economics research papers india

Environmental sustainability, trade and economic growth in India: implications for public policy

International Trade, Politics and Development

ISSN : 2586-3932

Article publication date: 10 November 2020

Issue publication date: 14 December 2020

Based on the hypothesis of the environmental Kuznets curve (EKC), the purpose of this study is to investigate the relationship between environmental pollutants (as measured by CO 2 emissions) and GDP for India, over the period 1980–2012. The presence of an inverted “ U ” shape relationship is examined while controlling for factors such as the degree of trade openness, foreign direct investment, oil prices, the legal system and industrialization.

Design/methodology/approach

To verify whether the EKC follows a linear, quadratic or polynomial form, autoregressive distributed lag (ARDL) bounds testing approach for cointegration with structural breaks is adopted. The annual time series data for carbon emissions (CO 2 ), economic growth (GDP), industrial development (industrialization), foreign direct investment and trade openness have been obtained from World Development Indicators online database. Crude oil price (international price index) for the period is collected from the International Monetary Fund. Data for total petroleum consumption are collected from the US Energy Information Agency. Data for economic freedom variables are from the Fraser Institute's Economic Freedom Index's online database.

The findings support the existence of inverted U -shaped EKC in the short-run, but not in the long-run. A linear monotonic relationship has also been estimated in select model specifications. Additionally, trade openness has been estimated to reduce emissions in models, which incorporate FDI. Else, where significant, its impact on carbon emissions is adverse. A rise in fuel price leads to reduction in carbon emissions across model specifications. Further, the lower size of government degrades the environment both in the long-run and short-run.

Practical implications

Given the existence of the pollution haven hypothesis, wherein more trade and foreign direct investments cause environmental degradation, the paper proposes formulation of appropriate regulatory mechanisms that are environmentally friendly. Additionally, India's new economic policies, favoring liberalization, privatization and globalization, reinforces the need to strengthen environmental regulations.

Originality/value

Incorporation of economic freedom as measured by the “Size of Government” in the EKC model is unique. “Size of Government” deserves a special mention. The rationale for including this explanatory variable is to understand whether countries with lower government size are more polluting. After all, theory does suggest that goods and services, which have higher social cost vis-à-vis private cost, shall be overproduced in economies that adopt more market-friendly policies, necessitating government intervention. In the study, size of government is measured as per the definition and methodology adopted by Fraser Institute's Economic Freedom of the World Index.

• Environmental Kuznets curve (EKC)
• Trade openness
• Foreign direct investment
• Economic freedom
• Size of government
• Autoregressive distributed lag (ARDL)

Sajeev, A. and Kaur, S. (2020), "Environmental sustainability, trade and economic growth in India: implications for public policy", International Trade, Politics and Development , Vol. 4 No. 2, pp. 141-160. https://doi.org/10.1108/ITPD-09-2020-0079

Emerald Publishing Limited

Copyright © 2020, Aparna Sajeev and Simrit Kaur

Published in International Trade, Politics and Development . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Energy has always been closely associated with economic growth and development. However, in the process the negative externalities associated with the usage of energy have not been taken care of adequately. Adverse externalities are major roadblocks to sustainable development. Climate change caused by anthropogenic global warming can undoubtedly be considered as the major hurdle to sustainable development. Left unmanaged, climate change may reverse the development progress and compromise the safety and security of present as well as future generations. According to the IPPC's fifth assessment report (AR5), the period between 1983 and 2012 has been the warmest 30-year period in the Northern Hemisphere. It is primarily caused by increased concentration of CO 2, CH 4 and nitrous oxide since industrialization. In fact, the concentration of CO 2 in 2012 was 40% more than it was in the mid-1800s [1] . Fossil fuel and land use changes primarily cause global increase of CO 2 concentration. Crude oil accounted for 39% of the world total primary energy source in 2017 and contributed to 33% of the global CO 2 emissions. In 2018, CO 2 emissions reached a historic high of 33.1 Gt. Nearly two-thirds of global emissions for 2011 originated from only 10 countries, with shares of China (25.4%) and the United States (16.9%) far surpassing the rest. Combined, these two countries alone produced 13.2 Gt of CO 2 . The two high emitter countries are followed by India, Russian Federation, Japan, Germany, Korea, Canada, Islamic Republic of Iran and Saudi Arabia. Further, by 2012, Brazil, Russia, India, China and South Africa (BRICS) countries emissions had increased to 39% of the total world emissions, from 27% in 1992. As represented in Figure 1 , a quarter of the total world emissions in fact are from China alone. India presently is the third largest emitter of CO 2 in the world. The emissions of Brazil and India as a percentage of total emissions in the world doubled in 2012 compared to 1992. Over the same period, Russia and South Africa's contribution to total world emissions decreased to 5 (from 9.44%) and 1% (from 1.5%), respectively, over the same period.

Globally, crude oil prices fell from 100US$ per barrel in mid-2014 to below 30US$ per barrel in early 2016. Natural gas and coal prices also fell during this period. International Monetary Fund (IMF) quantifies lower fossil fuel prices to act as a form of economic stimulus. According to World Energy Outlook ( WEO, 2015 ), lower oil prices not only supports growth, but stimulates oil use as well. It also diminishes the case for efficiency investments for switching to alternative fuels.

For emerging economies such as India, [2] it is important to understand how much environment friendly its economic growth is India's GDP growth rate and carbon emissions increased steadily over the period 1980–2013. India's GDP growth rate peaked at around 10% in 2010 and then slowly moved down to around 7% by 2013. In Figure 2 , India's real GDP and carbon emissions from total energy consumption, as well as, from petroleum consumption for the period 1980–2013 are presented. India's real GDP witnessed a steady increase from around US $0.2tn in 1980 to around US$1.48tn in 2013. A similar increasing pattern is witnessed in carbon emissions from total energy consumption, which increased from around 291 million metric tonnes in 1980 to around 1830 million metric tonnes in 2012. Similarly, India's carbon emissions from petroleum consumption also increased from around 100 million metric tonnes in 1980 to around 435 million metric tonnes in 2012.

Government policies in developing countries are crucial in deciding the flow of foreign direct investment (FDI) to these countries. According to the UN trade body, India is the 9th largest recipient of FDI of US$52 bn in 2019. The net inflow of FDI as a percentage of GDP though is considerably small for India, it has increased from 0.02% in 1991 to 3.62% in 2008. By 2019, the net flow of FDI is at 1.76%. India's new economic policy of liberalization, privatization and globalization adopted in 1991 led to this increase in FDI inflow/outflow. However, one of the key factors influencing foreign investment in developing countries like India, is that they set environmental standards below efficiency levels. As international trade relates one country to another, developing and underdeveloped economies rely on technology transfer through FDI that may reduce pollution in the long-run ( Dinda, 2004 ; Dean, 2004 ; Wheeler, 2000 ).

Pressure is mounting on India to commit for a legally binding agreement on cutting CO 2 emissions. Under such circumstances, the need to examine the impact of various contributing factors to CO 2 emissions cannot be negated. In this regard, an important element to analyze is the impact of GDP on CO 2 emissions. This hypothesized inverted U -shaped relationship between environment pollutant and economic growth in economic literature is referred to as the environmental Kuznets curve (EKC).

