareness and appropriate decisions. Breakthroughs in information technology have dramatically changed the accounting industry and the creation of financial statements. The Internet and the technologies that use the power of the Internet are playing an important role in the management and accounting activities of businesses - who always tend to be ready to receive and use public innovations technology in collecting, storing, processing and reporting information.
In recent years, Vietnam has joined international intergration by strong export agreements of bilateral and multilateral; Vietnam’s merchandise export in 1995 was only US $5.4 billion, in 2018 Vietnam’s merchandise export increased by 45 times compared to 1995 with US $244 billion. Vietnam’s imports increased by 29 times in 2018 compared to 1995. This study is an attempt to test a method of estimating the influence of exports on several Supply-sidefactors such as production value, value added and imports through the expansion of the standard system W. Leontief I.O and Miyazawa-style economic-demographic relations. This study also tries to make an experiment in the “Leontief Paradox”.The result is that Vietnam’s export value spread to production and imports but spread low to added value, especially in the processing industry group’s fabrication. The study is based on the non-competitive I.O table in 2012 and 2018 with 16 sectors.
The profitability of commercial banks is influenced by a number of internal and external factors. This paper attempts to identify the internal factors which significantly influence the profitability of commercial banks in Bangladesh. In this study, profitability is measured by ROA and ROE which may be significantly influenced by the internal factors such as IRS, NIM, CAR, CR, DG, LD, CTI and SIZE of the bank. Data are collected from published annual reports during 2014--2018 of 23 commercial banks. Using simple regression model, it is found that CR has significant effect on the profitability and CAR has significant influence on ROA only. In addition to this, DG has significant effects on PCBs’ profitability (ROE only) where as IRS and CTI have significant influence on profitability (ROA only) of ICBs. Further, none of these variables have significant effects on the profitability of SCBs but CAR and CR are correlated with profitability (ROA only) and the causes may be the nature of services provided by SCBs to its clients. The internal policy makers should manage the influential internal factors of the banks in order to increase their profitability so that they can meet stakeholders’ expectations.
Using a series of econometric techniques, the study analysed interaction between monetary policy and private sector credit in Ghana. This study made use of monthly dataset spanning January 1999 to December 2019 of credit to the private sector (PSC) and broad money supply (M2). The results reveal that there exists cointegration, a long run stationary relation between monetary policy and private sector credit. This implies, increases in credit should prompt long-term increases in monetary policy. It is not surprising that growth in the private sector might have a stronger effect on monetary policy. The Error Correction Test is statistically significant and that all the variables demonstrate similar adjustment speeds. This implies that in the short run, both money supply and credit are somewhat equally responsive to their last period’s equilibrium error. There is unidirectional causation from private sector credit to monetary policy. It can be said that, there is an interaction between money supply and private sector credit. Thus, credit to private sector holds great potential in promoting economic growth. It can be recommended to the government to increase the credit flow to the private sector because of its strategic importance in creating and generating growth of the economy.
This paper investigates if forecasting models based on Machine Learning (ML) Algorithms are capable to predict intraday prices in the small, frontier stock market of Romania. The results show that this is indeed the case. Moreover, the prediction accuracy of the various models improves as the forecasting horizon increases. Overall, ML forecasting models are superior to the passive buy and hold strategy, as well as to a naïve strategy that always predicts the last known price action will continue. However, we also show that this superior predictive ability cannot be converted into “abnormal”, economically significant profits after considering transaction costs. This implies that intraday stock prices incorporate information within the accepted bounds of weak-form market efficiency, and cannot be “timed” even by sophisticated investors equipped with state of the art ML prediction models.
Applying the Arrow-Debreu-Mundell-Fleming model as an economic standard model, with combining axiological framework and epistemological model, it is proposed to analyze economic policies with using a synthetic model, where interest, exchange and tax rates are integrated together. Except normal monetary and fiscal policies mainly via interest and tax rates, there are feasible ways to utilize modified strategies via exchange and tax rates. When ones need to simulate national local market, ones can raise the exchange rate. Otherwise, when ones need to promote international global trade, ones may lower the exchange rate. It is found that tax reduction is good policy when tax rate is higher than normal and that tax increase is good social policy when tax rate is lower than normal, during economic depression. Also it is revealed that tax reduction is good social policy when tax rate is lower than normal, and that tax increase is good policy when tax rate is higher than normal, during economic overheat. While economic system seeks efficiency and social system pursues equality, common interest modifications with elastic exchange and tax rates could be applied for balancing efficiency and equality.
In recent times, agricultural sector has returned to the forefront of development issues in Nigeria given its contribution to employment creation, sustainable food supply and provision of raw materials to other sectors of the economy. In lieu of that, this study examines the impact of agriculture on the economic growth in Nigeria using annual time series data covering the sample period of 1981 to 2018. To analyse the data collected, Autoregression Distributed Lag (ARDL) model through the bounds testing framework is employed to measure the presence of cointegrating relations between real GDP, agricultural productivity, labour force, and agricultural export. Results show the presence of both short-run and long-run relationship among the variables, and that agriculture has a positive and significant impact on economic growth in Nigeria. These findings inform the Nigerian government on the need to expedite labour force (human capital) and agricultural export (non-oil) development with the view to achieving sustainable growth and development. In addition, developing skills and competencies of labour force through capacity building in the agricultural sector will encourage research and development thereby increase the export size, hence essential for long-term growth.
