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Problems Faced By The Agricultural Sector Economics Essay

Agriculture, also called farming or husbandry, is the cultivation of animals, plants, fungi, and other life forms for food, fiber, biofuel and other products used to sustain life. Agriculture was the key development in the rise of sedentary human civilization, whereby farming of domesticated species created food surpluses that nurtured the development of civilization. The study of agriculture is known as agricultural science. Agriculture generally speaking refers to human activities, although it is also observed in certain species of ant and termite. The word agriculture is the English adaptation of Latin agricultÅ«ra, from ager, “a field”, and cultÅ«ra, “cultivation” in the strict sense of “tillage of the soil”. Thus, a literal reading of the word yields “tillage of fields”.
Agriculture has increased its contribution of value-added to the economy. However, it has declined in its contribution to GDP. In 1980-1990, its share of GDP fell from 22.9 to 18.7 per cent despite a 2 per cent annual growth rate (table 2). That share declined further to 13.6 per cent in 1995. Manufacturing, in contrast, increased its value added by 13.3 per cent a year during 1991-1995, and by 1995 it was contributing 33.1 per cent to GDP.
The best way for agriculture to expand is through the conversion of new land for planting. That avenue of expansion is, however, no longer possible as the country has run out of arable land. Instead, the opposite was increasingly occurring as agricultural land was taken over for industrial, infrastructural and housing purposes.
Less apparent problems faced by agriculture were trade and fiscal measures adopted by the country. Agriculture in humid tropical countries is relatively efficient because of the natural advantages they enjoy, a situation that has largely been taken for granted. Agriculture in Malaysia is no exception. Thus, in terms of market protection, for example, agriculture enjoys very little in contrast to, say, the automobile industry. Indeed, export taxes imposed on palm oil, rubber and pepper discourage agricultural production.
Fiscal incentives also did not favour the agricultural sector. For example, abatement of adjusted income (until its recent abolishment) largely did not apply to agricultural companies although the privilege was enjoyed by manufacturing companies, even those without pioneer or investment tax allowance status
Those basic discriminatory conditions in turn contributed to other problems for agriculture. Trade protection for manufacturing, for example, enhanced the credit worthiness vis-B -vis agriculture and made it easier to obtain financing. With such advantages, it is not difficult to see why there has been a persistent outflow of resources from the agricultural sector to the rest of the economy, thus stunting agricultural growth.
With resources pouring into the non-agricultural sectors, those sectors were able to offer higher wages and better conditions of work. Agricultural labour was drawn away and the sector had to offer higher wages merely to mitigate, not reverse, the outflow. Agricultural employment in 1990 was almost at the same level as in 1985 despite a larger workforce. Consequently, the share of employment in the agricultural sector fell from 39.7 per cent in 1980 to 27.8 per cent in 1990.
The agricultural sector also had to face the challenge of natural problems. Malaysia never had a comparative advantage in the production of food. Production of beef and mutton, for example, suffered from a lack of pasture, low production through reduced food intake by animals as a result of the hot and humid climate, and the high import costs of animals. In addition, rice production has continued to fall short of a series of successively lower targets.
