Sajid Ali1, Nouman Badar1, Hina Fatima2
E-mail | sajid_economist@yahoo.com
...">This study attempts to forecast production and yield of two main cash crops namely sug- arcane and cotton crops of Pakistan by using Auto Regressive Moving Average (ARMA) and Auto Regressive Integrated Moving Average (ARIMA) models of forecasting. Using data for 1948 to 2012, productions and yields of both crops were forecasted for 18 years starting from 2013 to 2030. ARMA (1, 4), ARMA (...
John Stinespring, Ryan T. Cragun*
...a simple Markov model to forecast future rates of religious nonaffiliation. A two-period, two-variable Markov switching model is used which yields a tractable steady state solution and growth path for the share of the population that is nonreligious. The model setup and solution are shown to be both intuitive and determined by three parameter values. The authors illustrate its use by estimating these parameter values using biannual data from the 1973 to 2012 G...
Usman Shakoor1*, Mudassar Rashid1, Abdul Saboor2, Nabila Khurshid1, Zuhair Husnain2 and Abdul Rehman2
...ion are helping tools to forecast scenarios for the climate in an area. Changes in these tools from the past due to any unavoidable circumstances for today and in the future is refers to climate change (CC). Besides other living being, crops are either benefited or adversely affected by these changes in the climate of an area. Maize is one of the widely grown crops in the world and even in Pakistan has also influenced in either way. Current study employed vect...
1S. A. Khan and 2S. Jha
Effect of dates of sowing, moisture regimes, varieties and weather factors on incidences of aphid, Lipaphis erysimi (Kalt.) in rape and mustard
...ith medium range weather forecasts of 5 days available from India Meteorological Department (IMD), could be useful to forewarn aphid 2 days in advance for farmers. To escape critical aphid incidence, rape and mustard crops need to be sown by 15 October, because crops sown beyond this period are likely to be adversely affected by aphid. Keywords : Aphid, sowing date, moisture regime, weather parameters, correlation, regression
...
Dhananjoy Mandal 2K. Baral 3M. K. Dasgupta
Developing site-specific appropriate precision agriculture
...ogy, agrometeorology and forecasting inputs and outputs by marketing, production, protection and processing, and other essential information provided through a decision support system (DSS), in an agriinformatics networking such that is not ordinarily available to Indian farmers in general. Due to Precision Farming (PF), production increased by 40 to 60 percent farmers’ margins of the produce and reduction of the commission charged by the middlemen to 7-...
Dilshad Ahmad*, Muhammad Irfan Chani and Asad Afzal Humayon
.... The study attempted to forecast major crops area, production, yield and per capita food availability using Autoregressive Integrated Moving Average (ARIMA) model. Sixty-seven years annual time series data from 1947-48 to 2013-14 was obtained to forecast major crops and per capita food availability for 21years from 2014-15 to 2034-2035. Findings of the study pointed out increasing trends; major crops area, production, and y...
Hassan Hashim Ghalib, Syed Attaullah Shah*, Abbas Ullan Jan and Ghaffar Ali
Muhammad Jamal Nasir*, Anwar Saeed Khan and Said Alam
... the area to predict and forecast the changing weather and climate. Knowing such traditional knowledge provides an opportunity to understand how the farmers are adapting to new type of weather. The study was carried out in Balambat Tehsil District Dir Lower. They study is primarily based on questionnaire survey and focus group discussion. A total of fifteen villages out of total 173 were selected for study, 75 farmers were interviewed, 05 from each of the 15 s...
Wang Jian1, Abdur Rehman2*, Noor Khan3, Wang Zhengjia4, Ji Peng-fei5, Xie Cong6, Muhammad Niamatullah Khan Babar7 and Raheel Saqib8
...ualified. Finally we can forecast the future development trend of rural households’ consumption structure and income level. By means of the positive analysis, the countermeasures and recommendations have been proposed to develop the rural economy and consumer market in Hebei Province. ...
