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Saghir Ghauri

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I am researcher, my interest is empirical analysis using time series models

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University of Karachi

Shaukat Hussain

Dr. Malik Ghulam Behlol

Samia Nadeem Zakai

zafarullah sahito

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Papers by Saghir Ghauri

Causality between Economic Development and Unemployment: Using ARDL Model

International Journal of Social Science & Entrepreneurship

The meditation of this study is to realizeunemploymentin Pakistan with the perspective of macroec... more The meditation of this study is to realizeunemploymentin Pakistan with the perspective of macroeconomic factors, including FDI,private investment,exports and government expenditure.Annual dataused in this study from 1985 to 2019was obtained from different issues of economic surveys and official website of the Pakistan’s Central Bank. The prerequisite required to exploretime series model is to check the stationarity, we apply ADF and PP tests to identify stationary series among our macroeconomic series. All variables are used log transformation in order to smooth the series. The results reveal that at level only unemployment is stationary while remaining series are stationary at first difference. Therefore,the appropriate time series model for different stationary series is Autoregressive Distributed Lag (ARDL) model. We apply four different ARDL models to detectthe long-run connection between unemployment and other macroeconomic series employed in this paper. Out of four, three mode...

The nexus between economic growth, corruption and external debt in Pakistan

International Journal of Social Science & Entrepreneurship

Corruption hurts various factors of a country, including welfare systems, governments and, most i... more Corruption hurts various factors of a country, including welfare systems, governments and, most importantly, economic growth. This paper investigates the relationship between economic growth and corruption in Pakistan from 1998 to 2021. We used time series models to check this relationship. The prerequisite of the time series model is the unit root test. We use the augmented dicky fuller (ADF) and Philips-Perron (PP) tests. To check the short-run and long-run relationship between economic growth and corruption, along with other macroeconomic variables, ARDL was used. As per our findings, the effects of crime and interest rates on economic growth (LGDP) are positive and statistically significant. However, the short-run association between LED and LGCF with LGDP is not statistically significant. Furthermore, corruption and gross capital formation truly influence economic growth over the long-term for this specific data, yet LED, and LIR factors are statistically insignificant, suggest...

How Relative Price Variability is Related to Unanticipated Inflation and Real Income

The paper examines the behavior of price setting agents as reflected in relative price changes in... more The paper examines the behavior of price setting agents as reflected in relative price changes in response to demand and supply factors. We have followed Parks (1978) model on monthly data of consumer price index of Pakistan. Results show that relative price variability is determined mainly by supply factors, as reflected by unanticipated inflation. The demand factors (i.e., changes in real income) are found insignificant in determining relative price variability.

Forecasting Inflation by Using the Sub-Groups of both CPI and WPI: Evidence from Auto Regression (AR) and ARIMA Models

Romanian Journal of Economic Forecasting, 2021

The undertaken study is conducted to forecast the inflation of Pakistan for the financial year FY... more The undertaken study is conducted to forecast the inflation of Pakistan for the financial year FY2018-19 using two different time series techniques. In this research, we used consumer price index (CPI) and wholesale price index (WPI) with their subgroups as inflation indicators for Pakistan. The undertaken research analyzes the proficiency of two important econometrics time series approaches such as Autoregressive (AR) with seasonal dummies, and Autoregressive integrated moving averaged (ARIMA) models by using root mean square (RMSE) criteria. In any economy, inflation and its forecasting are an imperative factor for the fiscal and monetary policies. The study is pertinent, as the forecasted figures of inflation start before the FY2018-19, which helps the policy makers to set the inflation target for FY2018-19. The month-to-month data has been considered for this study for the period from July 2008 to June 2018, and this research is concentrated on forecasting for the year 2018-19. In order to forecast CPI, we use 12 subgroups and for WPI we use 5 subgroups in both baskets for the 2007-08 base year. The result of this study reveals that the forecasted value of period average of CPI for the period FY2018-19 is 6.23 percent, however, for WPI is 8.96 percent.

An Empirical Analysis of Export, Import, and Inflation: A Case of Pakistan

Romanian Journal of Economic Forecasting, 2018

This article examines the association between inflation and exports & imports in perspective of t... more This article examines the association between inflation and exports & imports in perspective of the Pakistani economy. The researchers have taken month-to-month data of CPI (the indicator of inflation), imports and exports from July 2001 through June 2017. For the analysis purpose, researchers have employed error correction model to examine the short- run association amongst the variables; however, Johansen cointegration was used to investigate the long run association amongst the variables. The Granger causality approach has been applied to check the causal directionality between the pair of variables. Results of analysis exhibited that in a long run 1% increase in exports and imports cause 0.63% and 0.57% increase in the CPI (inflation) correspondingly. However, the coefficient of predictable error correlation signifies that approximately 1.18% deviance of inflation rate through the long run level of equilibrium has been adjusted every year. Whereas, the outcomes of variance decom...

