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This study investigates the rice price dynamics and their impacts on demand and supply over the time in agricultural markets of Pakistan. Time series data on production and prices for the period 1984-2018 were used to study the cobweb phenomenon in local rice markets. Linear demand and supply models were used to examine the unstable rice-market. Price dynamics were examined through identifying the time path of difference equation derived from demand and supply functions. The results inferred that market prices of rice have remained unstable in agricultural markets of Pakistan over the history. Furthermore, rice prices exhibited damped oscillations towards stable market equilibrium over last three decades in Pakistan. It is suggested that the government may respond promptly to the instability of rice markets by formulating the appropriate agricultural policies, developing state-of-the-art storage facilities and ensuring the steady transmission of market information across the national as well as international rice markets. The study provides deep insights into understanding the on-going and future trends of price fluctuations with respect to demand and supply shocks in rice market of Pakistan. It would greatly help the stakeholders and policy makers in forecasting and stabilizing the rice markets, and alleviating the food insecurity. [ABSTRACT FROM AUTHOR]

This study investigates the rice price dynamics and their impacts on demand and supply over the time in agricultural markets of Pakistan. Time series data on production and prices for the period 1984-2018 were used to study the cobweb phenomenon in local rice markets. Linear demand and supply models were used to examine the unstable rice-market. Price dynamics were examined through identifying the time path of difference equation derived from demand and supply functions. The results inferred that market prices of rice have remained unstable in agricultural markets of Pakistan over the history. Furthermore, rice prices exhibited damped oscillations towards stable market equilibrium over last three decades in Pakistan. It is suggested that the government may respond promptly to the instability of rice markets by formulating the appropriate agricultural policies, developing state-of-the-art storage facilities and ensuring the steady transmission of market information across the national as well as international rice markets. The study provides deep insights into understanding the on-going and future trends of price fluctuations with respect to demand and supply shocks in rice market of Pakistan. It would greatly help the stakeholders and policy makers in forecasting and stabilizing the rice markets, and alleviating the food insecurity. [ABSTRACT FROM AUTHOR]

This research analyzed the relationship between openness to agricultural exchange, foreign direct investment, capital, consumer price index, and GDP in Pakistan utilizing time series data for the 1971-2019 period. We used autoregressive distributed lag ARDL-bound testing method to analyze the long-run and short-run correlation between projected variables. The study's findings also confirmed a positive and important long-term correlation between openness to agricultural trade, foreign direct investment and Pakistan's economic development. There is no long-run relationship between consumer price and economic growth. [ABSTRACT FROM AUTHOR]

This study examines the link between marine resources exports and their impact on economic development in Pakistan by using Vector Error-Correction Models (VECM). The data of 57 years from 1960 to 2017 were used to analyse the impact among variables. The findings of this research were obtained as there is no long-run association discovered between the fisheries exports and economic development. However, we discovered that there is a short-run relationship sustained between them. In addition, the results from the Ordinary Least Squares (OLS) regression also validates that there is a robust relationship between GDP and exports of fisheries products. The findings indicated that the sub-sector (Fisheries) of the agriculture sector is playing an extensive role in the economic growth of Pakistan. [ABSTRACT FROM AUTHOR]

This paper made an attempt of econometric analysis of the investment situation in Pakistan for the period 1990-2017. The variables including domestic credit, national savings, lagged investment (IV), imports, and the real exchange rate were found to be the major factors affecting investment in Pakistan. Among all, the savings coefficient is positive and insignificant because of savings in Pakistan had no healthy pattern. Exchange rate has adversely affected the investment because of unidirectional causality. Specification and analytical tests supported reliability of the investment does not affect investment model from key econometric issues. The stability test shows that investment fluctuated during the 1990-2017 periods. OLS and GMM results are comparable. OLS estimation results are reliable since these variables do not suffer from Endogeneity problem. [ABSTRACT FROM AUTHOR]