The article illustrates the results of the economic development of the first fifteen years of the XXI century under the conditions of unprecedented economic freedom, globalization and the appearance of new informational sectors up to and including the first attempts at revising liberalism. The analysis of statistical data demonstrates an obvious increase in the percentage of well-off people in many countries as well as the increased economic capabilities of small, medium and large businesses, whose assets are distributed among an ever-increasing number of owners. This provides the impetus to review our collective approach to liberalization and globalization, as well as to view its unexpected strong sides that make human progress possible.
This paper investigates the relationship between working capital management and financial performance of Pharmaceuticals and Textile firms listed at the Dhaka Securities Exchange in Bangladesh. The data analysis was carried on ten Pharmaceuticals and Textile firms for a period of 2013 to 2017. Secondary Data was analyzed by applying Descriptive Statistics, Regression and Correlation analysis to findthe relationship of current ratio, inventory conversion period and average payment period with Return on Asset. The findings indicate that the Pharmaceuticals and Textile firms’ performance is influenced by the variables relating to working capital. There is a positive relationship between profitability and current ratioand Inventory Turnover period shows a negative relationship with profitability but Average payment period shows insignificant impact on profitability. The study concludes that there exists a relationship between working capital managementand financial performance of Pharmaceuticals and Textile firms in Bangladesh. The study recommends that for the Pharmaceuticals and Textile firms to remain profitable, they should employ working capital management practice that will help in making decisions about investment mix and policy, matching investment to objective, asset allocation for institution and balancing risk against profitability.
Organizational behaviour involves the design of work as well as the psychological, emotional and interpersonal behavioural dynamics that influence organizational performance. Management as a discipline concerned with the study of overseeing activities and supervising people to perform specific tasks is crucial in organizational behaviour and corporate effectiveness. Management emphasizes the design, implementation and arrangement of various administrative and organizational systems for corporate effectiveness. While the individuals, and groups bring their skills, knowledge, values, motives, and attitudes into the organization, and thereby influencing it, the organization, on the other hand, modifies or restructures the individuals and groups through its structure, culture, policies, politics, power, and procedures, and the roles expected to be played by the people in the organization. This study conducted through the exploratory research design involved 125 participants, and result showed strong positive relationship between the variables of interest. The study was never exhaustive due to limitations in terms of time and current relevant literature, therefore, further study could examine the relationship between personality characteristics and performance in the public sector, where productivity is not outstanding, when compared with the private sector. Based on the result of this investigation it was recommended that organizations should provide emotional intelligence programmes for their membership as an important pattern of increasing co-operative behaviours and corporate effectiveness.
More from International Journal of Economics and Financial Research (20)
how to sell pi coins on Bitmart crypto exchangeDOT TECH
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
how to sell pi coins at high rate quickly.DOT TECH
Where can I sell my pi coins at a high rate.
Pi is not launched yet on any exchange. But one can easily sell his or her pi coins to investors who want to hold pi till mainnet launch.
This means crypto whales want to hold pi. And you can get a good rate for selling pi to them. I will leave the telegram contact of my personal pi vendor below.
A vendor is someone who buys from a miner and resell it to a holder or crypto whale.
Here is the telegram contact of my vendor:
@Pi_vendor_247
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
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how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
what is the best method to sell pi coins in 2024DOT TECH
The best way to sell your pi coins safely is trading with an exchange..but since pi is not launched in any exchange, and second option is through a VERIFIED pi merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and pioneers and resell them to Investors looking forward to hold massive amounts before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade pi coins with.
@Pi_vendor_247
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
Economic Impact of Climate Change on Wheat and Cotton in Major Districts of Punjab
1. International Journal of Economics
and Financial Research
ISSN(e): 2411-9407, ISSN(p): 2413-8533
Vol. 2, No. 10, pp: 183-191, 2016
URL: http://arpgweb.com/?ic=journal&journal=5&info=aims
*Corresponding Author
183
Academic Research Publishing Group
Economic Impact of Climate Change on Wheat and Cotton in
Major Districts of Punjab
Noman Arshed*
Lecturer, Economics, University of Management and Technology, C II Johar Town, Lahore, Pakistan
Shukrillo Abduqayumov BS Economics, University of Management and Technology, Lahore, Pakistan
1. Introduction
Stability in production of food within the country is necessary for long term food security and steady
development process. For low development countries, consistent supply of food provides them foundation to grow
and compete in international markets. For the case of Pakistan, agriculture sector contributes to 21% of gross
domestic product, 18% of exports and 45% of the labor force.