Asymmetric influence of oil and gold prices on Baltic and South Asian stock markets : Evidence from Johansen cointegration and ARDL approach

The purpose of the undertaken research study is to examine the influence of crude oil and gold pr... more The purpose of the undertaken research study is to examine the influence of crude oil and gold prices on the equity returns of Baltic and South Asian stock markets. The study comprises of daily data from January 1, 2010, to June 30, 201 6. Nasdaq Baltic market (LOMXBBGI) data time series is stationary at level; however, rest of the data series became stationary at first difference by employing Philips-Perron and Augmented Dickey-Fuller approach es. Results of Johansen cointegration illustrated an ab sence of the cointegration amongst the considered e conomic indicators, therefore; we could not establish the long haul association am idst the equity returns of Baltic and South Asian m arkets, and crude oil and gold prices. The outcomes of VEC Granger Causality/Block Exogene ity Wald approach suggested unidirectional causalit y from LCOP to LKSE100 and LGP to LKSE100. Hence, it has been established that there is no causal affiliation amongst the variabl es. However, it is further concl...

Forecasting and the Causal Relationship of Sectorial Energy Consumptions and GDP of Pakistan by using AR, ARIMA, and Toda-Yamamoto Wald Models

Romanian Journal of Economic Forecasting, 2020

The objective of this research was to forecast the sectorial energy consumption of Pakistan for f... more The objective of this research was to forecast the sectorial energy consumption of Pakistan for five fiscal years, i.e., from FY18 to FY23 using two different time series techniques and explore the causal relationship between total energy consumption and its sectorial components, and Gross Domestic Product (GDP). The study further analyzed the efficiency of two different time series models, such as the Autoregressive model (AR with seasonal dummies) and Autoregressive Integrated Moving Average model (ARIMA/ARMA). In any economy, forecasting energy consumption and its relationship with GDP is paramount to ensure the economic development and fiscal policies. This study used components of total energy consumption (TEC) such as domestic energy consumption (DEC), commercial energy consumption (CEC), industrial energy consumption (IEC), agricultural energy consumption (AEC), transport energy consumption (TrEC) and other government energy consumption (OGEC). The data is taken from FY1977 t...

Forecasting tax revenues using time series techniques – a case of Pakistan

Economic Research-Ekonomska Istraživanja, 2018

The objective of this research was to forecast the tax revenue of Pakistan for the fiscal year 20... more The objective of this research was to forecast the tax revenue of Pakistan for the fiscal year 2016-17 using three different time series techniques and also to analyse the impact of indirect taxes on the working class. The study further analysed the efficiency of three different time series models such as the Autoregressive model (A.R. with seasonal dummies), Autoregressive Integrated Moving Average model (A.R.I.M.A.), and the Vector Autoregression (V.A.R.) model. In any economy, tax analysis and forecasting of revenues is of paramount importance to ensure the economic and fiscal policies. This study is important to identify significant variables affecting tax revenue specifically in Pakistan. The data used for this paper was from July 1985 to December 2016 (monthly) and focused on forecasting for 2017. For the forecasting of total tax revenue, we used components of tax revenues such as direct tax, sales tax, federal excise duty and customs duties. The results of this study revealed that among these models the A.R.I.M.A. model gives better-forecasted values for the total tax revenues of Pakistan. The results further demonstrated that major tax revenue is generated by indirect taxes, which cause more inflation that directly hits the working class of Pakistan.

Do Macroeconomic Factors Effects CARAMELS Financial Soundness Indicators? A Context of Non-Life Insurance Industry in Pakistan

International Journal of Experiential Learning & Case Studies, 2019

The research is carried out to f ind out the relationship of macroeconomic factors with the f ina... more The research is carried out to f ind out the relationship of macroeconomic factors with the f inancial soundness indicators of CARAMELS framework for the non-life insurance industry, by using a panel data set of 22 non-life insurance companies of Pakistan from the year 2007 to 2016. The study is established on the most applicable panel data technique (random-effects model). The Hausman test proves that the random-effects model is suitable for the macroeconomic factors' study. Based on the highest number of relationships among the variables, the results of the random-effects model indicate that macroeconomic factors (inflation and economic growth) have insignif icant relation with the CARAMELS f inancial soundness indicators. According to the author's best knowledge, it is the f irst study that identif ies the relationship of macroeconomic factors with the CARAMELS f inancial soundness indicators, which will assist the scholars, managers and policymakers of the non-life insurance industry of Pakistan to consider the signif icant factors.