This study empirically investigates the spillover between exchange rate risk and sectoral returns in Pakistan over the period of 1992–2017 using high-frequency data. Building on the Wavelet-multi-resolution-extended dynamic conditional correlation GARCH (MRA-EDCC GARCH) model, our findings suggest that exchange rate risk transmission to sectoral stock returns is scale-dependent. The extent of mean and volatility spillover prevalence varies across different scales. Hence, homogenous trading strategies for short-term and long-term investors may not be favorable. The finding further reveals that the risk transmissions are notable over the short run. In the context of cross spillover, there is greater evidence of exchange rate volatility impact on sectoral returns, whereas, few sectoral returns are found to affect exchange rate. Our results are robust to alternative methods of causality and short-run volatility spillover through GARCH-in-mean SVAR model. Our findings provide useful implications for risk mitigation of portfolio managers and speculators. [ABSTRACT FROM AUTHOR]

The objective of this paper is to ascertain the impact of Chinese FDI on economic growth in Pakistan. This study documents the exploration of the determinants of economic growth in Pakistan by emphasizing the significant role played by Chinese FDI and investments in renewable energy in particular. This paper employs time series data analysis to examine the relationship between GDP and Chinese FDI, inflation, trade openness, exchange rates, interest rates, remittances, and renewable energy consumption from 1990 to 2019. The study involved performing the ARDL bounds test, and it was determined that the dependent and independent variables are linked in the long term. Furthermore, the error correction model is negative and noteworthy, which checks the long-run relationship between variables. According to the findings of the autoregressive distributed lag (ARDL) model, Chinese FDI has a substantial favorable effect on Pakistan's economic growth. Furthermore, renewable energy usage has a long-term favorable and significant association with Pakistan's economic growth. This study established that FDI, and particularly renewable energy, will stimulate the economic growth of Pakistan. Our research has substantial policy implications, especially when it comes to the relationship between FDI and renewable energy. [ABSTRACT FROM AUTHOR]

This study tries to assess the Pakistani rice producer’s behaviour under the exchange rate volatility. The exchange rate variability is a risk which may force the producers to change their production preferences. The Cobb-Douglas production function used to examine the functional association between exchange rate variability and behaviour of Pakistani rice producers. The Exchange rate volatility is measured through the Moving Average Standard Deviation and time-series data from 1981 to 2018 collected from various sources. This study uses the Johansen Co-integration and Vector error correction model to assess the short run and long run association between the exchange rate variability and rice production in Pakistan. The results confirm that the appreciation in the exchange rate will adversely affect rice production in Pakistan. This negative and significant relationship confirms the risk-averse behaviour of Pakistani rice producers. Parameters stability is checked by the Cusum and Cusumq statistics. Policymakers, when designing policies to promote rice production, should consider the exchange rate volatility. [ABSTRACT FROM AUTHOR]

A significant corridor under the "Belt and Road Initiative" is announced by the government of China for numerous transport and energy projects. China focuses greatly on the sustainability of these projects, in accordance with Green Investment Principles. For this, environmental, social, governance, and technological considerations are taken into account. This paper offers a novel assessment of the impact of green sustainability under BRI and the current emission scenario in Pakistan. The question that needs to be addressed here is whether the projects under Belt and Road Initiative are as environment friendly as they claim. In the first phase of this study, we review theories establishing evidence based on existing literature to determine the influence of Belt and Road on economic development. In the next phase, we use Environment Kuznets Curve and apply estimates from Johansson's Cointegration Test to quantify the present environmental scenario of Pakistan and probable environmental risk portrayed by the China-Pakistan Economic Corridor (CPEC). This paper helps in determining the relationship between carbon emission and three major variables including energy consumption, economic growth, and foreign direct investment (FDI). Cointegration analysis is applied on time series data comprising of a 40 years' period from 1979 to 2019. The paper finds that (i) the belt and road corridors could substantially improve trade, foreign investment, and living conditions for citizens in participating countries; (ii) moreover, this study confirms the presence of one cointegrated equation suggesting the presence of a long term relationship between the CO2 and independent variables and a short run association running from EnC to CO2. The study also proposes a Green BRI Model which formulates a body that devises environmental performance standards, reviews procedures, and ensures that they get implemented on all CPEC projects. The Belt and Road Initiative increases emissions among participating countries. China and corridor economies need to adopt strict policy reforms that increase transparency, expand trade, improve debt sustainability, and mitigate environmental, social, and corruption risks. [ABSTRACT FROM AUTHOR]