Farhan Ahmed, Hassnain Shah, Irum Raza* and Abdul Saboor**
...stify;"> This paper forecasts milk production in Pakistan using time series data from 1990 to 2010. ARIMA (p, d, q) model is considered for estimation where ‘p’ is the order of the autoregressive process; ‘d’ is the order of the homegeneity and ‘q’ the order of the moving average process. Presence of trend in data was checked through time series plots and stationarity through auto correlation and partial auto correlatio...
Saleem Abid1*, Nasir Jamal2, Muhammad Zubair Anwar3 and Saleem Zahid4
...cus of this study was to forecast area and production of potato crop in Pakistan using the best fitted model. Time series data of potato area and production in Pakistan from 1980-81 to 2012-13 (33 years) were used. Five different forecasting models such as Linear trend model, Quadratic trend model, Exponential growth model, S-curve trend model and double exponential smoothing model were used to find the best fitted model for...
Saima Rani and Irum Raza*
COMPARISON OF TREND ANALYSIS AND DOUBLE EXPONENTIAL SMOOTHING METHODS FOR PRICE ESTIMATION OF MAJOR PULSES IN PAKISTAN
...ned to find out suitable forecasting method among the two forecasting methods namely trend analysis and double exponential smoothing. Measures of accuracy (MAPE, MAD and MSD) were used as the model selection criteria that could best describe the trend of prices of major pulses such as gram, mash, masoor and mung during 1975-76 and 2009-10. Double exponential smoothing method was found to be pertinent for price estimation of ...
Ayesha Tahir*
FORECASTING CITRUS EXPORTS IN PAKISTAN
...ne from 2012 to 2016.The forecasted export quantities are 1643.13, 1854.03, 2077.80, 2314.46 and 2564.00 thousand tons and forecasted export values are 673.67, 782.34, 898.57, 1022.35 and 1153.68 thousand dollars. Forecasted values are very close to actual values and have positive increasing trend in Pakistan....
Nouman Badar*, Hina Fatima**, Abdul Jabbar*** and Muhammad Asif*
MAJOR FOOD CROPS PRODUCTION AND YIELD FORECAST IN PAKISTAN
...;">This study focuses on forecasting the production and yield of food crops in Pakistan. Utilizing the “Autoregressive Integrated Moving Average” (ARIMA) model and data from 1948 to 2011. The data was obtained from Ministry of Food and Agriculture, Islamabad and various Economic Surveys of Pakistan. The result predicts that wheat (production and yield) forecast for 2029-30 to be -1 about 37188 thousand tons and 3...
Sobia Naheed*, Irum Raza*, M. Zubair Anwar*, Nusrat Habib*, Naheed Zahra* and Sabeen Siddiqui*
FORECASTING AREA AND PRODUCTION OF BARLEY IN PUNJAB, PAKISTAN
...2012 to 2016. Five years forecast for barley area in Punjab was 26.140,
25.360, 24.580, 23.800, 23.020 ha and forecast of barley production in Punjab was 24.620, 23.950, 23.270, 22.600 and 21.930 tonnes for 2012, 2013, 2014, 2015 and 2016, respectively, with a 95% prediction interval. Declining trends in
area and production of barley was observed from original series and this trend will be prevalent i...
Saqib Shakeel Abbasi*, Ayesha Tahir**, Irum Raza* Saleem Abid* and Muhammad Nisar Khan*
TREND ANALYSIS AND FORECASTING OF WHEAT AND RICE IN PAKISTAN
...d on statistical models, forecast their prices from 2013 to 2017. Different models have been applied to get the best fit model. These were linear trend model, quadratic trend model, exponential growth model and S-curve model. The minimum values of Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD) and Mean Squared Deviation (MSD) have been acquired and then the forecasting was made for the best fitted model...
Waqar Islam*
...gle and disease epidemic forecasting is very important. So here we have briefly introduced plant disease epidemiology through highlighting its various types by giving important examples. We further have explained the plant disease triangle and disease forecasting systems via inclusion of various models being utilized worldwide.
... 
Farhan Ahmad1,*, Muhammad Waris Sanjrani1, Shah Nawaz Khuhro1, Asif Sajjad2, Abid Ali3, Rashad Rasool Khan3, Farooq Ahmed3 and Junhe Liu4,*
...this study could help in forecasting and monitoring of whitefly incidence and its parasitism.
