Factors effecting on gdp intoduction economics essay

The economy of Pakistan is 47th largest in the world in nominal term and 27th largest in the world in term of purchasing power. The gross domestic product (GDP) in Pakistan expanded 2. 39 percent in the second quarter of 2011 over the previous quarter. Historically from 1952 until 2011, Pakistan’s average quarterly GDP growth was 5% and reaching an historical high of 10. 22% in June of 1954 and a record low of -1. 80% in June 1952. Pakistan’s economy has suffered in the past from decades of internal political disputes, a fast growing population, mixed level of foreign investment and a costly confrontation with neighboring India (www. tadingeconomics. com). However, IMF approved government policies, bolstered by foreign investment and renewed access to global markets, have generated solid macroeconomic recovery during the last decade. Our study related to factors effecting on GDP. Infrastructure is the fundamental requirement in the functioning of any country. In today’s modern era, we need electricity to power our homes and industry. We need roads to transport goods from one place to the other and then ports and airports to export our industrial products to foreign trade partners. Similarly, a modern nation requires effective water and sanitation to improve and sustain the health and cleanliness of its people. In all situations, infrastructure is such a necessity that it affects the lives of every single individual on this planet. Lack of proper infrastructure causes chaos and havoc in our lives. It also causes bottlenecks in the smooth functioning of the economy. Pakistan’s infrastructural situation is relatively poor by international standards and this has an acute effect on the lives of every Pakistani in the country. Everyone suffers from electricity shortages and the lack of proper water and sanitation provisions. Also as the population increases our problems have gotten worse. The Government of Pakistan and its people face an uphill battle against poor infrastructure and it seems like the latter is winning. The improvement and expansion of infrastructure is a pre-requisite for sustaining and accelerating economic growth and social development in a country. Improving quality and service coverage in power, water supply and sewerage treatment, transport and logistics is crucial for Pakistan’s economy and to improve the quality of life. It is estimated that due to insufficiency, Pakistan looses about 4 to 6 percent of its GDP (approximately $6 billion). Logistical bottlenecks increase the cost of production of our goods by about 30 percent. This has a significant impact as Pakistan is facing stiff competition from the likes of India and China in the export markets. To improve and expand infrastructure, Pakistan’s needs are massive and its resources are limited. Not only is there limited fiscal space, there are also huge gaps in public sector capacity to build and operate infrastructure. Tight fiscal indicators such as fiscal deficit of 4. 2 per cent, trade deficit of around $ 10 billion and current account deficit of 4. 4 percent of GDP does not permit to spare public sector resources for infrastructure development. As the economy is growing at the average rate of 7 percent per annum, it requires investment on infrastructure at around 7 to 9 percent of GDP. There are different types of factors which effect on GDP like; Inflation, poverty, infrastructure , balance of payment etc. Relating to our study different types of studies have already conducted by different countries at government level. As all studies conducted at government level so, that we find gap of study at domestic, private or community level. If we conducted study in these sectors we better understand the reasons why Pakistan’s current GDP growth rate is relatively low from past few decades. In this way we take steps for enhancing GDP growth rate of our country in upcoming years. Our objective of the study is to get complete knowledge about the factors effecting on gross domestic product (GDP), and find their relationship with GDP growth rate. There are different types of factors which effect on GDP but in our study we have discussed only three factors like; infrastructure, balance of payment and infrastructure. These two factors show greater effect than other factors. We have also discussed that at what percent these factors contribute to enhance the GDP growth rate, and how we can able to enhance the efficiency of these factors so that these factors can positively contribute to GDP growth rate.

OBJECTIVE:

Our objectiveof the study is to get complete knowledge about the factors effecting on gross domestic product (GDP), and find their relationship with GDP growth rate. There are different types of factors which effect on GDP but in our study we have discussed only two factors like; balance of payment and infrastructure. These three factors show greater effect than other factors. We have also discussed that at what percent these factors contribute to enhance the GDP growth rate, and how we can able to enhance the efficiency of these factors so that these factors can positively contribute to GDP growth rate.

SIGNIFICANCE OF THE STUDY:

This study has high significance. After study of factors effecting on GDP we get more things to learn. This study produces new knowledge for reader. This study tells us how we can enhance the GDP growth rate of a country. This study infrastructure, balance of payment and infrastructure are the variables which affect the GDP greater than other factors. In future this studies becomes helpful for policy makers, so that they will make policies, which will increase GDP growth rate. If we become able to increase our revenues than our GDP growth rate will enhance in future.

PURPOSE OF STUDY:

The first purpose of study is to find out relationship between infrastructure, balance of payment, infrastructure and GDP. Second purpose of this study is to learn how these factors positively contribute to enhance the GDP growth rate of country. Third purpose of the study is to provide some key points for policy makers.

RESEARCH QUESTION AND HYPOTHESIS:

Research question

Our research problem is” What are the factors affecting on GDP”.

Hypothesis

H1= There is relationship between balance of payment and GDPH0= There is norelationship between balance of payment GDPH1= There is relationship between infrastructure and GDPH0= There is no relationship between infrastructure and GDP

VARIABLES:

The variables of our study areGross domestic product or income (GDP)Balance of paymentInfrastructure

GDP:

GDP is our dependent variable. We can define GDP as” Income generated by factors of production in a country during a year is called gross domestic product or income”. GDP includes income generated from; wages and salaries, interest income, rent income, undistributed corporate profit, mixed income and direct taxes. We may write GDP in numeric form asGDP = C+I+G+(X-M)C = Private consumptionI = Investment privateG = Government spendingX = ExportsM = Imports

BALANCE OF PAYMENT:

This is independent variable. The balance of payment shows the balance of import and exports. If the imports volume are greater than exports volume the balance of payment will be unfavorable. And if the exports volume are greater than imports volume than this balance will be favorable. The balance of payments is said to be balanced when the credit items are exactly equal to the total of debit items. The balance of payment is comprehensive record of a countrywith the rest of the world during a given period of time.

