Discussion: Distributed Lags and the Measurement of Supply and Demand Elasticities

1958 ◽  
Vol 40 (2) ◽  
pp. 311 ◽  
Author(s):  
K. W. Meinken
Keyword(s):  
Supply And Demand ◽  
Demand Elasticities ◽  
Distributed Lags

Estimating Both Supply and Demand Elasticities Using Variation in a Single Tax Rate

Econometrica ◽  
2018 ◽  
Vol 86 (2) ◽  
pp. 763-771 ◽  
Author(s):  
Floris T. Zoutman ◽  
Evelina Gavrilova ◽  
Arnt O. Hopland
Keyword(s):  
Supply And Demand ◽  
Tax Rate ◽  
Demand Elasticities ◽  
Single Tax

scholarly journals Estimation of Supply and Demand Elasticities for Major Crops Produced in Pakistan

2020 ◽  
Vol 25 (1) ◽  
pp. 139-152
Author(s):  
Saima Rani ◽  
David Vanzetti ◽  
Elizabeth Petersen ◽  
Muhammad Qasim
Keyword(s):  
Supply And Demand ◽  
Demand Systems ◽  
Demand Elasticities ◽  
Traditional Crops

Thisarticlestudiesthe supply and demand of major Pakistani crops. We estimatesupply elasticities usinga Nerlovian partialadjustment processanddemand elasticities usingthe Deaton and MuellbauerAlmost Ideal Demand Systems (AIDS). We usesecondary data from various Household IntegratedEconomicSurveysand Agricultural Statistics of Pakistan. Our estimated supplyelasticities with respect to price liebetween 0.1 and 0.5 for all crops. Pulses tend to have higher elasticities than traditional crops such as wheat and rice. Demand elasticities with respect to price tend to beinelastic, with the exception of poultry andfruit which appearto be luxury items. Pulses are income inelastic, implying that consumption may not rise significantly asper capita incomesand thatthe introduction of yield enhancing varietieswill lead to lower prices.

scholarly journals Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments

2001 ◽  
Vol 15 (4) ◽  
pp. 69-85 ◽  
Author(s):  
Joshua D Angrist ◽  
Alan B Krueger
Keyword(s):  
Measurement Error ◽  
Instrumental Variables ◽  
Supply And Demand ◽  
Single Equation ◽  
Causal Relationships ◽  
Natural Experiments ◽  
Omitted Variables ◽  
Demand Elasticities ◽  
Key Variables

Instrumental variables was first used in the 1920s to estimate supply and demand elasticities and later to correct for measurement error in single equation models. Recently, instrumental variables have been widely used to reduce bias from omitted variables in estimates of causal relationships. Intuitively, instrumental variables methods use only a portion of the variability in key variables to estimate the relationships of interest; if the instruments are valid, that portion is unrelated to the omitted variables. We discuss the mechanics of instrumental variables and the qualities that make for a good instrument, devoting particular attention to instruments derived from “natural experiments.”

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