Modeling the effect of off-farm income on farmland values: A quantile regression approach

Ashok K. Mishra; Charles B. Moss

doi:10.1016/j.econmod.2013.02.022

Modeling the effect of off-farm income on farmland values: A quantile regression approach

Ashok K. Mishra, Charles B. Moss

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

Using the farm household as a unit of analysis and farm-level data, this study examines the impact of off-farm income on farmland values. In contrast to previous studies that assume a homogeneous relationship across the entire distribution, in this study quantile regression is used to estimate the empirical model. Results of this study show the effect of land attributes-captured by regional location and farm program payments; off-farm income on value of farmland can be better explained by estimating quantile regression across farmland value categories. Results indicate that a 1. percent increase in off-farm income could increase per-acre farmland value between 0.15 and 0.21%.

Original language	English (US)
Pages (from-to)	361-368
Number of pages	8
Journal	Economic Modelling
Volume	32
Issue number	1
DOIs	https://doi.org/10.1016/j.econmod.2013.02.022
State	Published - May 2013
Externally published	Yes

Keywords

Direct payments
Farm household
Farm program payments
Farmland value
Gross cash income
Indirect payments
Off-farm income
Ordinary least squares
Quantile regression

ASJC Scopus subject areas

Economics and Econometrics

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10.1016/j.econmod.2013.02.022

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title = "Modeling the effect of off-farm income on farmland values: A quantile regression approach",

abstract = "Using the farm household as a unit of analysis and farm-level data, this study examines the impact of off-farm income on farmland values. In contrast to previous studies that assume a homogeneous relationship across the entire distribution, in this study quantile regression is used to estimate the empirical model. Results of this study show the effect of land attributes-captured by regional location and farm program payments; off-farm income on value of farmland can be better explained by estimating quantile regression across farmland value categories. Results indicate that a 1. percent increase in off-farm income could increase per-acre farmland value between 0.15 and 0.21%.",

keywords = "Direct payments, Farm household, Farm program payments, Farmland value, Gross cash income, Indirect payments, Off-farm income, Ordinary least squares, Quantile regression",

author = "Mishra, {Ashok K.} and Moss, {Charles B.}",

note = "Funding Information: We would like to thank the editor and anonymous referees for their very useful comments and suggestions. The views expressed here are not necessarily those of the Economic Research Service or the U.S. Department of Agriculture. This project was supported by the USDA Cooperative State Research Education & Extension Service , Hatch project and Louisiana State University Experiment Station project # LAB 94163 .",

year = "2013",

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doi = "10.1016/j.econmod.2013.02.022",

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T1 - Modeling the effect of off-farm income on farmland values

T2 - A quantile regression approach

AU - Mishra, Ashok K.

AU - Moss, Charles B.

N1 - Funding Information: We would like to thank the editor and anonymous referees for their very useful comments and suggestions. The views expressed here are not necessarily those of the Economic Research Service or the U.S. Department of Agriculture. This project was supported by the USDA Cooperative State Research Education & Extension Service , Hatch project and Louisiana State University Experiment Station project # LAB 94163 .

PY - 2013/5

Y1 - 2013/5

N2 - Using the farm household as a unit of analysis and farm-level data, this study examines the impact of off-farm income on farmland values. In contrast to previous studies that assume a homogeneous relationship across the entire distribution, in this study quantile regression is used to estimate the empirical model. Results of this study show the effect of land attributes-captured by regional location and farm program payments; off-farm income on value of farmland can be better explained by estimating quantile regression across farmland value categories. Results indicate that a 1. percent increase in off-farm income could increase per-acre farmland value between 0.15 and 0.21%.

AB - Using the farm household as a unit of analysis and farm-level data, this study examines the impact of off-farm income on farmland values. In contrast to previous studies that assume a homogeneous relationship across the entire distribution, in this study quantile regression is used to estimate the empirical model. Results of this study show the effect of land attributes-captured by regional location and farm program payments; off-farm income on value of farmland can be better explained by estimating quantile regression across farmland value categories. Results indicate that a 1. percent increase in off-farm income could increase per-acre farmland value between 0.15 and 0.21%.

KW - Direct payments

KW - Farm household

KW - Farm program payments

KW - Farmland value

KW - Gross cash income

KW - Indirect payments

KW - Off-farm income

KW - Ordinary least squares

KW - Quantile regression

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Modeling the effect of off-farm income on farmland values: A quantile regression approach

Abstract

Keywords

ASJC Scopus subject areas

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