Global Crisis and Credit Risk Management by Banks: A Comparative Study of Banks in Pakistan

International Journal of Business and Economics Research

The world trade environment has worsened significantly after August 2007. The rapid and dynamic c... more The world trade environment has worsened significantly after August 2007. The rapid and dynamic changes in the global financial landscape pose various risks to banking institutions. Operating side by side with conventional banks, Islamic banks are equally vulnerable to risks. This paper examines the impact of global financial crisis on the credit risk management of banks operating in Pakistan during the period, 2007-2009. A comparison of the factors, affecting credit risk faced by these banks, is highlighted. Study finds that, whilst the Islamic banking industry has not been left unaffected by the global crisis, Islamic banks in Pakistan are in a relatively strong position. This is because of the industry's high levels of transparency and adherence to a strict code of business conduct and Management efficiency, which means that Islamic banks have the potential to emerge from the crisis in a stronger position than their conventional counterparts.

Forecasting Inflation and Economic Growth of Pakistan by Using Two Time Series Methods

International Journal of Business and Economics Research, 2013

Forecasting of time series is important subject in macroeconomics. We use two time series methods... more Forecasting of time series is important subject in macroeconomics. We use two time series methods. One of the most simple and basic method for forecasting time series is decomposition. Decomposing the time series means breaking the time series into four components, i.e., trend, cycle, seasonal and irregular. The second method is based on ARIMA model. In this paper we forecast the macroeconomic variables CPI, and LSM for period July 2013 to September 2013, based on decomposition of actual series of these variables and ARIMA model for monthly series from July 2008 to June 2013. We compare the out-of-sample forecast of two methods based on the mean absolute deviation (MAD) & sum of square of errors (SSE) and decide on which method provides the best forecasting accuracy which policy makers can rely on in forecasting inflation (CPI) and Economic growth (LSM).

PRICE LEVEL CONVERGENCE Evidence from Pakistan

We examine convergence of prices among 35 Pakistani cities and also explore how location of citie... more We examine convergence of prices among 35 Pakistani cities and also explore how location of cities affects the convergence. We have found that there is bilateral price-level convergence for only food group and speed of convergence is around 3 months. On the other hand, prices of non-food commodities have very low speed of adjustment with 20 months. As a result, the overall CPI basket (food and non-food combined) has a moderate speed of convergence -8 months. Moreover, relative prices have been found sensitive to locality as well as distance among them.

Estimation of Relationship Between Inflation and Relative Price Variability : Granger Causality and Ardl Modeling

The objective of this research paper is to examine the relationship between relative price variab... more The objective of this research paper is to examine the relationship between relative price variability and inflation by using consumer price index (CPI) of Pakistan. The outcomes of the research further divided into food and non-food groups too. The monthly data of CPI was taken from the Pakistan Bureau of Statistics, from August 2001 to July 2011 (with 2000-01 base) for 92 composite commodities with 12 sub-groups. We employed the Granger causality testing approach for the evaluation of any possible influence of one indicator to another. In this scenario, it is viable to state that there is a presence of causality and bidirectional feedback between the variables or the two variables are independent. The major issue is to identify a suitable statistical method that enables us to analyze the association among the variables. The findings of this study demonstrated that there is a probable relationship between inflation (DPt) and both un-weighted measures of price variability (VPt and S...

The Relationship between Wholesale Price Index and Consumer Price Index

Disclaimer Views expressed in this document belong to the author(s) only, and by no means a refle... more

Do Macroeconomic Factors Effects CARAMELS Financial Soundness Indicators? A Context of Non-Life Insurance Industry in Pakistan

International Journal of Experiential Learning & Case Studies, Dec 30, 2019

The research is carried out to f ind out the relationship of macroeconomic factors with the f ina... more The research is carried out to f ind out the relationship of macroeconomic factors with the f inancial soundness indicators of CARAMELS framework for the non-life insurance industry, by using a panel data set of 22 non-life insurance companies of Pakistan from the year 2007 to 2016. The study is established on the most applicable panel data technique (random-effects model). The Hausman test proves that the random-effects model is suitable for the macroeconomic factors' study. Based on the highest number of relationships among the variables, the results of the random-effects model indicate that macroeconomic factors (inflation and economic growth) have insignif icant relation with the CARAMELS f inancial soundness indicators. According to the author's best knowledge, it is the f irst study that identif ies the relationship of macroeconomic factors with the CARAMELS f inancial soundness indicators, which will assist the scholars, managers and policymakers of the non-life insurance industry of Pakistan to consider the signif icant factors.