INFRASTRUCTURE:

This is also independent variable. Infrastructure includes roads, building, hospital, motor vehicles, crude oil, streets etc. Investment in infrastructure thus will tend raise production given the level of private capital and employment. It will also raise the marginal product of private capital and thus raising the incentives to invest.

Model:

Political instabilities

GDP

Infrastructure

Balance of payment

Literature Review:

Relationship with political instability and GDP

(Kira, 2013) Gross Domestic Product (GDP) is one of the determinants of country’s economic growth. This study intends to analyze the factors that affect the GDP of Developing Countries whereby Tanzania is selected as a representative. Keynes model was adopted to be tested in Tanzanian GDP from 1970 to 2009. The result shows the GDP being at the same level year after year with no significant changes subject to some dormant factors. The most common GDP trendis a continuous growth with periods of acceleration and deceleration. Some occurrences of unconditional decline are afterwards plagued by further growth. Developing county’s GDP is confused and unbalanced, with regular and deep unconditional GDP falls and booms. Tanzanian GDP as a developing country is influenced by Consumption (Government Final Expenditure and Household Final Expenditure) and Exports. Investment sector have to be encouraged for its impact on GDP be realized including stimulation of industrialization at country level. Problems such as increase in oil prices, power shortages and political instabilities are a distinctive source of GDP sinking in developing countries which require abruptly solution.(Veiga, 2010) The purpose of this paper is to empirically determine the effects of political instability on economic growth. Using the system-GMM estimator for linear dynamic panel data models on a sample covering up to 169 countries, and 5-year periods from 1960 to 2004, we find those higher degrees of political instability are associated with lower growth rates of GDP per capita. Regarding the channels of transmission, we find that political instability adversely affects growth by lowering the rates of productivity growth and, to a smaller degree, physical and human capital accumulation. Finally, economic freedom and ethnic homogeneity are beneficial to growth, while democracy may have a small negative effect.(Chowdhury, 2006) Political Stability and Economic Development: The Case of Bangladesh Among the non-economic variables considered as sine qua non for development, political stability comes first. One may argue that other non-economic factors like rule of law, law and order situation are subsumed under political stability. On the other hand, major determinants of development like savings and investment, relative price stability, human resources, level of technology, factor productivity can play an effective role when political atmosphere is congenial. For example, it is argued that political stability and convenient law and order ensure the confidence of the people in the economy and its further development, which encourages the people to save. It also promotes confidence of the investors in the economy and convinces them to invest and reinvest. Of course, price stability, higher education and technical qualifications of the population, increasing factor productivity, technological modernity, export promotion etc. may not be directly related to political stability. But political stability in the long run ultimately ensures a relative price stability, improves educational and qualification status of the people, increases factor productivity, enables technology transfer, promotes exports. Those are the factors essential for economic growth. Moreover, long term political stability provides a congenial atmosphere for evolution of democracy. Democratic political order in turn, can ensure political stability.(Ahmad Jafari Samimi & Reza Moghaddasi, 2013) Political Stability and FDI in OIC CountriesThe purpose of the present paper is to investigate the impact of Political stability on foreign direct investment (FDI) revenues in Organization of Islamic Conference (OIC) countries. To do so, we have concentrated on a sample of 16 countries for which the necessary data were available for the period 2002-2009. We have used a panel data regression analysis. Our empirical results indicate that Population, openness and gross domestic product (GDP) have positive impact on FDI, whereas Political Stability has a detrimental effect on FDI in OIC countries.(ALI, 2001) Political Instability, Policy Uncertainty, and Economic Growth: An Empirical Investigation This paper elaborates upon the effect of political stability on economic growth using a novel approach. Unlike the literature on growth that emphasizes the turnover of decision makers, this paper focuses on the volatility of economic policies as the relevant indicator of stability. The literature on growth ignores the microeconomic instability associated with frequent changes of government policies. The empirical results of this paper indicate that the effect of political instability on economic growth is not conclusive. Most of the commonly used proxies for political instability have failed to explain growth differences across countries. The political instability indices have no significant effect on growth when a reasonable set of core variables is also included in the regression equation. The results also show that almost all of the policy uncertainty variables are significantly and negatively correlated with economic growth. However, the instability of economic policies has no significant impact on the accumulation of capital.(Ponzio, 2005) Determined the impact of political instability on economic growth in post independence Mexico, I study the connection between economic growth and political instability during the most turbulent period in Mexican history, the post-independence period in the nineteenth century. Political instability implied policy uncertainty, no public programs for development, but most important, violence, lack of property rights, and other forms of disorder that led to risk of loss for economic actors. Political differences were based on ideological disagreement among political agents. I measure political instability by a combination of four variables: changes in the executive post; internal wars; number of parallel governments; and most importantly, foreign wars. The evidence is very strong. There is a negative link between political instability and growth. The result is robust to different control variables, equation dynamics, estimation methods, and growth measurements. I show that between 50 and 100 per cent of the decline in the growth rate during the four or five ” lost decades” after independence can be attributed to political instability. And furthermore, political stability is responsible for about 50 to 88 per cent of the increase in the growth rate during the Belle Époque. And most important, there is no systematic difference in the growth rate after 1867 when I control for political stability. Political instability is the single most important factor in explaining why Mexico lagged behind during the nineteenth century.(Nadeem Qureshi, 2010) Political instability and economic development: Pakistan time-series analysis. In case of Pakistan, only economic variables are observed as causes to high economic volatility while political variables are completely ignored. Although, it is apparent that the development pattern in Pakistan is highly volatile during the years of political instability that spans almost over the half history of the country. By taking the sample of 1971 to 2008 and using simple OLS technique, we observe how far political instability hampers the economic development of Pakistan. For the political instability measurement, ignoring all traditional measures of political instability, we construct political instability index by using seven different variables for Pakistan by employing Principal Component Technique; while for economic development measurement frequently economic development variables are used. Through analysis, the negative relationship is found between political instability and economic development in Pakistan.(DIMITRAKI, 2010) Political instability and economic growth in Western Europe: a causality analysis for 55 years, This paper investigates the links between political instability and economic growth in Western Europe. A more complete measure of political instability than has previously been developed is used in combination with a simultaneous equations model and IV/Generalized Method of Moments (GMM) estimators approach to produce several interesting findings. First, the inverse relationship between political instability and economic growth documented by other studies is confirmed. Second, the results illustrate that economic growth and political instability are jointly endogenous.

