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Available. Open Access. Open Access
Article
Publication date: 7 July 2020

Juho Valtiala

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural…

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Abstract

Purpose

This study analyses agricultural land price dynamics in order to better understand price development and to improve forecast accuracy. Understanding the evolution of agricultural land prices is important when considering sound investment decisions.

Design/methodology/approach

This study applies threshold autoregression to model agricultural land prices. The data includes quarterly observations on Finnish agricultural land prices.

Findings

The study shows that Finnish agricultural land prices exhibit regime-switching behaviour when using past changes in prices as a threshold variable. The threshold autoregressive model not only fits the data better but also improves the accuracy of price forecasts compared to the linear autoregressive model.

Originality/value

The results show that a sharp fall in agricultural land prices temporarily changes the regular development of prices. This information significantly improves the accuracy of price predictions.

Details

Agricultural Finance Review, vol. 81 no. 2
Type: Research Article
ISSN: 0002-1466

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