Determinants of the Age at First Marriage among the University Teachers in Algeria: A mix Methodology Approach

This study examines the determinants of age at first marriage among the university teachers in Algeria. A Weibull proportional hazard and multivariable logistic regressions models were used on data set from a survey covering a sample of 682 teachers. The findings revealed that: The median ages at first marriage are: 36 and 39.4 years for men and women, respectively, with a gap of 3.1 and 8 years from the general population. For: birth order, teacher specialty, study place and working before joining the academic staff all together explain a very small percent of the variation of the age at marriage; in contrast, Housing, salaries’ level, and a suitable partner were the hidden factors determining the age at marriage. As policy implications, policy-makers have to focus on these factors in order to help teachers to satisfy this biological and sociological need. JEL Classification: C4; J12

Vulnerability to Climate Change and Socio-Economic Factors: A Comparison of Selected Districts of Punjab

This study analyzes ten districts of the province Punjab of Pakistan to investigate and compare the vulnerability of selected districts. Total Three sub-groups (socio-economic variables, adaptive capacity, bio-physical variables) are generated by using the data from Pakistan Social & Living Standard Measurement Survey (PSLM) and Pakistan Meteorological Department of the years 2014-15, to calculate total vulnerability. Using primary variables at the district level, this study determines each district’s rural and urban areas' total vulnerability score. The results show that few districts, e.g., Rawalpindi has 0.74 total vulnerability score out of 1, are highly vulnerable compared to other districts despite having a better socio-economic situation. On the other hand, few districts, like Multan, have a low vulnerability to climate change and socio-economic factors. Keywords: CO2, socio-economic, bio-physical, environment, Vulnerability. JEL Classification Codes: Q3, O13, P28.

Fiscal Response to Terrorism in Pakistan: The Role of Institutions

This study empirically estimates the fiscal consequences of terrorism in Pakistan by using annual time series data from 1984 to 2016. By employing the autoregressive distributed lag (ARDL) technique, the study has gauged the impact of terrorist incidents on two important facets of fiscal policy, namely, tax revenue and defense spending. The results reveal that terrorism has detrimental ramifications for fiscal policy in Pakistan. Specifically, on the one hand, an increase in terrorist incidents tends to bring a fall in tax revenue while on the other hand, they induce a rise in defense outlays, thus deteriorating both fronts of the fiscal position. Notably, the moderating role of institutional quality appears significant and indicates that institutional quality has not only a significant direct impact on fiscal policy, but it also helps in completely mitigating (reducing) the harmful impact of terrorism on defense spending (tax revenue) in Pakistan. These findings suggest that there is a need to take appropriate steps for strengthening institutional setup to control the fallouts of terrorism on fiscal behavior of the government of Pakistan. Keywords: Terrorism; Tax Revenue; Institutional Quality; ARDL JEL Classification: E62; H2; E02; H5; F35

Impact of Globalization on Major Macroeconomic Variables: Empirical Evidence from Pakistan

Globalization is a multi-dimensional phenomena with profound impact on different aspects of the modern world, including economic, social, political, cultural, environmental, and geographical. This study is an attempt to analyze how various components of globalization, i.e., trade openness, financial liberalization and labor mobility impacts the economic dynamics of a developing country affecting the performance of macroeconomic variables including the budget deficit, inflation and economic growth. In this study, we use the terms trade openness and liberalization along with financial openness, financial liberalization and financial development interchangeably. The purpose is to capture the overall impact irrespective of nature as nature may lead to contradictory results. Furthermore, the labour flows give due attention as human capital is an inevitable avenue for the effective and sustainable growth of any country. It is noticed that various global factors effect budget deficits, inflation and economic growth with varying intensities depending upon the size and dynamics of the economy. The empirical analysis involves the time series data of Pakistan from 1973 to 2014. The autoregressive distributed lag (ARDL) methodology is used to obtain the results and policy related suggestions.

Educational Expansion and Economic Growth Nexus in Pakistan: Instrumental Variable Approach

This study examines the relationship between economic growth and the expansion of education in Pakistan. The study utilizes 2SLS and GMM estimators to estimate the growth equations with a potential issue of endogeneity using data for the period 1973-2018. Empirical results show that educational expansion at the primary and secondary level effect economic growth positively. The evidence is quite compelling that the effect of educational expansion on economic growth is low due to the poor quality of education. Also, the lower effect of physical capital is due to lower human capital embodied in the labor force. Keywords: human capital; economic growth; GMM; Endogeneity; Pakistan. JEL Classification: O47, I21, C26

Tracing Return and Volatility Spillover Effect between Exchange Rate and Pakistan Stock Exchange Index

The volatility spillover is broadly measured as the transmission of variability from one financial market to other markets. This study explores the spillover effect between the newly emerged index of the Pakistan stock exchange (PSX) and exchange rate by using the newly proposed alternative methodology by Ghouse et al. (2019) and GARCH model. Furthermore, the index under study is more concise in its composition than other readily used indices. The study finds shreds of evidence for the bidirectional spillover effect between PSX and exchange rate, which will be helpful for central policy makers and markets players in designing effective policy frameworks. Keywords: ARDL; GARCH; spillover effect

