Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Farm-Level Risk-Balancing Behavior and the Role of Latent Heterogeneity
    Tamirat, Aderajew ; Du, X. ; Pennings, J.M.E. ; Trujillo Barrera, A.A. - \ 2020
    Journal of Agricultural and Resource Economics 45 (2020)2. - ISSN 1068-5502 - p. 265 - 281.
    Dynamic target capital structure and speed of adjustment in farm business
    Aderajew, Tamirat S. ; Trujillo-barrera, Andres ; Pennings, Joost M.E. - \ 2019
    European Review of Agricultural Economics 46 (2019)4. - ISSN 0165-1587 - p. 637 - 661.
    This paper quantifies the determinants and speed of adjustment to the target capital structure for a panel of 1,500 Dutch farms over the years 2001–2015. Using the System General Method of Moments (System-GMM) estimator, the results show that farm profitability, earnings volatility, asset tangibility and growth opportunity are important determinants of leverage. Leverage is highly persistent, i.e. the average adjustment speed is relatively low, with variations among farm types. This variation is mainly attributed to the difference in adjustment costs. Further, we show that the pecking order and signalling theories explain these leverage dynamics.
    Farm-Level Risk-Balancing Behaviour and the Role of Latent Heterogeneity
    Tamirat, Aderajew ; Trujillo Barrera, A.A. ; Pennings, J.M.E. - \ 2018
    - 51 p.
    Risk-balancing behaviour - latent heterogeneity - mixture regression model - farm business - Expectation-Maximization (EM) algorithm
    This study provides farm-level empirical support for the risk-balancing hypothesis using a longitudinal dataset from a panel of 1500 Dutch farms. Risk-balancing refers here to adjusting the level of financial risk in response to changes in business risk due to exogenous shocks, keeping the level of total farm risk constant or close to the optimal total farm risk. In empirical studies to date, the heterogeneity of risk-balancing farms has been neglected. In this paper, we explicitly account for latent heterogeneity using a latent mixture regression model. Using the iterative Expectation-Maximization (EM) algorithm, the model simultaneously identifies segments based on the influence of the selected explanatory variables and estimates the effects of these variables on farm risk-balancing behaviour for each identified segment. We find that profitability, risk, leverage, age, size, and diversification play an important role in driving farm risk-balancing behaviour. Interestingly, the heterogeneity at segment level appears to have been masked at aggregate farm-type level, notably the effects of leverage and total risk exposure. Assuming homogeneity in farms’ responses and estimating a pooled model or a priori classifying farms based on farm type yields a poor fit. The results provide new insights in the interdependence of financial and business risks, spark discussion about the linearity of farm risk reduction policies and total farm risk and underline the relevance of considering both observed and unobserved factors in devising relevant risk-management strategies.
    Do Profit Rates Converge? Evidence on the Persistence of Farm Profit in the Long-run
    Tamirat, Aderajew ; Trujillo Barrera, A.A. ; Pennings, J.M.E. - \ 2018
    - 37 p.
    Profit persistence - System-GMM estimation - quantile regression - dynamic panel model
    Ensuring farm survival and competitiveness requires a better understanding of why some farms consistently perform better (worse) than others. This article investigates the drivers of farm profitability, the degree of abnormal profit persistence, and its determinants based on a unique longitudinal data set collected from a panel of 2000 Dutch farms between 2001 and 2015. We apply a quantile regression approach to examine the drivers of farm profitability, and a dynamic panel System- GMM estimation to estimate the persistence of abnormal farm profit. The results of the quantile regression show that working capital, labor productivity, leverage, capital intensity, and investment are important determinants of profitability. The findings suggest that working capital is important for farms’ flexibility and their capacity of adapting to changing circumstances in environments where they don’t receive regular income from agricultural products. Estimates using the dynamic panel model provide evidence on abnormal profit persistence. Profit persistence is responsive to farm risk exposure, investment, capital intensity, leverage, working capital and diversification. Thus, long-run farm profit can be achieved and sustained by reducing costs through economies of scale, ensuring adequate working capital to cope with the cash flow mismatch, enhancing labor productivity, and minimizing the farm’s capital intensity levels.
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