Key words: political instability, economic growth, regime type, endogeneity, IV/GMM estimation.

(Nur-tegin, 2012) Corruption: Democracy, Autocracy, and Political Stability The recent empirical literature on corruption has identified a long list of variables that correlate significantly with corruption but only five were distinguished by Leamer’s Extreme Bounds Analysis as robust to various samples, measures of corruption, and regression specifications. Among these five factors that were found to reduce corruption are decades-long tradition of democracy and political stability. In today’s world, however, there are many countries that combine one of these two robust determinants of corruption with the opposite of the other: politically stable autocracies or newly formed and unstable democracies. The central question raised in this paper is: Is it worth, in terms of corruption, for a country to trade stability with autocratic rule for political freedoms but with transitional instability? We find that the answer to this question is in the affirmative – the level of corruption is indeed lower in unstable democracies than in stable dictatorships. Our results are robust to various measures of corruption, alternative regressor indices, and regression specifications.(Giskemo, 2012) exploring the relationship between socioeconomic inequality, political instability and economic growth. The hypothesis that socio-economic inequality has a detrimental effect on economic growth by breeding political instability has been subject to empirical investigation for decades. However, the numerous studies in the field have yielded highly different conclusions, and still no agreement has been reached as to what the relationship between these variables really looks like. This study investigates why empirical studies have given such diverging results. By using several different measures both of socio-economic inequality, political instability and economic development it examines whether differences in methods and measurement can explain the variation in previous findings. It is revealed that the effect of socio-economic inequality upon political instability is dependent on which measures are used, and that the effect of instability upon economic development varies between different analytical models. The study thus shows that conclusions about the relationship between these phenomena are not robust to alternative measurement. A possible explanation of why previous empirical studies have reported such diverging findings is therefore that socio-economic inequality and political instability have been measured in different ways, or that different analytical models have been used.

