Investigating agricultural productivity improvements in transition economies Supawat Rungsuriyawiboon Faculty of Economics Thammasat University

Outline Introduction - World food price situation - Motivation Methodology - Productivity growth decomposition - Malmquist productivity index Application - Data discussions - Results of transition countries Conclusions

Introduction Food security is back on policy agendas Overall food prices rose more than 70%. Rise in food prices has developed into a global crisis. “When all people at all times have both physical and economic access to sufficient food to meet their dietary needs for a productive and healthy life ” (USAID) Production of Wheat, Corn and Rice Food Price Energy Price

Introduction Some food price examples from the FAO Type $/ton White Thailand rice (second grade) (+77%), (+62%) Yellow corn (+58%), (+36%) Wheat (+64%), (+48%) Powdered milk1,8353,2884,750 (+61%), (+30%) Dutch soy oil ,400 (+63%), (+49%)

Introduction Food commodity price indices have increased across the board Cereals 48% Oil&Fat 52% Dairy 32%

Introduction Numerous factors are influencing this price rise Supply side: difficult seasonal conditions in the major production regions Demand side: increasing food demand, rising demand for grain for biofuels, and increased input costs. Each world region must have a sufficient supply in agricultural products to meet the growing food demand

Introduction Many countries have undergone a transformation from a CPE to a free market economy. These transition economies undergo economic liberalization, restructuring and privatization in order to create a financial sector, and move from public to private ownership of resources. These countries account for almost half of the regions population in Europe and Asia. Institutional reforms have helped transform the structure and volume of their agricultural production. Understanding the state of productivity improvements is important

Literature Review A number of studies examine intercountry differences in productivity growth using two frontier models (SFA or DEA) Both SFA and DEA models conducted in many studies to investigate intercountry differences in agricultural productivity growth using the panel data from the FAO A nonparametric DEA model: - Bureau, Färe, and Grosskopf (1995) - Fulginiti and Perrin (1997) - Suhariyanto and Thirtle (2001) - Arnade (1998) - Trueblood and Coggins (2003) - Coelli and Rao (2005) A parametric SFA model: - Fulginiti and Perrin (1993) - Wiebe et al (2000) - Craig, Pardey and Roseboom (1997) - Liu and Wang (2005) Because of data problems of transition countries, previous studies just ignored these countries

Objectives First, this study measures productivity growth in transition countries This study includes 35 transition countries in Asia and Europe over the period of Second, this study utilizes a nonparametric Malmquist index approach to measure and decompose productivity growth This paper pays attention to the magnitude and direction of productivity growth over different stages of their market reforms

Methodology Total Factor Productivity (TFP) growth: Residual growth in outputs not explained by growth in input uses Färe et al. (1989) proposed a Malmquist TFP index to measure productivity growth using the output distance function The output distance function at period t represents the minimum amount by which y t can be deflated and still remain producible with x t The Malmquist TFP index for period t The Malmquist TFP growth index (MTC) between period t and t+1 is defined as the geometric mean of two Malmquist TFP growth between these two time periods

Methodology The Malmquist TFP growth index (MTC) between period t and t+1 is decomposed as To calculate the Malmquist TFP index decomposition, we need to calculate four output-oriented distance functions. The ability of firm to use each input more efficiently Technical Efficiency Change (TEC) Catching up The ability of firm to adopt new technology Technical Change (TC) Frontier shift TFP progress TFP regress

Data The empirical analysis in this study focuses on agricultural production of 35 transition countries in Asia and Europe over the period from The primary source of data is obtained from the website of the Food and Agricultural Organization (FAO) acquired from the AGROSTAT system Production technology consists of two output variables and five input variables

Data Output Variables: The output series are derived by aggregating detailed output quantity data on 115 cropping commodities and 12 livestock commodities expressed in terms of the international average prices (in US dollars) Input Variables: Land: Arable land in hectare includes both land under permanent crops as well as the area under permanent pasture Tractor: the total number of wheeled- and crawler tractors used in agriculture Labor: the number of economically active people in agriculture Fertilizer: the commercial use of nitrogen, potassium and phosphate fertilizers in nutrient-equivalent terms expressed in thousands of metric tons Livestock: the sheep-equivalent of the six categories of animals (buffaloes, cattle, pigs, sheep, goats and poultry)

Country Profile

Results for All transition Countries RegionPeriodTECTCMTC All A griculture was healthy in terms of its improvement in productivity T hrough the entire period, the rate of TC was higher than 3.5 percent The adoption of new varieties of crops have pushed up the production frontier by 3.68% annually TFP growth has been pulled down due to declining TEC. This decline may be due to the continued rise in off-farm employment TFP growth in transition countries was relatively robust and rising

Results for Groups of Transition Countries CEE countries exhibited an impressive TFP growth after the start of the reform, the productivity increased quite strongly at 3.5%. NIS countries posted TFP growth rate of more than 4.0%. Rises in both TC and TEC lead to relatively high TFP growth in these regions TFP growth rate in Asia was comparatively low at the start period of transition. TFP growth rebounded and kept rising afterwards at a rate more than 4.5% annually. The relatively high TFP growth has relied on TC. RegionPeriodTECTCMTC CEE NIS ASIA

Productivity Profiles of the MTC Decomposition for Each Transition Country 1 = both “catching-up” and “frontier- shift” effects drove overall TFP progress 2 = only the “frontier-shift” effect drove overall TFP progress 3 = a decline in the “frontier- shift” effect led to overall TFP regress 4 = a decline in the “catching-up” effect led to overall TFP regress.

Productivity Profiles of the MTC Decomposition for Each Transition Country 1 = both “catching-up” and “frontier- shift” effects drove overall TFP progress 2 = only the “frontier-shift” effect drove overall TFP progress 3 = a decline in the “frontier- shift” effect led to overall TFP regress 4 = a decline in the “catching- up” effect led to overall TFP regress.

Results of the selected transition countries over different stages of their market reforms TFP growth decomposition differ considerably at different stages of the transition period. In the initial 5 years of transition, TFP growth rose quite strongly in some countries like Czech Republic, Poland, Russia and Myanmar, but it fell in other countries like Belarus, Bulgaria, Hungary, Uzbekistan and Vietnam due to declining TEC. During the second five years of transition, TFP growth rose considerably in most countries except Myanmar and Uzbekistan due to the improvement of TEC and TC. In the beginning of the 21 century, the annual growth of TFP rose above 5 percent in many transition countries.

Conclusion Transition economies experienced the comparatively high TFP growth over the transition period. Growth of TFP rose above 5 percent in many transition countries. TC was a major force of driving TFP growth in these transition countries. The pattern of TFP growth shows that TEC had fluctuated considerably over the transition period. Serious improvements in performance and efficiency, as well as continued technology transfer are required to meet the demand for food and anticipated increases in world population.