A System Dynamics Investigation of Employment in the Iranian Agricultural Production
Haghighi, Mohammad Hashem Moosavi (2007) A System Dynamics Investigation of Employment in the Iranian Agricultural Production. PhD thesis, Universiti Putra Malaysia.
Agriculture is an important economic sector and a strategic component for rural development in Iran. The sector contributed about 15% of the country‟s value added in 2005, and created 23% of the total employment in 2004. However, the sector is basseted with a labour surplus situation as indicated by the high labour/ land ratio. This situation, together with inappropriate combination of labour with other factors of production, has caused a low level of labour productivity, and hence, low growth rate in the agricultural sector. Thus, the general objective of this study is to determine the optimal employment and production policies in the agricultural sector of Iran. Whereas, the specific objectives are to estimate the econometric models of the Iranian agricultural sector to determine the production and other relationship in the System Dynamics (SD) model; to develop a SD model and identify the relationship among the socio-economic variables in the agricultural sector of Iran for simulating the future trend of employment and production; and to simulate the SD model pertaining to different scenarios.This study employed the econometric methods and SD simulation model by incorporating the dynamic changes of the socio-economic variables. Econometric methods provide representations of the system in equations. Production, export-import, demand for labour and agricultural products, as well as the wage functions were estimated using data collected over 35 years, and substituted in the economic component of the SD model. A dynamic demand for the labour equation incorporating a Disequilibrium Costs (DC) and Adjustment Costs (AC) was estimated from 1966/67 to 2000/01. The results indicated significant relationships between employment, production, wages and cross-price elasticity on labour demand. This suggests that the adjustment co-efficient was too slow (0.044) since AC was higher than DC, and the existent of substitution relation between the capital and labour, and the war which had negative effects on the agricultural labour demand. The exchange rate variable had the expected sign in the export and import functions. The per capita income in the „Organization for Economic Co-operation and Development‟ (OECD) countries, had a positive sign in the export equation. The agricultural price index and agricultural production had respectively negative and positive effect on the agricultural export. On the other hand, outcomes of the war and Islamic Revolution on the agricultural export were negative. In the import equation, the national income per capita had a positive effect, while the real exchange rate had a negative effect on the agricultural import. Analysis on the results of the production functions confirms the priori expectation that the Iranian agricultural sector is facing low marginal product. The capital and land were also found to be scarce resources, and have imposed a gradual binding constraint on the production. The Return to Scale (RTS) before the materialization of the Islamic Revolution was positive (1.87), but turned to negative after that event (-1.74). The Pure Technical Change (PTC) has increased over the time (0.30 to 0.43), while the Non-Neutral Technical Change (NNTC) has declined (-0.35 to -0.39). Obviously, the results of production functions reveal that the production technology of the Iranian agriculture does not have a well-behaved quality. The overall results suggest that policy makers should reduce the labour force in the agricultural sector, and improve the capital-intensive methods in order to simultaneously increase the output and productivity of the sector. In developing the SD model of the Iranian agriculture, the specifications of the estimated equations are substituted in the SD model to specify some relationships between a number of important variables. However, other mathematical formulations are also used to build the SD model. The validity of the model was done based on several tests such as error checking, dimensional consistency, behaviour reproduction, sensitivity analysis, extreme condition, boundary adequacy, structure assessment, parameter assessment, and integration error tests. The results of all tests indicated that the ability of the SD model to simulate agricultural sector was acceptable. The brief results of SD model are as follows: The rural population showed a collapse behaviour type during the 1998-2021 period. The rural population is a source of agricultural supply. The results of the SD model simulation indicate that a turnpike for the labour surplus problem will happen in 2008. After that period, the agricultural employment will decline gradually per year. Hence, it can be stated that the labour surplus problem automatically declines in the mid-term period. On the other hand, the rate of migration from the rural to the urban areas will increase and consequently move the unemployment problem from the rural to the urban areas. The results of the simulated agricultural production indicate that the average production growth rate in 2007-2021 is about 2% per year. According to the development plan, the real growth rate in the whole economy should increase 8.6% annually. Obviously, this shows that the growth rate in the agricultural sector is not much over the future time with the country‟s goals and production in the period (2007-2021) need more consideration. In supporting the increment in production, the increase in inputs (especially land and capital) is needed. When these increases in the process of production are successful, they have been accompanied with the improvement in the overall technical change.Based on the SD simulation model for the period of 2006-2021; the results indicated that rural population, export, and employment would decline (35%, 21%, and 30%, respectively) while the rural emigration, labour and agricultural demands, production, capital, and import would also increase (116%, 21%, 43%, 32%, 102%, and 193%, respectively). The major policy implications from the study suggest that if the government could increase arable land by providing improvement in the irrigation system, reduce labour in order to decrease labour/land ratio, improvement in the overall technological methods (PTC and NNTC), these efforts would considerably improve the agricultural productivity. When the government changes the market factors such as the agricultural price index, real exchange rate, worker wage, they will have great effects on the employment, but only a small effect on the production. The overall results of study demonstrate the way to combine the different methodologies, i.e., the SD and econometrics, to be further effective. Keywords: System Dynamics Simulation, Socio-Economic Model, Agricultural Labour, Production Functions, Dynamic Demand for Labour, Export-Import Functions, Agricultural Demand
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