Monirul Hasan Tóth József Corvinus University of Budapest May 3, 2013

Objectives To examine the impact of recent economic crisis on the production efficiency (technical efficiency) on EU agricultural output. To examine whether any regional disparity remains in the technical efficiency

Literature review To capture the effect of agricultural policy reform on technical efficiency, some authors used year specific dummy variables to capture policy changes. These works done by Morrison Paul et al. (2000), Carroll et al. (2009), Lambarra et al. (2009) and Brümmer et al. (2006). Several authors such as Weersink et al. (1990), Hallam and Machado (1996), Sharma et al. (1999), O ‟ Neill and Matthews (2001), Rezitis et al. (2003), Helfand and Levine (2004), Latruffe et al. (2008b), Zhu et al. (2008b), Tonsor and Featherstone (2009), and Bakucs et al. (2010) included location dummies like state, regional or country level in their regression of farm technical efficiency scores to see the regional disparity.

Literature review It is widely found that the impact on technical efficiency is almost consistently negative across literature. Giannakas et al. (2001), Rezitis et al. (2003), Hadley (2006), Latruffe et al. (2009), Bakucs et al. (2010), Zhu et al. (2008a) found the same trend in their studies. Leff (1964); Leys (1965); Huntington (1968); Beck and Mahler (1986); Lien (1986); Vial and Hanoteau (2010) establish that corruption increases efficiency.

Data World Bank data: for EU-23 member states  For measuring technical efficiency-  Inputs: - Agricultural land (square kilometre) - Labor (number of agricultural workers) - Fertilizer (kilogram/hector)  Output: - Aggregate output of agriculture (value added, constant 2000 US$)  other variables: - Government Effectiveness - Control of Corruption - Year dummies - Regional dummies

Government Effectiveness & Control of corruption Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. [WB] Control of corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. [WB]

Methodology Data Envelopment Analysis (DEA) for measuring the technical efficiency Panel data regression analysis- to examine the relationship among variables and years. Random effect model is used.

Data Envelopment Analysis (DEA) Source: Farrell Input orientation and CRS

Random effect regression

Descriptive stat.

Econometric results: RE panel regression model Random effect regression analysis of panel data Dependent variable: Technical Efficiency score Co-efficientStandard error Government Effectiveness Control of Corruption ***0.046 Year Year Year Year **0.017 Year **0.017 Year **0.017 Central and Eastern Europe ***0.172 Western Europe Observation161 Number of countries23 Wald chi2(8)28.35 Prob > chi20.001*** R-square Within Between Overall note: *** p<0.01, ** p<0.05, * p<0.1 Source: Author’s calculation

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