The Role of Top Management as a Moderator on Project Success during Project Life Cycle

The paper identifies the role of top management as a moderator during planning, monitoring, controlling, and evaluation phases for the success of a project. This study also discusses the novelties of the coordination between role of top management and legitimate power of project manager as significant impact on project performance and success during project life cycle phases. The instrument is adapted to measure planning, monitoring, controlling, evaluation, the role of project manager, project performance, project success, and the role of top management. Managers are targeted for data collection from the construction sector, education sector, and IT sector for the analysis. The findings show that coordination between variables as well as the role of a project manager is like a bridge between top management and other team members in four phases of project life cycle (planning, monitoring, controlling, and evaluation) for ultimate success. This study has a significant advantage for the organization and industries before implementing any project as it will be helpful for the top management to give authority and responsibility to the project managers while considering the scope of the project. For academia, this study helps to enhance the knowledge area of project management by introducing coordination management while discussing the other knowledge areas of project management. Keywords: project planning, project monitoring, project controlling, project evaluation, role of project manager, project performance, project success. Jell Classification: H43; O22

Forecasting COVID-19 Pandemic and Capital Market Efficiency in Africa

Despite a large and growing list of studies on COVID-19 across space and time and on heterogeneous social, environmental and welfare issues, the empirical relations on the consequences of COVID-19 pandemic and Africa’s market capitalization objectives remain dimly discerned. Even more worrisome is Africa, where the condition for growth and development has not been adequately fulfilled. This structural ambiguity calls for a policy document that is evidence-based to reach conclusions to aid the containment, risk analysis, structures and features of the deadly and fast-spreading disease. This study employed negative binomial and the Poisson regression to establish the contemporaneous influence of COVID-19 pandemic on market capitalization capabilities in Africa. Health data from various reports of the World Health Organization (WHO) is regressed on the all-share index from World Development Indicators (WDI) to establish a clear line of thought. It is found that the growth of confirmed cases and attributable deaths are inversely related to the growth in market capitalization in Africa. The findings from this study show that Africa market capitalization is inversely related to total growth in the number of confirmed cases of COVID-19 and attributable COVID-19 deaths. This leads to the assertion that Africa’s capital market is fast nosediving in the time of COVID-19 due to global uncertainties caused by the pandemic. With no known cure or vaccine procedure discovered yet, the global uncertainty around the novel coronavirus disease will lead to approximately 0.56 percentage decrease in market capitalization in Africa. To this end, emphases must be laid on identifying and including non-traditional sources of financing strictly tied to projects that could encourage institutional investors. It is therefore equally imperative for Africa to form a formidable and integrated capital market among themselves. Keywords: market capitalization; COVID-19 pandemic, negative binomial Regression, poisson, Regression, Africa JEL Classification: C10, C31, G15, I12

Panel threshold regression model analysis of real effective exchange rate impact on the Arab Maghreb Union economic growth

The purpose of this article was to explain the asymmetry of real effective exchange rate (REER) impact on economic growth for the Arab Maghreb Union during the period 1980-2019. This work sought to measure the adjustment rate of the exchange rate policy towards its equilibrium levels, justifying the use of nonlinear modelling. The complexity of the exchange rate dynamics has led to the application of the Panel Threshold Regression Model to test the hypothesis testifying for its effect on domestic economic growth. The empirical results reveal that the REER shows opposite effects below and over the estimated threshold. This highlights the asymmetrical effect of unforeseen shocks on its volatility. JEL Classification: C33; F31; F43; O55; O57

Evaluation of Test Statistics for Detection of Outliers and Shifts

Existence of outliers and structural breaks having mutually unknown nature, in time series data, offer challenges to data analysts in model identification, estimation and validation. Detection of these outliers has been an important area of research in time series since long. To analyze the impact of these structural breaks and outliers on model identification, estimation and their inferential analysis, we use two data generating processes: MA(1) and ARMA(1,1). The performance of the test statistics for detecting additive outlier(AO), innovative outlier(IO), level shift(LS) and transient change(TC) is investigated using simulation strategy through power of a test, empirical level of significance, empirical critical values, misspecification frequencies and sampling distribution of estimators for the two models. The empirical critical values are found higher than the theoretical cut-off points, empirical power of the test statistics is not satisfactory for small sample size, large cut-off points and large model coefficient. We have explored confusion between LS, AO, TC and IO at different critical values(c) by varying sample size. We have also collected empirical evidence from time series data for Pakistan using 3-stage iterative procedure to detect multiple outliers and structural breaks. We find that neglecting shocks lead to wrong identification, biased estimation and excess kurtosis. JEL Classification Codes: C15, C18, C63, C32, C87, C51, C52, C82 AMS Classification Codes: 62, 65, 91, DI, 62-08, 62J20, 00A72, 91-08, 91-10, 91-11 62P20, 91B82, 91B84, 62M07, 62M09, 62M10, 62M15, 62M20