Dynamic Effects of Changes in Government Spending in Pakistan’s Economy.

This study analyses the effects of changes in government spending on aggregate economic activity and the way these effects are transmitted in case of Pakistan for the period 1971-2008. To analyse the transmission mechanism of government spending innovations, the Vector Autoregressive Model is estimated for following five variables: government spending per capita, GDP per capita, consumption per capita, debt to GDP ratio, long term interest rate and real exchange rate. The consumption and output respond negatively to the innovation in government spending which is consistent with the standard neoclassical model. The interest rates increase in the face of expansionary fiscal spending. As government debt builds up with fiscal expansion, the rising risk of default or increasing inflation risk reinforce crowding out through interest rates. The real exchange rate tends to appreciate in response to rise in government spending. This finding is according to the open economy literature and also with the conventional literature. JEL classification: E21, E62, E63 Keywords: Government Spending, Vector Autoregressive Model, Impulse Response Function, Neoclassical Mode

THE IMPACT OF MACROECONOMIC VOLATILITY ON STOCK RETURN VOLATILITY: EVIDENCE FROM PAKISTAN STOCK MARKET

This study examines the impact of macro-economic volatilityon stock return volatility for fifty stocks listed at the Karachi StockExchange using monthly data from July 1998 to June 2014. Themacro-economic variables included in the analysis are market return,industrial production, inter-bank call money rate, term structure ofinterest rate, money supply, exchange rate and the inflation rate. Theresult of significant autoregressive process suggests existence ofvolatility persistence. The industrial production has a negative effecton stock market volatility and the volatility of exchange rate capturesthe external sector volatility and has a positive effect on stock returnvolatility. The increased variation in money supply and inflationmake stock returns more volatile and an unexpected change in callmoney rate and the term structure of interest rate has the oppositeeffect on stock returns volatility. This leads to the conclusion thatstock prices fluctuations in Pakistan are influenced by financial andeconomic variables’ uncertainty. Therefore, investors, authorities andpolicy makers are needed to take into account th

Microfinance Institutions and Poverty Reduction: A Cross Regional Analysis

The alleviation of poverty is one of the most debated issues among the academicians and policy makers. From 1950s to 1980s the poverty reduction program has been based on increase the participation of poor into the economy by better macroeconomic performance. Though the poor part of population mostly engaged in informal sector1 is identified by researchers but has not become the part of economic models and government policy [Robinson (2001)]. Poverty reduction has been institutionalised in 1944 when World Bank was set up. The World Bank worked through governments and institutions by giving loans to developing countries called structural-adjustment programmes. These programmes were highly unsuccessful, created dependence on aid with little help to poor part of societies [Murduch (1999) and Diop, et al. (2007)]

Forecasting performance of capital asset pricing models in case of Pakistani market

This study empirically tests the conditional CAPM, conditional consumption CAPM and conditional multifactor CAPM model with individual stocks traded at Karachi Stock Exchange (KSE), the main equity market in Pakistan for the period 1993-2004. The ability of conditional CAPM models in forecasting asset returns is assessed through predictability of excess return for the period 2005-2006. The results show that the macroeconomic variables that capture business cycle fluctuations are better in explaining the cross-section variation in expected returns, they are found to have better forecasting ability for out-of-sample stock returns in case of Pakistani Market. The evaluation of forecasting ability of the conditional asset pricing models shows that the forecasting power of conditional multifactor CAPM is relatively better compared to conditional CAPM model and conditional consumption CAPM models. It follows, therefore, that the business cycle variables provide useful information for predicting the future direction of stock prices. These variables include market return, call money rate, term structure, industrial production growth, inflation rate, foreign exchange rate and growth in oil prices

Event Study and Impulse Indicator Saturation Analysis to Assess Reaction of Terrorist and Political Events: Evidence from Oil and Gas Sector of Pakistan

The objective of this study is twofold, first, to assess the impact ofterrorist attacks and political events on returns and volatility oil and gassector of Karachi Stock Exchange from the period of 2004 to 2014.Second, to compare the results of these events applying event studymethodology, event dummy analysis and impulse indicator saturation.Results indicate that the oil and gas sector reacts on the occurrence ofterrorism and political events and the results of two methodologiesevent study and event dummy analysis are almost similar. However,impulse indicator saturation is able to provide better results incomparison to event study and event dummy analysis because as itcaptures all breaks and co-breaks within a sample period,moreover it clearly helps in defining rebounding period of the market. JEL Classification Codes: G12, G1