Considering the many benefits of the agricultural sector, it does not come easy. There are many challenges that
the agriculture sector faces, on top of this list is the effect of climate change. Karl (2009) explains the case of USA
where a rise in temperature and humidity lead to foster weeds, pests and fungi, which is costing farmers extra $11
billion per year to stabilize the crop production. Today, many countries on the globe are vulnerable to the climate
change and Pakistan is one among those countries exposed to it (Minister of Climate Change). Change in
temperature, and unpredictable precipitation serious problem for agricultural sector. Out of the 10 countries which
are most affected by the climate based disasters during 1994 – 2013 includes 5 from the Asia – Pacific Region as per
Global Climate Risk Index 2015 (APP, 2015). Zahid and Rasul (2011) highlighted that overall summers are
becoming warmer in Pakistan, which could adversely affect crop production. This increased temperatures will likely
increase the usage of water by industrial and agricultural users.
Climate change has a vital role in food security. Food security is defined as when all people at all times have
access to nutritious, sufficient and safe food to meet their food requirements and to maintain a healthy and active life
(FAO, 1996). Food security involves production, accessibility and distributions. Food Security also sees that those
who produce our food is able to earn decently from processing, producing, transporting and serving the food. The
studies show that for food production temperature and precipitation have significant impact (Janjua et al., 2010;
Mahmood et al., 2012), some studies found unfavorable effects of climate change on agricultural productivity
(Lobell and Field, 2007; You et al., 2009).
In most of the developing economies, low incomes are causing stagnant production of food, hence governments
are forced to boost the agricultural output increase the sale prices. This approach usually motivates the farmers to put
extra effort in production and increase in the output of agricultural products.
1.1. Agricultural Productivity
In 1961 3.5 billion world populations were cropping by using 1.37 billion hectares of the land. Later on when
world population doubled to 7 billion, while land under use increased only by 12 percent which is 1.53 billion
hectares. Previously world was concerned that by tripling of world population there will be a food shortage, but after
tripling world population agriculture has increased globally. World started receiving more outputs from the same
Abstract: The long run impact of climate change on the productivity of major crops in the districts of Punjab is
analyzed for the time period of 1970 to 2010. This study used deviations from average maximum annual
temperature and deviations from average rainfall are used as indicators for climate change. While other variables
include sale price, fertilizer use and number of tube wells. In order to incorporate long timer periods, this study
used Panel ARDL model. The results show that cotton productivity is more positively sensitive to price changes;
an increase in temperature, tube wells and fertilizers while wheat productivity is more positively sensitive to the
rainfall in the long run. Consequently, in the short run, wheat productivity equilibrium is faster converging. Hence
deviations from average rainfall are harmful to cotton crop in the long run and cotton & wheat in the short run,
while deviations in maximum temperature is only harmful for cotton crop in the short run.
Keywords: Climate Change; Agricultural productivity; Panel Co-integration; Panel ARDL; Punjab Districts.
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184
resources. At the global level the long run trend from 1900 food has been increasing in fact. Adjusted dollars in
inflation, food rates reduced by one percent over the year of the 20th century, but something changed over the past
decade. In 2002 real prices of food started increasing and the shock was not momentary one. In 2008, 2010, and
2012 agricultural prices of commodity sharply increased. Factors of demand side like growth of population increase
in meat per capita consumption and weather created food shocks. Events like 2012 North American drought are
major causes of higher prices of food in recent years. But the continuation of rising prices of commodity has brought
concerns that either agriculture is facing new stress on growth. In fact, for major grains as like wheat and rice, rates
of average growth yield have slow about 2 percent every year from 1970s to 1980s and about 1 percent every year
from 1990 (Boserup, 2005; International Food Policy Research Institute, 2015).
For the measurement of the effect of climate, maximum temperature reported can be used. Temperature
maximum is important because all functionalities of crops dependent on maximum temperature so that crops can
develop their growths. In Maximum temperature many crops can have rapid growth, but their productivity can be
reduced. If their higher growth period is not complemented with water and fertilizer supply (USGCRP, 2009).
Precipitation is another climatic variable which influences agricultural productivity. Annual precipitation is
measured in millimeters. Precipitation plays vital role in agriculture and agricultural crop’s life depend on water. In
Pakistan Indus Basin receives 40 million acre feet of water from precipitation yearly. Essentially, there are two
primary wellsprings of precipitations in Pakistan i.e. Monsoons and Western aggravations and around 70 percent of
yearly rainstorm precipitations happens from July to September (Ahmed et al., 2007).
Number of tube wells indicates water availability for farmers. Water availability is great concern for a farmer at
the time of sowing the seeds until harvest season. Number of tube wells include private and government owned tube
wells and it is used for irrigation purposes in agriculture. Total area irrigated in Pakistan is 18.63 million hectares
and total area irrigated in Punjab region is 14.88 million hectares, total area irrigated by tube wells in Pakistan is
3.71 million hectares (19.91% of total) and a total area of Punjab region irrigated by tube wells is 2.82 million
hectares (18.95% of total) (Pakistan Bureau of Statistics, 2014; Siddiqi, 2008). The previous green revolution
experience that Pakistan had was contributed because of fertilizers, improved seed and increased water supply
(Ahmad, 2004).
