An Alberta Gas Supply Response Model: Predicting Future Discoveries

1981 ◽  
Vol 20 (03) ◽  
Author(s):  
C.R. Winter ◽  
B.A. Craig
2008 ◽  
Vol 40 (3) ◽  
pp. 295-302
Author(s):  
Murali Adhikari ◽  
Krishna P. Paudel ◽  
Jack Houston ◽  
James Bukenya

1987 ◽  
Vol 19 (1) ◽  
pp. 111-118 ◽  
Author(s):  
James L. Seale ◽  
J. S. Shonkwiler

AbstractRisk has long been recognized as potentially important in determining agricultural supply. However, supply response models have either incorporated risk in an ad hoc manner or not at all. A rational expectations supply response model incorporating price risk is developed, an estimation procedure suggested, and an empirical example presented.


Author(s):  
P. Sumathi ◽  
B. Parthipan ◽  
J.S. Amarnath ◽  
B. Sivasankari

This study analyzed the supply response of maize in Dindigul District of Tamil Nadu. The data regarding price and non-price factors (area, yield, rainfall) were collected from the season and crop report of Tamil Nadu for the period of about 21 years (1991-2011). Nerlovian Partial Adjustment Model was used to analyze the supply response. In the acreage response model, lag maize area and lag maize price were found to be positively 1 per cent and 5 per cent significant with the current maize acreage respectively. If lag maize area and lag maize price is increased by one per cent, it will lead to an increase of about 0.59 per cent and 0.96 per cent of current maize acreage respectively. In the yield response model, lag maize yield and lag maize price were found to be significant with the current maize yield. In the production response model, lag own price was found to be significant with the current maize production.


1984 ◽  
Vol 13 (2) ◽  
pp. 142-154 ◽  
Author(s):  
Robert G. Chambers ◽  
Ramon E. Lopez

This paper is divided into two parts which are somewhat independent. The first part of this paper discusses certain properties of a general autonomous control model that appears promising for the analysis of general dynamic supply response models in agricultural economics, resource economics, and related fields. The second part of the paper, which can be read somewhat independently of the first, emphasizes the potential empirical applications of special cases of the general model discussed in the first part. In what follows, we always deal with continuous time and infinite horizon models because of their analytical tractability. Extension and modification of our results for discrete-time, finite-horizon problems should be fairly obvious and are left to the interested reader.


Author(s):  
Edison Edison ◽  
Dharia Renate ◽  
Denny Denmar

The purpose of the study is to explore the supply response model of the soybean crop in terms of alternative specifications also implications economics. To apply model, considerations through the availability of production lags concept also the existence of expected price and gross revenue because of producer’s response explanatory preference on movement economic situation. The results showed that the existing lags were due mostly to the problems also quick adjustment expenditure rather than correcting expected time. The quantitative result was the same as gross margins and prices alternative specification as the availability of economic decisions. Meanwhile, elasticities price found through the model response specification tended around a fourth of the model applying price specification. The model response specification produced more explanation in terms of production also elasticity of input expenditure.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mathew Abraham ◽  
Prabhu Pingali

PurposeThis paper aims to understand the significant farm and market-level factors that incentivize the adoption and marketing of pulses influencing its supply response to changing demand.Design/methodology/approachThe authors first use a modified Nerlovian supply response model using secondary data to identify the major price and non-price factors influencing the supply of pigeon pea, black and green gram in the major pulses growing states in India. Second, using primary qualitative data the authors map the pulses value chain from farm to retail to identify the how proportional and fixed transaction costs (FCTs) influence market participation of pulses growers and limit the transmission of price and quality information.FindingsThe supply response model shows some positive influence of price on area allocation for pigeon pea and black gram and some negative effects of yield and price increase of competing crops on pigeon pea acreage. However, for the most part, the area of Kharif pulses is inelastic to prices in the long run. Irrigation, rainfall and yields in the lag year are shown to have a significant influence on area allocation for pulses. The market study reveals that low yields, low landholding size and geographical disadvantages of high agro-climatic risk and poor connectivity hinder market access of pulses farmers relative to other crops. Market power in favor of buyers and poor price and quality information is a disadvantage to sellers, influencing their ability to participate in markets.Research limitations/implicationsA quantitative study would be required to identify the magnitude of farm and market-level transaction costs.Originality/valueThis study helps to understand the supply response of pulses and gives suggestions to direct policy to rectify this.


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