Forecasting Exports and Imports by using Autoregressive (AR) with Seasonal Dummies and Box-Jenkins Approaches: A Case of Pakistan

Inzinerine Ekonomik–Engineering Economics, Vol. 31(3), 291–301. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 1.000), 2020

This research aims to evaluate two econometric models to forecast imports and exports for the fin... more This research aims to evaluate two econometric models to forecast imports and exports for the financial year (FY) 2020. For this purpose, we used the annual exports and imports data of Pakistan from FY2002 to FY2019. Thus, in this regard, we employed, and compared the results of two econometrics models such as Box Jenkins or Autoregressive Integrated Moving Average (ARIMA), and Auto-Regressive (AR) with seasonal dummies. For examining the precision of forecasting, we employed mean absolute error and root mean square error approaches. The findings of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) reveal that the ARIMA or Box Jenkins approach provides better accuracy of the forecast for the exports as compared to the AR model with dummies. However, Auto-Regressive (AR) model has demonstrated more precision for the imports as compared to the Box Jenkins model. Hence, the projected forecasting for the growth of export is 1.87 % for the FY2020 and projected forecasting for t...

The effects of remittances on inflation (CPI and WPI) and exchange rate: A Case of Pakistan

Romanian Journal of Economic Forecastin, Vol. XXII(2): 146–165 (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 0.725), 2019

The objective of this research is to determine the effects of workers' remittances (WR) on lo... more The objective of this research is to determine the effects of workers' remittances (WR) on long-term inflation in the case of Pakistan. We use the consumer price index (CPI) and the wholesale price index (WPI) as indicators of inflation and the market determined exchange rate (EXR) regime. The data of workers' remittances (WR), CPI, WPI and EXR from July 2001 to December 2016 have been used for this analysis. The outcomes of Johansen cointegration confirmed the long run association between WR and CPI and EXR, and WR and WPI and EXR. Moreover, the WR and CPI food and EXR, and WR and WPI food and EXR also demonstrated a long run association. The results of Toda-Yamamoto Wald test and Granger causality VEC/Exogeneity Wald test concluded that there is a presence of one-way causality from workers remittances to CPI and WPI. Similar results have been revealed for food groups of both inflation indicators (CPI and WPI). Therefore, it is concluded that the influx of workers' remi...

Stock Returns, Volatility and Mean Reversion in Emerging and Developed Financial Markets

Technological and Economic Development of Economy, Vol. 24(3): 1149–1177. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 4.344), 2018

The objective of this research is to measure and examine volatilities between important emerging ... more The objective of this research is to measure and examine volatilities between important emerging and developed stock markets and to ascertain a relationship between volatilities and stock returns. This research paper also analyses the Mean reversion phenomenon in emerging and developed stock markets. For this purpose, seven emerging markets and five developed markets were considered. Descriptive statistics showed that the emerging markets have higher returns with the higher risk-return trade-off. In contrast, developed markets have low annual returns with a low risk-return trade-off. Correlation analysis indicated the significant positive correlation among the developed markets, but emerging and developed markets have shown relatively insignificant correlation. Results of ARCH and GARCH revealed that the value of likelihood statistics ratio is large, that entails the GARCH (1,1) model is a lucrative depiction of daily return pattern, that effectively and efficiently capturing the or...

Forecasting tax revenues using time series techniques a case of Pakistan

Economic Research-Ekonomska Istraživanja, Vol. 31(1): 722–754. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 1.381), 2018

The objective of this research was to forecast the tax revenue of Pakistan for the scal year 2016... more The objective of this research was to forecast the tax revenue of Pakistan for the scal year 2016–17 using three di erent time series techniques and also to analyse the impact of indirect taxes on the working class. The study further analysed the e ciency of three di erent time series models such as the Autoregressive model (A.R. with seasonal dummies), Autoregressive Integrated Moving Average model (A.R.I.M.A.), and the Vector Autoregression (V.A.R.) model. In any economy, tax analysis and forecasting of revenues is of paramount importance to ensure the economic and scal policies. This study is important to identify signi cant variables a ecting tax revenue speci cally in Pakistan. The data used for this paper was from July 1985 to December 2016 (monthly) and focused on forecasting for 2017. For the forecasting of total tax revenue, we used components of tax revenues such as direct tax, sales tax, federal excise duty and customs duties. The results of this study revealed that among...

Estimation of long-run relationship of inflation (CPI & WPI), and oil prices with KSE-100 index: evidence from Johansen multivariate cointegration approach

Technological and Economic Development of Economy, Vol. 23(4): 567–588. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 3.244), 2017

This research is an attempt to framework the applied strides to evaluate the long run relationshi... more This research is an attempt to framework the applied strides to evaluate the long run relationship among commonly used inflation proxies induces such as, wholesale price index (WPI) and consumer price index (CPI), and crude oil price (COP) with KSE100 index returns. In this research we used monthly data for the time period from July 1995 to June 2016, and thus, in this way total 252 observations have been considered. Time series have been made stationary by applying ADF and PP tests at first difference. Johansen multivariate cointegration approach was used to test the long-term association amongst the considered macroeconomic variables. The results indicated that CPI and COP significantly affect KSE100 index returns that indicated CPI along with COP have foreseen power to impact KSE100 index. In contrary, the results of WPI and COP do not have long run relationship with KSE100 index in case of Pakistani economy. Results of variance decomposition exhibited that the index of LKSE100 w...

