202 research outputs found

    FEASIBILITY OF BAY SALAM FINANCE: A SURVEY OF THE OPINIONS OF STAKEHOLDERS

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    The present study aims to explore the potential application of Bai Salam (forward sale agreement) as substitute financial instrument in the agriculture sector of Pakistan. The conclusion is drawn through a survey questionnaire from 300 farmers and bankers in a district of Punjab. For analysis, we use SPSS software and presented the results by using descriptive methods. This study overall concludes the banker’s and farmer’s awareness, willingness, risks, hurdles and the role of institutions in the Salam promotion. The majority of the farmers are not aware of the Salam contract because the Islamic bank’s branch network is limited to urban areas and there is no proper promotion campaign launched by the Islamic banks for awareness about Salaam among the farmers. Bankers are reluctant to finance the tenants, orchards due to more operational risk for the bank. Bankers opinion that small farmers do not have personal securities which is not a solid reason because half of the sampled farmers take a loan from the formal system if they can provide securities to conventional interest-based institution why they can’t provide securities to Islamic financial institutions? There is a vast market for the Islamic Banks if they sincerely pay their attention towards forward sale contracts. The concept applies to all areas of agriculture and livestock farming to overcome financing problems and boost production.

    Assessing Gains of stakeholders for Mega Project implementation: Learning from Beneficiary Assessment of Lahore Ring Road Project, Pakistan

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    The population is increasing rapidly globally, and urban expansion of the cities has become an extensive trend in developing nations. Urban expansion patterns, such as transportation structure and road networks, affect transportation planning. This research was conducted on a mega project in Lahore city of Pakistan, i.e., the Lahore Ring Road (LRR) project. Limited research focused on the beneficiary assessment of the road project, and this research was carried out to fill this research gap. This research aims to evaluate the beneficiary assessment of DHA Phase 8 and Halloki Settlement along the Lahore Ring Road. The simple Random Sampling technique was used to conduct the household survey in the study area. This study concluded that most of the residents did not modify their houses nor increase the built-up area and height after the introduction of the project. This study inferred that the rental potential was high at some locations and low at old existing settlements. This research further concluded that community participation was ignored, and public facilities were not improved in the study area. But a project of LRR was very much beneficial and alive for the residents of Lahore city. Community participation should be enhanced in such types of megaprojects, and allied facilities in the nearby community should be upgraded. This research will be helpful for policymakers, urban planners, transportation planners, development authorities, and other stakeholders in planning future road projects in the country

    On Stability of Money Demand Model in Pakistan: A Super Exogeneity Testing Approach Using Indicator Saturation

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    The study attempts to test the stability of the money demand (M2) model in the case of Pakistan under the shade of super exogeneity testing procedure with an amalgamation of recently developed techniques of selecting breaks or location shifts (data driven) using Indicator Saturation like; Impulse Indicator Saturation (IIS), Step Indicator Saturation (SIS) and Trend Indicator Saturation (TIS). The estimated Vector Error Correction Model (VECM) of money demand (M2) with Real Income, Inflation Rate, short and long term interest rates, Financial Innovation and Financial Development; reveals that the parsimonious model is structurally invariant and remains super exogenous to the relevant class of interventions for parameters of interest during the stipulated period (1972-2018) in Pakistan and hence can be used for policy purposes. Consequently, Lucas critique refuted in the case of Pakistan

    Modelling the nexus of carbon dioxide emissions, economic growth, electricity production and consumption: Assessing the evidence from Pakistan

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    The economy of Pakistan has constantly been plunged due to its severe electricity shortages over the last 2 decades and persistently faces challenges in revamping its electricity supply network. The purpose of this research was to assess the causal relationship between carbon dioxide emissions (CO2), combustible renewable and waste (CRW), electric power consumption (EC), electricity production from coal (EPC), hydroelectric (EPH) and natural gas (EPN) sources, energy use (EU) and gross domestic product (GDP). The scope of this research included Pakistan’s annual time series data from 1971 to 2014. This study employed Autoregressive Distributed Lag (ARDL) bound testing analysis to determine the long-term and short-term correlations among all research parameters. This research also conducted Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests to evaluate the stationarity existence among dependent variable and independent variables. The outcomes of the fully modified least squares (FMOLS), dynamic ordinary least square (DOLS) and canonical co-integrating regression (CCR) estimators showed that coefficients of EC, EPH and GDP all were a significantly positive relationship with CO2 emissions, while the coefficients of CRW, EPC and EU were negatively significant, respectively. Furthermore, the outcomes from the short-run analysis revealed that the error correction term value was -0.8668, which indicates that from short-run to long-run equilibrium, the adjustment of the deviation of CO2 emission is by 86.68 percent annually. Moreover, the diagnostic results also demonstrated that the model employed in this research is stable and reliable. Pakistan was selected in this research work because of the deficit of power and if environmental degradation continues unchecked, it will eventually affect the state’s economic growth and CO2 emissions. The study’s primary policy recommendation is that government energy policymakers in Pakistan who create the environment framework in should pursue conservative energy measures as such measures will not negatively impact economic growth

