T16P09 - Sustainable Development and Environment Policy

Topic : Sustainable Development and Policy

Panel Chair : Namrata Chindarkar - namrata.chindarkar@nus.edu.sg

Panel Second Chair : Sonia Akter - sonia.akter@nus.edu.sg

Panel Third Chair : Yvonne Chen - sppcj@nus.edu.sg

Objectives and Scientific Relevance of the panel

Call for papers

Session 1

Wednesday, June 28th 16:15 to 18:15 (Block B 5 - 2 )


Yvonne Chen - sppcj@nus.edu.sg - National University of Singapore - Singapore

Sonia Akter - sonia.akter@nus.edu.sg - Singapore


Classifying the Cities by Examining the Environmental Kuznets Curve for Low-carbon Development in China

Chao Zhang - zhangchao16@mails.tsinghua.edu.cn - Tsinghua University - China

Xufeng Zhu - zhuxufeng@tsinghua.edu.cn - Tsinghua University - China

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China is the largest carbon dioxide (CO2) emitter worldwide, triggering strong needs for low-carbon development. According to the Paris Agreement, China is proposed to take the initiatives to improve its own mitigation contribution for addressing climate change and transform its current economic growth pattern. However, with limited awareness on local level CO2 emissions, the central government could hardly decompose its mitigation plan into local administrative units. Moreover, there is a lack of precise-data based research on proposing unified benchmarking scheme for examining the low-carbon development status. In this research, based on the bottom-up monitoring data of CO2 emission from 1.5 million enterprises conducted by the Ministry of Environmental Protection (MEP) in China, a 1-km grid CO2 emissions warehouse was interpolated for prefectural cities all over China. Based on these city-level GDP and CO2 emissions data, the authors test the Environmental Kuznets Curve (EKC) by spatial econometric modeling, hypothesizing an inverted-U-shaped relationship between environmental pollution and economic growth. The research reveals an uneven city scale landscape of low-carbon development status, which shows that resource-intensive cities dragging the low-carbon development down, while the majority part of service-oriented coastal area and several sparsely populated western cities have passed the turning point of EKC and leading the low-carbon development in China. Altogether, this research offers a pivotal and feasible method for the study of finer city level CO2 emission and highlights approaches for decomposing the CO2 mitigation target under the scenario of achieving the Paris Agreement. This research especially matches the panel of Sustainable Development and Policy, under the T16P18 - Environmental Policy, considering the research provides an innovative strategy and benchmarking method for policy actors to promote the modification of low-carbon development policy. It also puts forward a big-data based scientific decision making mechanisms serving as policy advocacy tools for environmental protection.


Government administrative rank and industrial pollution in China

Hualiu Yang - yanghlhorse@hotmail.com - China

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This study investigates how China’s administrative hierarchy influences industrial pollution emissions. The argument is that lower ranked cities would have a higher industrial pollution level even if they reach the same income per capita level as higher ranked cities. This essay will investigate two channels through which administrative rank affects a local industrial pollution. First, a higher level city with more resources are able to attract less pollution intensive firms (industry structure), achieve higher production efficiency (technology), and perform better on pollution regulation enforcement leading to a local market with less pollution intensive industries. The other channel is the institutional quality of a city. Administrative rank enhances the quality in governance institutions (i.e., the local government and the local market) due to the resources advantage. The higher institutional quality leads to more efficient local spending and a spending structure towards more to the public services that are able to internalize the market externalities. The Chinese city-level data from 2003-2010 will be used to test these two channels through which the city administrative rank matters to the local industrial SO2 emissions. The policy implication from this study is that the Chinese central government needs to keep its efforts on containing this inequality within the administrative hierarchy for the benefits of itself (i.e., stability) and the benefits of the people located at lower level cities.

Using self-reported well-being assessment to value air quality in China

Jie-Sheng Tan-Soo - jiesheng.tan@nus.edu.sg

Recovering credible valuation of air quality is a cornerstone of environmental regulations as these estimates aid policymakers in deciding the tradeoff between economic growth and pollution control. Such estimates are widely available in the developing world where air quality is at relatively more acceptable levels. In contrast, due to data availability issues, there are very few studies of air quality valuation for developing countries, where pollution problems are at its worst. We contribute to the thin literature by assembling a unique dataset from China to examine the relationship between self-reported happiness and health status with air quality, and derive a willingness-to-pay measure for air quality. First, using households’ locations, we are able to determine air quality exposure for each household. Second, we can also recover the wind speed of the general location where the household is at. Wind speed acts as an instrument as air pollution is often correlated with desirable features such as economic activities or proximity to city centers. Contrary to intuition, we find that self-reported well-being is most highly associated with air quality at the hour during which the survey was field. The relationship weakens as we use increasingly lagged measurements of air quality measurements. This suggests that air quality may affect one’s mental well-being, even for acute exposure. Using these results, we recover Chinese residents’ marginal willingness-to-pay (MWTP) for PM2.5 at 1,111 RMB/year. This is approximately 1.6% of household income.