Causality between Economic Development and Unemployment: Using ARDL Model

International Journal of Social Science & Entrepreneurship

The meditation of this study is to realizeunemploymentin Pakistan with the perspective of macroec... more The meditation of this study is to realizeunemploymentin Pakistan with the perspective of macroeconomic factors, including FDI,private investment,exports and government expenditure.Annual dataused in this study from 1985 to 2019was obtained from different issues of economic surveys and official website of the Pakistan’s Central Bank. The prerequisite required to exploretime series model is to check the stationarity, we apply ADF and PP tests to identify stationary series among our macroeconomic series. All variables are used log transformation in order to smooth the series. The results reveal that at level only unemployment is stationary while remaining series are stationary at first difference. Therefore,the appropriate time series model for different stationary series is Autoregressive Distributed Lag (ARDL) model. We apply four different ARDL models to detectthe long-run connection between unemployment and other macroeconomic series employed in this paper. Out of four, three mode...

The nexus between economic growth, corruption and external debt in Pakistan

International Journal of Social Science & Entrepreneurship

Corruption hurts various factors of a country, including welfare systems, governments and, most i... more Corruption hurts various factors of a country, including welfare systems, governments and, most importantly, economic growth. This paper investigates the relationship between economic growth and corruption in Pakistan from 1998 to 2021. We used time series models to check this relationship. The prerequisite of the time series model is the unit root test. We use the augmented dicky fuller (ADF) and Philips-Perron (PP) tests. To check the short-run and long-run relationship between economic growth and corruption, along with other macroeconomic variables, ARDL was used. As per our findings, the effects of crime and interest rates on economic growth (LGDP) are positive and statistically significant. However, the short-run association between LED and LGCF with LGDP is not statistically significant. Furthermore, corruption and gross capital formation truly influence economic growth over the long-term for this specific data, yet LED, and LIR factors are statistically insignificant, suggest...

How Relative Price Variability is Related to Unanticipated Inflation and Real Income

The paper examines the behavior of price setting agents as reflected in relative price changes in... more The paper examines the behavior of price setting agents as reflected in relative price changes in response to demand and supply factors. We have followed Parks (1978) model on monthly data of consumer price index of Pakistan. Results show that relative price variability is determined mainly by supply factors, as reflected by unanticipated inflation. The demand factors (i.e., changes in real income) are found insignificant in determining relative price variability.

Forecasting Inflation by Using the Sub-Groups of both CPI and WPI: Evidence from Auto Regression (AR) and ARIMA Models

Romanian Journal of Economic Forecasting, 2021

The undertaken study is conducted to forecast the inflation of Pakistan for the financial year FY... more The undertaken study is conducted to forecast the inflation of Pakistan for the financial year FY2018-19 using two different time series techniques. In this research, we used consumer price index (CPI) and wholesale price index (WPI) with their subgroups as inflation indicators for Pakistan. The undertaken research analyzes the proficiency of two important econometrics time series approaches such as Autoregressive (AR) with seasonal dummies, and Autoregressive integrated moving averaged (ARIMA) models by using root mean square (RMSE) criteria. In any economy, inflation and its forecasting are an imperative factor for the fiscal and monetary policies. The study is pertinent, as the forecasted figures of inflation start before the FY2018-19, which helps the policy makers to set the inflation target for FY2018-19. The month-to-month data has been considered for this study for the period from July 2008 to June 2018, and this research is concentrated on forecasting for the year 2018-19. In order to forecast CPI, we use 12 subgroups and for WPI we use 5 subgroups in both baskets for the 2007-08 base year. The result of this study reveals that the forecasted value of period average of CPI for the period FY2018-19 is 6.23 percent, however, for WPI is 8.96 percent.

An Empirical Analysis of Export, Import, and Inflation: A Case of Pakistan

Romanian Journal of Economic Forecasting, 2018

This article examines the association between inflation and exports & imports in perspective of t... more This article examines the association between inflation and exports & imports in perspective of the Pakistani economy. The researchers have taken month-to-month data of CPI (the indicator of inflation), imports and exports from July 2001 through June 2017. For the analysis purpose, researchers have employed error correction model to examine the short- run association amongst the variables; however, Johansen cointegration was used to investigate the long run association amongst the variables. The Granger causality approach has been applied to check the causal directionality between the pair of variables. Results of analysis exhibited that in a long run 1% increase in exports and imports cause 0.63% and 0.57% increase in the CPI (inflation) correspondingly. However, the coefficient of predictable error correlation signifies that approximately 1.18% deviance of inflation rate through the long run level of equilibrium has been adjusted every year. Whereas, the outcomes of variance decom...

