This study investigates the effects of political instability on inflation in Pakistan. Applying the Generalized Method of Moments and using data from 1951-2007, we examine this link in two different models. The results of the 'monetary' model suggest that the effects of monetary determinants are rather marginal and that they depend upon the political environment of Pakistan.The 'nonmonetary' model's findings explicitly establish a positive association between measures of political instability and inflation. This is further confirmed on analyses based on interactive dummies that reveal political instability significantly leading to high (above average) inflation. JEL Codes:E31, E63

This paper examines the long-run relationship between carbon dioxide (CO2) emission and economic growth, financial development, trade, energy consumption, and foreign direct investment in the case of Lithuania by employing time series data of 1989-2018. In particular, this paper aims to test whether the Environmental Kuznets Curve (EKC) relationship for economic growth and financial development holds or not. The autoregressive distributed lag (ARDL) bounds testing procedure is employed for the empirical analysis. The results validate the existence of EKC in the long-run as well as in the short-run since there is an inverted U-shaped relation between CO2 emissions and economic growth. Conversely, we could not validate the EKC relationship between CO2 emissions and financial development. Trade and energy consumption are other significant determinants of CO2 emissions. The causality analysis results show that unidirectional causality runs from economic growth to CO2 emissions and trade to CO2 emissions. The validity of the EKC hypothesis indicates that Lithuania can achieve short-term, medium-term, and long-term climate change mitigation and adoption goals and objectives approved by the Parliament of the Republic of Lithuania without deteriorating its economic growth. 8.5 %, 6.7 %, 4.5 %, 3.7 %, 3.5 %, 2.4 %, 1.9 %, and 0.6 % respectively. These estimates are based on the Eurostat data. For further details on Lithuania

In recent years there has been a growing interest in academics, international policy institutions and central banks1 in developing small-to-medium, even large-scale, open economy macroeconomic models called Dynamic Stochastic General Equilibrium (DSGE) models based on new-Keynesian framework.2 The term DSGE was originally used by Kydland and Prescott (1982) in their seminal contribution on Real Business Cycle (RBC) model. The RBC model is based on neoclassical framework with micro-founded optimisation behaviour of economic agents with flexible prices. One of the critical assumptions of this model is that fluctuations of real quantities are caused by real shock only; that is, only stochastic technology or government spending shocks play their role. Later research in DSGE models however included Keynesian short-run macroeconomic features (called nominal rigidities), such as Calvo (1983) type staggered pricing behaviour and Taylor (1980) type wage contracts. Hence this new DSGE modeling framework labeled as new-neoclassical synthesis or new-Keynesian modeling paradigm. 3 This new approach combines micro-foundations of both households and firms optimisation problems and with a large collection of both nominal and real (price/wage) rigidities that provide plausible short-run dynamic macroeconomic fluctuations with a fully articulated description of the monetary policy transmission mechanism; see, for instance, Christiano, et al. (2005) and Smets and Wouters (2003). The key advantage of modern DSGE models, over traditional reduce form macroeconomic models, is that the structural interpretation of their parameters allows to overcome the famous Lucas critique (1976).4 Traditional models contained equations linking variables of interest of explanatory factors such as economic policy variables. One of the uses of these models was therefore to examine how a change in economic policy affected these variables of interest, other things being equal. In using DSGE models for practical purposes and to recommend how central banks and policy institutions should react to the short-run fluctuations, it is necessary to first examine the possible sources,5 as well as to evaluate the degree of nominal and real rigidities present in the economy. In advanced economies, like US and EURO area, it is easy to determine the degree of nominal and real rigidities as these economies are fully documented. In developing economies like Pakistan, where most of economic activities are un-documented (also labeled as informal economy, black economy, or underground economy), it is very difficult to determine the exact degree of nominal and real rigidities present in the economy. However, one can approximate results using own judgments and through well defined survey based methods

Falling energy intensity (increasing efficiency) is believed to be a result of more efficient production methods that have evolved over time, indicating overall sustainability in the production process. The objective of this study is to investigate the diminishing trend of energy intensity and the related volatilities in growth of energy consumption and income growth through the energy–growth nexus. The country specific long-run and short-run causal relationships among real energy consumption per capita, real GDP per capita, and the volatilities of growth in income and the growth in energy consumption are established using the method proposed by Yamamoto–Kurozumi within a cointegration framework in 48 countries. The overall findings suggest that energy intensity is falling, in conjunction with the existing evidence on the energy–growth nexus in most of the countries studied; hence, implicitly this confirms sustainability. The results based on volatility analysis show a significant decrease in energy use in response to increasing income growth volatility. The negative effects of income growth volatility on energy consumption are usually countered through compensation measures, with subsidies provided to households and producers in order to smooth the energy consumption behaviours in those economies.