...
Saleem Ashraf1*, Ashiq Hussain Sangi1Zakaria Yousaf Hassan3 and Muhammad Luqman2
...late compound growth and forecast area, production and average yield in the Punjab Pakistan For this purpose, data collected from government reports for the period of 1990-2017 was criticaly examined. Empirical results indicated that area under cultivation showed negative compound growth rate while production and average yield showed positive compound growth in Pakistan. While, in Punjab, compound growth rate of area under cotton cultivation and production sho...
Aftab Khan, Shahid Ali, Syed Attaullah Shah and Muhammad Fayaz
...This study estimated and forecasted the effect of temperature and precipitation on net revenue of maize growers across Northern, Eastern, Central and Southern zones of Khyber Pakhtunkhwa, Pakistan. 200 maize growers were randomly selected through multistage sampling technique. Primary data on net revenue from maize crop was collected through an interview schedule and secondary data on temperature and precipitation was collected from Regional Metrological Depar...
Jhan Zeb, Muhammad Javed
Forecasting percentage contribution of plankton biomass towards increase in fish yield under composite culture conditions
Muhammad Amin1, Aftab Ahmad Khan2, Abida Perveen1, Zareen Rauf1, Sher Shah Hassan2*, Muhammad Arif Goheer2 and Muhammad Ijaz2
...line for delineation and forecasting of drought years in Pakistan. ...
Faheem Aslam1*, Aneel Salman1 and Inayatullah Jan2
...53 years’ data and forecasts the future wheat production for the remaining 14 years. There are 16 indicators used as input variables for wheat production and top ten most important variables highlighted. The findings show, that the model captures much of the trend, and some of the undulations of the original series. The results reveal that the most important features in wheat production includes production prevailing trends, momentum and volatility.
Qaisar Mehmood1*, Maqbool Hussain Sial1, Saira Sharif1, Abid Hussain2, Muhammad Riaz3 and Nargis Shaheen4
... in Pakistan. Therefore, forecasting the production of fish is important for better production and for planning of fish export. Objective of this research is to propose suitable Autoregressive Integrated Moving Average (ARIMA) model for forecasting the production of fisheries, using Box-Jenkins’s (1976) methodology. Secondary data, “50 years of Pakistan: volume-iii (1947-1997)” published by Pakistan Bureau ...
Dilawar Khan1*, Arif Ullah2, Zainab Bibi1, Ihsan Ullah1, Muhammad Zulfiqar4 and Zafir Ullah Khan3
...gn: justify;">This paper forecasts guava area and production in Pakistan using time series data over the period 1997-98 to 2014-15. The study used the Box Jenkins approach and forecast was made up to the period 2029-30. The order of ARIMA model was identified using autocorrelation function (ACF) and partial autocorrelation function (PACF). Suitable model for area and production of guava are ARIMA (0,0,0) and ARIMA (1,1,0) re...
Riffat Sultana1, Nuzhat Soomro1,*, Santosh Kumar2, Ahmed Ali Samejo1 and Samiullah Soomro1
...study might be useful to forecast the exact hatching dates in near future.
... 
Samreen Fatima1*, Mudassir Uddin1
COMPARISON OF ASYMMETRIC GARCH MODELS WITH ARTIFICIAL NEURAL NETWORK FOR STOCK MARKETS PREDICTION, A CASE STUDY
... This study compares the forecasting performance
and also investigates more volatile stock markets using Asymmetric GARCH (A-GARCH) models and non-parametric
method (Artificial Neural Networks). In the A-GARCH; EGARCH and PGARCH models are used. Firstly, suitable
Asymmetric GARCH (A-GARCH) model was developed for forecasting and investigating leverage effect. Secondly,
an Artificial Neural Network...
and also investigates more volatile stock markets using Asymmetric GARCH (A-GARCH) models and non-parametric
method (Artificial Neural Networks). In the A-GARCH; EGARCH and PGARCH models are used. Firstly, suitable
Asymmetric GARCH (A-GARCH) model was developed for forecasting and investigating leverage effect. Secondly,
an Artificial Neural Network...
