Human Capital and Foreign Direct Investment: Lessons for Pakistan

Foreign direct investment plays a key role in economic development of all countries. Because of its enormous importance, a large number of empirical studies has focused on finding out the factors determining foreign direct investment. Level of human capital development is one of the major factors influencing foreign inflows. However, earlier studies examining impact of human capital on foreign investment inflows has majorly used literacy rate, school enrolment and government spending on education as its proxies. This paper also examines the impact of human capital as determinant of foreign direct investment. Contrary to earlier empirical studies, it uses cognitive skills as proxy for human capital. Cognitive skills measure the quality of education instead of literacy rate or government spending on education as proxy for human capital. Results indicate that human capital has significant positive effect on foreign direct investment for sample countries. This result is robust to disaggregated data for developed and developing countries. Other factors that determine foreign direct investment inflows are inflation, capital account openness, trade account openness and real income. Based on empirical results, it is recommended that the relevant authorities must make human capital as part and parcel of strategies aimed at augmenting economic growth in the country. There is also a lesson for a developing country like Pakistan to focus more on quality of education instead of school enrolment or education spending for attracting foreign direct investment to boost economic activity (J.E.L Classification Codes: O4, O15, P22).

Performance Improvement of Wireless Cellular Technology Using Adaptive Array System

The objective of this dissertation is to investigate and design adaptive beamforming algorithms in order to improve the performance of wireless cellular technology in spatial domain. For this purpose, blind and non-blind beamforming concepts and related algorithms are investigated; Least Mean square (LMS), Constant Modulus Algorithm (CMA) and others. These algorithms suffer from optimization problems like gain enhancement, interference rejection, high power transmission, bit error rate (BER), minimization of mean square error (MSE) and rate of convergence which undermines their performance in the application of smart antenna array system. In view of these deficiencies, non-blind technique using LMS and MUSIC algorithms is evaluated for selection of parameters for further analysis. A new algorithm namely Bessel Least Mean Square (BLMS) is proposed. Its performance is then evaluated and compared with LMS in order to determine its efficiency in terms of array gain, MSE, BER and convergence performance based on the chosen parameters. Performance improvement is achieved by proposed algorithm over the conventional LMS algorithm. The improvement in BLMS is attributed by introducing a non-uniform step size. This non-uniform step size is obtained from the interaction of Bessel and step size functions. The Bessel function of the first kind has inherent monotonically decreasing property which generates coefficients equal to the number of elements that helps the proposed BLMS algorithm in convergence effectively as compared to LMS algorithm that is based on a constant step size. Further, the analysis of blind technique using CMA and MUSIC algorithms has similarly been investigated for the same selected parameters as above. For blind beamforming, novel algorithms named as Kaiser Constant Modulus Algorithm (KCMA) and Hamming CMA (HAMCMA) using window techniques are proposed and implemented. Their performance is then compared with CMA in terms of array gain, MSE and BER. The KCMA has shown improved performance and this improvement in KCMA is justified in terms of facilitating independent control of the main lobe width and ripple ratio. The HAMCMA, based on fixed type window function has shown better xx iv results in terms of array gain and sidelobe level (SLL) but lacks in BER performance as compared to CMA. The reduction in SLL by these blind beamforming algorithms signifies that using the proposed methods the interferences are very low. Finally, BLMS with Automatic Gain Control (AGC) is proposed by making its step size variable which can update itself from signal array vector. The real model of BLMS is developed and tested for its efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format into the MATLAB workspace and compared with real model of LMS in terms of gain and MSE. From the results presented in the thesis, it is concluded that the proposed algorithms lead to improve in the performance as compared to LMS and CMA algorithms and can be utilized efficiently for further enhancement of wireless cellular technology.