Impact of Recent Economic Crisis on Agricultural Production Efficiency of

the European Countries

Monirul Hasan Tóth József

Corvinus University of Budapest

May 3, 2013

ObjectivesTo 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 reviewTo 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: 2003-2009 for EU-23

member statesFor 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 1957.Input orientation and CRS

Random effect regression

Technical Efficiency (TEit) = f {govt. effectiveness, control of corruption, specific year dummy (t 2003 to t2009), specific region dummy of EU}

Descriptive stat.

Econometric results: RE panel regression modelRandom effect regression analysis of panel data Dependent variable: Technical Efficiency score Co-efficient Standard error

Government Effectiveness -0.018 0.039Control of Corruption -0.124*** 0.046Year 2004 -0.008 0.017Year 2005 -0.033 0.017Year 2006 -0.026 0.017Year 2007 -0.037** 0.017Year 2008 -0.042** 0.017Year 2009 -0.039** 0.017Central and Eastern Europe -0.527*** 0.172Western Europe 0.092 0.180Observation 161Number of countries 23Wald chi2(8) 28.35Prob > chi2 0.001***R-square Within 0.1182 Between 0.5320 Overall 0.3461note: *** p<0.01, ** p<0.05, * p<0.1Source: Author’s calculation

Thank you