A major challenge to the agricultural sector and more specifically TDT systems is to develop/adapt the technologies which can increase the overall on farm production and productivity of all major farming groups: peasant subsistence farmers (psf); small scale farmers (ssf); medium scale farmers (msf) and large scale farmers (lsf), through intensification (where there are land shortages) or extensification (where availability of land is not a constraint). Either way the increase in overall on-farm production and productivity can only occur through increased utilization of modern technological inputs (e.g. high yielding seed varieties, fertilizers, mechanization and water management etc.)…
The second challenge to the agricultural sector and the TDT systems follows from the first – this is the development of the technology transfer system (both the software and hardware) to ensure its efficient supply and utilization. There is need, in addition to develop a system (be it publicly, privately or cooperatively owned) which provides/distributes the technological inputs in a timely manner and at an affordable prices to the farmers. This will require research and innovation into institutional management and organizational structures which can best serve the farmers to increase their productivity. With Government’s role in the provision of services to the agricultural sector being reduced, this becomes a major challenge and priority for agricultural policy research…
The third challenge is to ensure that whatever is produced is safely stored on the farm (for home consumption) and/or is transported, processed and marketed/exported to the urban consumer/external markets with a minimum of post-harvest losses. The output recovery system will need both physical (e.g. storage structures, post harvest processing technology, transportation systems, rural roads, etc.) as well as socio-economic (e.g. prices, marketing institutions, etc.) technologies. With dismantling of the public marketing organizations due to ESAP, an alternative system, which will largely be privately or cooperatively owned, needs to be developed to ensure that the produce is efficiently stored/transported/ processed/marketed in the urban areas/export markets…
The fourth challenge is to maintain the sustainability of the agricultural resource base i.e. in meeting challenges 1-3, there must be minimum environmental degradation (i.e. minimum soil erosion, maintenance of productivity of the land, biodiversity, etc., development of alternative sources of energy to firewood, etc.). In tackling the above, African leaders, scientists, civil servants, the private sector etc, will have to avoid getting bogged down with fads and fashions which emerge from the development community. They will have to establish institutions and structures which ensure that the strategies formulated are implemented. Even more important, this will also require the establishment and/or strengthening of the capacity for institutional crafting in most countries of the sub-region.
Fourth – Challenges Facing the Agricultural Development Process Agro activity could realize and impact economic development, in other words, it can reach its specific objectives in a shorter period compared to any other activity, because it has primary and secondary links with the other activities, but it faces several challenges:
Natural Resources: Owns un-exploited agricultural natural resources (land, water, scientific brains, labor force), waiting for intensive investment to use for increasing agro productivity; animal and plant production.
1. Water It is known that water resources available for agro purposes are limited, in addition of lack of any agreement to guarantee a fair share of Tigris and Euphrates rivers, however, there are other challenges on the internal level, that are not less serious:
A- The random usage of water in the three main sectors: agriculture, industrial, and domestic, is still continuing, in addition to lack of internal coordination and absence of agreement among the main users which calls for developing a vision for water policy.
B- Weak participation of water users in its management.
C- Irrational methods of irrigation, especially in surface irrigation.
All this require a flexible system to manage the demand on water for getting the best usage of the available water, while taking social, political, economical, and ecological factors into account. Demand management strategies and tools will enable us to use water efficiently and in an equal and sustainable manner, weather in practices or policies. Basically, managing the demand on water requires making a difference in the behaviors and practices related to water usage.
2. Agricultural Lands In Iraq, there are wide arable lands, but what is actually used is still small, however, some challenges still face using these lands and hinder its appropriate usage, as follows:
A- The problems of salinity and copious in central and southern Iraq soil.
B- Land fragmentation, and small agricultural acquisitions hinders efforts to develop agro processes and introduction of modern technology.
C- The gypsum soil that spread across wide areas which constitute a challenge to agro development since it needs experience and special care to manage.
D- The spread of dunes and erosion as a result of natural elements, these are serious risks facing agriculture.
3. Human Resources and Capacity Building A- The technical and administrative capacities for the people working in this sector is still in need of support, by enhancing extension, raising awareness, leading negotiations to reach acceptable agreements to improve water quality and quantity to guarantee a fair and acceptable share for Iraq.
B- Severe shortages in all field research requirements, and the need to twin it with agricultural extension to apply research results and deliver them to the farmers.
C- The need for technical means to transform the productive capacities to real capacities to bridge the gap between the actual needs and actual production, even partially, since the achieved harvest rates are still humble and could be improved.
4. Agro Investments The investment environment is still not attractive in spite of issuing the investment law number 13 for 2006, since no investments were pumped in the agricultural body to strengthen it, however, agro investments are the key to sustainable development and the best way to achieve sustainable food security, creating job opportunities, enhancing the income and nutrition of rural people, and decreasing migration from rural to urban areas.
The country is in need for annual, or even seasonal requirements, like agro machines, fertilizers, pesticides, and others, imported from abroad with huge amounts of money in hard currency, which could be transformed onto added value for the GDP, or capital accumulation, if we invest locally in these requirements. Governmental investment plays a significant role in spending on the infrastructure, operation, and maintenance of the natural resources and providing and improving services, issuing the necessary laws and legislations to regulate processes, in addition to providing direct and indirect support. This methodology of state carrying all the burdens had the impact of: creating a feeling of carelessness which resulted in abuse and waste of these resources.