Relationship with Infrastructure and GDP

According to Thrilwall (1979) balance of payment shows the balance of imports and exports. The imports volume is greater than exports volume than this balance will be unfavorable and if the exports volume was greater than the imports than this balance will be favorable. In a nutshell he states that the rate of growth of a country compatible with equilibrium in the balance of payments is a function of the rate growth of its main trading partners multiplied by the ratio of income elasticity of demand for a country`s exports by the rest of the world to the income elasticity of demand for its imports. Exports performance is measured by the ratio of exports to the average propensity to imports (i. e the ratio of imports to GDP). when exports are equal to imports; the exports performance ratio is equal to GDP (THRILWALL, 1979). The balance of payments constrained growth model determines the rate of growth of an economy that is compatible with equilibrium in the balance of payments. This require that exports and capital flows equal Imports valued at current prices (Thrillwall, 1979). It can also written formally as, According to Thrillwall(1979) the volume of exports and imports are specified as constant elasticity multiplicative functions. Exports volume is the function of the relative Price of exports and international prices and of world income. In a symmetric fashion import volume depends on the relation between import prices and the domestic price level and of domestic income. Foreign direct investment is a major component of capital inflow for developing countries, its contribution towards economic growth is widely argued, but most researchers concur that the benefits outweigh its cost on the economy(musila and sigue, 2006)The growing interest in foreign direct investment stand from perceived opportunities derivable from utilizing this form of foreign capital injunction into the economy, to augment domestic savings and further promote economic development in most developing countries or economies(Aremu, 2005). Foreign direct investment contributes to the host country`s gross capital formation, higher and growth, Industrial productivity and competitiveness and others spin off benefits such as transfer of technology, managerial expertise, Improvement in the quality of human resources and increased investment.(2011)A study about foreign direct investment in NIGERIA reveals that the FDI effects on economic growth and exchange rate in turn affect the inflow of FDI. In other words balance of payment and GDP depends upon FDI.(Ehnimare, 2011)According to king current account shows the balance of payment of imports and exports. If balance of exports is greater than imports than this balance will be surplus and if balance of imports is greater than exports than this balance will be deficit. GDP= Y= dollar value of final goods and serviced produced and sold in an economy in a given time period (King). The balance of payment accounts shows a detailed record of country`s economic transactions with the row during an accounting period i. e. its payment to foreigners is a debit (-) and a receipt from foreigners is credit (+), (King)Infrastructure : Infrastructure refers to o shape government revenues and expenditures. The earliest organized school of macroeconomic thought is the “classical“ school. The classical economists were proponents of the price mechanism (market system) which assumes a effective resources allocation (Ekanem and Loyan, 1999). The market failed to achieve a satisfactory level of welfare for the society by providing an equitable or fair distribution of income and wealth, or all of these (Ogiji, 2004). Keynes submitted that the lingering unemployment and economic depression were a result of failure on the part of the government to control the economy through appropriate economic policies (Lyoha, 2003). Consequently, Keynes proposed the concept of government intervention in the economy through the use of macro-economic policies such as fiscal and monetary policies. Infrastructure deals with government deliberate actions in spending money and levying taxes with a view to influencing macro-economic variables in a desired direction. This includes sustainable economic growth, high employment creation and low inflation (Microsoft Corporation, 2004). Thus infrastructure aims at stabilizing the economy. Increase in government spending or a reduction in taxes tend to pull the economy out of a recession; while reduced spending or increased taxes slow down a boom(Dornbusch and fiscal, 1990). Government interventions in economic activates are basically in the form of control of selected areas of the economy. These controls differ, and depend on the specific needs or purpose the government desires to achieve. (Samuelson and Nordau’s, 1998). Aregbeyen (2007) believed that although government expenditures are necessary for economic growth, yet the impact of such expenditures on the economy is of primary importance. He concluded that the key to rapid economic growth constituted capital and public expenditure and that increased government budget deficits do not automatically guarantee rapid economic growth. According to Adeoye (2006)“The debate on the effectiveness of infrastructure as a tool for promoting growth and development remains inconclusive, given the conflicting results of current studies”. The responses of the monetary variables and the government spending variable to the business cycle shock were not restricted at all by the identification method and their responses are quite interesting. The interest rate rise and the adjusted reserves fall in response to a positive business cycle shock. This could be caused by a systematic counter-cyclical response of monetary policy given by (romer and romer, 1994). Government expenditures in contrast do not behave in a counter-cyclical fashion. Rather they increase, slowly with a positive business cycle shock. Thus if a business cycle boom fill the government`s offers with cash, it will spend more eventually (Blanchard and Perolti , 2002). Drazen (1990) argues that the effects of infrastructure depend on the size and persistence of fiscal impulse, because both in finance the signaling effect with respect to infrastructure that is to be expected in future (Giavazzi , 2000)Additionally, in times of high negative output gaps and high unemployment individuals and firms are facing tighter credit constraints, as banks eliminate credit lines or increase the risk premier on interest rates of loans. Severely credit-constrained borrowers tend to adjust spending substantially in response to even a contemporaneous change in disposable income, which can even result from a change in interest rate (Jaakela, 2007). Government`s around the world must formulate and implement policies for taxation and public spending. These policies can have major impacts on economic growth, income distribution, poverty and thus they tend to be at the cener of economic and political debates. Economic successes have been accompanied by significant reforms in public finances. Government spending has fallen in line with the changing role of the state, and revenues have picked up form low levels as tax policies have been restructured and tax administrations strengths. Fiscal deficits have narrowed as a result of increasing revenues and control on spending (Gray). Patterns of public spending affect economic growth in at least two ways. First, broad allocations of spending among government functions may affect overall growth rates because some categories of activities appear to spur growth more than others. Second, within each broad category of spending it is possible to allocate resources more or less efficiently and effectively. Determining appropriate policies and funding mechanism for health is a difficult public finance challenge everywhere. As with education, a healthier labor force contributes to economic growth but levels and patterns of public spending on health are not necessarily related to health outcomes-Richer countries tend to have better health outcomes than poor countries. Thesis due not only to higher spending per capita health spending is highly correlated with per capita income.(Gray). According to Kopeck , infrastructure affects aggregate demand, the distribution of wealth and the economy`s capacity to produce goods and services. In the short run changes in spending or taxiing can alter both the magnitude and the patron of demand for goods and services. With time this aggregate demand affects the allocation of resources and the productive capacity of an economy through its influence on the returns to factors of production, the development of human capital, the allocation of capital spending, and investment in technological innovations. Tax rates, through their effects on the net returns to labor, saving and investment, also influence boy the magnitude and allocation of productive capacity. To illustrate the importance of the difference in these two view for infrastructure stabilization, consider the effects of a cut in personal taxes, a classic countercyclical infrastructure action, lower taxes, everyting else being constant, increase household`s disposable income, allowing consumers to increase their spending. The consequences of the cut- how much is spent or saved, and the response of economic activity-depend on the way households make their decisions and on prevailing macroeconomic conditions(Kopcke, Tootell, Triest, 2008). Fatas and Minov (2001) use Colicky ordering to identify fiscal shocks and shows that increase in Govt expenditures are expansionary, but lead to an increase in private investment that more than compensates for the fall in private consumption. Balanchard (2002) use information about the elasticity of fiscal variables shocks increase output have positive