The Response of the Pakistani Stock market to a Cataclysmic Event

This study has examined the reaction of Pakistani stock market to earthquake of October 8, 2005 and its impact on the price, volume and volatility behavior of sixty firms listed on Karachi Stock Exchange (KSE) The event study methodology is adopted to assess the KSE response to this unforeseen disaster and result shows that it quickly rebounded. The market displayed amazing resilience by being effected less severely than it was expected by bouncing back following its initial level because the market was already in recession after mi-March 2005 decline. As regards the firm level activities, the analysis indicates that the increase in the return and volume of cement, steel, food, chemicals and pharmaceuticals and banking stocks indicates that individual has expectation for the upcoming demand of investment in these sectors. Furthermore there is no significant increase in the volatility because the investors take lessons from the crash of March 2005 and seem certain about the future outlook. These findings support the hypothesis that Pakistani market is reactive to unanticipated shocks however, it is resilient and it recovers soon from the catastrophic shock

The Response of the Pakistani Stock market to a Cataclysmic Event

This study has examined the reaction of Pakistani stock market to earthquake of October 8, 2005 and its impact on the price, volume and volatility behavior of sixty firms listed on Karachi Stock Exchange (KSE) The event study methodology is adopted to assess the KSE response to this unforeseen disaster and result shows that it quickly rebounded. The market displayed amazing resilience by being effected less severely than it was expected by bouncing back following its initial level because the market was already in recession after mi-March 2005 decline. As regards the firm level activities, the analysis indicates that the increase in the return and volume of cement, steel, food, chemicals and pharmaceuticals and banking stocks indicates that individual has expectation for the upcoming demand of investment in these sectors. Furthermore there is no significant increase in the volatility because the investors take lessons from the crash of March 2005 and seem certain about the future outlook. These findings support the hypothesis that Pakistani market is reactive to unanticipated shocks however, it is resilient and it recovers soon from the catastrophic shock

Test of Higher Moment Capital Asset Pricing Model in Case of Pakistani Equity Market

In this study we test the mean-variance capital asset pricing model (CAPM) developed by Sharpe (1965) Lintner (1966) on individual stocks traded at Karachi Stock Exchange (KSE), the main equity market in Pakistan for the period 1993-2004 using daily and monthly data. The empirical findings do not support standard CAPM as a model to explain assets pricing in Pakistani equity market. In response to this finding first, we have extended the model to mean-variance-skewness and mean-variance-skewness-kurtosis model following Kraus and Litzenberger (1976). In the second step we allow the covariance, coskewness and cokurtosis to vary over time in autoregressive context leading to conditional three-moment CAPM and conditional four-moment CAPM. The results of unconditional and conditional higher-moments CAPM reveal that three-moment CAPM performed relatively well in explaining risk-return relationship in Pakistan during the sample period However, the results of higher-moment model indicate that systematic covariance and systematic cokurtosis have marginal role in explaining the asset price behavior in Pakistan

Testing multifactor capital asset pricing model in case of Pakistani market

The analysis of this study explores a set of macroeconomic variables along with market return as the systematic sources of risks explaining variations in expected stock returns for 49 stocks traded at Karachi Stock Exchange for the period 1993-2004. Some of these economic variables are found to be significant in explaining expected stock returns. The test of conditional multifactor CAPM is carried out by specifying conditional variance as a GARCH (1,1)-M process. The results of the conditional multifactor CAPM-with-GARCH-M model reveal that conditional model shows very marginal improvement in explaining risk-return relationship in Pakistani Market during the sample period. As regards the risk premium for variance risk, the results are not so supportive, only for a few stocks significant compensation for variance risk to investors is observed. The model is then extended to allow variability in economic risk variables and conditioning information is taken as lagged macroeconomic variables that influence business conditions in Pakistan. The results show evidence in support of conditional multifactor CAPM. The economic variables that are observed to perform relatively well in explaining variations in assets’returns include consumption growth, inflation risk, call money rate, term structure. However, the market return, foreign exchange risk and oil price risk, which explain a significant portion of the time series variability of stock returns, have limited influence on the asset pricing. Therefore we can conclude that expected returns variation could be explained by macroeconomic variations and this variability has some business cycle correlations