Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis

This thesis estimates the production, cost, and profit functions for North Dakota agriculture using state-level input-output quantity and price data for the period 1960-2004. A Cobb-Douglas functional form with Hick-neutral technology change is used to measure the contribution of capital, land, labo...

Full description

Bibliographic Details
Main Author: Marroquin, Jacklin Beatriz
Format: Others
Published: North Dakota State University 2019
Subjects:
Online Access:https://hdl.handle.net/10365/29736
id ndltd-ndsu.edu-oai-library.ndsu.edu-10365-29736
record_format oai_dc
spelling ndltd-ndsu.edu-oai-library.ndsu.edu-10365-297362021-09-28T17:11:08Z Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis Marroquin, Jacklin Beatriz Agriculture -- Economic aspects -- North Dakota. Agricultural productivity -- North Dakota. Production functions (Economic theory) Regression analysis. This thesis estimates the production, cost, and profit functions for North Dakota agriculture using state-level input-output quantity and price data for the period 1960-2004. A Cobb-Douglas functional form with Hick-neutral technology change is used to measure the contribution of capital, land, labor, materials, energy, and chemical inputs quantities and output quantity using the primal production function; contribution of capital quantity, land quantity, output quantity, labor price, materials price, energy price, and chemical price to cost using the dual restricted cost function; and the contribution of capital quantity, land quantity, labor price, materials price, energy price, chemical price, output price to profit using the dual restricted profit function. In contrast to previous studies, quantile regression is used to explore the linear or nonlinear relationship between the independent and dependent variable by estimating parameter coefficients at each quantile using time-series data. Empirical findings suggest the cost function is the best model to examine the relationship between input prices, output quantity and cost using quantile regression for North Dakota agriculture, Further, the quantile regression suggests a linear and non-linear relationship between cost and certain independent variables. 2019-05-15T19:19:01Z 2019-05-15T19:19:01Z 2008 text/thesis https://hdl.handle.net/10365/29736 NDSU policy 190.6.2 https://www.ndsu.edu/fileadmin/policy/190.pdf application/pdf North Dakota State University
collection NDLTD
format Others
sources NDLTD
topic Agriculture -- Economic aspects -- North Dakota.
Agricultural productivity -- North Dakota.
Production functions (Economic theory)
Regression analysis.
spellingShingle Agriculture -- Economic aspects -- North Dakota.
Agricultural productivity -- North Dakota.
Production functions (Economic theory)
Regression analysis.
Marroquin, Jacklin Beatriz
Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
description This thesis estimates the production, cost, and profit functions for North Dakota agriculture using state-level input-output quantity and price data for the period 1960-2004. A Cobb-Douglas functional form with Hick-neutral technology change is used to measure the contribution of capital, land, labor, materials, energy, and chemical inputs quantities and output quantity using the primal production function; contribution of capital quantity, land quantity, output quantity, labor price, materials price, energy price, and chemical price to cost using the dual restricted cost function; and the contribution of capital quantity, land quantity, labor price, materials price, energy price, chemical price, output price to profit using the dual restricted profit function. In contrast to previous studies, quantile regression is used to explore the linear or nonlinear relationship between the independent and dependent variable by estimating parameter coefficients at each quantile using time-series data. Empirical findings suggest the cost function is the best model to examine the relationship between input prices, output quantity and cost using quantile regression for North Dakota agriculture, Further, the quantile regression suggests a linear and non-linear relationship between cost and certain independent variables.
author Marroquin, Jacklin Beatriz
author_facet Marroquin, Jacklin Beatriz
author_sort Marroquin, Jacklin Beatriz
title Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
title_short Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
title_full Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
title_fullStr Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
title_full_unstemmed Examination of North Dakota's Production, Cost, and Profit Functions: A Quantile Regression Analysis
title_sort examination of north dakota's production, cost, and profit functions: a quantile regression analysis
publisher North Dakota State University
publishDate 2019
url https://hdl.handle.net/10365/29736
work_keys_str_mv AT marroquinjacklinbeatriz examinationofnorthdakotasproductioncostandprofitfunctionsaquantileregressionanalysis
_version_ 1719485745921523712