effect on private consumption and a negative effect on private investment. According to Kopeck,( 2008) infrastructure affects aggregate demand, the distribution of wealth and the economy`s capacity to produce goods and services. In the short run changes in spending or taxation can alter both the magnitude and the pattern of demand for goods and services. With time this aggregate demand affects the allocation of resources and the productive capacity of an economy through its influence on the returns to factors of production, the development of human capital, the allocation of capital spending, and investment in technological innovations. Tax rates, through their effects on the net returns to labor, saving and investment, also influence both the magnitude and allocation of productive capacity. To illustrate the importance of the difference in these two view for infrastructure stabilization, consider the effects of a cut in personal taxes, a classic countercyclical infrastructure action, lower taxes, Everything else being constant, increase household`s disposable income, allowing consumers to increase their spending. The consequences of the cut- how much is spent or saved, and the response of economic activity-depend on the way households make their decisions and on prevailing macroeconomic conditions (Kopcke, Tootell; Triest, 2009). Fatas and Minov (2001) use Colicky ordering to identify fiscal shocks and shows that increase in Govt. expenditures are expansionary, but lead to an increase in private investment that more than compensates for the fall in private consumption. Blanchard (2002) use information about the elasticity of fiscal variables shocks increase output have positive effect on private consumption and a negative effect on private investment.(Prof. Keith Griffen, 2003) in his book, ” The Political Economy of Agrarian Change” and Prof. Berry and Cline, in their book ” Agrarian Structure and Productivity in Developing countries” writes that Modern Technology has been monopolized by large farmers. As a result of the higher earnings made possible by modern technology, large landowners have terminated land-rental arrangements and purchased land from small farmers who did not benefit from modern technology. Here both books writers say that the benefit from modern technology always taken by large farmers firstly because in start when any new machinery announced, it`s price be so high that small farmers cannot purchase that. So due to this reason small farmers can not earn more and large farmers take maximum earnings. After all result come in front so worst that the large farmers purchase the land from small farmers. So most attention should be focused to help the small farmers and protect them from large farmers. On other hand sometimes, small farmers take inputs as seeds and pesticides on the behalf of traders or large farmers, so those take the crops from small farmers at low price than market price. According to Javid Hamid — a research economist, the farm mechanization will have the effect of lowering the costs of production by allowing more efficient utilization of land, labor, irrigation and other inputs. As it is evident that more use of tubwells, harvesters and the threshers will have the effect of reducing the cost per acre of wheat, rice and maize etc. it is absolutely true and correct view that if farmers use modern technology then they can decrease their per acre cost and can increase their per acre yield. Every farmer wish to take benefit from modern machinery but problem is not availability of finance. For data collection 20 villages from district OKARA, result is that in these 20 villages 44 peoples having more than 30 acre land, 73 peoples having 20-30 acre land, 107 peoples having 10-20 acre land and remaining almost 810 peoples having less than 10 acre land. 44 peoples with more than 30 acre land all have modern technology as tractors, harvesters, threshers etc. and proper source of water. Peoples with 20-30 acre have 75% of modern technology and have proper water system. Peoples with 10-20 acre land have 45% modern technology. Remaining all having less than 10 acre land have 20% modern technology. So as compared to peoples with more than 30 acre land to peoples with less than 10 acre land having a very small agricultural inputs. So reason of low productivity is here that almost our 75% peoples are having less than 10 acre land who cannot purchase modern inputs but peoples who can purchase modern inputs those are only 25%. According to study made by Mr. Gill, the mechanization led to increase of 16 to 33% agriculture productivity. He describe that we can increase the productivity from 16 to 33% through the use of advance machinery for agriculture. As agriculture machinery consists tractors, harvesters, drills, diggers, sprayers etc. can increase the agriculture production. In fact, these machines control the agriculture costs, make proper irrigation, save the farmers time and control the wastage in cultivation process. According to World Bank report, the mechanization resulted in about 140 to 200% increase in cropping intensity farms in the Punjab. Here the report has a main focus on the cropping intensity. World Bank concluded that through the use of mechanization we can increase the cropping intensity in Punjab. Reason to increase the cropping intensity is that if we use machines for cropping, then machines save the farmer`s time, so he can irrigate more crops in minimum timing. So it is concluded that farmers can increase cropping intensity upto 140 to 200% by using advance machines. According to the Nadeem-ul-haq and M. Mahmood these exists a U-type relationship between size of farms and productivity of farms. Their statistics are based upon the data collected from different districts of the country. Hey are of the opinion that the medium sized farm owners did not avail any benefits from new technology. Technology concerned with the green revolution is highly expensive. The big farmers were in a position to purchase superior seeds, fertilizers, pesticides, threshers and harvesters etc. they could easily borrow from lending institutions. They get easy awareness regarding new seeds and new technology. Consequently, the benefits which arise due to large farms are more than those from small farmers. Nadeem Akmal and Sajida Taj say that the many factors are responsible for the low productivity of the agriculture including the non-availability of funds for purchasing various critical inputs. No doubt the productivity of agriculture sector could be enhanced by timely availability of the inputs including micro credit. In the absence of credit, farmers purchased inputs on credit from the input dealers, who were free to charge prices much higher than the actual market rates. The availability of credit enabled farmers to buy inputs from reputed sources at market prices. The use of recommended inputs both in quantity and the quality improved with credit. It was found that the use of only improved seed could increase the yield up to 20 per cent. The major change was that before the credit availability, seed was available to farmers from informal sources like their own farm produced (43 per cent) and fellow farmers (18 per cent), whereas after the provision of credit, the majority of beneficiary farmers (78 per cent) purchased improved seeds from formal sources. Due to agriculture sector occupies key position in the economy of the country. It earns foreign exchange, provides employment to over 42 per cent, and contributes about 23 per cent to the GDP. Moreover, other sectors are directly or indirectly dependent on agriculture for their development. Therefore the availability of credit on easy terms and conditions allow optimum consumption and increased use of inputs to achieve optimum production levels leading to the welfare of farming community. Niaz (1984) says Pakistan has a history of subsidising agricultural inputs. Although none of the agricultural inputs were subsidized during the early 1950s, the process was initiated in the second half of the decade by subsidising chemical fertilizers in order to popularize their use. In Pakistan from the middle of 1950s the agriculture inputs are started to use in cropping. But in starting times these inputs not perfectly beneficial because these are not upto the mark. But as well as time passed, the improvements are come in the inputs as machines, pesticides etc. so in these days, the agriculture inputs are maximum useful to agriculture sector. Aresvik (1967) and Kuhnen (1989) say the list of subsidized inputs and the rate structure of the subsidies were expanded considerably throughout the Sixties. Towards the end of the Sixties, it was noted that almost all the agricultural inputs including fertilizers, insecticides, seeds, irrigation water, tubwells installations, and the operation and purchase of tractors and tractor-related equipment were subsidized in one form or another. He describes that from the Pakistan indepency to these days all the required inputs for agriculture come in front. Basically mostly these inputs start to come in market from the end of sixties (1960s). after as well as time passed these inputs come in market with updated features and now a days all these inputs are in a such mode that, these are maximum benefitial for agriculture. Chaudhry (1982) says In the 1970s, some curtailment of subsidies occurred as a result of input price increases which followed the worldwide recession, a major oil shock, the credit crunch, the war with India, and the consequent steep devaluation of Pakistani Rupee. He gives a real picture about the subsidies curtailment in 1970s, which effect bad with agriculture in 1970s. Reasons behind this curtailment of subsidies are the worldwide recession of oil, credit crunch, the war with India and the devaluation of Pakistani rupee.

