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Farm growth in Hungary, Slovenia and France AgEcon
Bakucs, Lajos Zoltan; Bojnec, Stefan; Ferto, Imre; Latruffe, Laure.
The article investigates the validity of Gibrat’s Law for French, Hungarian and Slovenian farms with FADN data and Heckman selection models, quantiles regressions and panel unit root tests. The contribution to the literature is threefold. First, we compare farm growth in countries with rather different farm structures. Second, we apply two different testing techniques. Finally, we focus on specialised crop and dairy farms rather than all farms, avoiding biases due to heterogeneous structures across the agricultural sector. Results reject the Gibrat’s Law for crop farms in France (except for one sub-period) and Hungary but confirm it for French and Slovenian dairy farms.
Tipo: Conference Paper or Presentation Palavras-chave: Farm growth; Gibrat's Law; Panel unit root; Quintile regression; Agricultural and Food Policy; Farm Management.
Ano: 2010 URL: http://purl.umn.edu/60911
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Modeling Nonlinearities in Farmland Values: A Dynamic Panel Threshold Error-Correction Model AgEcon
Onel, Gulcan.
Earlier studies usually indicate that farmland prices and cash rents are not cointegrated, a finding that seems at odds with the implications of the present value model. The main objective of this study is to explore whether this absence of empirical support for the present value model can be attributed to the restrictiveness of conventional time series methods. I suggest a panel unit root model with two regimes in which the adjustment process may be characterized by the presence of thresholds and discontinuities reflecting the presence of transactions costs and other barriers to adjustment. Using farmland value and cash rents data for 10 agricultural states of the U.S. between 1960 and 2008, empirical findings give modest improvement over the linear unit...
Tipo: Conference Paper or Presentation Palavras-chave: Present Value Model; Transactions costs; Thresholds; Panel unit root; Land Economics/Use; Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/49445
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