Asymmetric influence of oil and gold prices on Baltic and South Asian stock markets : Evidence from Johansen cointegration and ARDL approach

The purpose of the undertaken research study is to examine the influence of crude oil and gold pr... more The purpose of the undertaken research study is to examine the influence of crude oil and gold prices on the equity returns of Baltic and South Asian stock markets. The study comprises of daily data from January 1, 2010, to June 30, 201 6. Nasdaq Baltic market (LOMXBBGI) data time series is stationary at level; however, rest of the data series became stationary at first difference by employing Philips-Perron and Augmented Dickey-Fuller approach es. Results of Johansen cointegration illustrated an ab sence of the cointegration amongst the considered e conomic indicators, therefore; we could not establish the long haul association am idst the equity returns of Baltic and South Asian m arkets, and crude oil and gold prices. The outcomes of VEC Granger Causality/Block Exogene ity Wald approach suggested unidirectional causalit y from LCOP to LKSE100 and LGP to LKSE100. Hence, it has been established that there is no causal affiliation amongst the variabl es. However, it is further concl...

Forecasting and the Causal Relationship of Sectorial Energy Consumptions and GDP of Pakistan by using AR, ARIMA, and Toda-Yamamoto Wald Models

Romanian Journal of Economic Forecasting, 2020

The objective of this research was to forecast the sectorial energy consumption of Pakistan for f... more The objective of this research was to forecast the sectorial energy consumption of Pakistan for five fiscal years, i.e., from FY18 to FY23 using two different time series techniques and explore the causal relationship between total energy consumption and its sectorial components, and Gross Domestic Product (GDP). The study further analyzed the efficiency of two different time series models, such as the Autoregressive model (AR with seasonal dummies) and Autoregressive Integrated Moving Average model (ARIMA/ARMA). In any economy, forecasting energy consumption and its relationship with GDP is paramount to ensure the economic development and fiscal policies. This study used components of total energy consumption (TEC) such as domestic energy consumption (DEC), commercial energy consumption (CEC), industrial energy consumption (IEC), agricultural energy consumption (AEC), transport energy consumption (TrEC) and other government energy consumption (OGEC). The data is taken from FY1977 t...

Forecasting tax revenues using time series techniques – a case of Pakistan

Economic Research-Ekonomska Istraživanja, 2018

The objective of this research was to forecast the tax revenue of Pakistan for the fiscal year 20... more The objective of this research was to forecast the tax revenue of Pakistan for the fiscal year 2016-17 using three different time series techniques and also to analyse the impact of indirect taxes on the working class. The study further analysed the efficiency of three different time series models such as the Autoregressive model (A.R. with seasonal dummies), Autoregressive Integrated Moving Average model (A.R.I.M.A.), and the Vector Autoregression (V.A.R.) model. In any economy, tax analysis and forecasting of revenues is of paramount importance to ensure the economic and fiscal policies. This study is important to identify significant variables affecting tax revenue specifically in Pakistan. The data used for this paper was from July 1985 to December 2016 (monthly) and focused on forecasting for 2017. For the forecasting of total tax revenue, we used components of tax revenues such as direct tax, sales tax, federal excise duty and customs duties. The results of this study revealed that among these models the A.R.I.M.A. model gives better-forecasted values for the total tax revenues of Pakistan. The results further demonstrated that major tax revenue is generated by indirect taxes, which cause more inflation that directly hits the working class of Pakistan.

Do Macroeconomic Factors Effects CARAMELS Financial Soundness Indicators? A Context of Non-Life Insurance Industry in Pakistan

International Journal of Experiential Learning & Case Studies, 2019

The research is carried out to f ind out the relationship of macroeconomic factors with the f ina... more The research is carried out to f ind out the relationship of macroeconomic factors with the f inancial soundness indicators of CARAMELS framework for the non-life insurance industry, by using a panel data set of 22 non-life insurance companies of Pakistan from the year 2007 to 2016. The study is established on the most applicable panel data technique (random-effects model). The Hausman test proves that the random-effects model is suitable for the macroeconomic factors' study. Based on the highest number of relationships among the variables, the results of the random-effects model indicate that macroeconomic factors (inflation and economic growth) have insignif icant relation with the CARAMELS f inancial soundness indicators. According to the author's best knowledge, it is the f irst study that identif ies the relationship of macroeconomic factors with the CARAMELS f inancial soundness indicators, which will assist the scholars, managers and policymakers of the non-life insurance industry of Pakistan to consider the signif icant factors.

