Milk Demand, Supply, and Price Relationships, 1950–1968

Prato, Anthony A.

doi:10.2307/1238441

Cited by 19 publications

(6 citation statements)

References 6 publications

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“…The coefficient of P r was negative in half the models, and significant in only three of the models, indicating that real price was not a very important factor in KCC intake. Studies in the U.S.A. have also found the price of milk in a supply function to be not significant (Wilson and Thompson, 1967;Prato, 1973 ).…”

Section: Resultsmentioning

confidence: 99%

Linkages between regulated and unregulated markets: the case of milk supply in Kenya

Howard

McDonald

1988

Agricultural Economics

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Linkages between the regulated and unregulated dairy markets in Kenya were examined using an econometric model of the fluid milk intake for eight processing plants. Counter-intuitive results were obtained: an increase in the regulated price was significant in decreasing intake in the regu lated market, indicating that a price increase in the regulated market also increased price and quantity supplied in the unregulated market. Lagged rainfall was a proxy for available feed and was highly significant in explaining milk intake in the regulated market.

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Section: Resultsmentioning

confidence: 99%

Linkages between regulated and unregulated markets: the case of milk supply in Kenya

Howard

McDonald

1988

Agricultural Economics

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“…The first set of identities comprises the basic supply/demand balance equations for unprocessed food and nclnfood and processed food: In the quantification of equations (16) and (17), unprocessed farm output is defined as output in the form in which it leaves the farm. Thus on the left-hand sides of equations (16) and (17), GV embraces all farm output, and M comprises unprocessed imports (a numerically small group consisting mainIy of tobacco, coffee and tea), The left-hand 3 An identity between PF, VA and PR notionally exists, but cannot be specified here because of the nature of these variables-PF and PR are indices, not unit prices, and V A is an aggregate measure. Hence we must specify the relationship between these variables in terms of stochastic equations, as postulated in equations (12) , (14) and (15).…”

Section: Identitiesmentioning

confidence: 99%

“…The distinction between processed and unprocessed food is difficult to maintain preciseIy. The variable Of in equation ( 18) comprises all food demanded at retail including fresh fruit, vegetables and meat which have not been exported via equation ( 16) and have therefore been transferred via C"f to equation (18). In relation to exports, grains, meats, eggs and fresh fruit and vegetables are classified as unprocessed, whilst dairy products, sugar, flour, and dried and canned fruit and vegetables are regarded as processed.…”

Section: Australian Journal Of Agricultural Economics Decmentioning

confidence: 99%

“…at farm gate prices. This necessitated a revaluation of the variable Xu" so that it would be expressed in the same terms as the other variables in equation ( 16) .5…”

Section: Australian Journal Of Agricultural Economics Decmentioning

confidence: 99%

“…In such cases, usual estimation procedures may be inappropriate. We have used a modification of 2SLS suggested by Kelejian [7] by approximating each reduced form equation by a firstorder polynomial in the predetermined variables, a method used previously by Prato [16]. In the estimation of the demand and retail price equations, (11) to (14), which were affected by serial correlation in the residuals, a Hildreth-Lu procedure [ 6 ] was employed to estimate the structural coefficients.…”

Section: Data and Estimationmentioning

confidence: 99%

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A Quarterly Model of the Australian Agricultural Sector*

Throsby¹,

Rutledge²

1977

Australian Journal of Agricultural Economics

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Several farm sector econometric models are reviewed hitially and the aggregation problem highlighted. A t!&ty-eyuation model of the Australian agricultural sector is specified m which farm output, stocks and exports and the domestic demand for farm products are endogenous, as well as farm., export and retail prices. Disaggregation is into food and non-food componeuts of unprocessed output, and the processing o f food is traced through to final demand. The model is estimated by a modified 2SLS procedure using quarterly data covering the period 1960-1970. In a recent review of the state of the art of econometric modelling of the agricultural sector, King [9] drew attention to the relative paucity of models of the agricultural sector as a whole. A major question confronting builders of econometric models of the agricultural sector has been the choice of a level of aggregation. At one extreme is a model such as that of Egbert [2] which concentrates on explaining annual aggregate supply and demand for the U.S. agricultural sector as a whole without any consideration of the structure of component industry or commodity groups. The endogenous variables in Egbert's model are total agricultural output, domestic consumption of agricultural products, farm prices and the level of farm stocks; imports and exports are assumed to be exogenous. Models such as Egbert's may be relatively straightforward to specify and estimate, but their usefulness for policy analysis and forecasting is limited by their highly aggregative nature.At the other extreme, an agricultural sector model may aggregate upwards from individual commodities, such as in Cromarty's El] pioneering work of the late 1950s. He specified supply equations, and demand equations for consumption, inventories and government stocks, * The research on which this paper is based was supported by a grant from the 157

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World dairy market structure

Blank¹

1986

Agribusiness

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A method for defining a “world market” and its “world price” is outlined for dairy products in a way that can be used with any product traded internationally. Analysis of a world price model indicates that exporters of both butter and cheese have enough market power (relative to importers) to have some influence on prices. Also, the world cheese market is less competitive than the world butter market.

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Milk Demand, Supply, and Price Relationships, 1950–1968

Cited by 19 publications

References 6 publications

Linkages between regulated and unregulated markets: the case of milk supply in Kenya

Linkages between regulated and unregulated markets: the case of milk supply in Kenya

A Quarterly Model of the Australian Agricultural Sector*

World dairy market structure

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