Simon Kuznets first proposed the inverted U -shaped relationship in 1955, while explaining the relationship between income inequality and per capita income. The Kuznets curve was adapted in environmental economics literature in 1990's by economists such as Grossman and Kruger (1991) , Shafik and Bandhyopadhay (1992) , Panayotou (1993) and Selden and Song (1994) . The EKC hypothesis summarizes a dynamic process of change – namely, as income of an economy grows over time, emission levels first grow; reach a crest and then start turning down after a threshold level of income ( Y 1 ) has been attained ( Figure 3 ). Further, as the economy reaches income levels higher than Y 2 , the direction of relationship between environmental degradation and per capita income (GDP) changes. Beyond Y 2 , both environmental degradation and GDP move in the same direction. EKC is a long-term phenomenon and does not make an explicit reference to time. It is a development path for a single economy that grows through different stages over time. Other things remaining constant, in their process of development, each country experiences income and emission situations lying on the specific EKC. While a typical EKC is an inverted U -shaped curve, linear and N-shaped curves are also plausible.

Scale effects, technological effects and composition effects are the three channels through which economic growth affects the environmental quality ( Grossman and Krueger, 1991 ). In this initial stage of economic development, pollution increases with increasing output. As, the economy transforms from an industrial to a service economy, the pollution level plateaus. Also, with technical progress like the adaption of cleaner technologies, pollution level further reduces. Thus, scale effect that has a negative impact on the environment dominates the first stage; then with economic growth, composition effect and the technological effect that has a positive impact on the environment start dominating; thereby the inverted- U shaped curve.

International trade is a crucial factor that can explain EKC. As trade volume increases, environmental quality could decline or improve because of opposing directional impacts of scale effect, composition effect and technique effect. The composition effect is associated with two related hypotheses: displacement hypothesis and pollution haven hypothesis (PHH) ( Dinda, 2004 ). The displacement hypothesis states that trade liberalization or openness will lead to the more rapid growth of pollution-intensive industries in less developed economies, as developed economies enforce strict environmental regulations ( Harrison, 1996 ; Rock, 1996 ; Tobey, 1990 ; Dinda, 2004 ). PHH argues that with trade increasing income levels, there will be more demand for a cleaner environment, thereby pushing heavy polluting industries to countries with weaker regulations. PHH refers to the possibility of multinational firms, especially the ones engaged in highly polluting activities, relocating to countries with lower environmental protection rules and regulations. Environmental regulation exerts a moderating effect on the inverted- U shaped relationship with economic development and carbon emissions.

Since EKC is a long-run phenomenon ( Lindmark, 2002 ), the same using time series technique is considered more appropriate ( Akbostanci, 2009 ). As such, we use a time series methodology for the present study. In this study, we hypothesize the EKC between carbon emissions and GDP. The control variables used are, crude oil prices, trade openness, FDI inflow and select variables of economic freedom, especially as captured by size of government.

The flow of the paper is as follows: Section 2 provides the review of literature. This is followed by Section 3 , where the methodology (pertaining to unit root test with structural break and ARDL technique) and data sources are discussed. Empirical results are reported in Section 4 . Finally, in Section 5 , the paper concludes from a broad policy perspective.

2. Review of literature

In last few decades, there has been an increasing attention on how economic growth impacts environmental degradation. Though literature documents this relationship, in general, the causal links and direction of impact remains ambiguous. While reviewing the EKC literature we begin by examining research papers that use similar econometric methodology as adopted in the present research. Thereafter, papers that adopt an alternative methodology have been reviewed. Accordingly, the next two subsections follow:

2.1 Papers based on autoregressive distributed lag (ARDL) econometric methodology

In this subsection, papers that support the EKC relationship are reviewed first, followed by papers that do not support the EKC hypothesis. Thereafter, specific papers that examine the EKC relationship for India are reviewed.

Balaguer and Cantavella (2016) perform a structural analysis on EKC for Spain for the period 1874–2011. In the research paper, real oil prices are used as an indicator of variations in fuel energy consumption. Evidence supports the EKC hypothesis in the long-run, as well as, in the short-run. Further, empirical results support the idea that changes in real oil prices are relevant in order to explain CO 2 emissions. They observe that with a 1% rise in oil prices, the CO 2 emissions reduce by 0.4% in Spain. They also check the possibility of flatter EKC curve in presence of technological effectiveness put forward by Dasgupta et al. (2002) and reject the same for the sample period for Spain. Boluk and Mert (2015) provide empirical evidence for the potential of renewable energy within an EKC framework for Turkey. Using ARDL approach, the relationship between carbon emissions, income and the electricity production from renewable energy sources has been investigated for the period 1961–2010. Based on their analysis, the authors conclude that there is an inverted U -shaped relationship between per capita emissions and per capita real income, supporting the EKC hypothesis in both the long and short-run. Jelbi and Youssef (2015) investigate the dynamic causal relationships between CO 2 emissions, economic growth, renewable and nonrenewable energy consumption, and trade in Tunisia during the period 1980–2009. The authors observe that EKC hypothesis is not supported in the long-run, whereas in the short-run the inverted U -shaped EKC hypothesis is supported. In case of trade, both per capita exports and imports have a positive impact on per capita CO 2 emissions.

The study by Ahmed and Long (2012) hypothesize EKC to investigate the relationship between CO 2 , energy consumption, economic growth, trade liberalization and population density in Pakistan. The study uses an ARDL model approach for a sample period from 1971 to 2009. Two main findings of the study are – first, while there is a long-run inverted U -shaped relationship between variables; there is no evidence to support the existence of EKC in the short-run. Second, trade openness improves the environment only in the short-run. Additionally, Pakistan's population density has been estimated to contribute to environmental degradation.

Tiwari et al. (2013) test the EKC hypothesis for Indian economy by incorporating coal consumption and trade openness. The study employs an ARDL model for the period 1966–2009, and reinforces the results using Johansen cointegration. Based on their analysis, the authors conclude that there is presence of EKC both in the long-run and short-run. Further, both coal consumption and trade openness also contribute to carbon emissions in the long-run. Jayanthakumaran et al. (2012) using ARDL methodology compares the relationship between growth, trade and energy use for India and China. Structural breaks are endogenously determined for the period 1971–2007 using the Lagrange multiplier unit root test proposed by Lee and Strazicich (2003 , 2004) . Further, existence of EKC relationship is established for both India and China. In India, the increase in energy consumption increases per capita emission by 0.97% in the long-run. However, the authors find that when manufacturing – GDP ratio is incorporated in the model, the long-run relationship between the variables no longer exists for India.

2.2 Papers based on econometric methodology, other than ARDL

For the period 1951–1986, Holtz-Eakin and Selden (1995) employ a panel data model for 130 countries. Their findings suggest evidence of diminishing marginal propensity to emit CO 2 as economies develop. Further, the forecast results indicate that global emissions of CO 2 will continue to grow at an annual rate of 1.8%. The study by Apergis (2016) assesses the “emission-income” relationship in EKC hypothesis using common correlated effects, fully modified ordinary least squares and the quantile estimation procedures. The analysis for 15 countries is done using data for the period 1960–2013. The results of the study indicate the presence of a nonlinear link between emissions per capita and personal income per capita across the majority of 15 countries. The paper concludes by recommending the use of more renewable sources of energy to reduce energy dependence and ensure energy security.

Using the panel data over the 1996–2012, Li et al. (2016) estimate the impact of economic development, energy consumption, trade openness and urbanization on the carbon dioxide, liquid waste and solid waste emissions for 28 Chinese provinces. The generalized method of moments estimate (GMM) estimator, as well as, ARDL estimates (long-run as well as short-run) support the EKC hypothesis for three major pollutants, namely, carbon dioxide, industrial waste water and industrial waste solid emissions in China. The results also indicate that trade openness and urbanization leads to environmental degradation in the long-run (estimates are insignificant in the short-run) in China, though the magnitude of severity varies across different pollutant emissions.