Carbon emissions constitute a large portion of greenhouse gases that are responsible for global warming and climate change. This study examines the impact of export variety on carbon emissions along with foreign direct investment (FDI) and technological development as determinants of environmental degradation in Pakistan. Moreover, this study is conducted in the context of the environmental Kuznets curve hypothesis (EKC). This study applies dynamic ordinary least squares and error correction models for long-term and short-term estimates, respectively. The results indicate that the EKC hypothesis is valid in the long term. This implies that Pakistan's economy reached the threshold level of income, after which an increase in income was not responsible for environmental degradation. Export variety restrains environmental degradation in the short term and is not a significant factor in the long term. Energy consumption has aggravated environmental degradation, while FDI and technological development are restraining environmental degradation. Policy measures are recommended to curb environmental degradation in Pakistan. [ABSTRACT FROM AUTHOR]

Consistent estimation techniques need to be implemented to obtain robust empirical outcomes which help policymakers formulating public policies. Therefore, we implement the least squares (LS) and the high breakdown robust least trimmed squares (LTS) regression techniques, while using econometric regression model based on a growth equation for the two countries, namely, India and Pakistan. We used secondary annual time series data which covers a long period of 41 years. The adequacy of the time series econometric model was checked through cointegration analysis and found that there is no spurious regression. Classical and robust procedures were employed for the estimation of the parameters. The empirical results reveal that the overall fit of the model improves in case of LTS technique, while the significance of the predictors changes significantly in cases of both countries due to the removal of outliers from the data. Thus, empirical findings exhibit that the results, obtained through LTS, are better than LS techniques. [ABSTRACT FROM AUTHOR]

The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap has become a policy issue considering ever-increasing factors and their influence on this relation. Most existing studies have explored this interaction from a general perspective, or for developed countries. This paper explores time-series analysis of the dynamic variables and their inter-related influence in both the short and long run on the relationship between modern logistic industry and economic growth—a more specific perspective, particularly for developing countries. Accordingly, we exemplify our analysis by employing the vector autoregression (VAR) model to the most updated time series data of investment in the logistics industry and the economic growth of Pakistan from 1990 to 2018. The empirical findings endorse the previous studies' outcomes and recognize the importance of sustainable economic development concerning continuously improving the logistics industry. However, a unidirectional relation is observed that economic growth leads to developing the logistics industry—economic growth exerts a significant demand-pull effect on Pakistan's logistics. It implies that logistic industrial development is comparatively quicker in the geographical areas where economic growth is higher than those areas where economic growth is low. To conclude this study's findings, logistics industry reforms should prioritize the selected geographical areas in improving the economy that would lead to the modern logistics industry's development. As the model adopts Pakistan's context, the overall statistical analysis can be generalized to other developing economies. These results would be of particular interest to strategy makers working in developing countries and help them design and develop modern transportation and logistics, coupled with interlinked technological factors, which would attract investment in the logistics industry for sustainable economic development. [ABSTRACT FROM AUTHOR]

Current study was conducted in the Department of Business Administration, National College of Business Administration and Economics, Multan Campus, Pakistan during 2019. The principal objective of the study is to observe the relationship of manufacturing value added (MVA), agriculture value added (AVA), and Pakistan's economic growth. Existence of long run relation among AVA, MVA and economic growth is checked by using annual time series data for the period of 1972 to 2017 collected from World Bank. Results of the study show that (AVA), (MVA), domestic investment (DI), trade openness (TO) and labor force (LF) have long-run cointegrated relationship with GDP. The Granger causality analysis shows that there is bidirectional relationship between (AVA) and GDP. Similarly, TO and AVA have bidirectional relationship between each other. While the GDP granger cause (DI), (TO), (MVA) granger cause (AVA), (DI) granger cause (MVA), (TO) granger cause (MVA), (LF) granger cause (MVA). It is also found that there is Bi-variate co-integration among GDP, AVA, MVA, DI, TO and LF. It is concluded that improvement in agriculture value added and manufacturing value added means increase in economic growth of Pakistan. Additionally, study suggest that agriculture value addition could be improved by using the modern technology. [ABSTRACT FROM AUTHOR]

