What is Existing Situation?
Agriculture is one of the largest sector of Pakistan’s economy and still remains a dominant deriving force for growth and the main source of living for more than sixty per cent of the national population. It accounts for around 21 percent of the Gross Domestic Product (GDP) providing employment to about 45 percent of the total labor force, raw materials to the industry and an assured market for industrial products, besides remaining the main source of foreign exchange earnings. As a result of inordinate spike in prices of major crops, an additional amount of Rs. 342 billion was transferred to the rural areas in 2010-11 alone. Agriculture sector recorded modest growth of 1.2 percent in 2010-11 (Govt. of Pakistan, 2011).
Pakistan, with a rich endowment of natural resources and hardworking farming community, has had varied experience in agricultural growth and food security. Soon after independence, the country faced serious difficulty in producing enough food even for a population of 32.5 million from a cultivated area of around 15 million hectares. Badly damaged infrastructure, absence of supportive institutions, large-scale movement of the farming communities across the borders and continued reliance on traditional technologies and farming practices, had pushed the country into low productivity and a low production trap. Slow growth of the national economy combined with poor crop harvests and under developed marketing & distribution system, had created serious food insecurity problems.
Agriculture in Pakistan has had two phenomenal growth experiences during the past century. The first significant improvement in crop production, both through acreage expansion and productivity increase, occurred soon after the development of the Indus Basin irrigation system. The second phenomenal increase in crop production occurred during the sixties and the seventies following the wide-spread adoption of new farm technologies comprising high yielding varieties (HYVs), chemical fertilizers, pesticides, mechanization and improved farming practices.
Pakistan has two principle crop seasons, namely the ‘Kharif and ‘Rabi’. Pakistan’ agriculture sector is dominated by crop and livestock production. In crop sub-sector, wheat and rice are the major food staples for about 180 million people in Pakistan. Wheat and rice are the major crops of rabi and kharif seasons, respectively. Wheat always occupies a central position in formulating agricultural policies. It is the main staple food for most of the population and largest grain source of the country. It contributes 13.1 percent to the value added in agriculture and 2.7 percent to GDP. The total production and per hectare yield of wheat shows the fluctuating trend with no sustainable growth pattern. Rice is the second largest staple grain crop in Pakistan and is a major source of foreign exchange earnings in recent years. It accounts for 4.4 percent of value added in agriculture and 0.9 percent in GDP. Per hectare yield and total production of rice also not shows a consistent pattern.
An increase in agriculture production can result from a horizontal expansion, that is, by increasing input use (Collins and Bosworth, 1997) or from vertical expansion, that is, through improvement in productivity (Ahmad and Bukhari, 2007). Agricultural growth through horizontal expansion by increasing the cultivated land and the use of labor, fertilizers, pesticides and water, is not only becoming increasingly difficult but less sustainable. Therefore, the second option, namely, an improvement in productivity of resources becomes more critical for achieving higher and sustainable agricultural growth (Mongia and Sathaye, 1998).
There can be no denying the fact that in Pakistan, poor management of natural resources remains the real problem. The management of inputs at the farm-level and implementation of programs and policies at the provincial and national levels have remained very weak. Irregular and inadequate supply of inputs, policy lapses, distribution inefficiency, and unjustified price escalations remain a serious and perennial problem. Delayed and less responsible policy decisions and market inefficiencies frequently lead to input shortages and rising gaps between the officially announced prices and the actually received/paid prices for inputs/crops by the average farmer. This widens the trust deficit between growers and the managers of national affairs leading to lowering grain farm productivity.
Since the scope for horizontal expansion in grain production is limited, the present agriculture policy aims for vertical expansion through increase in productivity of cereal crops. When we compare the average yield of different major crops achieved in different countries of the world there exists a considerable yield gap between our national average and the average of the countries where agriculture has been the focus of policy reforms. This productivity gap can be bridged by removing the obstacles in farming practices, efficient utilization of available resources and by overcoming the productivity barriers.
- b) Justification
Like in many other developing countries, Pakistan’s agriculture is continuing to face numerous challenges. Her current population of 180 million is growing at a rate of more than 2.0 percent per annum. At this of growth rate, Pakistan is projected to become the fourth most populous country in the world by the year 2050. Such a huge rise in population will undoubtedly become a major constraining factor for achieving sustained economic growth and food security. Along with the startling demographic bulge, limited possibilities of further increase in cultivated land, slowing returns to input intensification and relatively high income elasticity of food in developing countries like Pakistan, would require significant increase in food supply. Further increase in local food (cereals) would only be possible from enhanced productivity growth (Ali, 2005).
c) What are the scope and issues to be addressed and your approach to address them?