Robalion-Lopez et al. (2015) analyze various conditions for fulfillment of EKC hypothesis in the medium term for an oil-producing developing country, Venezuela. Using a model based on Kaya and Yokobori (1993) , they use data from 1980 to 2010. The value of the GDP, the energy consumption and the CO 2 emissions from 2011 to 2025 have also been estimated under four different scenarios which constrain GDP, productive sectoral structure, energy intensity and energy matrix. Based on the analysis, authors conclude that Venezuela does not fulfill the EKC hypothesis under any of the scenarios. The results show that Venezuela in 2010 is still in the first stage of the EKC. However, the authors state that the country could be on the way to achieve environmental stabilization in the medium term, if economic growth is accompanied with increasing use of renewable energy, appropriated changes in the energy matrix and in the productive sectoral structure.

Saidi and Hammami (2015) use a dynamic panel model to examine the impact of energy consumption and CO 2 emissions on economic growth of 58 countries. The results show that energy consumption and FDI have a positive and significant impact on economic growth in the panel of countries and that CO 2 emissions have a negative and statistically significant impact on economic growth. Zakaraya et al. (2015) analyze the interactions between total energy consumption, FDI, economic growth and CO 2 emissions in the BRICS countries for the period 1990–2012. The major contribution in their study is the consideration of environmental pollution and the amount of carbon emissions caused by foreign investment. Their study reinforces the view that environmental policies of developing countries are incomplete. Resultantly, foreign investors who are limited by policies in their own countries, are attracted to developing economies resulting in environmental degradation.

Tutulmaz (2015) investigates the EKC relationship between CO 2 emissions and GDP per capita for Turkey for the period 1968–2007. An initial phase of an inverted U -shape EKC relationship has been determined for Turkey from their estimations. Rather surprisingly, this result is conflicting with that of similar models for Turkey. Basis that, the authors title their paper as, “Environmental Kuznets Curve time series application for Turkey: Why controversial results exist for similar models?” Wang et al. (2015) provide specific application of EKC in explaining the effect of population growth on environment using overlapping generation model. Further, using data for 30 provinces from China between 2001 and 2010, effects of population growth on the population–income relationship is examined. The empirical analysis supports the presence of an inverted U -shaped relationship between polluting emissions and income. Simulation results in the paper illustrate that higher population growth makes the EKC steeper with higher peaks.

Pao and Tsai (2011) examine the dynamic relationship between CO 2 emissions, energy consumption and economic growth in Brazil for the period 1980–2007. The results support the EKC hypothesis as energy–income relationship appears to be an inverted U -shaped curve. Ghosh (2010) probes the relationship between CO 2 emission, energy supply and economic growth while controlling investment and employment in India for the period 1971–2006. The empirical results (using ARDL), establishes a long-run equilibrium among the variables. The results show the presence of bi-directional causality between CO 2 emissions and economic growth, justifying India's stand against mandatory emissions cut by developing nations. Further, results also establish presence of unidirectional causality from economic growth to energy supply and energy supply to carbon emissions.

Cole (2004) constructs a model to examine the evidence for the PHH and to assess the extent to which trade, through pollution haven effects and structural change has contributed to the EKC relationship. Using detailed data on North–South trade flows for pollution intensive products, the evidence for the PHH is assessed. EKC analysis for six air pollutants and four water pollutants has been undertaken; and pollution haven effects have not been found to exist for all pollutants. Also, when found, their economic significance has been limited. The author also interprets that the share of manufacturing output in GDP has a positive and statistically significant relationship with pollution. Hill and Magnani (2002) too examine the EKC relationship for a panel of 156 countries using generalized least squares model. However, they find no evidence of an inverted U -shaped EKC hypothesis as emissions monotonically increase with income per capita.

List and Gallet (1999a , b) use a state-level panel data of sulfur dioxide and nitrogen oxide emissions for the period 1929–1994 for several states of America to test the appropriateness of the “one size fits all” reduced-form regression used in EKC literature. The results provide evidence to support the presence of inverted- U path. Further, the results also indicate that state-level EKC's differ from one another and over time as well, which restricts cross-sections to undergo identical experiences over time. Another observed trend is that states whose EKCs peak to the left of the traditional confidence interval tends to have higher per capita emissions of the respective pollutant presumably because states with higher per capita emissions react more quickly to adopt policies designed to reduce pollution.

To summarize, while literature on EKC is rich, the specific EKC relationship is unique to each country. Resultantly, the motivation to take up the present EKC study for India. Also, since the environment impact of India's New Economic Policy (which promotes liberalization, privatization and globalization), remains largely unexplored, the present paper analyzes the same.

3. Research methodology and data sources

The objective of the study is to verify the EKC hypothesis for India. In order to do so we examine whether the EKC follows a linear, quadratic or polynomial form. Though literature predominantly discusses quadratic form, we also examine if a cubic form EKC relationship exists between environmental pollutants and economic growth. The time period of our study is from 1980 to 2012.

In this study, to test the validity of EKC hypothesis the following equation has been estimated [3] : (1) EP t = α t + β 1 Y t + β 2 Y t 3 + β 3 Y t 3 + β 4 Z t + e t

EP: It represents environmental pollutant as measured by carbon emissions (CO 2 ) . In our study, carbon emissions (CO 2 ) are from the consumption of petroleum. CO 2 is in million metric tons.

Y: It represents real GDP per capita. It is the gross value of goods and services produced within the domestic territory of India in a specific period, adjusted for inflation. Real GDP divided by mid-year population provides real GDP per capita. Data are in constant 2005 US$. As represented in Eqn (1) , its square and cubic form is also incorporated.

Z: It represents other variables such as trade openness, foreign direct investment, crude oil price, petroleum consumption and economic freedom as measured by Size of Government. Each of these is hereby described:

Trade openness is total value of import and exports as a percentage of GDP; FDI is net inflows as a percentage of GDP; Crude oil price is the simple average of three spot prices: Dated Brent, West Texas Intermediate and the Dubai Fateh (Base year −2005); Petroleum consumption is the total value of crude petroleum consumed. It is in thousand barrels per day and economic freedom as measured by “Size of Government”.

t : represents time

α ,   β : constant term and coefficient parameters

e : error term

β 1 , β 2   and   β 3 jointly determine the shape of EKC curve, i.e. a linear, inverted- U or N type EKC curve.

A linear relationship implies: β 1 > 0 and β 2 = β 3 = 0 .

An inverted U -shaped relationship implies: β 1 > 0 ,     β 2 < 0     and   β 3 = 0.

A U -shaped curve implies: β 1 < 0 ,     β 2 > 0   and   β 3 = 0.

A N -shaped figure or a cubic polynomial relationship implies: β 1 > 0 ,     β 2 < 0     and β 3 > 0.

The variables are briefly explained:

Data: The annual time series data for carbon emissions (CO 2 ), economic growth (GDP), industrial development (industrialization), FDI and trade openness has been obtained from World Development Indicators (WDI) online database. Crude oil price (international price index) for the period is collected from IMF. Data for total petroleum consumption is collected from the US Energy Information Agency. Data for economic freedom variables are from Fraser Institute's Economic Freedom Index's online database.

To examine the said relationships, unit root tests with structural break, and ARDL technique has been adopted.