This study aims to analyse the impact of public spending on economic growth in Pakistan. Various econometric techniques have been applied to estimate the relationship among public spending on education, health, road length, defence, trade openness, worker remittances, total cropped area and economic growth. Pakistan' economic growth rate fluctuated from 1972 to 2014. During this period for some years, the economic growth was high while it slowed down in some years. The study utilised Annual time series data from 1972 to 2014. Empirical evidence suggests that public spending has a significant positive influence on economic growth. Augmented Dickey-Fuller (ADF) has been used for investigating the unit root in time series data. Johansen's Cointegration test and error correction model (ECM) is applied to estimate the long run and the short run relationship amongst the variables. The long-run analyses revealed the existence of a positive relationship among variables. The coefficient of ECM term (-0.389026) was found to be negative and statistically significant, which validates stable long-run relationship among variables, with a speed of 39 per cent to restore disequilibrium in case of any shock. The empirical estimation reveals that public spending on education, health, total road length, trade openness, worker remittances and total cropped area have a strong positive impact on economic growth. Moreover, the study also examines the impact which Pakistan's economic growth has had on the Agriculture sector. While public spending on defence has failed to contribute to economic growth. The study suggests the allocation of more resources to education, health, transport and communication for increasing Pakistan's economic growth. [ABSTRACT FROM AUTHOR]

This study evaluates the behaviour of Pakistani cotton producer due to exchange rate volatility using the Cobb Douglas production function. The data (1973 to 2018) of different variables collected from various sources. Moving Average Standard Deviation is used to measure the Exchange rate volatility and results confirm the long-run effect of exchange rate volatility on cotton production in Pakistan. For checking the stability of the parameters, cusum and cusumq tests are used and found structural break-through intercept at 1985. The variables, exchange rate volatility, and cotton production have a significant and negative relationship. It shows that the cotton producer in Pakistan has risk-averse behaviour. Another variable, capital-labour ratio has a positive and significant impact on cotton production in Pakistan. [ABSTRACT FROM AUTHOR]

Agriculture is one of the primary contributors to Pakistan's economy. However, over the last few decades, the atmospheric carbon dioxide emission has been amplified to a great extent in Pakistan. This amplification may cause climate change, global warming, and environmental mitigation in Pakistan. This paper empirically investigates the impact of CO2 emissions on the agricultural export trade of Pakistan over the period 1975–2017. Evidence suggests that climate change could be a primary cause for the decline in Pakistan's agriculture export trade; no studies have been carried out for this specific issue, particularly over time. In this paper, the empirical analysis suggests the negative coefficient of agriculture export trade with CO2 emissions subsequently decreases agriculture export trade, which leads to direct impact on Pakistan's economy. Both theoretical and empirical outcomes suggest that the adaptation of clean and green energies and technologies are the key to reduce pollution in Pakistan. Overall, the effects of carbon dioxide emissions on agriculture export trade are stronger in the long‐run dynamics, thus making the finding heterogeneous. Possible initiatives should be taken by the government of Pakistan to improve the agriculture sector and it should also introduce new policies to reduce the emissions of carbon dioxide. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyse the impact of government spending on agricultural growth in Pakistan. The relationship among agriculture value added per worker and public spending on education, health, road length, the number of tube wells in the agriculture sector, improved seed distribution has been estimated through various econometric approaches in the study. Pakistan's agriculture growth has registered mixed trends from 1972 to 2014. Empirical evidence from developing countries suggests that public spending has a profoundly positive relationship with agricultural growth. Agriculture is the second largest sector of Pakistan's economy, accounting for more than one-fifth of Gross Domestic Product (GDP) and employing almost half of the country's workforce. The study utilized time series data for the period 1972 to 2014. The stationarity of time series data has checked through Augmented Dickey-Fuller (ADF) test. Johansen Co-integration test and Error Correction Model (ECM) have employed for the long run and short run empirical estimation. The Co-integration test results show the presence of a long run relationship among the variables. The coefficient of the ECM term (-.537563) in the ECM model is negative and statistically significant, which validates stable long-run equilibrium relationship among the variables, with speed of 53 per cent to restore disequilibrium in case of any shock. The regression results reveal that public spending on education, health and road length has a positive influence on agriculture value addition in Pakistan. The study recommends the allocation of greater resources to education, health and transport and communication sectors for agricultural growth. [ABSTRACT FROM AUTHOR]