CHAPTER No. 3

DATA & METHODOLOGY

3. 0 Introduction

The purpose of this chapter is to explain the research methodology used for collecting and analyzing data used to test the research model, the factors that affect on GDP of in Pakistan. In this chapter data collection method, population and sampling, measures, reliability and validity and data analysis are discussed.

3. 1 Research Paradigm

Three main paradigms are used in research which is positivism, interpretivism, and pragmatism. In positivism quantitative research approach is used. In positivism existing theory is verified. To verify the existing theory assumptions are made. In positivism the numeric data is collected. The collected data is analyzed through SPSS. In interpretivism qualitative research approach is used. In interpretivism a new theory is generated. The data is collected through observations and interviews are used to collect the data. The collected data is analyzed through images and words in interpretivism approach. The third approach is pragmatism approach which is the mixture of both positivism and interpretivism. The present study used the positivism research approach because present study employed the quantitative research method to verify the existing theories. The present study collected the secondary data through financial statements. Secondary data collection is one of the data collection technique used in quantitative research approach. The study collected the numeric data and analyzed through SPSS.

3. 2 Data Collection

In order to find the data on the factors effect on GDP in Pakistan, the data was collected on four variables namely infrastructure, balance of payment and GDP the present study used the positivism research approach which is a quantitative research approach. The present study used the numeric the data on the variables because quantitative method vastly used by social sciences. The data on the variables was collected from the WDI.

Research design:

The data for this study has been collected from the software called world development indicator (WDI). In which we found frequency of our related research data that what were the fact and figures of this inflation in last five years 2007 or 2011 year in Pakistan. This study conduct on the two independent variables to check the relationship between independent variables or dependent variables, and our dependent variables is GDP and the independent variables are infrastructure and balance of payment. According to the (WDI) Software the data for these variables are already available in the world development indicator so that’s why the secondary source tool for the information. For this study is the world development indicators software the frequency or all data already has been posted in the world development indicators software.

Measures

Secondary data obtained thorough web site web site. From data collected through 2007 to 2011. we are not used data before 2007. Face validity is the validity where measure apparently reflects the content of the concept in question. For this study I used the face validity to measure the study it is right. Asked to the expert and relevant person whether extrinsically the measure seems to reflect the concerned concept or not. For this research I check the reliability through Cronbach’s Alpha

Research site:

Research site means that where we want to conduct this research in Pakistan. Pakistan our main focus is that we want to conduct research in the Pakistan to check the GDP condition which is increased day by day. We will complete our research with the help of the economic survey for Pakistan.

GDP Growth (Economic growth):

The data for this variable is selected from the predefined software which is called (WDI) World Development Indicators and the sample year is ……..

BALANCE OF PAYMENT:

This is independent variable. The balance of payment shows the balance of import and exports. If the imports volume are greater than exports volume the balance of payment will be unfavorable. And if the exports volume are greater than imports volume than this balance will be favorable. The balance of payments is said to be balanced when the credit items are exactly equal to the total of debit items. The balance of payment is comprehensive record of a countrywith the rest of the world during a given period of time.

INFRASTRUCTURE:

This is also independent variable. Infrastructure includes roads, building, hospital, motor vehicles, crude oil, streets etc. Investment in infrastructure thus will tend raise production given the level of private capital and employment. It will also raise the marginal product of private capital and thus raising the incentives to invest.

Data Analysis

The collected data of the study was analyzed by using SPSS 16. 0 software. The data was analyzed by using descriptive statistics, correlation, and regression analysis.

Descriptive Statistics

The objective of the descriptive statistics was to find the frequency of the data. Descriptive statistics also tells the minimum and maximum range of the data.

Histograms

Histograms were applied to check the graphical representation of the entire data whether it is normally distributed or not. The bell curved shapes of the data in histogram verify that the data is normally distributed.

Scatter Plots

Scatter plots were applied to the data to check the relationship between variables. Scatter plots also confirm the linear or non linear relationship between two variables.

Correlation

Correlation is used to check the inter relationship among variables. For checking the relationship we will make two hypotheses: null (H0) and alternative (H1). We interpret the findings on the acceptance or rejection of the hypothesis. We used correlation matrix to check the mutual relationship of different variables.

Regression Analysis

Regression analysis is a statistic technique used to investigate the relationships between a dependent variable and one or more independent variables. In regression analysis technique the strength of the relationship among the variables is checked. T-test is applied in regression analysis to check the significance of the relationship and R-test tells about the dependence of variables on each other. F-test is also applied to check the influence of the independent variable on the dependent variable in regression analysis.

Chapter . 4

Data and Analysis

Analysis

Descriptive Statistics

NMinimumMaximumMeanStd. DeviationPolitical instability5. 501. 00. 7800. 25884Balance of payment5-9. 55-. 77-3. 93003. 72275infrastructure53. 704. 103. 9080. 18349GDP56. 228. 847. 59001. 17934Valid N (listwise)5

Interpretation:

Table 4. 1 presents the descriptive statistics that show the overall picture of all the four variables. There were scales of 5 responses observe the above output to assess the average response rate or the respondent then we come to know the mean of different variables political instability (mean: . 78), balance of payments (mean:-3. 93), infrastructure (mean: 3. 70) and GDP (mean: 7. 59). If we observe then for all variables (infrastructure, balance of payment, political instability and GDP) the average response rate of responded is lie within the option 3-7 (and for GDP the average response rate of GDP is lie in the option 7. 5 which is high value of all variables.. So, if we observe then in the response rate for the variable of infrastructure is value of standard deviation is (S. D. 183) which is the lowest value as compare to other variable values. Which shows that most we observe then for balance of payment the value of standard deviation is (S. D 3. 70) which is quite high as compare to other variables which clearly shows that the response regarding balance of payment of not consistence.