An increase in grain production can result from a horizontal expansion, that is, by increasing input use (Collins and Bosworth, 1997) or from vertical expansion, that is, through improvement in productivity (Ahmad and Bukhari, 2007). Growth in grain production through horizontal expansion by increasing the cultivated land and the use of labor, fertilizers, pesticides and water, is not only becoming increasingly difficult but less sustainable. Therefore, the second option, namely, an improvement in productivity of resources becomes more critical for achieving higher and sustainable growth in grain production (Mongia and Sathaye, 1998).
The above analysis clearly shows that overall agricultural production is of the level and type of inputs used and the productivity growth. The factors such as land, labor , irrigation, new seed varieties, fertilizers and pesticides continue to remain critical to productivity enhancement, the knowledge and empowerment of the farming community, strengthening of institutions supporting institutions and infrastructure, favorable policies and macroeconomic stability, play an equally important role in the realization of better resource productivity and sustained growth. The proposed research aims to investigate the impact that various programs and policies have had on the productivity of grains (wheat and rice) over the years.
The proposed research will ensure the increase in productivity growth of grains in Pakistan, enhance the mechanism of technology transfer and fulfill the objective of food security.
THE TECHNOLOGY
a) Give brief overview of the Technology to be transferred.
Lessons learned from earlier research studies will be transferred to farmers, particularly to researchers, policy makers, academicians and donors.
b) Have you practically tested these methods earlier? If, yes, where? NA
Objectives:
The proposed research study will therefore aims to:
- Analyze the productivity growth of grain crops (wheat and rice) in Pakistan.
- Identify the factors effecting the productivity growth of grain crops.
- Based on the analysis and findings of the study, make policy and program recommendations for the policy makers, agricultural scientists and identify the required adjustments at macro level that ensure the transfer of technology and thus can achieve sustained productivity growth in grain crops.
PROCEDURES
a) Methodology, Estimation of productivity growth of grain crops
Output series both for wheat and rice crops available from secondary sources will be used for the estimation of TFP growth of cereal crops. Time series price data for two categories of output will be collected to construct the output indices. The production data regarding wheat and rice crop will be collected from the official publications and reports. The data for wheat and rice output prices will be collected from the website of Food and Agriculture Organization (FAO), Agricultural Statistics of Pakistan, Economic Survey of Pakistan, etc. Similarly, time series data on the input used in the production of wheat and rice crops, that is, land, labor, capital (separately for tractors, diesel tube-wells, electric tube-wells and draught animals), fertilizer off-take (separately for nitrogen, phosphorus and potash), pesticide consumption, fodder, wheat straw, feed-concentrates, etc, will be collected from secondary sources and used in the construction of input indices.
In the growth accounting framework, the most frequently applied techniques in literature to measure total factor productivity are: (i) Arithmetic Index (AI); and (ii) Tornqvist-Theil Index (TTI). The Tornqvist index has been used in numerous total factor productivity studies conducted during the last two decades. In most of the empirical applications for calculating TFP indices, the Tornqvist index formula was used for developing output and input indices. Since the continuous time derivation of Divisia index cannot be done empirically due to the non- availability of almost all time-series data at discrete intervals, the Tornqvist-Theil (T-T) approximation to the Divisia index for TFP estimation, will be employed. The most frequently used formulation by (Capalbo and Antle, 1988; Thirtle and Bottomley, 1992, Ali, et.al, 2009) will be applied. Expressed in logarithmic form, the Tornqvist-Theil total factor productivity index is as follows:
Most probably, TFP IP version 1:0 software will be used for the estimation of productivity index.
Identification of factors responsible for productivity growth of grain crops
The estimated TFP index of grain crops will be used as a dependent variable and the macro parameters that can affect the growth in grain productivity, directly or indirectly, will be used as explanatory variables. To investigate the effect of macro variables and government policies on grain productivity growth, co-integration and error correction approaches will be applied. This approach will investigate both the short-run and long-run effect of those variables on the productivity growth of grain crops.