Unit root tests: Numerous unit root tests are available in applied economics to test the stationarity properties of the variables. The unit root tests are augmented Dickey–Fuller by Dickey and Fuller (1979) , Phillips–Perron (P–P) by Phillips and Perron (1988) , Ng–Perron by Ng and Perron (2001) and Kwiatkowski–Phillips–Schmidt–Shin by Kwiatkowski et al. (1992) . All these do not have information about structural break points that occur in the series and hence provide biased and spurious results. Thus, in our paper, we perform a breakpoint unit root test similar to that of Perron (1989) . The null hypothesis is that the time series has a unit root with possibly nonzero drift, against the alternative that the process is “trend-stationary”. For carbon emissions, the break point has been estimated in the year 1993, for both the “intercept” and “intercept and trend” model

Autoregressive distributed lag model (ARDL): Cointegration is defined as a systematic comovement among two or more macroeconomic variables over the long-run. The presence of cointegration can be considered as a pretest for possibility of “spurious” correlation among variables. A standard ARDL equation with a dependent variable, y , and two other explanatory variables, x 1 and x 2 will be: (2) Δ y t = β 0 + θ 0 y t − 1 + θ 1 x 1 t − 1 + θ 2 x 2 t − 1 + ∑ β i Δ y t − i + ∑ γ j Δ x 1 t − j + ∑ δ k Δ x 2 t − k + e t where Δ is the first difference operator.

The ARDL method of cointegration analysis was first introduced by Hendry (1995) and extended by Pesaran and Shin (1999) and Pesaran et al. (2001) . An ARDL model gives a simple univariate framework for testing the existence of single level relationship between the dependent and independent variables, when it is not known with certainty whether the regressor are purely I(0) , purely I(1) or mutually cointegrated.

One of the key assumptions in the bounds testing methodology of Pesaran et al. (2001) is that the errors of Eqn (2) must be serially independent. To test for serial correlation of the residuals the Q -stat correlogram test is performed. Since we have a model with autoregressive structure we have to be sure that the model is “dynamically stable”. To test for the stability of the long-run relationship over time, the cumulative sum of recursive residuals (CUSUM) [5] test is utilized. This stability test is appropriate in time series data, especially when we do not know when structural change might happen.

θ 0 = θ 1 = θ 2 = 0 (No long-run relationship exists).

θ 0 ≠ θ 1 ≠ θ 2 ≠ 0 (A long-run relationship exists).

The computed F -statistic value is evaluated with the critical values tabulated in Pesaran et al. (2001) . Pesaran et al. (2001) supply bounds on the critical values of the asymptotic distribution of the F -statistic. They give lower and upper bound critical values for various situations (different number of variables, ( k +1)). In each case, the lower bound is based on the assumption that all the variables are I(0), and the upper bound is based on the assumption that all of the variables are I(1). If the computed F -statistic falls below the lower bound one concludes that the variables are I(0), so no cointegration is possible. If the F -statistic exceeds the upper bound, it is concluded that cointegration exists. Finally, if the computed F -statistic falls between the lower and upper bound values, then the results are inconclusive. Further, if there is evidence of long-run relationship (cointegration) among the variables, ARDL-EC model is used to estimate the long-run relationship and also to estimate the short-run dynamics.

4. Empirical results

4.1 unit root test.

To ensure that none of the variables are stationary at I (2) or beyond that order of integration, breakpoint unit root test has been conducted. All variables have been tested at level and at first differences. Table 1 reports the results of the breakpoint unit root tests with “intercept” and “intercept and trend”. It shows that all variables are stationary at I (0) or I (1).

Thereafter, the ARDL bound testing approach has been applied to examine the long-run relationship between variables. The advantage of bound testing is that it is flexible regarding the order of integration of the series [6] . Following the Schwarz criteria (SC), a lag length of 2 was chosen, for all models. The structural break of CO 2 emissions series estimated at year 1993 is taken across all model specifications.

The aim of the present study is to investigate the relationship between environmental pollutant (as measured by CO 2 emissions) and GDP for India. Following the methodology as developed by Jebli and Youssef (2015) and Jayanthakumaran et al. (2012) , among others, we develop two models based on EKC hypothesis: Model 1 and Model 2 [7] .

The general empirical form of Model 1 is: C O 2 = f ( GDP t ,   GDP t 2 ,   GDP t 3 ,   CrudePrice t ,   Petroleum   Consumption t ,   Trade   Openness t )

Model 1 can be rewritten as an ARDL model with intercept and trend as follows: (3) Δ CO 2 = α 0 + α 1 t + ∑ i = 1 m β 1 i Δ CO 2 t − 1 + ∑ i = 0 m β 2 i Δ GDP t − i + ∑ i = 0 m β 3 i Δ GDP t − 1 2 + ∑ i = 0 m β 4 i Δ GDP t − 1 3 + + ∑ i = 0 m β 5 i Δ Crude   Price t − 1 + ∑ i = 0 m β 6 i Δ Petroleum   Consumption t − 1 + ∑ i = 0 m β 7 i Trade   Openness t − 1 + β 9 CO 2 t − 1 + β 10 GDP t − 1 + β 11 GDP t − 1 2 + β 12 GDP t − 1 3 + β 13 Crude   Price t − 1 + β 14 Petroleum   Consumption t − 1 + β 15 Trade   Openness t − 1 + β 16 Break + β 17 Trend + v t Model 2 is an extension of Model 1 and includes two more explanatory variables, namely, size of government and FDI.

Table 2 reports the results of ARDL bounds testing approach to cointegration in the presence of a structural break in the series. The results show that our calculated F -statistics is greater than upper bound at 1 and 10% levels in models 1 and 2, respectively. This leads us to reject the null hypothesis of no cointegration. This indicates that there is a cointegrating relationship among the variables across models in the long-run. Q -stat for Model 1 and Model 2 are provided in Tables A1 and A2 .

As for the expected sign of explanatory variables other than β 2 , β 3 and β 4 (estimated coefficients of GDP PC , GDP PC 2 and GDP PC 3 , respectively), one expects the coefficient of crude oil price to be negative since an increase in price of oil is expected to reduce oil consumption. Further, the coefficient for petroleum consumption is expected to be positive, as higher consumption is expected to promote pollution. The coefficients of trade openness and FDI may be positive or negative depending upon the level of economic development. In general, if developing economies have less stringent environment regulations, greater trade openness and more FDI are expected to increase pollution. Finally, coefficient of economic freedom index as measured by “Lower Size of Government” is expected to be positive as economies with greater private sector participation may overproduce goods and services for which social costs outweigh private costs. This certainly is the case with pollution emitting industries where negative externalities are immense.

The results of cointegration tests are reported in Table 3 . We proceed with a cubic form for EKC hypothesis for both the models.

In models 1 and 2 [8] , the coefficient of GDP PC remains positive and significant across specifications. For Model 1, the coefficient of GDP PC square and GDP PC cube equals zero implying that there is a monotonic increase in carbon emissions with an increase in per capita GDP. This largely implies that EKC's linear model hypothesis (and not inverted U -shaped hypothesis) is valid for India both in the long-run and short-run. However, in Model 2, in the short-run, presence of an inverted U -shaped EKC has been estimated. Further, as expected, increase in crude oil price has a negative and significant effect on carbon emissions, as the estimated coefficient is negative (and significant) across model specifications. Also, where significant, the coefficient of petroleum consumption is positive. This implies that higher consumption of energy is associated with increase in carbon emissions. This result is also as per expectation. In Model 1, the coefficient of trade openness is positive and significant at 5% level in the long-run. This implies that increase in trade openness is expected to be linked with higher carbon emissions in the long-run. However, in Model 2, the coefficient of trade openness is negative and significant at 1% level, both in the long-run and short-run.

Further, in Model 2, the coefficient of FDI is positive and significant at 1% level in the long-run but negative and significant in the short-run. This implies that an increase in FDI is expected to be linked directly with carbon emissions in the long-run, but not in the short-run. In Model 2, the coefficient of economic freedom as measured by lower “size of government” is positive and significant. This means that periods during which size of government is lower are associated with higher carbon emissions. In Model 2, the coefficient of trade openness and size of government in the short-term corroborates with the long-term relationship established.