Histogram :

4. 2. 14. 2. 24. 2. 34. 2. 4

Interpretation:

This above figures shows the graphical representation of the variables with the curve to check the normality of the response rate. This above histogram shows variables with the curve to check data is normally distributed or not according to response rate. Above figure 4. 2. 1 show response of GDP, Mostly data lie on option 8-9. Similarly small numbers of data were lie on very low. Data shows data is not normally distributed bell curve also shows data normality. The figures 4. 2. 2 show the graphical representation of the bars that is showing the response of the respondent’s infrastructure. Most of the data lies in the option 3 – 4. The bars in the histogram from a distribution (pattern or curve) that is similar to not normal, bell shaped curve. Thus, frequency distribution of the infrastructure is normal. The figures 4. 2. 3 show the graphical representation of the bars that is showing the response of the respondents regarding balance of payment. Most of the data lies in the option -6to -2. Similarly small numbers of data were lie very low. The bars in the histogram from a distribution (pattern or curve) that is similar to not normal, bell shaped curve. Thus, frequency distribution of the balance of payment is approximately not normally distributed. The figures 4. 2. 4 show the graphical representation of the bars that is showing the response of the respondents regarding political instability. Most of the data lies in the option . 90to 1 Similarly small numbers of data were lie very low. The bars in the histogram from a distribution (pattern or curve) that is similar to not normal, bell shaped curve. Thus, frequency distribution of the political instability is approximately not normally distributed.

Scatter plot:

Interpretation:

The output shows a scatter plot matrix shows the four scale variables i. e. infrastructure, balance of payment and political instability the overall pattern of dots show that it is diagonal upward straight regression line showing positive relationship between all variables infrastructure, balance of payment and political instability a positive relationship.

Correlation

Correlations

Political instabilityBalance of paymentinfrastructurePolitical instabilityPearson Correlation1. 934*. 988**Sig. (2-tailed). 020. 001N555Balance of paymentPearson Correlation. 934*1. 943*Sig. (2-tailed). 020. 016N555InfrastructurePearson Correlation. 988**. 943*1Sig. (2-tailed). 001. 016N555*. Correlation is significant at the 0. 05 level (2-tailed). To verify if there was a statistically significant association between and infrastructure, balance of payment and political instability a correlation matrix was computed all the variables were approximately normal there is linear relationship between them hence fulfilling the assumption for Pearson correlation. r calculated of balance of payment and political instability is r=. 934, p value is less than 0. 05 that’s shows there is positive relationship balance of payment and political instability according to Cohen’s (1988) the effect size is large that’s shows there is strong relationship. Similarly the infrastructure and political instability value of r=. 988, p=. 001 is shows the highly significant and strong relationship in the same way the relationship between infrastructure and balance of payment is strong and highly significant the value of between two variable is r=. 943, p=. 000. First hypothesis accept there is relationship between balance of payment and political instability its means H1 accept and H0 is rejected in the same way second hypothesis there is relationship between infrastructure and political instability H1 is accept and H0 is rejected and last also there is relationship between infrastructure and balance of payment means H1 is accepted and H0 is rejected.

Regression:

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate1. 827a. 684. 579. 76504a. Predictors: (Constant), infrastructure

ANOVAb

ModelSum of SquaresdfMean SquareFSig. 1Regression3. 80813. 8086. 505. 084aResidual1. 7563. 585Total5. 5634a. Predictors: (Constant), infrastructureb. Dependent Variable: GDPThe value of the coefficient of determination (R2) is . 57. This shows that the relation between the observed values of infrastructure and the fitted value of the GDP 57% percent. The adjusted coefficient of determination (adj. R2) shows is adjusted for the degrees of freedom. The value of F-statistic is statistically significant at less than five percent that exhibits that in the estimated model at least one of the partial regressions coefficients is not different from zero.

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientsTSig. BStd. ErrorBeta1(Constant)28. 3698. 1543. 479. 040infrastructure-5. 3172. 085-. 827-2. 551. 084a. Dependent Variable: gdpThe coefficient table presents the results of the regression analysis. The objective of the regression in this study is to find such an equation that could be used to find the factor that affect on GDP of Pakistan . The specified regression equation takes the following form: GDP = C + infrastructure X1GDP= 28. 36 -5. 31 X1The results show the relationship among the independent and dependent variables, infrastructure not significantly affect the GDP. Alternative hypothesis in GDP and infrastructure is rejected as the significance level is greater than o. o5 which means that there is no significant relationship between GDP and infrastructure.

Simple regression:

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate1. 723a. 522. 363. 94115a. Predictors: (Constant), balanceofpayment

ANOVAb

ModelSum of SquaresdfMean SquareFSig. 1Regression2. 90612. 9063. 281. 168aResidual2. 6573. 886Total5. 5634a. Predictors: (Constant), balanceofpaymentb. Dependent Variable: gdpThe value of the coefficient of determination (R2) is . 36. This shows that the relation between the observed values of balance of payment and the fitted value of the GDP 36% percent. The adjusted coefficient of determination (adj. R2) shows is adjusted for the degrees of freedom. The value of F-statistic is statistically significant at less than five percent that exhibits that in the estimated model at least one of the partial regressions coefficients is not different from zero.

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientsTSig. BStd. ErrorBeta1(Constant)6. 690. 65110. 275. 002Balanceofpayment-. 229. 126-. 723-1. 811. 168a. Dependent Variable: gdpThe coefficient table presents the results of the regression analysis. The objective of the regression in this study is to find such an equation that could be used to find the factor that affect on GDP of Pakistan . The specified regression equation takes the following form: GDP = C + balance of payment X1GDP= 6. 69 -. 229 X1The results show the relationship among the independent and dependent variables, balance of payment not significantly affect the GDP. Alternative hypothesis in GDP and balance of payment is rejected as the significance level is greater than o. o5 which means that there is no significant relationship between GDP and infrastructure.