A study was conducted in the Department of Agricultural Economics, Sindh Agricultural University, Tandojam, Pakistan during the year 2016. This study is a first attempt of its kind to analyze the extent of market integration in the whole country using an advanced dynamic model, which takes into account the unobserved transaction costs via thresholds. It is based on secondary data, monthly wholesale price data collected from five regional markets from January 1988 to April 2011. Price series were tested for stationarity with the Augmented Dickey Fuller (ADF) test and it was found that all prices are integrated of order one. Co-integration was also identified using Johansen's co-integration test. Firstly, Vector Error Correction Model (VECM) was applied to the data to analyze the extent of market integration. The Threshold Vector Error Correction Model (TVECM) with a band of non-adjustment was then applied to incorporate transaction costs, without relying on observations for these costs. It was found that linear VECMs provide misleading results as compared to TVECMs. Short-run adjustments in the TVECM model provide further insight depending on regimes as well as on the markets. In most cases, higher and significant adjustments were found in the upper regime. Lahore market showed the highest adjustment of 68 percent, whereas Hyderabad market adjusted for 34 percent in the upper regime. Multan market adjusted significantly to the shock in Lahore market with 65 and 36 percent in lower and upper regimes, respectively. [ABSTRACT FROM AUTHOR]

This study investigates the spatial price transmission among major wheat and rice markets of Pakistan using their monthly retail prices. For analysis Vector Error Correction Model and Co-integration approach were employed. Results showed that wheat and rice market prices are integrated. Some markets have positive or negative transmission shocks on each other due to the different geographical locations and transport infrastructure. All the wheat markets are adjusted to price changes in the long run equilibrium except few markets. Unidirectional and bidirectional causality exists between wheat and rice markets. Bad and poor infrastructure is a major impediment to price transmission among the markets. These market imperfections lead to food insecurity in the country. Government should formulate better policies and develop infrastructure towards better and efficient market function. The results of this study will help the policy makers to formulate a better policy to enhance marketing function to overcome food insecurity situation. [ABSTRACT FROM AUTHOR]

Pakistan with highest number of terrorism related deaths of any country over the past decade, the number exceeding the total terrorism related deaths for both the European and North American continents, provides an ideal laboratory to study impact of terrorism on the macroeconomy. Quasi-Structural VAR, Vector Error Correction Model, Impulse Response Functions and Granger-Causality tests on a sample that covers over 4500 terrorist incidents and consequent 10, 200 deaths [from 1973 to 2010] are employed to study the relationship between terrorism and the macroeconomy. One of the major advantages of the current methodology is that it not only enables one to circumvent the heterogeneity biases inherent in cross-country studies but it also allows distinguishing between short and long-run effects. It is documented that cumulatively terrorism has cost Pakistan around 33.02% of its real national income i.e. terrorism costs Pakistan around 1% of real GDP per capita growth every year. [ABSTRACT FROM AUTHOR]

Pakistan is facing an energy crisis and is also severely affected by climate change. Moreover, Pakistan is not doing well as far as health outcome indicators are concerned. The causal nexus among energy, environment, and health outcomes is well-established in literature. Besides, financial development also grabs the attention of health outcome literature as financial development can play a significant role in improving health outcomes. Thus, this study was conducted to test the causal nexus among energy consumption, environmental degradation, financial development, and health outcomes in the case of Pakistan. This study proxies health outcomes with life expectancy and infant mortality. Time series data have been analyzed through different econometric techniques, such as unit root tests, cointegration techniques, causality techniques, and cointegration regressions. Moreover, this study not just discovers the causal direction among variables but also determines the strength of causality through variance decomposition. Results of the study confirm that all variables of the study are cointegrated in the long run. The causality analysis reveals that unidirectional causality is running from energy consumption and environmental degradation to health outcomes, whereas bidirectional causality is found between financial development and health outcomes in the long run. Besides, this study also determines the effect of energy, environmental degradation, and financial development in the health outcome model and finds that energy and financial development can help Pakistan to improve health outcomes. Policy implications are recommended for Pakistan. [ABSTRACT FROM AUTHOR]