In the short-run as expected, the coefficient of the error correction terms is negative and significant across model specification (at 1% level). This corroborates with our established long-run relationship between carbon emissions, GDP PC and other variables. The changes in carbon emissions are expected to be corrected within a year. Further, it is expected that full convergence will take place within a year and reach the stable path of equilibrium. Thus, we may conclude that the adjustment process is fast for the Indian economy.

5. Conclusion and policy recommendations

Based on the hypothesis of EKC, the study investigates the relationship between environmental pollutants (as measured by CO 2 emissions) and per capita GDP for India, over the period 1980–2012. Making use of the ARDL bounds testing approach for cointegration with structural breaks, the presence of EKC has been examined (in two model specifications: both long-run and short-run) while controlling for factors such as oil prices, petroleum consumption and trade openness in Model 1, as also, FDI and size of government in Model 2.

A monotonic relationship is observed between per capita carbon emissions and per capita GDP in Model 1, both in the long-run and short-run. Evidence to support existence of an inverted “ U ” shaped EKC, in India is validated only in the short-run for Model specification 2. This implies that carbon emissions begin to decline, once the threshold level of GDP per capita is achieved.

Rise in fuel price leads to reduction in carbon emissions and increase in petroleum consumption promotes emissions.

Impact of trade openness is ambiguous across model specifications. While in Model 1, the long-run impact of trade openness induces carbon emissions,in model 2, increase in trade is associated with lower levels of carbon emissions. The short-run impact of trade openness in Model 2 is negative (and significant) implying that as the Indian economy opened to trade, in the short-run, the CO 2 emissions reduced.This can be on account of technological and composition effects that are expected with economic growth and FDI inflow in an open economy.

In Model 2, an increase in net FDI inflow has an adverse effect on environment in the long-run, though the short-run impacts on environment are favorable. Some of these findings are in line with those of Pao and Tsai (2011) , Jian and Rencheng (2007) and Havens (1999), as they too have estimated that higher FDI increases environmental degradation. This indicates that India (like other developing countries) attracts FDI in polluting industries, maybe because of lower environmental standards. This incentivizes heavy polluters to move to countries with lower environment regulations. The migration or displacement of “dirty” industries from the developed regions to the developing regions is referred to as “Pollution Haven Hypothesis (PHH)”. The PHH theory of polluting multinational companies coming to countries with lower environmental standards is supported by our results. In addition, the environmental quality could decline through the scale effect as increasing FDI/trade volume raises the size of economy, which per se increases pollution as well.

Our findings indicate that higher economic freedom as measured by lower size of government has a positive impact on carbon emissions. Adverse impact of lower size of government on environment is in sync with the theory of negative externalities as proposed by Stiglitz. This relationship validates the theory that greater participation by the private sector in economic activities of a nation, promotes negative externalities such as those caused by smoke or air pollution. To address concerns of market failure, governments must introduce effective regulations to address climate concerns.

Adopting interventionist policies to control environmental degradation : Several studies ( Tiwari et al. , 2013 ; Jayanthakumaran et al. , 2012 ; Agras and Chapman, 1999 ; Sajeev, 2018 ) have shown that one may expect a delinking between environmental degradation and economic growth beyond the threshold limit, as and when it is attained. In such cases, promotion of economic growth seems to be a sufficient condition for safeguarding environment. However, our finding suggests that growth and carbon emissions go together. Since economic growth cannot be compromised, especially for developing economies such as India, governments need to actively introduce interventionist policies to control environmental degradation.

Rationalizing and phasing of government fossil fuel subsidies: According to the IEA statistics, oil subsidies in India were 29.7bnUS$ in 2014 (Real, 2013). For the same period, China's oil subsidies stood at 11.8bn US$. Such high subsidies need to be reduced and rationalized. IEA reports that removing fossil fuel subsidy can limit carbon emissions by 2.6Gt by 2035, which is nearly half of the reduction needed to limit global warming to 2°C. While the main aim for subsidy is to make it more affordable, especially for the poor and vulnerable, often the impacts are not optimal due to poor targeting and/or associated systemic leakages. Since subsidies reduce the incentive to curb wasteful energy consumption, there is an associated environment cost of subsidy as well. Straining of government budgets in such cases also reduces government's flexibility to invest in greener technologies. To mitigate the adverse social consequences of removal of fossil fuel subsidies, cross-subsidization can be introduced for promoting use of renewable energy sources, as also more energy efficient technologies.

Imposition of carbon tax : The explicit costs of carbon emissions, in general, are paid by the public in the form of rising health care costs and higher food prices due to crop failures. Stern Review ( 2006 ) suggests that climate change is a classic example of market failure. By introducing carbon tax, governments can reduce the gap between private and social cost of fossil fuel consumption. This shall promote more efficient usage and utilization of the fuel as carbon tax increases the price that consumers pay for energy. IMF proposes a global carbon tax at $75 per tonne of carbon to help limit global warming to 2°C above preindustrial levels. The IMF estimates that a carbon tax of $75 per tonne of carbon consumed in India will increase the price of coal by 230%, natural gas by 25%, electricity by 83% and petrol by 13%. Fortunately, the current fall in oil prices have presented an opportunity to emerging economies to introduce a flexible regime of carbon taxing that can be linked with crude oil prices. Removal of fossil fuel subsidy and carbon taxation should be integrated with clean energy and energy savings scheme derived from technology transfers that are aimed under the Kyoto Protocol. Usage of renewable energy sources is to be promoted as well for energy secure future.

To conclude, reinforced by India's stance on promoting liberalization, privatization and globalization, effective environment friendly regulatory mechanisms must be in place.

Total carbon emissions in BRICS (1992 and 2012)

India's real GDP and carbon emissions (1980–2013)

Environmental Kuznets curve

Breakpoint unit root test

Note(s) : *Probabilities may not be valid for this equation specification

International Energy Agency Report, 2015, Outlook-India report. International Energy Agency.

Fastest growing economy in 2018 with a growth rate of 7.3%, ADB.

De Bryun and Heintz (2002)

Economic freedom of the world measures the degree to which the policies and institutions of the countries are supportive to economic freedom.

CUSUM test and the cumulative sum of squares of recursive residuals (CUSUMSQ) test was proposed by Brown et al. (1975) . The null hypothesis is that the coefficient vector is the same in every period and the alternative hypothesis is that they are different. The CUMSUM and CUSUMSQ statistics are plotted against their 5% critical bound. If the plot of these statistics remains within the critical bound, one fails to reject the null hypothesis of no structural change.

The variables can be integrated of the order I(0) or I(1) or I(0)/I(1).

Only the Models that are stable and without autocorrelation are reported in the study.

Model 1, controls for trade as a factor influencing EKC, whereas in Model 2, FDI and size of government along with trade and other variables are considered. Thereby, contributing to the differences in results of EKC between Models 1 and 2. In Model 2, both in the long- and short-run an increase in volume of trade is associated with lower levels of carbon emissions. This can be attributed to technological and composition effects on account of economic growth and FDI.

