Movers and Stayers in The Farming Sector: Accounting for Unobserved Heterogeneity in Structural Change

Abstract

Summary The paper investigates whether accounting for unobserved heterogeneity in farms' size transition processes improves the representation of structural change in agriculture. Considering a mixture of two types of farm, the mover–stayer model is applied for the first time in an agricultural economics context. The maximum likelihood method and the expectation–maximization algorithm are used to estimate the model's parameters. An empirical application to a panel of French farms from 2000 to 2013 shows that the mover–stayer model outperforms the homogeneous Markov chain model in recovering the transition process and predicting the future distribution of farm sizes.

Heterogeneous farm‐size dynamics and impacts of subsidies from agricultural policy: Evidence from France

“…As ES classes of farms are defined using continuous variables, one could argue that the results may depend on the position of a farm in relation to the boundaries of its ES class (Saint-Cyr & Piet, 2016). Indeed, farms that are close to the boundaries need a smaller size variation to change ES class.…”

“…While these analyses were conducted in different countries, one may suppose that the two types of effects may exist at the same time even in the same spatial scale because some farms are more likely to enlarge or shrink than others. Such a difference in farms’ behaviours may be explained by some individual farm and farmer characteristics (Saint‐Cyr & Piet, 2016). Accounting for heterogeneity in farmers’ behaviours may thus be crucial to fully understanding farm‐size dynamics and the impact of agricultural policy because this results from individual farmers’ decisions (Bollman, et al, 1995; Freshwater & Reimer, 1995; Jackson‐Smith, 1999).…”

“…Although the M‐MCM has been widely applied in some other strands of the literature (Blumen, et al, 1955; Cipollini, et al, 2012; Frydman, et al, 1985), very few applications can be found in agricultural economics. Recently, Saint‐Cyr and Piet (2016) showed that even a restricted mover‐stayer model represents farm‐size dynamics more efficiently than the homogeneous MCM that assumes that all farms behave alike. The present article extends this approach in two directions.…”

mixmcm: A community-contributed command for fitting mixtures of Markov chain models using maximum likelihood and the EM algorithm

“…Mixed Markov chain models ( MMCM ) have a long history in the literature and have proved to be useful for analyzing dynamic Markovian processes in heterogeneous populations. MMCM have been applied to analyze several economic issues such as labor mobility (see Blumen, Kogan, and McCarthy [1955] and Fougère and Kamionka [2003] for examples); income mobility (see Shorrocks [1976] and Dutta, Sefton, and Weale [2001] for examples); financial rating (see Frydman and Kadam [2004] and Frydman and Schuermann [2008] for examples); or firm-size dynamics (see Cipollini, Ferretti, and Ganugi [2012] and Saint-Cyr and Piet [2017] for examples). Other applications of MMCM can be found in sociology (see Singer and Spilerman [1974] and Dias and Vermunt [2007] for examples); in medicine (see Albert [1991], Chen, Duffy, and Tabar [1997], and Dias and Willekens [2005] for examples); or in other strands of the literature such as natural resources management (see Jackson [1975] for example).…”

“…Other applications of MMCM can be found in sociology (see Singer and Spilerman [1974] and Dias and Vermunt [2007] for examples); in medicine (see Albert [1991], Chen, Duffy, and Tabar [1997], and Dias and Willekens [2005] for examples); or in other strands of the literature such as natural resources management (see Jackson [1975] for example). These studies of dynamics use different forms of the MMCM , ranging from a simple stationary mover–stayer specification (see Blumen, Kogan, and McCarthy [1955], Fougère and Kamionka [2003], and Saint-Cyr and Piet [2017] for examples) to more general specifications (see Dias and Vermunt [2007], Frydman and Schuermann [2008], Saint-Cyr [2017], and Frydman and Matuszyk [2018] for examples).…”