Developing countries, including Pakistan, need a considerable effort to withstand economic growth; however, these countries have to cope with greenhouse gases emission and other environmental concerns. Financial advancement gives rise to modern, sometimes even innovative and energy-efficient technologies and, thus, contributes to a decline in energy usage among market entities: organizations and households. The current study explores the nonlinear asymmetric relationship between economic growth (Y) and the selected exogenous variables in Pakistan by incorporating time series data spanning from 1971 to 2016. Economic growth was considered as a target variable, while energy consumption (EC), electric power consumption (EPC), financial development (FD), and energy imports (EM) were considered independent variables. To investigate cointegration among the given variables, a nonlinear ARDL bound testing approach was employed. BDS independence test was used to check the nonlinearity, and a structural break unit root test was used for testing data stationarity. The findings confirm the presence of co-integration in the selected variables. A symmetric unidirectional significant causality exists running from EPC to Y, while a bidirectional symmetric causality was found between FD and Y. In contrast, any negative shocks in EPC, FD, and EM were found to have a positive asymmetric effect on Y. Meanwhile, a neutral effect was found between EC and Y. The outcomes of this study can provide guidelines for future researchers and policymakers. [ABSTRACT FROM AUTHOR]

This paper examines the effect of remittance income on energy consumption and the economy between 1976 and 2019 in the four highest remittance recipient nations of South Asia. The detailed analysis explores long-run and directional relationships utilizing stationary tests, the panel cointegration test, dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), and Granger causality tests using a Vector Error Correction Model (VECM). The study reveals the presence of long-run relationships among remittances, energy consumption, GDP and urbanization. Cointegrating regression identifies that remittance income, economic growth and urbanization individually have a positive and significant effect on energy consumption in the long-run. Results showed that a 1% increase in remittance income results in a 0.045% increase in energy consumption. Among nations analyzed, this effect was found to be strongly dominant in case of Bangladesh and Pakistan. The statistically significant and negative coefficient of the error correction term confirms long-run causality from remittance, GDP, and urbanization toward energy consumption. Variance decomposition analysis demonstrated that energy usage is heavily impacted by remittance inflows among studied variables. Policy implications of this study suggest that higher remittance inflows will increase energy consumption in South Asian countries, engendering positive economic growth and sustainable development. Image 1 • The effects of remittance on energy consumption studied for South Asian countries. • Novel statistical approaches applied to explore the causality and direction between remittance income and energy use. • Remittance income provides a potential stimulus toward national investments and ensures reliable and clean energy sources. • It is evidence that 1% raise in remittance income results in a 0.045% increase in energy consumption in the long run. • Policy makers can formulate strategic plans for migrant workers to ensure affordable clean energy. [ABSTRACT FROM AUTHOR]

Environmental degradation as a consequence of military activities largely remains a neglected subject, especially in South Asia. To fill this gap, we have investigated the impact of armed conflicts and militarization on the environmental dilapidation of South Asian countries from 1984 to 2019. A second generational unit root test has been applied to check the problem of cross-sectional dependency. Westerlund panel cointegration method is used to analyze the cointegration between selected variables. Long-run and short-run estimates have been calculated using the panel autoregressive distributed lag (ARDL) method. Besides, the Granger Causality test is employed and results indicate the causality runs from armed conflict and militarization to ecological footprint. Empirical estimates also confirm that the military expenditures, internal conflict as well as external conflict have a positive impact on ecological footprint and these results are highly significant both in the long run and short run. Our study also confirms the presence of the Environmental Kuznets Curve in South Asia. South Asia is marred by the aggressive posturing bitterness as witnessed by the sour relationship that exists between Pakistan and India, the two strongest nations in the region. This animosity left them with consistent and incremental growth in defense expenditure. To achieve sustainable development in South Asia it is imperative to initiate peace talks and to impose necessary restrictions on hazardous military operations contaminating the environment. [ABSTRACT FROM AUTHOR]

