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Fads versus Fundamentals in Farmland Prices

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TLDR
In this article, the authors developed an approach to decompose farmland price time series into three uncorrelated components: permanent fundamental component, temporary fundamental component and non-fundamental component.
Abstract
We develop an approach to decompose farmland price time series into three uncorrelated components: permanent fundamental component, temporary fundamental component, and nonfundamental component. This decomposition is useful for studying the importance of fundamental versus nonfundamental factors in explaining farmland price behavior and the dynamic response of farmland prices to shocks to each of these components. The approach is applied to annual Iowa farmland prices over the 1922–94 sample period. We find that fads and overreactions play important roles in explaining short-run price behavior, while long-run price movements are explainable by permanent fundamental shocks.

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Precio de la tierra con presión urbana: un modelo para España

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The Response of Stock Prices to Permanent and Temporary Shocks to Dividends

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The Joint Influence of Agricultural and Nonfarm Factors on Real Estate Values: An Application to the Mid-Atlantic Region

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Financial Structure of Farm Businesses under Imperfect Capital Markets

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Journal ArticleDOI

A new look at the statistical model identification

TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Journal ArticleDOI

Estimating the Dimension of a Model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.

Estimating the dimension of a model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI

Testing for a Unit Root in Time Series Regression

TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
Book

Introduction to Statistical Time Series

TL;DR: In this paper, Fourier analysis is used to estimate the mean and autocorrelations of the Fourier spectral properties of a Fourier wavelet and the estimated spectrum of the wavelet.
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