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This study aims to achieve two main objectives; first, it provides a brief but critical description of the empirical literature on the environmental Kuznets curve (EKC) in terms of history, origin, micro-foundations, measurement of environmental degradation, methodologies and samples. Second, it examines the curious attraction of the EKC despite considerable criticism it has attracted over time. The motivation stems from the mixed results probably due to different econometric techniques, sample periods, country-specific factors and environmental indicators used to test EKC. The study concludes that of course, the EKC has attracted a great deal of criticism, but its survival power is undeniable. Different taxonomies of the approaches to explain income-environment nexus have been established by various commentators producing different results under different scenarios. It is still equally important among researchers to interpret the relationship between income and pollution due to its charismatic characteristics; therefore, the empirical literature on EKC continues to grow despite criticism on its validity and assumptions. However, we should not be convinced that economic growth on its own will solve environmental ills. The proposition that affluent countries will invest heavily to level off and gradually contain their environmental pollution should not be persuaded. Therefore, policymakers must not encourage unlimited economic growth to cure environmental problems.

The main objective of the present study is to examine the determinants of greenhouse gas emissions in Canada using panel data of 10 provinces from 1990 to 2019. The pooled ordinary least squares method is used to estimate the models. The main findings of the basic model show that provinces with larger populations, younger ages, and more income produce higher levels of greenhouse gas emissions. The results of the extended model (per capita greenhouse gas emissions as the dependent variable) show that only five factors (out of ten potential determinants identified)—oil production per capita, gas production per capita, motor vehicles registered per capita, electricity generation intensity, and heating degree days—are significant determinants of per capita greenhouse gas emissions. The results also reveal that the provinces with older populations have lower per capita greenhouse gas emissions in Canada. However, both trend variables played an important role in explaining the greenhouse gas emissions per capita in Canada. Moreover, there were no significant differences among the patterns of the per capita greenhouse gas emissions in Canada after 2005.

PurposeThe empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes their estimates unreliable. This paper aims to investigate the relationships between climate change and agriculture and test the potential reverse causality and endogeneity of climatic variables to agriculture.Design/methodology/approachThis study introduces a geographical instrument, longitude and latitude, for temperature to assess the impact of climate change on agriculture by estimating regression using IV-two-stage least squares method over annual panel data for 60 countries for the period of 1999-2011. The identification and F-statistic tests are used to choose and exclude the instrument. The inclusion of some control variables is supposed to reduce the omitted variable bias.FindingsThe study finds a negative relationship between temperature and agriculture. Surprisingly, the magnitude of the coefficient on temperature is mild, at least 20 per cent, as compared to previous studies, which may be because of the use of the instrumental variable (IV), which is also supported by an alternative robust measure when estimated across different regions.Practical implicationsThe study provides strong implications for policymakers to confront climate change, which is an impending danger to agriculture. In designing effective policies and strategies, policymakers should focus not only on crop production but also on other agricultural activities such as livestock production and fisheries, in addition to national and international socio-economic and geopolitical dynamics.Originality/valueThis paper contributes to the growing literature in at least four aspects. First, empirical settings introduce an innovative geographical instrument, Second, it includes a wider set of control variables in the analysis. Third, it extends previous studies by involving agriculture value addition. Finally, the effects of temperature and precipitation on a single aggregate measure, agriculture value addition, are separately investigated.

The main objective of this paper is to examine the relationship between employment and economic growth in developed and developing countries over the period of 1970–2019. As documented in the literature in the past, economic growth in most developing countries has been less job-generating than in developed countries, even though high economic growth is observed in most of the developing world, indicating jobless growth. Based on the Cobb–Douglas production function, we developed an employment demand model to find the employment elasticity with respect to economic growth using working hours and population as explanatory variables. The main findings of the present study reveal that the employment elasticities with respect to GDP are positive and significant in developing and developed countries. But in the developing countries, the employment elasticity is relatively very low (0.11 to 0.15) compared to the developed countries (0.43 to 0.48), which led to the conclusion that a possibility of jobless growth exists in these countries. The findings of the study imply that policymakers should focus more on employment-led growth policies instead of growth-led employment policies, especially in developing countries.

The present study investigates the relationship between nitrous oxide emissions and economic growth using the ARDL bounds testing approach in Canada over the period of 1970–2020. The agricultural land use and exports are included in the estimated models as additional control variables. The empirical findings confirmed the environmental Kuznets curve hypothesis when total N2O emissions are used as a dependent variable in the case of Canada, and similar results are found when we used agricultural induced N2O emissions as a dependent variable. The results also indicate that Canada is already in the decreasing segment of the Kuznets curve, and the turning point of GDP per capita for the total N2O emissions is$41,718, while for agricultural induced N2O emissions, it is $ 38,825. Our empirical evidence confirms that agricultural land use had a positive and significant effect on total N2O emissions, while a negative but insignificant effect in the case of agricultural induced N2O emissions. However, Canadian exports are negatively associated with total N2O emissions as well as agricultural induced N2O emissions, but it requires more stringent laws to curb N2O emissions-oriented exports to keep the ecosystem in balance in the short-run and intends to meet its long-term target of reducing emissions as it progresses towards Canada’s 2050 net-zero ambition.