Fertilizer is basically a chemical or natural substance used on land to boost its fertility. Most important types of
fertilizer are mixture of carbon, hydrogen and oxygen. Land which has been frequently cropped, usually gets
infertile over the time and exhibits fall in productivity. The consumption of fertilizer in Pakistan is 4089.1 thousand
nutrient tons and its 2803.9 thousand nutrient tons in the Punjab region in 2014 (National Fertilizer Development
Center, 2014).
Studies by United Nations agencies on food price variation and natural hazards in Pakistan has found that wheat
consumption was decreasing as a result of high food prices and falling income (FAO, 2005).
Following to introduction section, is a literature review section which will be explored through the empirical
studies regarding the role of independent variables. After this is the methodology section which provides the model
and the data descriptive, this is followed by the estimation of the model using the data. At the end the conclusion and
policy implication will be illustrated.
1.2. Objective of the Study
Considering the fact that Agriculture is the backbone of Pakistan, hence studying the determinants of
agricultural productivity is crucial. In this case, the objective of the study the productivity of the major crops (i.e.
wheat and cotton) using the 30 year each, data of 12 major districts of Punjab. Primary determinants include the
indicators of climate change like temperature and rainfall, secondary determinant include the sale price and control
variables include the fertilizer use and the number of tube wells. Since each district includes 30 years of data, this
study will use a panel ARDL approach to determine the short run and long run effects.
2. Literature Review
Wheat is one of the important staples on the globe, which consists high quality fiber and protein that consists of
carbohydrates in starch form (Bayer Crop Science). Wheat is the most critical crop in Pakistan; it is sown in rabbi
(winter) season and harvested in kharif (spring) season. It is grown under different climates and soils and temperate
regions are more compatible for wheat production under rainfall of 30 and 90 centimeters. Total area cultivated
under whet production in Pakistan is 9199.3 thousand hectares and total wheat production 25979.4 thousand tons in
2014 (Pakistan Bureau of Statistics, 2014).
Siddiqui et al. (2012) concluded that increase in the temperature in the short run hampers wheat productivity
while it boosts productivity in the long run. While an increase in rainfall harms wheat in the short run as well as in
the long run. Hanif et al. (2010) studied two harvesting season kharif and rabbi, and their results from rainfall in
kharif season has significant positive effects on land prices, because of an increase in the productivity of the crops.
Mendelsohn et al. (1996) use the Ricardian model to predict the farm value against changing temperatures for USA.
This showed that the effect of temperature followed inverted U shape even for fertile lands.
Janjua et al. (2010) advocated that wheat crop is not sensitive to changes in climate in the case of Pakistan.
Sultana et al. (2009) compared the wheat crops for ten locals of Pakistan based on climatic zones. Overall increase
in temperature leads to decrease in the productivity.
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(Cotton) is the most important fiber producing crops on the globe. It produces fiber for textile industries and also
feeds oil industries with its seeds which are rich of oil. It is also considered as a cash crop for many underdeveloped
cotton producing countries and main source of income for them. This crop is grown in tropical, sup-tropical and
temperate climates. It is sensitive to temperature which requires higher than 20 degrees. Punjab cotton production
mainly takes place around the Indus River, where water from the glaciers is vital for this crop (Raza, 2009). Siddiqui
et al. (2012) showed that the change in temperature and rainfall has negative impact on cotton productivity.
Anwar et al. (2007) investigates that worldwide temperature variation may decrease the crop productivity by
29%. Hussain and Mudasser (2007) studied two districts of Pakistan, first Sawat 960 meters above sea level and
other is Chitral 1500 meters, here the effect of increase in temperature of crops was positive in Chitral and negative
in Sawat.
Kotschi and Müller-Sämann (2004) stated that organic way of cropping can be opted to dampen the effects of
environmental change. Reidsma et al. (2010) indicated that if the farmers do not have alternative crops to rotate then
the harmful effect of climate will be translated into farmer wages.
Vanhove and Van Damme (2011) concluded that if the climate change is not adapted, then by 2050 average
yield of wheat will be reduced by 10%. It is expected that the temperature will rise 2 degrees Celsius and the rainfall
will change about 300 mm per year, so there need to focus on crop sustainability as by 2050 there will be 240
million hungry people in sub-Sahara Africa only. Zhai and Zhuang (2009) forecasted the weather change in
Southeast Asia and proved that the under developing economies in this region will experience loss in their
agriculture. By 2080 the agricultural output will be reduced by 17.3%. Since these economies are dependent on crops
they will experience fall in welfare and incomes.