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The past, present, and future of health economics in India

Singh, Nihaal 1, ; Shukla, Rushikesh 1 ; Acharya, Sourya 1 ; Shukla, Samarth 2

1 Department of Medicine, Jawaharlal Nehru Medical College, DMIMS (DU), Sawangi, Wardha, Maharashtra, India

2 Department of Pathology, Jawaharlal Nehru Medical College, DMIMS (DU), Sawangi, Wardha, Maharashtra, India

Address for correspondence: Nihaal Singh, MBBS Student, Jawaharlal Nehru Medical College, DMIMS (DU), Sawangi, Wardha, Maharashtra - 442 001, India. E-mail: [email protected]

This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 4.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Health economics has long been neglected as a subset of the larger discipline of Economics and Finance. However, this could not be further from the truth. There is a large body of researchers and professionals alike that are of the consensus that extensive studying and working upon Healthcare Economics can help us avert the situation that arose in the wake of the recent COVID-19 pandemic. Applying the core principles of Health Economics to a situation like that would help avert bad outcomes. In this article, the authors begin by defining and establishing the concepts of Health Economics and then building on them. We further explain the concepts in light of the Indian Economy and Healthcare Sector and how it has seen unprecedented growth in the last decade. Furthermore, we touch on the various diseases that put the most strain on the healthcare infrastructure and what we can do to make the situation better. We also shed light on how the COVID-19 pandemic affected the Health Economics in the Indian setting and go on to elaborate how India managed to tackle it. Finally, we elaborate on what steps we can take, as researchers and healthcare professionals, to make it easier for the common man to get access to better and more economical healthcare. We determine the importance and effectiveness of data collection and processing and also how to make better research attempts to study, evaluate and process that said data. The onus falls on the academic and the healthcare professional to ensure that the true meaning of Health Economics is not reduced to a mere numbers game, but is something which is truly subjective and for the benefit of the masses.

Introduction

Health Economics is an amalgamation of two very distinct schools of thought. One is heavily reliant on trying to describe what health means to an individual and what factors influence health, both at the individual and at the community level. The other ties healthcare to its monetary statistics and tries to point out how tweaking certain modalities can influence the final cost that the individual seeking healthcare services has to bear. We will talk about both these lines of investigation in the sections that follow.

Health economists since times immemorial have faced an important dilemma. The dilemma being that health economics is remarkably distinct from its parent branch, which is Classical Economics. This situation arises due to the often constant involvement of third-party players like insurance companies and hospital financing infrastructure. This, combined with issues such as the vagueness of involved metrics, viz-a-viz. QALY (Quality Adjusted Life Years), which are very commonly used to measure healthcare statistics makes it increasingly difficult to trust the computations that are churned out when the numbers are run.

Factors such as the presence of third-party insurers, external intervention, barriers to entry, inevitability of uncertain outcomes, and heavy government involvement make it extremely difficult to consider healthcare in the same domain as other goods and services. Thus, a very distinct perspective is required to evaluate healthcare from the economic lens.

It is important to note that healthcare is conceptually very distinct from other goods that are dealt with in Classical Economics. This is due to the fact that healthcare can be incredibly subjective in terms of success. And this subjective viewpoint can vary from individual to individual and community to community. To avoid making erroneous calculations and coming to conclusions that are based on a standardized metric, we must ensure that healthcare data are collected and processed with due context always analyzed with respect to the individual or community in question.

Health economics in the Indian context

There have been several factors that have caused a massive growth of the healthcare sector in India. Some of these are increase in population, increased life-expectancy, affordable private healthcare, more spare income, and Government’s emphasis on improving healthcare.

This growth means that Indian Healthcare is now valued at over a massive $40 billion. And out of this more that 80% of spending is in private sector and by means of money-at-hand. India thus, has various growth opportunities along with challenges that India has to tackle on its way to success. Medical tourism has become one of the most popular destinations in India, with a $2 billion business. Many super-specialty hospitals, highly qualified medical staff, telemedicine, and government incentives all help to boost health tourism in the country. The huge population, diverse genetic pool, and wide range of disorders make it ideal for clinical trials and personalized medicine research. [ 1 ]

By 2030, India will become the most populated nation on this planet, and approximately 200 million Indians would be at minimum 60-years-old. The expanding ageing demographic, on the other hand, is putting a huge strain on the healthcare infrastructure. With the growth in infectious and behavioral illnesses, urbanization has put a strain on national infrastructure.

A few of the major issues is that healthcare in India is primarily paid for out of cash; over 3/4 th of hospitals and almost half of hospital beds are privately owned. The lower classes cannot pay private health insurance since it is mostly private. [ 1 ]

Our healthcare expenditure is insufficient; overall healthcare spending accounts for only 4.1 percent of gross domestic product (GDP), the lowest among the Brazil, Russia, India, China and South Africa (BRICS) countries. In India, there is a difference in the providing of resources and infrastructure among various socio-economic regions. In comparison to the WHO’s assessment of the global averages of 3,960 beds/million people, India has roughly 860 beds/million inhabitants.

Conditions that most severely burden Health Economics in India

A place like in India where you have less to eat and more glucose in one’s body creates an irony that by itself remains unsolved. Thousands of cases of explosively high numbers of patients with uncontrolled diabetes are handled and often lead to the worst prognosis. The number of patients suffering from diabetes in India, mainly type 2, is rising each day. It also raises the cases of ophthalmic issues and requirement of dialysis machines. As dreadful this disease is, the more dreadful its outcome on economics is. It holds a major chunk of India’s economy to deliver dialysis machines to every Primary Health Centre and government aided hospitals. Even after adjusting for GDP per capita, our regression study found that direct diabetes expenses are closely and positively linked with a country’s GDP per capita, and that the United States stands out as having exceptionally high expenditures. [ 2 ]

Dialysis is not just expensive for the individual itself but it is a major monetary setback even for the country’s GDP. The cataract and glaucoma caused by the same needs equal monetary help for treatment. Carelessness of the patient and the doctors leading to such preceding health concerns require a stronghold in the money. India has to report every case to the WHO which sets up a margin of how the work needs to proceed. The work to reduce its monetary dependence needs to be started at the level of doctors and government aided hospitals itself. Diabetes being 13 th most dangerous cause of death in India, each diabetes case needs to be examined well and its related prognosis needs to be set so that we do not suffer from its allied morbid progression like renal failure in case of diabetes. Renal failure being another burden for Indian economics. The dependence of patients on dialysis machines needs to be reduced as well. The next step that needs to be taken is at the state level and to improve prevention methodologies.

Hypertension

Ischemic heart disease being the sixth most common form of disability-related death in India and hypertension being the most important etiology of it. The prevalence of hypertension in the Indian subcontinent however is due to various factors like poor nutrition due to poverty, low air quality, and the proportion of people who are aware of risk factors like smoking. According to data released in 2017, hypertension, often known as high blood pressure, affects nearly three out of ten Indians and is responsible for 17.5% of all deaths and 9.7% of disability-adjusted life years (DALYS) in the country. DALYS are a unit of measurement that measures the entire disease burden as well as the years lost owing to disability, illness, and premature mortality. [ 3 ] Obesity had the largest socioeconomic status gradient, followed by diabetes and hypertension. [ 4 ]

The associated treatment is also very expensive. The government of India provides the poor with generic medicine for the same. The ischemic heart damage associated with hypertension also bridges a lot of problems along with them. The diagnosis of such heart disease requires a lot of expensive interventions and also the cost of a basic ECG has to be taken into account. Stenting being the most expensive intervention whereas anticoagulant and statin therapy being another one. Even after all of the medicine provided by the doctors and the government at dirt cheap costs, the prognosis of such illness is not always good. The increase in death in relation to this demands an increase in incineration plants and dumping grounds. Bio-waste management is also required. All of this increases the monetary demand from the government and hence bending the economy more towards the decline.

