Thepros and cons of the infrastructure are vigorously debated but little is knownconclusive about its relationship to economic growth. Different theoreticalpremises, supported by different empirical examples, imply oppositepredictions. Lots of works have been done around this area of research. Here wemention work already done.Esfahani and Ramirez (2003) analyzedstructural model of infrastructure and output growth. They used growth rate ofGDP per captia as a dependant variable and population growth rate, log ofinitial telephone per captia used as independent variables. Cross countryestimation of the model indicate that the contribution of infrastructureservices to GDP is substantial and, in general, exceeds the cost of provisionof those services.
Malik, (2009) described the infrastructure of South Asia andEast Asia. In her model, she used GDP per Capita as a dependent variable andinflation, GDP ratio and political stability as independent variables. Applyingthe fixed-effect model, the study found a positive and significant impact ofprivate participation in the energy and telecom sectors on GDP per capita andcurrent expenditures. Navarro andBerkeley(2010) in their research examined an infrastructure experiment in Mexicoto evaluate the impact of street pavement on housing values and householdoutcomes. The data for this study is pre- andpost-intervention rounds of a dedicated household survey.The baseline surveywas held in February-March 2006.
Sahoo and Dash (2010) investigated the role ofinfrastructure in promoting economic growth in China. They took the secondary dataand data source are World Bank and international financial corporation. Theyused GDP as a dependent variable and investment in private sector, publicsector, labor force and human capital as independent variables. Ishaq and Mushtaq (2011) described public investment onrural infrastructure not only increases agricultural productivity but alsoreduces poverty. They used TFP (total factor productivity) as dependantvariable and AGRI (aggregate expenditure on the crops), livestock and RHE(expenditures on rural health and education) as independent variables.
Theresults showed that public investment on physical infrastructure and socialinfrastructure has contributed significantly and positively to TFP. The studysuggested that more resources should be diverted towards the development ofphysical and social infrastructure that will improve the agriculturalproductivity as well as reduce the rural poverty.Faridi et al.
(2011) described that Transport andcommunication sector having significant influence on economic growth. They tookGDP as dependant variable labor transportation and commutation as independent variables. To check theeffect of transportation and communication on economic development they usedSolow growth model.
Haider et al. (2012) interpreted the impact ofinfrastructure on economic growth of Pakistan. They used GDP as a dependentvariable and GFCF (gross fixed capital formation) and TGE (total generation of electricity) used as independentvariables, time series data has been collected from 1972 to 2009. Then theyapplied Ordinary Least Square (OLS) to find short-run relation betweenvariables and found that infrastructure is positively and significantlycontributing in Pakistan.
The study suggested that government and policy makersshould focus for the development of infrastructure.Sohail et al. (2012) analyzed the impact of natural disasteron economic growth in Pakistan. They used GDP as a dependent variable andgrowth in agriculture production and growth in industrial production asindependent variables. By using time series data from 1975 to 2010, ADF testwas used to test the stationary of the series and then OLS method was appliedto estimate the impact of natural disasters.
Soneta et al.(2012) explained that infrastructure is basicphysical and organizational structures needed for the operation of society andfacilities necessary for an economy to function. They used manufacture growthas a dependent variable and log of transportation and communication, log ofelectricity and gas distribution as independent variables.