Darwin et al. (1995) studied the crop productivity in Canada. They proposed that increase in temperatures in
alpine and arctic regions is prone to expand the land's quantity suitable for productivity of agriculture while an
increase in the temperature in dry areas lead to lessen soil wetness. Xiao et al. (2008) evaluated the effect of
temperature between two areas which are different in terms of the altitude as compared to the sea level. The results
revealed that in higher altitudes increase in temperature is beneficial to the crop productivity.
Lobell et al. (2005) studied the effect of temperature for the wheat crops in Mexico for the case of 1988 to
2002. In these two decades the rise in temperature lead to 25% rises in the productivity of wheat.
Zhang and Nearing (2005) showed though the controlled study in the central state of Oklahoma and showed that
a decrease in the rainfall has a higher detrimental impact on crops while the increase in the increase in the
temperature can be countered little bit using the proper fertilization of crops.
Wolf et al. (1996) studied the wheat crops in Europe and found that extreme temperatures will lead to a
reduction in the productivity.
All the previously studied only checked the effect of increase in temperature or rainfall on the crops, but since
the level of rainfall or temperature can be different in different regions, so its coefficient cannot be compared. Hence
this study has use deviations from the mean, which will represent the effect of volatility of climate on crops.
3. Methodological Framework
3.1. Data
In order to evaluate the impact of climate change on the cotton and wheat productivity, 12 major districts of
Punjab Pakistan are selected.
i. Lahore
ii. Multan
iii. Sargodha
iv. Sialkot
v. Faisalabad
vi. Rawalpindi
vii. Bahawalpur
viii. Bahawalnagar
ix. Kasur
x. Rahim Yar Khan
xi. Mianwali
xii. Jhelum
For these districts the data for the years of 1970 to 2010 is extracted from the annual reports of Punjab Bureau of
Statistic (2009). Since the number of years per district is more than 20 and more than the cross sections, hence this
study will use panel cointegration approach (Eberhardt, 2011; Pedroni, 2008).
3.2. Estimation Model
This study will construct the productivity model for the wheat and cotton crop as they are two of the major crops
of Pakistan, covering both kharif and rabbi season.
𝑃𝑊𝑖𝑡 = 𝛽𝑖 + 𝛽1 𝑇𝑀𝐴𝐷𝑖𝑡 + 𝛽2 𝑇𝑀𝐼𝐷𝑖𝑡 + 𝛽3 𝑃𝑅𝐷𝑖𝑡 + 𝛽4 𝑇𝑊𝑖𝑡 + 𝛽5 𝐹𝐸𝑅𝑖𝑡 + 𝛽6 𝑊𝑃𝑅𝑖𝑡 + 𝜀𝑡 --
(Wheat Model)
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186
𝑃𝐶𝑖𝑡 = 𝛼𝑖 + 𝛼1 𝑇𝑀𝐴𝐷𝑖𝑡 + 𝛼2 𝑇𝑀𝐼𝐷𝑖𝑡 + 𝛼3 𝑃𝑅𝐷𝑖𝑡 + 𝛼4 𝑇𝑊𝑖𝑡 + 𝛼5 𝐹𝐸𝑅𝑖𝑡 + 𝛼6 𝐶𝑃𝑅𝑖𝑡 + µ𝑡 --
(Cotton Model)
I is number of years from 1970 to 2010 t is number of twelve districts of Punjab region
Above are the basic equations for the wheat and cotton model, but since these variables depict non stationary
nature, they form equilibrium which is influenced by their past disequilibrium. In order to incorporate this dynamic,
this study will use the panel ARDL model in which the long run model is same for all cross sections, but the short
run model is allowed to vary across the cross sections.
𝛥𝑃𝑊𝑖𝑡 = 𝛽𝑖 + 𝛽11𝑖 𝛥𝑇𝑀𝐴𝐷𝑖𝑡 + 𝛽12𝑖 𝛥𝑇𝑀𝐼𝐷𝑖𝑡 + 𝛽13𝑖 𝛥𝑃𝑅𝐷𝑖𝑡 + 𝛽14𝑖 𝛥𝑇𝑊𝑖𝑡 + 𝛽15𝑖 𝛥𝐹𝐸𝑅𝑖𝑡 + 𝛽16𝑖 𝛥𝑊𝑃𝑅𝑖𝑡 −
𝛿(𝑃𝑊𝑖𝑡 − 𝛽1 𝑇𝑀𝐴𝐷𝑖𝑡 − 𝛽2 𝑇𝑀𝐼𝐷𝑖𝑡 − 𝛽3 𝑃𝑅𝐷𝑖𝑡 − 𝛽4 𝑇𝑊𝑖𝑡 − 𝛽5 𝐹𝐸𝑅𝑖𝑡 − 𝛽6 𝑊𝑃𝑅𝑖𝑡) + 𝜀𝑡
′
--
(Wheat ARDL model)
𝛥𝐶𝑊𝑖𝑡 = 𝛼𝑖 + 𝛼11𝑖 𝛥𝑇𝑀𝐴𝐷𝑖𝑡 + 𝛼12𝑖 𝛥𝑇𝑀𝐼𝐷𝑖𝑡 + 𝛼13𝑖 𝛥𝑃𝑅𝐷𝑖𝑡 + 𝛼14𝑖 𝛥𝑇𝑊𝑖𝑡 + 𝛼15𝑖 𝛥𝐹𝐸𝑅𝑖𝑡 + 𝛼16𝑖 𝛥𝐶𝑃𝑅𝑖𝑡 −
𝜃(𝐶𝑊𝑖𝑡 − 𝛼1 𝑇𝑀𝐴𝐷𝑖𝑡 − 𝛼2 𝑇𝑀𝐼𝐷𝑖𝑡 − 𝛼3 𝑃𝑅𝐷𝑖𝑡 − 𝛼4 𝑇𝑊𝑖𝑡 − 𝛼5 𝐹𝐸𝑅𝑖𝑡 − 𝛼6 𝐶𝑃𝑅𝑖𝑡) + µ𝑡
′
--
(Cotton ARDL model)
Above equations is the panel ARDL specification for wheat and cotton model, the coefficients θ and δ will
depict the error adjustment terms, while coefficients inside the parenthesis are long run coefficients and outside are
the short run coefficients.