Tuberculosis

The burden of tuberculosis (TB) in India outweighs any other factor that droop the monetary use in health economics India. According to a paper published in The Lancet, TB-related fatalities cost India $32 billion per year, or over Rs 2 lakh crore. [ 5 ] The extreme poverty commonly linked with TB is one of the most important characteristics of the disease’s burden in India. Despite the availability of free TB diagnosis and treatment services, persons with TB may become impoverished. [ 6 ]

For impoverished TB patients, getting nominally free TB testing and treatment facilities can be costly. The Indian government puts innumerable efforts in building vaccines for TB, giving vaccines to people for free, preventing TB by cleanliness, despite all the effort, it goes in vain if people are not educated enough to understand the situation. Cost of BCG vaccination surges high due to the huge population. The reporting of all cases has to be mandatorily done to the WHO and hence, WHO creates a lot of pressure on the country for it to escape such lethal and highly contagious disease. The progression of TB to lung abscess or any pulmonary condition may also be very difficult to treat. The reports of drug-resistant TB have been on rise for a long time in India. No specific treatment modality or regime offers 100% better prognosis to this.

Burden due to overpopulation

The population, though not having an ill effect on the health of an individual, has major concerns when it comes to economics for the country. Feeding the population of the country and looking after its wellbeing and its unfurling illnesses is not a piece of cake and surely requires a handful of money. With each additional member aged 60 years and above, the likelihood of catastrophic health expenditures increases: 33% of households with one 60+ member and 38% of households with 2 or more 60+ members experienced catastrophic health expenditures, compared to only 20% of households with all members under the age of 60 years. [ 7 ]

The major burden carried by the population is the spread of infectious diseases like TB, COVID-19. Both of them explained further. Spread of such highly contagious diseases piles up a plethora of patients under latency. With such a skyrocketing population, waste management becomes an undefeatable issue. For that matter, not just India but many other Asian countries suffer from the same issue. Malnutrition also accompanies the population. The protein energy malnutrition burden has also seen a rise in numbers in India. The fact that per square meter of space shared by a set of people is not enough to suffice the entire population. The majority of patients with lung disorders in India are chronic obstructive pulmonary disorders or a vast number of people suffer from exaggerated allergy in India. Most of these illnesses are in dire need of clean air. The pollution in India is indexed at peak. All such factors need special attention from the government and enough funding has to be made to engulf them all. The more the population, the greater will be the monetary support required. Increase in morbidity associated with population-related disease, will lead to rise in the requirement of better end care facilities. More hospice care will hence require more economic grasp from the country. The grasp of which is really loose in a country like India.

How COVID-19 affected health economics in India

The COVID-19 pandemic was a global catastrophe that caused a massive and ugly strain on the healthcare infrastructure. However, during the second wave of the infection, no country was as strained for medical resources, as India.

India’s corporate medical industry has made a considerable contribution, accounting for over 2/3 rd s of inpatient treatment. Several private hospitals began their preparations in reaction to the COVID-19 outbreak, which included considerable expenditures in infrastructure for treatment, as well as appropriate equipment and increased labor. Furthermore, owing to prolonged treatment times for other diseases and elective procedures, clinics, and laboratories have seen a significant drop in income, as the outbreak is expected to reduce private institutions’ operating profit by nearly half this year. [ 8 ]

The medical industry, in collaboration with the federal and local agencies, developed a sophisticated reaction strategy to counter the outbreak, including the establishment of specialized COVID-19 clinics, exclusion facilities, and technology-enabled identification of resources. The Government of India also used software to efficiently control the pandemic, developing a variety of programs at the federal and local strata. The Aarogya Setu smartphone app, which helped with symptomatic detection and tracing of contacts, was commonly deployed across India. [ 8 ]

We saw unprecedented number of hospitalizations and deaths following the pandemic and the wave upon wave of rise in infections was not mitigated by loose government regulations. This must be a wake-up call to authorities in the nation to make better policies for future situations that keep in mind the fragile state in which it puts the Healthcare Economy.

What can be done to improve the state of health economics in India

Health technology assessments (HTAs) are an essential tool for determining the economic worth of medical treatments across the world. It is utilized to divide healthcare spending in an effective and equitable manner. There is no centralized medical reimbursement system in India, no payee-willingness levels, no general statement, regulations, or standards for health economics assessment models. Furthermore, healthcare delivery is not consistent. [ 1 ]

Nevertheless, HTAs could still be used to navigate general compensation of medical procedures, to advise valuation process for new drugs or drug categories, and to assist healthcare authorities in developing clinical practice framework to ensure uniformity in delivery and scientifically backed treatments for peak effectiveness.

The majority of health economics research in India are partnerships with scholars from other countries. In India, there is a dearth of understanding of the ideas and methodologies for performing pharmaco-economic analyses. In India, there is presence of a few practitioners of healthcare economic analysis working in education and professional institutes, although these are small communities of expertise. On a national basis, we need educational sessions and the exchange of best practices. This will aid in the provision of information as well as a reservoir of qualified academics. [ 1 ]

The outcome of an investigation is determined by the data. As a result, the input obtaining process for these studies must be reliable. In India, policies for healthcare evaluation models must be authorized by the administration. There is still a lot of work to be done, even though the maiden pharmaco-economic recommendations have seen development and delivery to consumers.

Thus, delivering upon better data collection and processing, institutions, both private and public can make better and more informed decisions that will make it easier for the healthcare sector, as well as the individual gain benefit out of situations. This is only possible if everyone involved makes a collective effort in the spirit of improving the Health Economy of the nation.

Health Economics is a discipline that has only been vaguely defined and intensely debated. In order to make better decisions that are data-driven and justifiable by number crunching, we must partake in extensive research and planning at both national and international levels. This will enable us to make bold and substantial claim about how to better manage situations that strain the Healthcare Infrastructure and the associated financial institutions.

There are some diseases that affect the individual and the collective more so and in higher frequencies than the others, and it is imperative that we target them and isolate them. Following Pareto’s distribution, 20% of work will solve 80% of our problems. With this spirit, we must move forward by being both optimistic and rational. This will help us tackle the problems posed to us, such as the recent COVID-19 pandemic much more efficiently and economically.

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• DOI: 10.21511/pmf.13(1).2024.11
• Corpus ID: 270823195

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• Darmawati Elis , Mediawati Syarifuddin , +3 authors Ph. Syarifuddin Rasyid
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कोविड १९ चा भारतीय अर्थव्यवस्थेवर परिणाम (COVID-19 Effects on Indian Economy)

4 Pages Posted: 30 Aug 2021

Rakshit Bagde

Late. Mansaramji Padole Arts College Ganeshapur Bhandara

Date Written: August 21, 2021

Marathi Abstract: भारतीय अर्थव्यवस्था आपल्या उर्जितावस्थेत असताना, तसेच सण 2014 पासून निरंतर कमी होता चाललेला विकास दर यात ताळमेळ घालत असताना त्यात 2020 वर्षाच्या सुरवातीलाच Covid 19 ची झड अर्थव्यवस्थेला पोहचली असल्याचे चित्र आज आपल्या समोर दिसते आहे. चीन या देशातून सुरु झालेला कोरोना हा संसर्ग जन्य आजार आज संपूर्ण जगभर आणि भारत भर पसरत चालला आहे. या आजाराने आजवर जगभर 41,94,728 च्या वर मनुष्यबडी घेतलेला आहे. आणि त्यात निरंतर वाढ होत असल्याचे आपणास दिसते आहे. विकसित तसेच विकसनशीलन देश याच्या प्रभावातून सुटलेले नाहीत. या Covid 19 चा परिणाम हा मानवाच्या अस्तित्वावर प्रश्न चिन्ह निर्माण करणारा ठरत आहे. प्रश्न निर्माण होतो आहे तो जगण्याचा आणि जिवंत राहण्यासाठीची साधने टिकविण्याचा. आजपर्यंतच्या विकासाला Covid 19 मुळे खिड लागत चालली आहे. केलेला विकास कसा टिकवायचा याची नव्याने उपाययोजना यातून निर्माण केल्या जाईल पण तोवर पोहचलेली झड भरून काढणे कठीण आणि श्रमाचे काम ठरणार आहे. भारताने स्वीकारलेल्या लॉक डाउन चा परिणाम हा पूर्ण अर्थव्यवस्थेवर पडलेला आहे. यातच जागतिक पातडीवरील अनेक संस्थांनी भारताचा विकास दर 0% राहण्याचे संकेत दिलेले आहेत. English Abstract: While the Indian economy is in its infancy, the festival has been steadily declining since 2014 COVID-19 at the beginning of 2020 while the current growth rate is adjusting. Today we see the picture that Chi Zad has reached the stage of Athavadayavastha. From this country of China Coronavirus is a contagious disease that has spread all over the world and all over India Is. The disease has killed over 41,94,728 people worldwide to date. And so on You can see the growth. Of developing as well as developing countries Not escaped the influence. The result of this COVID-19 is a question mark over human incompetence Is becoming a builder. The question is how to survive and live Tooling. To date, growth has been hampered by COVID-19. Done The river will be the solution to how to stop the development, but until then It will be difficult and laborious to fill in the gaps. Locks accepted by India The downfall has had a devastating effect on the economy. This includes many areas on the world stage Institutions have shown that India's growth rate is expected to remain at 0%. Some of them have not been studied due to the impact on the Indian economy The emphasis will be on suggesting solutions.

