On estimating dynamic factor demands

Mahmud, Syed F.; Robb, Alicia; Scarth, William

doi:10.1002/jae.3950020106

Cited by 19 publications

(8 citation statements)

References 4 publications

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“…The fact that the demand for "other inputs" has a different functional form than the rest of the inputs is not problematic in this context as this composite is not expected to be used in fixed proportions. This is in contrast to other situations in which homogeneity in functional form does matter for economic analysis (Mahmud et al 1987).…”

Section: The Inflection Point Of Ddgs Supply Occurs At a Relative Promentioning

confidence: 71%

A Variable Cost Function for Corn Ethanol Plants in the Midwest

Sesmero¹,

Perrin²,

Fulginiti

2015

Canadian J Agri Economics

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This study estimates a variable cost function for corn ethanol plants, using data from a unique survey of Midwest plants. The objective is to better understand the effect of prices and scale of production on Marshallian shutdown price, input choice, and by‐product choice. We estimate a novel specification of a cost function capable of accommodating two distinctive features of ethanol plants’ technology: (1) the production process results in by‐products that can be sold in different forms in response to price signals, and (2) decisions on the mix of by‐products may be subject to constraints, such as thin livestock markets or imperfect price foresight. This cost function is estimated by nonlinear seemingly unrelated regression with correlated random effects. Constant returns to variable inputs, homotheticity, and proportionality of by‐products to ethanol production, assumptions held in previous studies, are strongly rejected by our analysis. Increases in ethanol production require less than proportional increases in corn and other variable inputs when the increases are achieved through increased capacity utilization as opposed to capacity expansion. Moreover, the reduction in input requirements per gallon, reduces both cost and greenhouse gas emissions per gallon. Constraints in by‐product marketing decisions seem to slightly increase Marshallian shutdown price. Dans la présente étude, nous estimons une fonction de coût variable à l'aide des données tirées d'une enquête réalisée auprès des usines de production d’éthanol de maïs dans le Midwest. L'objectif de notre étude vise à mieux comprendre l'effet des prix et de l’échelle de production sur le seuil de rentabilité selon Marshall, le choix des intrants et le choix des sous‐produits. Nous estimons une fonction de coût spécifiée pour tenir compte de deux éléments distinctifs de la technologie des usines de production d’éthanol : 1) le processus de production génère des sous‐produits qui peuvent être vendus sous diverses formes en réaction aux signaux de prix; 2) les décisions concernant l’éventail de sous‐produits peuvent être confrontées à des contraintes telles que des marchés du bétail restreints ou des prévisions imparfaites concernant les prix. Cette fonction de coût est estimée à l'aide d'une régression non linéaire sans corrélation apparente avec effets aléatoires corrélés. Certaines hypothèses émises dans des études antérieures, telles que les rendements constants des intrants variables, l'homothéticité et la proportionnalité des sous‐produits de la production d’éthanol, sont nettement rejetées par notre étude. L'augmentation de la production d’éthanol nécessite des augmentations inférieures aux augmentations proportionnelles de maïs et autres intrants variables lorsque l'augmentation découle d'un accroissement de la capacité de production comparativement à une expansion de capacité. De plus, la diminution des intrants nécessaires à la production d'un gallon d’éthanol réduit à la fois le coût et les émissions de gaz à effet de serre par gallon. Les contrain...

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Section: The Inflection Point Of Ddgs Supply Occurs At a Relative Promentioning

confidence: 71%

A Variable Cost Function for Corn Ethanol Plants in the Midwest

Sesmero¹,

Perrin²,

Fulginiti

2015

Canadian J Agri Economics

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“…Alternatively, internal adjustment costs can be incorporated into the model; this is theoretically superior, but often leads to intractable models [unless static expectations are assumed or a suitable, and often more restrictive, form of the cost function is used-see Mahmud, Robb, and Scarth (1986), who use a generalized Leontief function]. This brief look at recent factor demand models indicates that the preferred approach centers on the use of translog (or similar) cost functions, with their associated flexibility when more than two factor inputs are included.…”

Section: -1983mentioning

confidence: 99%

The Employment Creation Effects of Factor Subsidies: Some Estimates for Northern Ireland Manufacturing Industry, 1955‐1983

Harris

1991

Journal of Regional Science

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In this paper, I use estimates of the parameters of an industry demand function and a CES production function for Northern Ireland manufacturing in order to measure the relative impact of factor subsidies on employment, capital, and output. A simulation model is able to differentiate the output and substitution effects of subsidies. The results indicate that since manufacturing industry in the province tends to operate with a labor-intensive technology and, since its price-elasticity of demand for output is very low, the employment creating effects of capital subsidies are strongly negative.

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“…Besides that numerous studies treating with factor demand derived from cost functions also included a price equation, which was estimated simultaneously with the factor demand equations in one system. Important examples for this line of research mainly using the flexible cost functions ‚Translog' and ‚Generalized Leontief' are Berndt -Hesse (1986), Morrison (1989Morrison ( , 1990, Meade (1998) and Conrad -Seitz (1994). The price setting equations combined with the factor demand equations differ in these studies.…”

Section: Input Demand and Output Pricesmentioning

confidence: 99%

“…Different concepts of extending the function for technical progress variables and fixed factors have been developed since then , an example for the extension by fixed factors is Mahmud (1987). Extensions to take into account technical progress have first been presented by Parks (1971), Woodland (1975) and Diewert, Wales (1987).…”

Section: Input Demand and Output Pricesmentioning

confidence: 99%

Prices and factor demand in an endogenized input–output model

Kratena

2005

Economic Systems Research

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This paper combines factor demand functions and price equations derived from a Generalized Leontief cost function with the traditional input-output price model. At the first level of aggregation Generalized Leontief cost functions for the factors intermediate input and labour are set up for the manufacturing industries of the Austrian economy. These functions determine factor demand for materials and labour as well as output prices for given input prices. At the second level of aggregation the intermediate demand input is split up according to the input-output structure. There the repercussion of domestic prices on input prices as described in the traditional input-output-price model is taken into account. Model simulations reveal the link between the technical coefficients and the econometric equations for domestic prices, input prices and factor demand.

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On estimating dynamic factor demands

Cited by 19 publications

References 4 publications

A Variable Cost Function for Corn Ethanol Plants in the Midwest

A Variable Cost Function for Corn Ethanol Plants in the Midwest

The Employment Creation Effects of Factor Subsidies: Some Estimates for Northern Ireland Manufacturing Industry, 1955‐1983

Prices and factor demand in an endogenized input–output model

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