3.2.1. Dependent Variables
PW = Wheat productivity
PC = Cotton productivity
3.2.2. Independent variables
TMAD = Temperature maximum deviation
PRD = Log of Precipitation deviations
TW = Log of number of tube wells
FER = Log of sale of fertilizers
WPR = Log of wheat price
CPR = Log of cotton price
3.3. Descriptive Statistics
Table 1 of descriptive statistics reveals that all of the variables included in the model are non-normal, which are
only allowed for estimation as per central limit theorem. While variables other than the fertilizer use have kurtosis
values, not equal to 3 which means that either the variable have too many outlier (case of kurtosis > 3) or too few
outliers (case of kurtosis < 3), this advocates the case of using heterogeneous intercepts in panel data model instead
of pooled ordinary least squares. Here we can see that only the productivity of cotton (PC) and the deviations of
maximum temperature have standard deviation higher than the mean value, which shows that these variables are
over-dispersed, this means that these variables are not following a similar pattern in each district.
Table-1. Descriptive stats
Statistics PC PW LWPR LCPR FER LPRD2 TMAD TW
Mean 4.08 1.66 4.67 5.37 10.17 6.03 0.00 8.70
Median 1.83 1.75 4.50 5.03 10.40 6.11 0.03 8.79
Maximum 138.33 3.47 6.86 6.59 12.37 7.21 3.64 11.43
Minimum 0.00 0.14 2.90 4.72 6.91 -3.19 -14.14 4.49
Std. Dev. 14.65 0.75 1.04 0.58 1.34 0.72 1.22 1.27
Skewness 6.85 -0.27 0.06 0.88 -0.76 -6.57 -5.45 -0.81
Kurtosis 51.23 2.20 2.09 2.37 2.95 76.18 60.72 3.61
Jarque – Bera 39483.90 17.31 16.71 41.66 46.39 88900.60 55921.66 52.72
Probability 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Sum 1537.97 749.31 2242.34 1545.45 4942.38 2329.10 0.53 3688.92
Sum Sq. Dev. 80681.82 253.12 513.70 95.78 868.67 199.38 574.54 686.22
Observations 377.00 451.00 480.00 288.00 486.00 386.00 389.00 424.00
Table 2 provides the multicollinearity diagnostics; here 5 different criteria, are provided which can indicate the
presence of the multicollinearity in the model. Here we can see that none of the Eigen value is near to 0, none of the
condition index value is above 15, none of VIF is more than 10, none of tolerance value is less than 0.10 and none of
the R square of auxiliary regression is higher than 0.7, all of these indicators are within the thresholds hence we can
say that there is no multicollinearity (Belsley et al., 1980; Belsley, 1991; Gujarati and Porter, 2004; Theil, 1971).
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Table-2. Multicollinearity diagnostics
Wheat model
Variables Eigen value C Index VIF Tolerance R2
xi,X
WPR 1.98 1.00 1.23 0.81 0.19
TMAD 1.19 1.29 1.04 0.96 0.04
PRD 0.84 1.53 1.05 0.95 0.05
FER 0.67 1.72 1.88 0.53 0.47
TW 0.31 2.51 1.99 0.50 0.50
Cotton Model
CPR 1.91 1.00 1.10 0.90 0.09
TMAD 1.15 1.28 1.03 0.97 0.03
PRD 0.92 1.44 1.10 0.91 0.09
FER 0.76 1.58 2.18 0.46 0.54
TW 0.25 2.77 2.41 0.41 0.58
4. Estimation
The following section will estimate the data according to the estimation model provided in order to achieve the
objectives of the study.