Note: Downloadable document is in Marathi.

Keywords: COVID-19, Indian Economy

JEL Classification: I15, I20, I28

Suggested Citation: Suggested Citation

Rakshit Bagde (Contact Author)

Late. mansaramji padole arts college ganeshapur bhandara ( email ).

Late. Mansaramji Padole Arts College Ganeshapur Bh Bhandara, IN 441904 India 0997 003 3139 (Phone) 441904 (Fax)

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Indian Economy Continues to Show Resilience Amid Global Uncertainties

NEW DELHI, 04 April 2023 – India’s growth continues to be resilient despite some signs of moderation in growth, says the World Bank in its latest India Development Update , the World Bank India’s biannual flagship publication.

The Update notes that although significant challenges remain in the global environment, India was one of the fastest growing economies in the world . The overall growth remains robust and is estimated to be 6.9 percent for the full year with real GDP growing 7.7 percent year-on-year during the first three quarters of fiscal year 2022/23. There were some signs of moderation in the second half of FY 22/23. Growth was underpinned by strong investment activity bolstered by the government’s capex push and buoyant private consumption, particularly among higher income earners. Inflation remained high, averaging around 6.7 percent in FY22/23 but the current-account deficit narrowed in Q3 on the back of strong growth in service exports and easing global commodity prices.

The World Bank has revised its FY23/24 GDP forecast to 6.3 percent from 6.6 percent (December 2022). Growth is expected to be constrained by slower consumption growth and challenging external conditions. Rising borrowing costs and slower income growth will weigh on private consumption growth, and government consumption is projected to grow at a slower pace due to the withdrawal of pandemic-related fiscal support measures.

“The Indian economy continues to show strong resilience to external shocks , "  said Auguste Tano Kouame, World Bank's Country Director in India.   “Notwithstanding external pressures, India’s service exports have continued to increase, and the current-account deficit is narrowing.”

Although headline inflation is elevated, it is projected to decline to an average of 5.2 percent in FY23/24, amid easing global commodity prices and some moderation in domestic demand. The Reserve Bank of India’s has withdrawn accommodative measures to rein in inflation by hiking the policy interest rate. India’s financial sector also remains strong, buoyed by improvements in asset quality and robust private-sector credit growth.

The central government is likely to meet its fiscal deficit target of 5.9 percent of GDP in FY23/24 and combined with consolidation in state government deficits, the general government deficit is also projected to decline. As a result, the debt-to-GDP ratio is projected to stabilize. On the external front, the current account deficit is projected to narrow to 2.1 percent of GDP from an estimated 3 percent in FY22/23 on the back of robust service exports and a narrowing merchandise trade deficit.

“Spillovers from recent developments in financial markets in the US and Europe pose a risk to short-term investment flows to emerging markets, including India,”   said Dhruv Sharma, Senior Economist, World Bank, and lead author of the report .  “But Indian banks remain well capitalized.”

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Auguste Tano Kouamé, World Bank Country Director for  India , says, "India shows strong resilience to external shocks, supported by robust investment in  infrastructure  & strong service  exports ."

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‘There is No Economic Incentive for AI to Kill Humans,’ says Illia Polosukhin

• Published on July 1, 2024
• by Tarunya S

 In a recent interview, Illia Polosukhin , co-founder of Near , said AI is not a human but just a system. 

He explained , “I think the important part to understand about AI is that it’s not a human, it’s a system. And the system has a goal. Unless somebody explicitly programs it to harm humans, it won’t magically do that. In the blockchain world, you realise that everything is driven by economics one way or another. There’s no economic incentive to kill humans.” 

Polosukhin highlighted that right now, they’re building systems to improve individuals and expand the capabilities of minds. They will have autonomous agents with specific missions and goals, and they will perform tasks in the physical world. 

However, their actions will be governed by the same laws as ours. Using AI to develop biological weapons is no different from doing so without AI. Ideally, AI should help us better detect and prevent such misuse.

Google Transformer 

As one of Google’s ‘Transformer 8,’ Polosukhin played a pivotal role in revolutionising deep learning. 

In the interview, he also discussed the inception of the Transformer paper and the importance of democratising AI. Polosukhin also reflected on his journey from Google to founding his own AI company.

Now, Polosukhin is considered one of the founding fathers of modern AI.

Polosukhin co-wrote the now famous 2017 paper, “ Attention Is All You Need ” along with seven Google colleagues, who have collectively become known as the “Transformer 8”. 

Google integrated transformers into Google Translate in 2018, resulting in improvements. However, the technology didn’t see widespread use until OpenAI introduced ChatGPT in November 2022. 

“OpenAI had very little to lose by opening this up,” Polosukhin told CNBC. 

“If, for example, any other company, especially a public company, opened it up and the first question you ask there, it was like an inappropriate answer, that would be in the news.”

By the time the transformer paper was published in late 2017, Illia Polosukhin had already left Google to co-found Near with Alexander Skidanov . Since then, all eight authors have left Google, with Polosukhin being the first to depart. 

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Reliability Options in Renewables-Dominated Electricity Markets

Recent energy shortfalls in renewables-dominated electricity markets call for a mechanism to ensure demand is met under all system conditions. We demonstrate severe shortcomings of an increasingly popular mechanism—reliability options—caused by its interaction with fixed-price forward contracts for energy. Large generators can trigger the option exercise, weakening the short-term incentive to sell output provided by forward contracts alone. In the longer term, hydro generators sell more forward contracts and store less water, reducing system reliability. We empirically show that Colombian generators respond to these incentives. We analyze a standardized energy contracting approach to long-term resource adequacy that does not create these economic incentives.

We thank Meredith Fowlie, Jakub Kastl, Gordon Leslie, Nick Ryan, Romans Pancs, and Bert Willems, as well as seminar participants at CIDE, ITAM, FGV-EPGE, PUC-Rio, University of Southern California, Paris School of Economics, the NBER Summer Institute IO meeting, the IAEE International Conference, the Economics of Low Carbon Markets Workshop, the Energy Institute at Haas POWER Conference, the International Industrial Organization Conference, the Toulouse Conference on the Economics of Energy and Climate, the From Theory to Practice conference at the Becker Friedman Institute, the Property and Environment Research Center (PERC), and the Transportation and Public Utilities Group ASSA meeting, for their many helpful comments and suggestions. McRae gratefully acknowledges financial support from the Asociación Mexicana de Cultura. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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