    Growth of Albizia lebbeck (L.) Benth. (Mimosaceae) in Polluted Soils of Landhi and Korangi Industrial Areas of Karachi, Pakistan

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    Growth of Albizia lebbeck was observed in the polluted soils from towel, garment, rubber and ply board factories in the vicinity of Landhi and Korangi industrial areas of Karachi. Growth of A. lebbeck was reduced in most of the industrial area soils as compared to the control soil from Karachi University campus. The rubber factory soil reduced all the growth parameters as compared to the control soil. Percentage of soil pollutants (total soluble salts and available sulfate) in all of the industrial area soils was higher than in the control area soil. Percentage of coarse sand, calcium carbonate, total soluble salts, available sulfate, and chromium was higher in soil of rubber factory then in the control area soil whereas percentage of water holding capacity, organic matter and zinc was lower in soil from rubber factory than in the control area soil. This showed that the soil of industrial areas of Landhi and Korangi particularly from rubber factory and ply board factory was contaminated by the pollutants in the area and drastically affected the plant growth. The findings of this research could be helpful in monitoring and controlling the pollutant levels in soils of the industrial areas. Such information could also be useful for landscaping and urban planning

    Choice of Spectral Density Estimator in Ng-Perron Test: Comparative Analysis

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    Ng and Perron (2001) designed a unit root test which incorporates the properties of DF-GLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of negative moving average. However, the performance of test depends heavily on the choice of spectral density estimators used in the construction of test. There are various estimators for spectral density available in literature, having crucial impact on the output of test however there is no clarity on which of these estimators gives optimal size and power properties. This study aims to evaluate the performance of Ng-Perron for different choices of spectral density estimators in the presence of negative and positive moving average using Monte Carlo simulations. The results for large samples show that: (a) in the presence of positive moving average, test with kernel based estimator give good effective power and no size distortion (b) in the presence of negative moving average, autoregressive estimator gives better effective power, however, huge size distortion is observed in several specifications of data generating proces

    The modified R a robust measure of association for time series

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    Since times of Yule (1926), it is known that correlation between two time series can produce spurious results. Granger and Newbold (1974) see the roots of spurious correlation in non-stationarity of the time series. However the study of Granger, Hyung and Jeon (2001) prove that spurious correlation also exists in stationary time series. These facts make the correlation coefficient an unreliable measure of association. This paper proposes ‘Modified R’ as an alternate measure of association for the time series. The Modified R is robust to the type of stationarity and type of deterministic part in the time series. The performance Modified R is illustrated via extensive Monte Carlo Experiments

    Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis

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    Ng and Perron (2001) designed a unit root test, which incorporates the properties of DFGLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of a negative moving average. However, the performance of the test depends heavily on the choice of the spectral density estimators used in the construction of the test. Various estimators for spectral density exist in the literature; each have a crucial impact on the output of test, however there is no clarity on which of these estimators gives the optimal size and power properties. This study aims to evaluate the performance of the Ng-Perron for different choices of spectral density estimators in the presence of a negative and positive moving average using Monte Carlo simulations. The results for large samples show that: (a) in the presence of a positive moving average, testing with the kernel based estimator gives good effective power and no size distortion, and (b) in the presence of a negative moving average, the autoregressive estimator gives better effective power, however, huge size distortion is observed in several specifications of the data-generating process

    Choice of Spectral Density Estimator in Ng-Perron Test: Comparative Analysis

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    Ng and Perron (2001) designed a unit root test which incorporates the properties of DF-GLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of negative moving average. However, the performance of test depends heavily on the choice of spectral density estimators used in the construction of test. There are various estimators for spectral density available in literature, having crucial impact on the output of test however there is no clarity on which of these estimators gives optimal size and power properties. This study aims to evaluate the performance of Ng-Perron for different choices of spectral density estimators in the presence of negative and positive moving average using Monte Carlo simulations. The results for large samples show that: (a) in the presence of positive moving average, test with kernel based estimator give good effective power and no size distortion (b) in the presence of negative moving average, autoregressive estimator gives better effective power, however, huge size distortion is observed in several specifications of data generating proces
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