4.1. Unit Root Test
Gujarati and Porter (2004) specify one OLS assumption relevant to the data which has long time series
component, the assumption is ‘data must be fixed in repeated sampling’, this in other words mean that variables must
be stationary in order to use the OLS model. Table 3 below shows 4 types of panel unit root tests which includes
LLC (Levin et al., 2002), IPS (Im et al., 2003) and Fisher based unit root tests. Here the null hypothesis is that the
variable is non stationary as compared to the alternative hypothesis of variable being stationary. Table 3 below
provides the p values in parenthesis which will be used to decide. From the results in table 3 we can say that variable
WPR, CPR, PW, PC and TW are non-stationary while others are stationary at level. Since variables are in mixed
order of integration, this implies using ARDL cointegration based model.
Table-3. Panel Unit Root Tests
Panel Unit Root Test
Levine, Lin & Chu Im, Pesaran & Shin ADF - Fisher PP - Fisher
Variables Statistic (P value) Statistic (P value) Statistic (P value) Statistic (P value)
PW -3.20 (0.00)* -1.06 (0.14) 24.41 (0.44) 36.42 (0.05)*
PC -1.27 (0.10) -1.25 (0.10) 33.97 (0.05)* 36.12 (0.03)*
TMAD -8.39 (0.00)* -9.66 (0.00)* 128.5 (0.00)* 178.4 (0.00)*
PRD -2.74 (0.00)* -7.99 (0.00)* 102.6 (0.00)* 196.7 (0.00)*
TW -1.00 (0.16) 0.56 (0.71) 27.32 (0.29) 39.64 (0.02)*
FER -5.62 (0.00)* -2.17 (0.01)* 45.56 (0.00)* 173.5 (0.00)*
WPR 4.69 (1.00) 8.99 (1.00) 0.19 (1.00) 0.15 (1.00)
CPR 10.38 (1.00) 9.87 (1.00) 0.03 (1.00) 0.00 (1.00)
* significant at 10%
4.2. Panel Cointegration Tests
Since few of the variables are non-stationary, this could lead to spurious results unless cointegration between the
variables is confirmed. In table 4, Pedroni (1999;2004) and Kao (1999) residual based panel cointegration tests are
provided, for these tests the null hypothesis is that there is no cointegration. Using the p values in parenthesis we can
conclude that majority of tests are indicating the presence of cointegration between the variables for wheat and
cotton model. This allows us to use the non-stationary variables in the estimation process.
Table-4. Panel Cointegration Tests
Pedroni Residual Panel Cointegration Test
Productivity of Wheat Productivity of Cotton
Panel v-Statistic -1.59 (0.78) -0.71 (0.97)
Panel rho-Statistic -1.91 (0.03)* 0.99 (0.72)
Panel PP-Statistic -11.31 (0.00)* -2.24 (0.00)*
Panel ADF- Statistic -5.22 (0.00)* -1.96 (0.01)*
Group rho-Statistic -0.82 (0.20) 1.36 (0.91)
Group PP-Statistic -15.02 (0.00)* -6.02 (0.00)*
Group ADF-Statistic -8.34 (0.00)* -2.63 (0.00)*
Kao Residual Panel Cointegration Test
ADF T Statistic -4.26 (0.00)* -2.73 (0.00)*
* significant at 10%
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4.3. Long Run Estimates
Table 5 shows the long run estimation results generated from the estimation of the panel ARDL model. Here we
can see that since other than the price, all of the variables in both models are supply related hence the model depicts
the supply of wheat and cotton. Because of this the coefficient of the price variable is positive. Here we can see that
the coefficient of price in cotton model is bigger as compared to wheat model, this means the cotton has the higher
price elasticity of supply, so boosting cotton production is easier by increase cotton support price as compared to
wheat using wheat support price. While studying the climate effects we can see that if there is a 1% increase in the
maximum temperature above average, it increases the productivity of wheat and cotton by 0.08% and 0.10%
respectively in the long run, this is because both crops required dry season at the time of harvest. While if there is a
1% increase in rainfall above average, then it increases the productivity of wheat by 0.29%, while decreases the
productivity of cotton by 0.15% on average in the long run. An increase in the tube wells improves the irrigation,
here if there is a 1% increase in the number of tube wells; it improves the productivity by 0.14% for wheat and
0.80% for cotton. Similarly fertilizers are also more beneficial for cotton as1% increase in fertilizer use increases its
productivity by 0.47%, while it only increases productivity of wheat by 0.07% in the long run.
Table-5. Panel ARDL Long run Estimates
Long Run ARDL Estimates
Productivity of Wheat Productivity of Cotton
Independent variables Mean value Coef. (prob.) Coef. (prob.)