Kadir Karakuş1, Turgut Aygün2, Şenol Çelik3, Mohammad Masood Tariq4*, Muhammad Ali4, Majed Rafeeq4 and Farhat Abbas Bukhari4
...ditions and to build the forecasting model of live weight in lambs using 4 data mining CHAID, Exhaustive CHAID, CART, and multivariate adaptive regression splines (MARS). Effects of genotype and some environment factors such as birth type, dam age, lamb’ age in control and live weight on testis characteristics were also researched. The furthest importance sequence was obtained for testis length (TESLENG) (100%), followed by age, testis diameter (TDIA), a...
Yonghua Liu*, Xianhua Li, Xiongfei Yan and Gang Li
...e an important basis for forecasting and integrated management of A. fimbriana.
...
Mehar Ul Nissa Rais1*, Tahmina Mangan1, Jam Ghulam Murtaza Sahito1 and Naeem Ahmed Qureshi2
A Trend Analysis: Forecasting Growth Performance of Production and Export of Chilli in Pakistan
...t growth performance and forecasting of chilli in Pakistan. Annual time series data of 38 years (1981-2018) of chilli production and export was employed for this study. Overall, chilli production of the Pakistan exhibited a positive growth of 1 percent over the time; however, in Pakistan negative growth was recorded during 2001-02 and 2011-12, these losses can be attributed to major floods, diseases attack, poor management practices and shortage of high yieldi...
Muhammad Waqas1*, Muhammad Shoaib2, Muhammad Saifullah1, Adila Naseem4, Sarfraz Hashim1, Farrukh Ehsan1, Irfan Ali3 and Alamgir Khan1
...gn: justify;">Streamflow forecasting is a crucial hydrological variable. In the current study, the Artificial Intelligence (AI) based techniques: TB (Tree Boost), DTF Decision Tree Forest, SDT Single Decision Tree and conventional Multilayer Perceptron Neural Networks (MLPNN) are used for predicting streamflow of Jhelum River basin. The dataset was divided into two sections, i.e., training dataset (1971-2000); and testing dataset (2001-12). The tendency invest...
Muhammad Nasir1, Muhammad Usman Asif2*, Abdul Hayee Abid1, Qurat ul Ain Haneef1 and Muhammad Awais2
... pest managers as a pest forecasting tool for initiating management strategies at appropriate time during the cotton season....
Jing Yu1*, Yao Lu1,2, Zhaojin Lin1, Pimao Chen1 and Yuting Feng1,3
...based on GMM and MINM in forecasting spawning grounds in the Western Guangdong Waters.
...
Syed Ismat Hussain1, Khalid Mehmood2, Mudassar Khaliq3, Habib Anwar1, Syed Muhammad Zaka4, Ateeq ur Rehman5*, Muhammad Shahid6, Syed Atif Hasan Naqvi5*, Ummad ud Din Umar5 and Muhammad Asif Zulfiqar7
...n of degree days for its forecasting was calculated from 1st January by using the metrological data and base line temperature and found 7 generations of pink boll worm to be found in all districts. Data for moths trapped in sex pheromone traps was noted as highly significant i.e., P>0.0001. Peaks of moth catches in 14 districts were observed in the month of September to October while for pest survey P= 2 X 10-16 were highly significant meaning that all vari...
Fahima Khatun1, Abdullah-Al-Maruf2, Md. Mizanur Rahman2, Afroja Yasmin1, Mohammad Ali Zinnah3, Md. Aminul Islam4 and Mohammad Shah Alam5*
...ovide an epidemiological forecast in the distribution of gastrointestinal parasitism in different age groups of cattle and seasonal variation of occurrence which can assist the clinicians for the diagnosis of such parasitic infections and necessary steps for prevention and control measures against them....
