This paper attempts to model a real demand for money function of Pakistan. For this purpose we apply bounds test based cointegration technique using the time series data for the period 1973 to 2010. Our findings included three determinants: 1) real income and 2) foreign exchange contain positive relation as well as for both long run and short run dynamics they are the most significant factors of real demand for money. While we found real demand for money is negatively affected by 3) call money rate (is proxied by interest on deposit). However being in a short-run dynamic specification, money demand is found important with the elasticities of real income, exchange rate and call money rate being much smaller in the short-run than in long-run. Stability tests of the paper do not show any serious structural change in the model. As for both CUSUMSQ and CUSUM statistics, showing the critical value line within the bounds that present the model is stable. This model strongly recommends the real demand for M2 is an important monetary aggregate in terms of policy implications of our results including the suitability of the model in Pakistan. Keywords 1) Real income 2) Foreign exchange rate 3) Call money rate 4) Call money rates 5) Interest rate 6) Autoregressive distributed lag (ARDL) 7) GDP deflator 8)

Estimating a model of foreign direct investment has been one the central elements of FDI policy makers in Pakistan. This paper attempts to model, Determinants of Foreign Direct Investment Inflow in Pakistan: A Time Series Analysis with Auto Regressive Distributive Lag (ARDL) approach using the time series data for the period 1977 to 2010. However in a specification, FDI is found important with the elasticity of GDP growth rate 10% level of significance and infrastructure at 1% level of significance. These factors show do not show better performance in short-run dynamics like only infrastructure is elastic with FDI at 1% level of significance. Stability tests of the paper do not contain any serious structural change in the model as case of and CUSUM and CUSUMSQ statistics show the critical value lines lying inside the bounds, presenting the model is stable.