Wheat price 0.26 (0.00)*
Cotton price 0.44 (0.00)*
Dev. in Max Temperature 0.001 0.08 (0.00)* 0.10 (0.05)*
Dev. in Precipitation 3.33 0.29 (0.00)* -0.15 (0.02)*
Tube wells 0.14 (0.02)* 0.80 (0.01)*
Fertilizers 0.07 (0.27) 0.47 (0.01)*
* significant at 10%
4.4. Short Run Estimates
Panel ARDL provides heterogeneous short run estimates in table 6, which are different for each cross section,
and also reports the mean coefficient in the overall model. Hence this model allows each district to deviate around
the equilibrium differently in the short run, and also take different time to reach to homogeneous equilibrium. We
can see here that the increase in the wheat and cotton price in short run increases the productivity of wheat and
cotton by 0.52% and 0.97% respectively. In the short run if there is a 1% increase in the average maximum
temperature, it increases the wheat productivity by 0.06% while decreases the cotton productivity by 0.12% on
average. In the short run, an increase in the average rainfall is harmful for wheat crop by 0.28% and for cotton by
0.58% on average. Increase in tube wells and fertilizers do not improve the productivity of wheat, but both of them
improve the productivity of cotton by 0.72% and 0.68% on average in the short run.
While analyzing the short run coefficients it is pertinent that the adjustment coefficient must be evaluated, here
we can see that if there is 1% deviation from the long run equilibrium for both crops, on average across the districts,
the wheat model will adjust itself 0.58% each time period, while the cotton model will adjust itself 0.29% each time
period significantly. These coefficients are negative and significant showing the long run model is sustainable, while
the coefficients are not near to -1 which is because of high production lag of crops.
Table-6. Panel ARDL Short run Estimates
Short Run ARDL Estimates
Model Productivity of wheat Productivity of Cotton
Independent variables Coef. (prob.) Coef. (prob.)
ECM-1 -0.58 (0.01)* -0.29 (0.00)*
Wheat price 0.52 (0.03)*
Cotton price 0.97 (0.06)*
Dev. in Max Temperature 0.06 (0.10) -0.12 (0.00)*
Dev. in Precipitation -0.28 (0.00)* -0.58 (0.03)*
Tube wells -0.20 (0.54) 0.72 (0.00)*
Fertilizers -0.05 (0.66) 0.23 (0.42)
Intercept -1.77 (0.01)* 0.68 (0.01)*
Diagnostics
Lag order 3,3,3,3,3,3 1,1,1,1,1,1
Observations 314 177
AIC -0.18 -0.57
* significant at 10%
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Following table 7 provides the diagnostic tests for both productivity of wheat and productivity of cotton model.
For both models, only Jarque Bera normality test shows the presence of non-normal residuals, since the sample size
is more than 30, hence as per central limit theorem model is asymptotically normal. While other tests like
autocorrelation test, hetroskedasticity test, cross sectional dependence, Ramsey mis-specification test and
contemporaneous correlation test show absence of any issue in both wheat and cotton model.
Table-7. Post Regression Diagnostics
Diagnostic Tests
Model Productivity of Wheat Productivity of Cotton
Autocorrelation Q stat first order 0.63 (0.42) 2.57 (0.07)
Hetroskedasticity Test
Breusch Pagan Godfrey1 6.28 10.62
Cross Sectional Dependence Pesaran Scaled LM 1.14 (0.26) 2.12 (0.08)
Normality test Jarque Bera 83.46 (0.00) 23.79 (0.00)
Mis-Specification Test
Ramsey RESET F-Test
0.16 (0.67) 0.78 (0.37)
Contemporaneous Correlation -0.00 (0.95)
5. Conclusion
This study is designed to evaluate the effect of fluctuations of climate of major crops for several districts of
Punjab Pakistan. In this regard study used deviations of temperature and rainfall as the indicator of climate change.
And control variable includes the price of the crop, use of fertilizers and tube wells.
This study used Panel ARDL to evaluate the short run and long run impact of climate change on wheat and
cotton crops. Diagnostic test revealed that model is free from the problems of autocorrelation, cross sectional
dependence, hetroskedasticity, multicollinearity, mis-specification and contemporaneous correlation.
The long run results show that the rise in temperature from its mean value will lead to increase the productivity
of cotton and wheat. While the increase in the rainfall from the mean value, will lead to increase in productivity of
wheat but decrease in productivity of cotton. An increase in the tube wells leads to increase in wheat and cotton
productivity. Also in long run fertilizer is only fruitful in the case of cotton crops. Most importantly the positive
coefficient of prices reveals that model is supply function, price increase have a stronger effect on increase in
productivity for the case of cotton as compared to wheat.
In the short run for the case of wheat we can see that wheat price still has a persuasive effect for the sellers of
wheat, the change in temperature is insignificant, rainfall fluctuations are harmful, while no effect of tube wells and
fertilizer use. In the case of cotton, it can be seen that the cotton price has a higher persuasive effect on suppliers.
Temperature and rainfall fluctuations are harmful and increase in irrigation through tube wells is beneficial.
Both wheat and cotton models are converging, it indicates that the constructed models can be used to apply
intervention to boost the productivity using the policy options to counteract the reduction in productivity from
climate or other factors. District governments can boost the output by offering sellers higher sale prices. Increase in
tube well installation and proper utilization of fertilizers can counteract to decrease in the productivity.
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