5. Environmentental Challenges Laws and legislation for the agricultural sector guarantees a sustainable environment but the problem is in the implementation of procedures. Despotic fishing and hunting; usage of electricity and poisons, irrational application of fertilizers and pesticides, and the lack of effective system for contention, and sewage water recycling process which require: preserving the bio diversity, monitoring the activities that adversely influence eco diversity, establishing reservoirs and organizing them to keep the types in their locations keeps ecosystems, multiplication of endangered species, and establishing plan and animal genetic banks.

Macro Econometric Income Consumption Model for India

Consumer spending is an important factor that can stimulate the economic growth and development through the multiplier process. This study aims to estimate the pattern of consumption expenditure and tries to identify the consumption function for Indian Economy. The study intends to identify the determinants of consumption and to build a econometric model using the annual data from RBI Handbook of Statistics on Indian Economy (2008-2009) for the time period 1970 to 2009. Following are the variables taken into consideration for empirical analysis; Private Final Consumption Expenditure (PFCE), Personal Disposable Income (PDI), Rate of Interest (ROI) and Inflation (INF). We have employed rigorous econometric techniques in analyzing the time series data so as to ensure the credibility and reliable economic relations. The results confirm income (PDI) as the most significant factor. The MPC calculated which ranges between 0.80 to 0.90, which is in affirmation with the theoretical assumptions and is more or less similar to the previous studies. The conclusions from the model suggest that the Keynesian Absolute Income Hypothesis is found to be appropriate to Indian context.
INTRODUCTION: The relation between aggregate consumption or aggregate savings and aggregate income, generally termed the consumption function, it has occupied a major role in economic philosophy ever since Keynes made it a keystone of his theoretical structure in The General Theory of Employment, Interest and money. The role of consumption in the multiplier process has increased the scope and dynamics of the topic which led to further developments in this field by developing more realistic and logical consumption (Income) hypothesizes. Consumption which was considered only as a function of income was later refined and redefined.
The purpose of the study is to examine and comprehend the issues, trends and rationale behind the consumption pattern in India. In our study an attempt is done so as to understand and estimate the potential factors that had led development. We estimate the consumption model in India using advanced econometric tools. The study is conducted for period from 1970 to 2009 using the annual data from RBI Hand Book of Statistics on Indian Economy.
THEORETICAL MODELS: Consumption function indicates a functional relationship between consumption, income and other factors. It shows how consumption expenditure varies as there is change in the income and other factors such as age, social status, interest rates etc. Whereas Consumption refers to amount spent on consumption at a given level of income. On the other hand consumption function refers to actual consumption at various level of income.
Major development in this respect took place when In 1936 Keynes formulated a consumption function which was the basic element in the income expenditure approach to the determination of national income. Consumption function for him was the basic building block of multiplier analysis. According to Keynes marginal propensity to consume is less than average propensity to consume this is well described in the stagnation thesis around 1940. Keynes observed this as behavior of the consumption expenditure in the short run over the long run.
Keynes offered no precise functional formulation of the propensity to consume; his analysis has come to be associated with a simple version of the consumption function that embodies only the more quantitative aspects of his considerations, popularly known as the simple Keynesian consumption function or Absolute Income Hypothesis (AIH). The theory asserts as income rises, the theory asserts, consumption will also raise but not necessarily at the same rate. The basic principle of the absolute income hypothesis is that the individual consumers who determine what fraction of his income will he devote to consumption on the basis of the absolute level of that income. AIH provided a background for the further studies in this field. This resulted in the development of three more theoretical models namely Relative Income Hypothesis (RIH), Permanent Income Hypothesis (PIH), and Life Cycle Hypothesis (LCH).