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate1. 826a. 683. 577. 76694a. Predictors: (Constant), politicalinstability

ANOVAb

ModelSum of SquaresDfMean SquareFSig. 1Regression3. 79913. 7996. 458. 085aResidual1. 7653. 588Total5. 5634a. Predictors: (Constant), politicalinstabilityb. Dependent Variable: gdpThe value of the coefficient of determination (R2) is . 57. This shows that the relation between the observed values of political instability and the fitted value of the GDP 57% percent. The adjusted coefficient of determination (adj. R2) shows is adjusted for the degrees of freedom. The value of F-statistic is statistically significant at less than five percent that exhibits that in the estimated model at least one of the partial regressions coefficients is not different from zero.

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig. BStd. ErrorBeta1(Constant)10. 5271. 2058. 733. 003Politicalinstability-3. 7651. 481-. 826-2. 541. 085a. Dependent Variable: gdpThe coefficient table presents the results of the regression analysis. The objective of the regression in this study is to find such an equation that could be used to find. the factor that affect on GDP of Pakistan. The specified regression equation takes the following form: GDP = C + political instability X1GDP= 10. 52-3. 765 X1The results show the relationship among the independent and dependent variables, political instability not significantly affect the GDP. Alternative hypothesis in GDP and balance of payment is rejected as the significance level is greater than o. o5 which means that there is no significant relationship between GDP and infrastructure.

Multi regression:

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate1. 848a. 718. 711. 25196a. Predictors: (Constant), infrastructure, balance of payment, political instability

ANOVAb

ModelSum of SquaresDfMean SquareFSig. 1Regression3. 99631. 332. 850. 003aResidual1. 56711. 567Total5. 5634a. Predictors: (Constant), infrastructure, balance of payment, political instabilityb. Dependent Variable: GDP

Interpretation:

The value of the coefficient of determination (R2) is . 71. This shows that the relation between the observed values of political instability and the fitted value of the GDP 71% percent. The adjusted coefficient of determination (adj. R2) shows is adjusted for the degrees of freedom. The value of F-statistic is statistically significant at less than five percent that exhibits that in the estimated model at least one of the partial regressions coefficients is different from zero anova value show the model is good fit because its less than 0. 05.

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig. BStd. ErrorBeta1(Constant)32. 93984. 844. 388. 764Political instability-1. 84015. 997-. 404-. 115. 927Balance of payment. 167. 507. 528. 330. 797Infrastructure-5. 95124. 338-. 926-. 245. 847a. Dependent Variable: GDPThe coefficient table presents the results of the regression analysis. The objective of the regression in this study is to find such an equation that could be used to find. The factor that affect on GDP of Pakistan. The specified regression equation takes the following form: GDP = C + political instability X1+balance of payment X2+ infrastructureX3+E1FDI= 32. 97-1. 84 X1+. 167X2-5. 95X3+E1The results show the relationship among the independent and dependent variables political instability, balance of payment and infrastructure not significantly affect on GDP. Alternative hypothesis in instability, balance of payment and infrastructure and GDP is rejected because significance level greater than 0. 05.

Chapter 5

Discussion and conclusion

The present study was done to check The factor that affect on GDP of Pakistan. For this purpose the present study used quantitative research method to check the proposed model in the context of Pakistan and the present study used the last five years data from WDI. The present study collected the data by using WDI on the variables of the study from the sample of the study. The study selected the infrastructure, political instability and balance of payment as the independent variables while GDP as the dependent variables of the study. The literature review of the present study has reported the theoretical evidence from past studies which confirmed the factor that affect on GDP of Pakistan. The literature also provided evidences from previous studies which have been done to check this relationship but in Pakistan specifically in GDP, this linkage still has a gap which was filled by the present study. So the present study attempted to enhance the literature on the GDP. In the present study descriptive analysis used the descriptive statistics to find the maximum and minimum range of data and also to find the mean and standard deviation of data through frequency tables as well as histogram to check normal distribution curve. To check the acceptance or rejection of hypothesis and check the relationship between variables the present study used inferential analysis. In inferential analysis the present study tested the relationship among the variables of the study. After observing the descriptive analysis, histograms, scatter plot matrix, and the correlations, the regression has been used for further analysis. The factor that affect on GDP of PakistanThe empirical evidences showed that infrastructure has strong correlation with the political instability and balance of payment. The results of correlation also confirmed that balance of payment has strong correlation with the political instability. The results of regression analysis showed that the infrastructure has significant and positive relationship with the balance of payment. Since Pakistan is a developing country and the topic of research has little evidence from developing countries so this study helped to enhance the evidence from the developing countries context. The present study helps the finance managers to build strategies keeping in mind infrastructure, political instability and balance of payment which can result in GDP in Pakistan. Despite of the many benefits of the study, there are several limitations of the study. First, the study is only limited to the on three variable who effect of Pakistan because it collected the data only from the five years, thus the results may not be valid to the other country. The results of the present study may not be valid to the other developing countries as the present study has evidence from the developing country of Pakistan.

5. 2 Conclusion

The present study concluded that infrastructure, political instability and balance of payment resulted in better performance of the country by positively effecting its GDP of Pakistan. So the economists and higher authorities of Pakistani government sector must use infrastructure, political instability and balance of payment to take maximum output from the country.

5. 3 Suggestion and Recommendation:

The existing literature suggests that there are links between the infrastructure, political instability and balance of payment with GDP. But this study denied the result of previous researches because regression analysis shows there is not positive relationship between infrastructure, political instability and balance of payment with GDP of Pakistan.