The Impact of capital intensive farming in Thailand: a computable general equilibrium approach

Abstract

Although the structure of Thai economy has been transforming from an agricultural economy to an industrialized country (measured by the share of agriculture to GDP), in 2008 nearly 40 % of overall employment was still engaged in the agricultural sector. In addition, most of the poor (57%) were farm operators and farm workers. Since 1960, the outflow of workers from the agricultural sector to non-agricultural sectors has been increasing. A shortage of agricultural labour has resulted in increased use of farm machinery, a trend that seems to be continuing. Hence, Thai agriculture is expected to become more capital-intensive farming than labour-intensive farming. The aim of this study is to explore whether efforts to encourage producers to use agricultural machinery and equipment will significantly improve agricultural productivity, income distribution amongst social groups and macroeconomic performance in Thailand. A 2000 Social Accounting Matrix (SAM) of Thailand was constructed as a data set, and then a 20 production-sector Computable General Equilibrium (CGE) model was developed for the Thai economy. The CGE model is employed to simulate the impact of capital-intensive farming on the Thai economy under two different forces: technological change and free trade. Four simulations were conducted. Simulation 1 increased the in share parameter capital in the agricultural sector by 5%. Simulation 2 is a 5% increase in agricultural capital stock. A removal in import tariffs for agricultural machinery sector forms the basis for Simulation 3. The last simulation (Simulation 4) is the combination of the above three simulations. The results for each simulation are divided into five effects: input, output, price, income and macroeconomic effects. The results of the first two simulations were opposite in terms of the five effects. Simulation 2 accelerated the capital intensification of all agricultural sectors, whereas Simulation 1 led to more capital intensity in some agricultural sectors. The effects of the input reallocation had a simultaneous impact on output in every sector. Simulation 1 led to a fall of almost all outputs in the agricultural sector, whereas there was an increase in agricultural output in Simulation 2. Overall, almost all prices in Simulation 1 increased whereas Simulation 2 resulted in a decrease in agricultural prices but an increase in non-agricultural prices. In terms of domestic income effects, as a result of the decline of the average price of factors in Simulation 1, there was a decrease in factor incomes belonging to households and enterprises. Consequently, government revenue decreased by 0.7%. In contrast, Simulation 2 resulted in an increase in all incomes above. Finally, regarding macroeconomic variables, Simulation 1 had a negative impact on private consumption, government consumption, investment, exports and imports, resulting in Gross Domestic Product (GDP) decreasing by 0.8%. On the other hand, Simulation 2 had a positive impact on those same variables, affecting a 0.4% rise of GDP. The effects of Simulation 3 were very small in everything compared with the first two simulations. The effect of Simulation 4 was mostly dominated by Simulations 1 and 2; the negative results of Simulation 1 were compensated by the positive effects of Simulation 2.