Zahid Iqbal*, Farhat Ullah Khan and Jalal-ud-Din
...The study is designed to forecast, production of rapeseed and mustard in Pakistan by using time series analysis. Among different appropriate models like (1,0,0), (1,0,1), and (2,0,0) it is based on Normalized Bayesian criterion (NBIC), Akaike information criterion (AIC), Hannan-Quinn and Schwarz Criterion that Autoregressive (AR) model (1,0,0) is best. The Brock, Dechert and Scheinkman (BDS) test is also applied on the residuals of model (1,0,0) for checking t...
Asmaa A. Badr, Eman A. Abo Elfadl, Mohammed M. Fouda, Sayed M. Elsayed
... from 2013-2021 aimed to forecast milk production in two different farms of Holstein Friesian and Holstein German in Dakahlia governorate of Egypt using Autoregressive Integrated Moving Average (ARIMA) model. Data of daily milk production (kg) of two farms were collected to get total milk production (kg) through 305 days during period of 2013-2021 during COVID-19 occurrence. The study employed stationary of data by checking out Autocorrelation Function (ACF) a...
Samreen Fatima* and Muddasir-Uddin
...tic in Mean (GARCH-M) to forecast the stock markets data. The data of two stock markets namely, Karachi Stock Exchange 100 (KSE-100) of Pakistan and Standard and Poor’s 500 (S and P 500) of USA stock market covering the period 1st January 2013 to 31st, December 2019 are considered for analysis. Various forms of GARCH-M models are applied by inserting conditional standard deviation, conditional variance, or conditional log var...
Sajjad Ali1*, Atta ur Rahman1 and Sher Ali2
...e is employed to get the forecasted values regarding Acreage, Yield, and Production of crops till 2050 in Peshawar valley. Remote sensing (RS) and geographic information systems (GIS) were used to analyze the satellite imageries. The analysis showed a persistent increase in built-up areas from 1990 to 2020 as the built-up area increased by 57090 hectares. However, the barren land indicates a decreasing pattern of growth, decreasing by 102452 hectares in Peshaw...
Olufemi Bolarin, Sijuade Adebukola Adebayo and Sola Emmanuel Komolafe*
... also shows that weather forecast (Mean=1.42) and change in farming type (crop- livestock Mean=1.36) were not commonly used by farmers meanwhile the farmers preferred planting of early maturing yam seed (Mean=3.58), use of mulching (Mean=3.46), crop rotation (Mean=3.27), organic fertilizer (Mean=3.07) and cover crops (Mean=3.05). The result of regression analysis showed that coefficient value of farm size (p=0.017) and membership of cooperatives (p=0.013) posi...
Marcos E. Bollido1,2*, Renell Jay G. Villaluz1,2 and Ronald L. Orale1
...ply and consumption were forecasted using Autoregressive Integrated Moving Average (ARIMA) models. Pork prices increased by 22-50% in 2021 compared to 2010 data. Live-weight pig prices also increased by 9-39% for the same year in review. It was noted that 27% of the supply was locally produced, and 73% were imported from other regions. Locally sourced pig supply is pegged at 53%, and the rest (47%) are imported from various towns in Samar and other regions. Th...
Adefunke Fadilat O. Ayinde1*, Peter Allison Johnston2, Olanrewaju Olusoji Olujimi3, Purnamita Dasgupta4 and Dare Akerele5
...ad access to the weather forecast, some (55.4%) utilise it, while 58.4% engaged in artisanship (blue-collar jobs) and vegetable production (63.2%). Lessons on adaptation are critical for putting in place, policies that reduce the vulnerability of arable crop farmers to help to achieve sustainable development goals. The State governments should reintroduce the highly adaptable and high yielding TMS 30572 (an improved cassava variety) to farmers, given its inher...
Abdul Hassan1*, Arshad Farooq1, Muhammad Ishaq2, Ghulam Sadiq2 and Asif Nawaz3
...gies factor were weather forecast for adjusting production practices, adopt new technology and production diversity. Leasing inputs, market monitoring and switching to other markets had loadings in market strategy while maintaining good relationship with friends/relatives and maintaining good relationship with market actors in institutional strategy. Human strategy was related to engaging on off-farm employment for income generation and reducing hiring of labo...