Global Crisis and Credit Risk Management by Banks: A Comparative Study of Banks in Pakistan

International Journal of Business and Economics Research

The world trade environment has worsened significantly after August 2007. The rapid and dynamic c... more The world trade environment has worsened significantly after August 2007. The rapid and dynamic changes in the global financial landscape pose various risks to banking institutions. Operating side by side with conventional banks, Islamic banks are equally vulnerable to risks. This paper examines the impact of global financial crisis on the credit risk management of banks operating in Pakistan during the period, 2007-2009. A comparison of the factors, affecting credit risk faced by these banks, is highlighted. Study finds that, whilst the Islamic banking industry has not been left unaffected by the global crisis, Islamic banks in Pakistan are in a relatively strong position. This is because of the industry's high levels of transparency and adherence to a strict code of business conduct and Management efficiency, which means that Islamic banks have the potential to emerge from the crisis in a stronger position than their conventional counterparts.

Forecasting Inflation and Economic Growth of Pakistan by Using Two Time Series Methods

International Journal of Business and Economics Research, 2013

Forecasting of time series is important subject in macroeconomics. We use two time series methods... more Forecasting of time series is important subject in macroeconomics. We use two time series methods. One of the most simple and basic method for forecasting time series is decomposition. Decomposing the time series means breaking the time series into four components, i.e., trend, cycle, seasonal and irregular. The second method is based on ARIMA model. In this paper we forecast the macroeconomic variables CPI, and LSM for period July 2013 to September 2013, based on decomposition of actual series of these variables and ARIMA model for monthly series from July 2008 to June 2013. We compare the out-of-sample forecast of two methods based on the mean absolute deviation (MAD) & sum of square of errors (SSE) and decide on which method provides the best forecasting accuracy which policy makers can rely on in forecasting inflation (CPI) and Economic growth (LSM).

PRICE LEVEL CONVERGENCE Evidence from Pakistan

We examine convergence of prices among 35 Pakistani cities and also explore how location of citie... more We examine convergence of prices among 35 Pakistani cities and also explore how location of cities affects the convergence. We have found that there is bilateral price-level convergence for only food group and speed of convergence is around 3 months. On the other hand, prices of non-food commodities have very low speed of adjustment with 20 months. As a result, the overall CPI basket (food and non-food combined) has a moderate speed of convergence -8 months. Moreover, relative prices have been found sensitive to locality as well as distance among them.

Estimation of Relationship Between Inflation and Relative Price Variability : Granger Causality and Ardl Modeling

The objective of this research paper is to examine the relationship between relative price variab... more The objective of this research paper is to examine the relationship between relative price variability and inflation by using consumer price index (CPI) of Pakistan. The outcomes of the research further divided into food and non-food groups too. The monthly data of CPI was taken from the Pakistan Bureau of Statistics, from August 2001 to July 2011 (with 2000-01 base) for 92 composite commodities with 12 sub-groups. We employed the Granger causality testing approach for the evaluation of any possible influence of one indicator to another. In this scenario, it is viable to state that there is a presence of causality and bidirectional feedback between the variables or the two variables are independent. The major issue is to identify a suitable statistical method that enables us to analyze the association among the variables. The findings of this study demonstrated that there is a probable relationship between inflation (DPt) and both un-weighted measures of price variability (VPt and S...

The Relationship between Wholesale Price Index and Consumer Price Index

Disclaimer Views expressed in this document belong to the author(s) only, and by no means a refle... more

Do Macroeconomic Factors Effects CARAMELS Financial Soundness Indicators? A Context of Non-Life Insurance Industry in Pakistan

International Journal of Experiential Learning & Case Studies, Dec 30, 2019

The research is carried out to f ind out the relationship of macroeconomic factors with the f ina... more The research is carried out to f ind out the relationship of macroeconomic factors with the f inancial soundness indicators of CARAMELS framework for the non-life insurance industry, by using a panel data set of 22 non-life insurance companies of Pakistan from the year 2007 to 2016. The study is established on the most applicable panel data technique (random-effects model). The Hausman test proves that the random-effects model is suitable for the macroeconomic factors' study. Based on the highest number of relationships among the variables, the results of the random-effects model indicate that macroeconomic factors (inflation and economic growth) have insignif icant relation with the CARAMELS f inancial soundness indicators. According to the author's best knowledge, it is the f irst study that identif ies the relationship of macroeconomic factors with the CARAMELS f inancial soundness indicators, which will assist the scholars, managers and policymakers of the non-life insurance industry of Pakistan to consider the signif icant factors.

Forecasting Exports and Imports by using Autoregressive (AR) with Seasonal Dummies and Box-Jenkins Approaches: A Case of Pakistan

Inzinerine Ekonomik–Engineering Economics, Vol. 31(3), 291–301. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 1.000), 2020

This research aims to evaluate two econometric models to forecast imports and exports for the fin... more This research aims to evaluate two econometric models to forecast imports and exports for the financial year (FY) 2020. For this purpose, we used the annual exports and imports data of Pakistan from FY2002 to FY2019. Thus, in this regard, we employed, and compared the results of two econometrics models such as Box Jenkins or Autoregressive Integrated Moving Average (ARIMA), and Auto-Regressive (AR) with seasonal dummies. For examining the precision of forecasting, we employed mean absolute error and root mean square error approaches. The findings of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) reveal that the ARIMA or Box Jenkins approach provides better accuracy of the forecast for the exports as compared to the AR model with dummies. However, Auto-Regressive (AR) model has demonstrated more precision for the imports as compared to the Box Jenkins model. Hence, the projected forecasting for the growth of export is 1.87 % for the FY2020 and projected forecasting for t...

