Factor Substitution, Price Elasticity of Factor Demand and Returns to Scale in Police Production: Evidence from Michigan

1988 ◽  
Vol 54 (4) ◽  
pp. 863 ◽  
Author(s):  
Anthony O. Gyapong ◽  
Kwabena Gyimah-Brempong
Keyword(s):  
Price Elasticity ◽  
Returns To Scale ◽  
Factor Demand ◽  
Factor Substitution

An econometric analysis of output supply and input demand in the Canadian softwood lumber industry

2000 ◽  
Vol 30 (9) ◽  
pp. 1419-1428 ◽  
Author(s):  
Gregory S Latta ◽  
Darius M Adams
Keyword(s):  
British Columbia ◽  
Price Elasticity ◽  
Labor Demand ◽  
Lumber Industry ◽  
Softwood Lumber ◽  
Demand Elasticities ◽  
The Past ◽  
Forest Policies ◽  
Factor Demand ◽  
Wood Demand

Few studies have examined the own-price elasticity of Canadian softwood lumber supply or output-adjusted factor demand elasticities over the past two decades, despite the utility of these measures in understanding producer response to tariffs, to market shifts (such as the decline in U.S. public harvest), and to changes in domestic forest policies. The present analysis employs a normalized, restricted quadratic profit function approach to estimate lumber supply and Marshallian factor demand elasticities for three Canadian regions. Results indicate that the lumber supply elasticity in the British Columbia coast region may be twice as large as that in the interior or eastern regions. Comparison of Hicksian factor demand elasticities with earlier studies suggests that the own price elasticity of labor demand may be two or more times larger than that for wood. Results also indicate differential time trends in Marshallian lumber output and wood demand elasticities across regions, rising in the British Columbia coast and falling elsewhere over the past two decades. Morishima elasticities of substitution from the present and past studies indicate that the wood for labor factor intensity is more sensitive to changes in labor price than is the labor for wood intensity to changes in wood price.

Factor Demand and Returns to Scale in Milk Production: Effects of Price, Substitution and Technology

1984 ◽  
Vol 13 (2) ◽  
pp. 238-244 ◽  
Author(s):  
Anwarul Hoque ◽  
Adesoji Adelaja
Keyword(s):  
Structural Changes ◽  
Returns To Scale ◽  
Dairy Industry ◽  
Scale Parameters ◽  
Section Data ◽  
Factor Demand ◽  
Demand Structure ◽  
Input Demand ◽  
Pooled Time Series ◽  
Production Effects

A translog cost function was estimated using pooled time series-cross section data from five Northeastern States to study structural changes in the dairy industry. The approach given in the duality theory was found useful in estimating the input demand structure under changing input prices and technology conditions. The estimated Allen partial elasticities of substitution show the existence of substitution between energy and non-energy inputs in dairy farming. Despite input price increases the dairy industry maintained competitiveness as seen by the returns to scale parameters.

EXPECTATIONS-DRIVEN FLUCTUATIONS WHEN FACTOR UTILIZATION IS VARIABLE

2004 ◽  
Vol 8 (1) ◽  
pp. 3-26 ◽  
Author(s):  
PATRICK A. PINTUS
Keyword(s):  
Empirical Studies ◽  
Returns To Scale ◽  
Increasing Returns ◽  
Constant Input ◽  
Input Substitution ◽  
Factor Substitution ◽  
Local Determinacy ◽  
Local Indeterminacy ◽  
Labor Utilization ◽  
Constant Returns To Scale

The present paper studies the influence of variable labor utilization on local indeterminacy and expectations-driven fluctuations, in one-sector models with (nearly) constant returns to scale. It is shown that, in comparison to the configuration of constant input utilization, considering variable utilization reduces the actual possibilities of factor substitution and, consequently, the range of input substitution elasticities that are compatible with endogenous fluctuations. In particular, local indeterminacy and expectations-driven fluctuations occur only if utilization rates are sufficiently inelastic, whereas local determinacy prevails when utilization is highly elastic. However, accounting for the fact that variable utilization reduces theeffectiveelasticity of capital/labor substitution leads us to argue that expectations-driven fluctuations are more plausible because they require larger elasticities ofapparentinput substitution. In contrast with the recent literature, the analysis does not rely on significantly increasing returns to scale in production. Accordingly, the results are not at variance with recent empirical studies emphasizing the importance of variable utilization and denying the evidence of large increasing returns.

BIASED TECHNICAL CHANGE, SCALE, AND FACTOR SUBSTITUTION IN U.S. MANUFACTURING INDUSTRIES

2016 ◽  
Vol 21 (2) ◽  
pp. 488-514 ◽  
Author(s):  
Xi Chen
Keyword(s):  
Production Function ◽  
Technical Change ◽  
Control Function ◽  
Returns To Scale ◽  
Manufacturing Industries ◽  
Macroeconomic Analysis ◽  
Data Limitations ◽  
Factor Substitution ◽  
Using Data

Although a realistic characterization of the production function is critical to macroeconomic analysis, estimating the function's characteristics is hampered by both data limitations and methodological difficulties. In this paper, I develop a new empirical strategy for estimating the CES production function with biased technical change. The proposed method extends the control function approach to the CES specification to address endogeneity concerns and is able to retrieve sector-specific and time-varying estimates of technical change. Using data from U.S. manufacturing industries, I find evidence that (i) the production technology exhibits nonincreasing returns to scale, (ii) the elasticity of substitution between capital and labor is below unity, and (iii) technical change is generally labor-augmenting along the balanced growth path.

The sawmill industry of the Lake States: a study of productivity, technological change, and factor demand

2006 ◽  
Vol 36 (10) ◽  
pp. 2633-2641 ◽  
Author(s):  
James RG McQueen ◽  
Karen Potter-Witter
Keyword(s):  
Technical Change ◽  
Time Series Data ◽  
Returns To Scale ◽  
Elasticity Of Substitution ◽  
Series Data ◽  
Variable Cost ◽  
Price Elasticities ◽  
Factor Demand ◽  
Sawmill Industry ◽  
Variable Cost Function

A translog variable cost function of the sawmill industry in Michigan, Minnesota, and Wisconsin was estimated using pooled time-series data for the period 1963–1996 with inputs labour, materials, and capital. The estimated model imposed Hicks-neutral technical change and allowed for nonconstant returns to scale as well as nonunitary elasticities of substitution amongst the inputs. Results for the Allen–Uzawa partial elasticity of substitution and the Morishima elasticity of substitution indicate that the three inputs were inelastic substitutes. The own-price elasticities of demand and the cross-price elasticities were all inelastic. The industry exhibits increasing returns to scale and positive technical change. Total factor productivity was increasing by 0.69%/year over the study period.

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