Planning process focusing on Energy-Environment-Economy nexus heavily relies upon the results of causality studies for policy and decision guidance. These studies are mostly aimed to determine the true direction of the causal-path among key variables such as energy consumption, economic growth and GHGs emissions. However, there are some weak points attached to already available methods and their variants such as Granger type causality tests and Peter and Clark (PC) algorithms based on Graph theoretic approach. Swanson and Granger (1997) [89] used the vector autoregressive (VAR) residuals in the PC algorithms to find the causal ordering in time series. However, these residuals carry only contemporaneous information about cross-variable effect and remove the past information. This study modified the original PC algorithms based on modified R-residuals test to analyze the causal relationship between energy consumption, economic growth and GHGs emissions in Pakistan. The results reveal that, unidirectional causality is running from economic growth towards CO 2 emissions. However, no causality is running from energy consumption towards economic growth and vice-versa. This is due to the fact that, a significant portion of energy is consumed in residential and transportation sectors, both of which does not contribute to economic growth in long-run. [ABSTRACT FROM AUTHOR]

This paper investigates the electricity production from different sources in Pakistan, and the contribution of these sources to economic growth. An ADF (Augmented Dickey-Fuller) unit root test was used to check the variables stationarity, while an ARDL bounds testing approach was used to check the long-term relationship among the study variables. Results illustrate that electricity produced from coal, hydropower, natural gas and nuclear sources has a significant influence on the economic growth of Pakistan. [ABSTRACT FROM AUTHOR]

This study contributes to the extant literature on the nexus among energy consumption, agriculture, capital and economic growth in Pakistan. We use time series data from 1971 to 2014 and employ the Non-linear Autoregressive Distributed Lag (NARDL) model. The NARDL testing results affirms asymmetric co-integration among the variables. Asymmetric causality is noted between positive shocks in energy consumption and economic growth running from energy consumption to economic growth. A feedback effect is found between agriculture and economic growth for positive shocks. A unidirectional nexus is noted between capital and economic growth for both positive and negative shocks. Similarly, the results of a Granger causality test indicate symmetric causality between energy consumption, agriculture, capital and economic growth. This research suggests that policymakers should revisit their policies regarding agriculture and energy sectors by attracting foreigner investors to build new hydropower dams to both affirm the availability of energy to the industrial sector and control the scarcity of water. • Nonlinear nexus examine among energy, agriculture, capital, and economic growth. • Asymmetric nexus observed for Pakistan over the span of 1971–2014. • We examined asymmetric co-integration among the variables. • Asymmetric growth nexus noted between energy consumption and economic growth. [ABSTRACT FROM AUTHOR]

This study aims to explore the casual relationship between agricultural production, economic growth and carbon dioxide emissions in Pakistan. An autoregressive distributed lag (ARDL) model is applied to examine the relationship between agricultural production, economic growth and carbon dioxide emissions using time series data from 1960 to 2014. The Augmented Dickey–Fuller (ADF), Phillips–Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests are used to check the stationarity of variables. The results show both short-run and long-run relationships between agricultural production, gross domestic product (GDP) and carbon dioxide emissions in Pakistan. From the short-run estimates, it is found that a 1% increase in barley and sorghum production will decrease carbon dioxide emissions by 3% and 4%, respectively. The pairwise Granger causality test shows unidirectional causality of cotton, milled rice, and sorghum production with carbon dioxide emissions. Due to the aforementioned cause, it is essential to manage the effects of carbon dioxide emissions on agricultural production. Appropriate steps are needed to develop agricultural adaptation policies, improve irrigation facilities and introduce high-yielding and disease-resistant varieties of crops to ensure food security in the country. [ABSTRACT FROM AUTHOR]