The effects of remittances on inflation (CPI and WPI) and exchange rate: A Case of Pakistan

Romanian Journal of Economic Forecastin, Vol. XXII(2): 146–165 (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 0.725), 2019

The objective of this research is to determine the effects of workers' remittances (WR) on lo... more The objective of this research is to determine the effects of workers' remittances (WR) on long-term inflation in the case of Pakistan. We use the consumer price index (CPI) and the wholesale price index (WPI) as indicators of inflation and the market determined exchange rate (EXR) regime. The data of workers' remittances (WR), CPI, WPI and EXR from July 2001 to December 2016 have been used for this analysis. The outcomes of Johansen cointegration confirmed the long run association between WR and CPI and EXR, and WR and WPI and EXR. Moreover, the WR and CPI food and EXR, and WR and WPI food and EXR also demonstrated a long run association. The results of Toda-Yamamoto Wald test and Granger causality VEC/Exogeneity Wald test concluded that there is a presence of one-way causality from workers remittances to CPI and WPI. Similar results have been revealed for food groups of both inflation indicators (CPI and WPI). Therefore, it is concluded that the influx of workers' remi...

Stock Returns, Volatility and Mean Reversion in Emerging and Developed Financial Markets

Technological and Economic Development of Economy, Vol. 24(3): 1149–1177. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 4.344), 2018

The objective of this research is to measure and examine volatilities between important emerging ... more The objective of this research is to measure and examine volatilities between important emerging and developed stock markets and to ascertain a relationship between volatilities and stock returns. This research paper also analyses the Mean reversion phenomenon in emerging and developed stock markets. For this purpose, seven emerging markets and five developed markets were considered. Descriptive statistics showed that the emerging markets have higher returns with the higher risk-return trade-off. In contrast, developed markets have low annual returns with a low risk-return trade-off. Correlation analysis indicated the significant positive correlation among the developed markets, but emerging and developed markets have shown relatively insignificant correlation. Results of ARCH and GARCH revealed that the value of likelihood statistics ratio is large, that entails the GARCH (1,1) model is a lucrative depiction of daily return pattern, that effectively and efficiently capturing the or...

Forecasting tax revenues using time series techniques a case of Pakistan

Economic Research-Ekonomska Istraživanja, Vol. 31(1): 722–754. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 1.381), 2018

The objective of this research was to forecast the tax revenue of Pakistan for the scal year 2016... more The objective of this research was to forecast the tax revenue of Pakistan for the scal year 2016–17 using three di erent time series techniques and also to analyse the impact of indirect taxes on the working class. The study further analysed the e ciency of three di erent time series models such as the Autoregressive model (A.R. with seasonal dummies), Autoregressive Integrated Moving Average model (A.R.I.M.A.), and the Vector Autoregression (V.A.R.) model. In any economy, tax analysis and forecasting of revenues is of paramount importance to ensure the economic and scal policies. This study is important to identify signi cant variables a ecting tax revenue speci cally in Pakistan. The data used for this paper was from July 1985 to December 2016 (monthly) and focused on forecasting for 2017. For the forecasting of total tax revenue, we used components of tax revenues such as direct tax, sales tax, federal excise duty and customs duties. The results of this study revealed that among...

Estimation of long-run relationship of inflation (CPI & WPI), and oil prices with KSE-100 index: evidence from Johansen multivariate cointegration approach

Technological and Economic Development of Economy, Vol. 23(4): 567–588. (ISI Web of Science – Social Sciences Citation Index® & Journal Citation Reports/Social Sciences Edition) (Impact factor 3.244), 2017

This research is an attempt to framework the applied strides to evaluate the long run relationshi... more This research is an attempt to framework the applied strides to evaluate the long run relationship among commonly used inflation proxies induces such as, wholesale price index (WPI) and consumer price index (CPI), and crude oil price (COP) with KSE100 index returns. In this research we used monthly data for the time period from July 1995 to June 2016, and thus, in this way total 252 observations have been considered. Time series have been made stationary by applying ADF and PP tests at first difference. Johansen multivariate cointegration approach was used to test the long-term association amongst the considered macroeconomic variables. The results indicated that CPI and COP significantly affect KSE100 index returns that indicated CPI along with COP have foreseen power to impact KSE100 index. In contrary, the results of WPI and COP do not have long run relationship with KSE100 index in case of Pakistani economy. Results of variance decomposition exhibited that the index of LKSE100 w...