Relative Income Hypothesis (RIH) developed by Duesenberry in 1949 conceives consumption in relation to the income of other households and past income. It implies that the proportion of income consumed remains constant provided that a household’s position on the income distribution curve holds constant in the long run. This is consistent with long-run evidence. Higher up the income curve, however, there is a lower average propensity to consume. The second part of the hypothesis suggests that households find it easier to adjust to rising incomes than falling incomes. There is, in other words, a “ratchet effect” that holds up consumption when income declines. Duesenberry’s analysis is based on two relative income hypotheses. The first hypothesis is essentially that consumers are not so much concerned about the absolute level of consumption as they are with their consumption relative to that of rest of population. Second hypothesis Duesenberry argues that present levels of consumption is not influenced merely by present levels of absolute or relative income, but also by levels of consumption attained in previous periods.
Absolute income hypothesis when captures the effect of current income on current consumption the theories developed there after focus on the influence on income on consumption in a broad sense. Permanent income hypothesis developed Milton Friedman further divide the income component into two parts. First include the permanent income component and transitory component the second. He states that consumption is determined by the permanent component and normally transitory income is saved.
To be more specific, The Permanent Income Hypothesis decomposes measured total disposable income, Y, into a permanent component (YP), and a transitory component, (YT). The permanent income component is deemed systematic but unobservable, reflecting factors that determine the household’s wealth, while the transitory component reflects “chance” income fluctuations. Similarly, measured consumption, c, is decomposed into a permanent component, CP, and a transitory component, cT. In giving the hypothesis empirical substance, Friedman assumes the transitory components to be uncorrelated across consumption and income, and with their respective permanent components.
A little different from these above mentioned hypotheses the Life-Cycle Hypothesis presents a well-defined linkage between the consumption plans of an individual income and income expectations as passes from childhood, through the work participating years, into retirement and eventual decease. The main building block of life-cycle models is the saving and consumption decision, i.e., the division of income between consumption and saving. The saving decision is driven by preferences between present and future consumption (and the utility derived from consumption). Given the income stream the household receives over time, the sequence of optimal consumption and saving decisions over the entire life can be computed. It should be noted that the standard life-cycle model as presented here is firmly grounded in expected utility theory and assumes rational behavior.
THE ECONOMETRIC MODEL AND THE SPECIFICATIONS Data Used For the Study: We have used annual long-run time series data on Private Final Consumption Expenditure, Personal Disposable Income, Gross Domestic Savings, Rate of Interest and Inflation from The Handbook of Statistics on Indian Economy 2008-2009 published by Reserve Bank of India (2008-2009). They are represented as the following: Private Final Consumption Expenditure (PFCE), Personal Disposable Income (PDI), Rate of Interest (ROI) and Inflation (INF). Where in PFCE is the dependent variable. Econometric Methodology:
One of the major and crucial problems that can be faced while dealing with time series data is, many a times data may be non – stationary. So avoid spurious regression it is necessary to check the time series data for stationarity using unit root tests. Keeping this in mind the unit root test has been carried out for each series using the Augmented Dickey-Fuller test for the period 1970 – 2008. All the variables are non stationary at the levels and in order to make them stationary we employed the technique of differencing. All variables other than rate of interest is differenced twice, where (D) stands for differencing once and D (D) for differencing twice.
Table: 1 Unit root tests with Trend and Intercept: 1970 – 2008 Variable
Level
Inference
1st difference
Inference
(LnPFCE)
-1.51
Non -stationary
-5.23
Stationary
(LnPDI)
-1.38
Non -stationary
-5.26
Stationary
(LnSAV)
-2.04
Non -stationary
-5.94
Stationary
(LnROI)
-2.56
Non -stationary
-8.26
Stationary
(LnINF)
-4.49
Stationary
1% critical value = -3.50, 5% critical value = -2.89, 10% critical value = -2.58
The analysis also takes into account the lag structure that plays a vital role in the consumption analysis. To study the role of previous peak incomes and the role of habits the functional form that we can use is as follows:
Ct = α β0Yt β1 Yt-1 εt
Using the given functional model where Ct is consumption at time period (t), Yt represent income at time period (t), Yt-1 representing one year lagged value of income where in we can study the long run effects of income on consumption. But the above equation (distributed lag model), since takes the lag of independent variable there is all possibility of encountering the problem of multicolinearity. Thus we need to transform this model into some other model which takes care of the problems. When we have distributed lag models where lag structure follow the geometric form we can transform them using the Koyack transformation.
