SIMULATION MODEL BASED ON IACS DATA; ALTERNATIVE APPROACH TO ANALYSE SECTORAL INCOME RISK IN AGRICULTURE

Review of Agricultural and Applied Economics, RAAE, VOL.19, No. 1/2016

ARTICLE TYPE: REGULAR ARTICLE
RECORD ONLINE: 15.04.2016
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KEYWORDS:
income stabilisation tool, risk analysis, direct payments, MCS, EU
DOI NUMBER:
10.15414/raae/2016.19.01.56-64
ABSTRACT:
We develop a static simulation model to analyse income losses and income risks at aggregated agriculture sector level. Our empirical case study is based on farm level records for direct payments claims (IACS data) and covers the period 2010–2011. Using Monte Carlo simulations, we investigate the impact of different levels of risk on income trends. Results show that 80% of farms are extremely dependent on direct payments. Farm production types highly supported by direct payments consequentially fall into the low-risk group. Results show that a significant share of income loss at sector level is carried by small farms (by economic class). Average probability of larger losses at the sector level ranges between 2% and 64%. Our results also indicate that larger farms often have better risk-return ratios and thus face lower relative income risks.
JEL CODES:
R52, R58, H41
PAGES:
56 - 64
Please Cite this Article as:

Jaka ZGAJNAR (2016) Simulation Model Based On Iacs Data; Alternative Approach To Analyse Sectoral Income Risk In Agriculture. Review of Agricultural and Applied Economics. XIX (Number 1, 2016): 56-64. doi: 10.15414/raae/2016.19.01.56-64
URL for sharing:

https://roaae.org/1336-9261/doi/abs/10.15414/raae/2016.19.01.56-64

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Review of Agricultural and Applied Economics | ISSN 1336-9261
Faculty of Economics and Management of the Slovak Agricultural University in Nitra and the Association of Agricultural Economists in Slovakia.
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