Contemporary literature mentions two major approaches for testing co-integration. These include Residual-based ADF-approach proposed by Engle and Granger (Engle and Granger, 1987) and Johansen’s Full Information Maximum Likelihood (FIML) approach (Johansen and Juselius, 1990). Major weaknesses in the Residual-based ADF approach include its low power and finite sample biasness. This approach cannot be used in a situation where there are more than two variables (Charemza and Deadman, 1992). Therefore, Johansen’s approach will be preferred over the Engle and Granger’s approach.
Error Correction Mechanism (ECM) explains the dynamics of short run adjustment towards long run equilibrium. When the variables are co-integrated, there is a general and systematic tendency for the series to return to their equilibrium value. It means that the short run discrepancies may be constantly occurring but cannot grow indefinitely implying thereby that the adjustment dynamics is intrinsically embodied in the co-integration theory. The theorem of Granger representation states that if a set of variables is co-integrated, it implies that residuals of co-integrating regression is of the order I(0), where an ECM describing that relationship exists. This theorem explains that both co-integration and ECM can be used as a unified theoretical and empirical framework for analyzing both short run and long run behaviour. The ECM specification is based on the premise that adjustments are made to get closer to the long- run equilibrium relationship. Hence, link between co-integrated series and ECM is intuitive; an error correction behaviour induces co-integrated stationary relationship and vice versa (McKay et al., 1998).
The growers of wheat and rice in Pakistan, both small and large, will be the main beneficiaries of the findings and policy recommendations of the proposed research. The planned analysis of productivity and the underlying factors will provide useful empirical information for the formulation of programs and policies aimed at achieving sustainable growth in cereal crops and enhancing food security.
References:
Ahmad, Q. M. and S. K. H. Bukhari (2007). “Determinants of Total Factor Productivity in Pakistan”. SDPC, Karachi, Research Report No. 68.
Ali, A., Mushtaq, K., Ashfaq, M., and Raza, M.A. 2009. An Analysis of Productivity Growth of Agriculture in Pakistan 1971-2006. J. of Agri. Res., Vol. 47(4), 439-450.
Ali, S. (2005). “Total Factor Productivity Growth and Agricultural Research and Extension: An analysis of Pakistan’s Agriculture, 1960-1996”. The Pakistan Development Review, Vol. 44 No. 4, pp. 729-746.
Capalbo, S. M., and J. M. Antle (1988). “Agricultural Productivity: Measurement and Explanation”. Washington, D.C.: Resources for the Future.
Charemza, W. C., and D. F. Deadman (1992). “New Directions in Econometric Practice: General to Specific Modelling, Cointegration and Vector Autoregression”. Edward Elgar Publishing Limited.
Collin, S., and B. P. Bosworth. (1997). “ Economic Growth in East Asia: Accumulation VS Assimilation”. In W.C Brainard and G. L. Perry. Brookings papers in Economic Activity2.
Engle, R. F. and C. W. J. Granger (1987). “Cointegration and Error Correction: Representation, Estimation and Testing”. Journal of Econometrica Vol. 55, pp. 251-276.
Johansen, S., and K. Juselius (1990). “Maximum Likelihood Estimation and Inference on Cointegration- With Application on Demand for Money”. Oxford Bulletin of Economics and Statistics, Vol. 52, pp. 170-209.
McKay, A., O. Morrisery and C. Vaillant (1998). “Aggregate Export and Food Crop Supply Response in Tanzania”. CREDIT Discussion Paper No. 4, Nottingham. Centre for Research in Economic Development and International Trade.
Mongia, P., and J. Sathaye (1998). “Productivity Trends in India’s Energy Intensive Industries: A Growth Accounting Analysis”. Earnest Orlando Lawrence Berkeley National Laboratory, LBNL-41838.
Pakistan, Government of (2011). “Economic Survey of Pakistan, 2010-11”. Ministry of Finance, Economic Advisor’s Wing, Islamabad.
Thirtle, C., and P. Bottomlay (1992). “Total Factor Productivity in U.K agriculture, 1967-90”. Journal of Agricultural Economics, Vol. 43, No. 3, pp. 381-400.
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Author: Ali Hassan Shabbir
MSc (Hons) Agricultural Economics, Institute of Agricultural and Resource Economics,
University of Agricultural Faisalabad, Pakistan.
Email: [email protected]