Canada is one of the most emission-intensive economies in the world and the big challenge for Canada and its provinces is in how to mitigate the GHGs while keeping the same pace of economic growth. This paper’s main objective is to examine the relationship between greenhouse gas (GHGs) emissions and clean growth using cross-sectional data for Canadian provinces from 1995 to 2019. Based on the results of the cross-sectional dependence, slope heterogeneity, and Hausman test, the study applied the pooled mean group (PMG) estimators. For the robustness of the results, the study also provided the results of augmented mean group (AMG) estimators. The results of Westerlund’s test show that the variables of the estimated models are cointegrated in the long run except in the case of the carbon intensity (GHGs/Energy) model, while no short-run relationship was observed. The main findings of both estimators show that an inverted U-shaped relationship exists in the case of the carbon intensity model. In contrast, as expected, a U-shaped relationship exists in the case of the energy intensity model. The results also confirmed that Canada reduced its GHGs emissions after 2005 and that GHGs emissions and energy intensity are decreasing over time. At the province level, only Alberta has no long-run relationship as regards carbon intensity and energy intensity, while Nova Scotia and British Colombia have no long-run relationship as regards energy intensity. In terms of tipping points, Canada is in the increasing phase of the inverted U-shaped curve in the case of carbon intensity, while in the decreasing phase of the U-shaped curve in the case of energy intensity. There is a significant decrease in greenhouse gas emissions per capita at the provincial level compared to the 2005 base levels. It is imperative to reduce greenhouse gas emissions per capita in Canada and its provinces over time by gradually rolling out energy-saving incentives rather than by using more efficient energy-saving technology. The government of Canada should shift towards low-carbon energy and renewable sources which emit fewer greenhouse gases per unit of energy produced.

This paper analyses the relationship between Nitrous Oxide emissions, agricultural land use, and economic growth in Pakistan. Agriculture largely contributes to Nitrous Oxide emissions. Hence, models of agriculture induced Nitrous Oxide emissions are estimated in addition to models of total Nitrous Oxide emissions. Estimated models accommodate more flexible forms of relationship between economic growth and emissions than those of the widely adopted models in testing the Environmental Kuznets Curve. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach to co-integration and the vector error correction model approach is applied to test the Environmental Kuznets’s Curve hypothesis for Pakistan and to detect the directions of causality among variables using the time series data for the period 1971 to 2012. Results indicate that an N-shaped rather than an inverted U-shaped relationship exists in the case of Pakistan. The tipping values for total Nitrous Oxide emissions and agriculturally induced Nitrous Oxide emissions indicate that Pakistan passes through a phase of increasing environmental degradation. Increases in agricultural land use and per capita energy use will increase the level of Nitrous Oxide emissions. However, controlling Nitrous Oxide emissions from agricultural land use and per capita, energy use without adversely affecting economic development will be a serious policy challenge for Pakistan.

This paper evaluates the potential impact of education levels of immigrants and Canadian-born on economic growth in Canada and its smaller provinces by using data for the period 2006–2013. We specify a production function in which levels of educational attainments of immigrants and Canadian-born workers are entered separately. Feasible generalized least square (FGLS) method is applied to estimate the production function separately for all immigrants, and also for established immigrants (those who have been in Canada for 10 years or longer). The results show that all educational levels of immigrants have positive and statistically significant effects on economic growth. A similar conclusion applies to Canadian-born workers, although the impacts of their university degree holders is lower than that of immigrant university degree holders. Both immigrant and Canadian-born workers have smaller effects on economic growth in smaller provinces, which have attracted larger numbers of immigrants in recent years. The results also show that the economic growth effects are similar for all and established immigrants. Although these results are consistent with previous findings on discounting of immigrants’ educational credentials, more data are needed to strengthen their validity. We also suggest that the higher economic growth impact of immigrant university degree holders than that of Canadian-born is indicative of greater social returns to higher education resulting from increased diversity of population which in turn, as some previous studies suggest, can result in increased technological innovation, new ideas, and production of a wide variety of goods and services.

This paper explains sectoral re-allocation as a factor underlying the jobless growth for Pakistan by using aggregated employment data for seven sectors of the economy over the time period 1967-2008. The analysis employs four commonly used measures of sectoral reallocation proposed by Lilien (1982), Groshen and Potter (2003), Rissman (1997), and Aaronson, Rissman, and Sullivan (2004). Recent changes in the use of capital-based foreign technology have resulted in substitution of labour with non-labour inputs. Employment shifts between industrial sectors are often witnessed as indicators of structural change in an economy. The findings of this paper suggest that the economy of Pakistan underwent structural changes during the periods of recession and recovery. It appears that the structural changes were more pronounced around the time of the 1969 recession than that of 1991. A plausible explanation for this result might be the significant shifts in employment from agriculture towards the services sectors. It is concluded from evidence that sectoral reallocation is one of the major causes of the jobless growth in Pakistan.

State Bank of Pakistan (SBP) has mandate of price stability along with output growth. However, inflation deviation from the announced target is common. Employing impulse response functions and variance decomposition, over the period, 1991Q1-2007Q4,this paper attempts to explain why inflation targets have been missed in Pakistan. The results are indicative that inflation gap responds to shocks in government credit from State Bank, world crude oil price, real effective exchange rate and money supply. The response is more prominent in case of government credit from central bank. On the other hand, variance decomposition analysis suggests that most of the variation in deviation from the target is explained by its own lagged values followed by variation in government loan from central bank.