The transformed model AR (1) can be re written as follows:
Ct = α β0Yt δCt-1 ut
This model is called a Auto regressive model where lagged value of dependent variable itself will be a independent variable. In the above model β0 measure the short run effect or the short run MPC and δ measure the long run effects, in our model it is the long run MPC.
Estimated Equations: Equation: 1 For the above consumption equation the independent variables are income, rate of interest, inflation and a year lagged value of the dependent variable. According to the theoretical setup the coefficient of income demands a positive relationship. This is for the reason that when income increases consumption also increases and more over the coefficient of income indicate the MPC which is supposes to be a positive value less than one. Both our equations satisfy this condition. In both the equation the coefficient of savings and rate of interest shows a negative relationship. It is obvious that when savings increases consumption decreases because savings is considered as an alternative for consumption and savings increases when rate of interest is high thus when rate of interest is high savings increases and the consumption expenditure decreases. Inflation is included as an independent variable to evaluate the effect of prices, when prices increases the expenditure on consumption is bound to increase so we expect a positive relation. The AR coefficient showing a positive relation is having a number of theoretical implications for example for permanent income hypothesis to hold good the AR coefficient should be negative. The theoretical implications of the positive AR coefficient are explained in the following discussions.
Since the estimates are partial regression coefficients all the coefficients are explained by keeping the assumption, when effect all the other variables are kept constant what is the impact of a variable on consumption. From equation one the value of income co efficient can be read as follows, when there is one percent increase in income there will be 0.83 percent increase in consumption. Thus a value of 0.92 in the second equation for the income coefficient indicates, when there is one percent increase in income consumption will increase by 0.92 percent. Theoretically the coefficient of income is the MPC which give information about the change in consumption when income changes by one unit. The limits of MPC are zero to one and our both equation satisfies this condition. It is also important to note that both the equations income turns out to be the most significant factor, the t values for this coefficient is 19.31 and 23.82 respectively.
The coefficient of savings and the rate of interest show a negative relation which indicate an inverse relation of these variables with respect to the dependent variable consumption, this holds good for both the equations. For both the equations the coefficient is same for savings. When all other variables are kept constant an increase in savings by one unit will decrease consumption by 0.06 percent and for a unit increase in rate of interest will decrease the consumption by 0.0183 percent in the first equation and 0.0244 percent according to the second equation. In both the equations savings is backed by significant t- values but interest rates are relatively in significant in both the equations
In the first equation inflation is one of the very significant variable, it is proved that inflation will have a positive impact on consumption and this was expected, this is because of the reason that in a developing nation like India the maximum is spend on the necessary commodities thus an increase in price will increase the consumption expenditure. It is estimated that one percent increase in inflation will lead to increase in consumption by 0.0115 percent.
Equation (1) is supported by statistically significant t value and high R2 of 0.97 which imply 97%, of the variation in consumption expenditure is explained by the explanatory variables. A DW statistic of 2.01 rules out the problem of series auto correlation. Equation (2) is also supported by statistically significant t values and high R2 of 0.95 which imply 95%, of the variation in consumption expenditure is explained by the explanatory variables. In an AR (1) for identifying the elements of auto correlation we need to look at D.W ‘h’ statistic. The calculated D.W ‘h’ of 0.07 rejects the possibility of auto correlation.
Calculation of Long Run MPC For the given AR model (Equation: 2):
Ct = α β0Yt δCt-1 ut
β is the short run MPC and according to theoretical models the β (MPC) should be less than one. AR model can be used even to calculate the long run MPC. According to theoretical models long run MPC should be greater than the short run and should be equal to one. The long run MPC can be calculated as follows:
Long run MPC (δ) = β / 1- δ
= 0.92 / 1-0.07
= 0.989
Thus the AR coefficient of 0.07 can be interpreted as follows, when the increase in the income is sustained, then the increase in the MPC (long run MPC) out of income will be 0.989. In other words when consumers have time to adjust for one unit change in income, they will increase their only for about 0.989 percent.
Theoretical Implications: Macro Econometric models must fit into a theoretical framework and should be handy in terms of policy implications. This holds well in the case of Consumption models also. So in this respect it is necessary to validate the model (Equation 1

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