Session 2

Thursday, June 29th 08:15 to 10:15 (Block B 5 - 2 )


Jie-Sheng Tan-Soo - jiesheng.tan@nus.edu.sg

Yvonne Chen - sppcj@nus.edu.sg - National University of Singapore - Singapore

The role of private schooling on children learning outcomes and prevalence of female mathematical anxiety in India?

Karan Singhal - karansinghal1993@gmail.com - Indian Institute of Management - India

Upasak Das - upasak@sas.upenn.edu - University of Pennsylvania - India

In light of the upcoming New Education Policy in India, it is important to assess the current quality of education in context to the aims set under the previous major policies such as Right to Education (2009), National Policy on Education (1986), consultation and position papers by the National Curriculum Framework set up by the National Council of Educational Research and Training in India.


Learning outcomes among children play a major role in shaping up future individual earnings, development and hence economic growth. Along with the demand side factors like parental income and education, supply side factors are important as well. In the view of increasing preference of private schooling in India, this paper assesses its impact on learning outcomes of children aged 8-11 years in rural India. Despite earlier attempts to study this, the existing literature does not control for confounding unobservable factors that may affect learning factors. While some experimental and longitudinal studies may have controlled for unobservable factors through randomisation and value added models, their designs suffer from limitations especially in terms of external validity where the causal inferences cannot be generalised to other situations and people. This paper uses the Indian Human Development Survey data collected in the latest round (2011-12) and attempts to examine children attendance in private schools and its relationship with educational outcomes. In this paper, by applying instrumental variable regressions through credible instruments that would control for the unobservable characteristics, we find positive and significant impact of private schooling on learning outcomes among children in rural India. We also find some evidence of gender difference among children from public schools in terms of learning outcomes and the prevalence of mathematical anxiety among females. Also, male children from public schools are found to perform better than girls not only in mathematics but also in reading indicating that prevalence of a stronger gender difference among children attending government schools.


We also evaluate the scenario of education and gender inclusion at the primary level, throwing light on the distance from achieving related targets under the Sustainable Development Goals (SDGs)- ‘Quality Education’ and ‘Gender Equality’. Pertinent questions about the role of private sector through reservation policy for socially and economically backward sections as being currently implemented under Section 12(1)(c) of the Right to Education Act as are also discussed. It further attempts to shed light on whether the political environment is more conducive to implement similar changes which haven’t been able to see effective implementation in the past.  

Social cohesion and community-shared adaptation financing in the coast of Bangladesh 

Sonia Akter - sonia.akter@nus.edu.sg - Singapore

In the absence of an internationally agreed multilateral framework for climate financing, mobilization of internal resource for funding adaptation initiatives in low income countries is becoming increasingly important. In this context, the concept of community-shared adaptation financing for large-scale infrastructure projects, in the form of cost sharing by the beneficiaries or local user group, can be considered as a stopgap measure. This study examines the acceptability of this concept to the local population and identifies factors that may potentially hinder the prospect of such a financing model being widely popular. The study uses household level data obtained through a contingent valuation survey administered in a tropical cyclone prone coastal district of Bangladesh. Four hundred randomly sampled male and female inhabitants of the district were asked to pay a one-off surcharge to co-finance the government led Coastal Embankment Improvement Project which aims to reconstruct and rehabilitate coastal embankments to increase resilience against climate change risks. Over two-thirds of the sampled population were willing to pay the surcharge and the average willingness to pay per household was US$50 (3% of the annual average household income). In addition to individual level risk exposure (measured by economic damage cost), risk preference and risk perception; social cohesion index measuring social solidarity and trust played a significant positive role in determining household willingness to pay for the project. As theoretically expected, the social cohesion index was significantly negatively correlated with religious diversity and income inequality. These findings imply considerable support for community-shared adaptation financing in the coastal region of Bangladesh. However, the effectiveness of this model hinges crucially on the level of social cohesion in a community and as such, this model is less likely to be popular in areas that are characterized by high income inequality and high degree of religious fragmentation.  

Effect of Rural Electrification on Farm Investments in India

Yvonne Chen - sppcj@nus.edu.sg - National University of Singapore - Singapore

Namrata Chindarkar - namrata.chindarkar@nus.edu.sg - Lee Kuan Yew School of Public Policy - Singapore

According to Census of India (2011), about two-thirds of India’s population depends directly or indirectly on agriculture and related activities for their livelihoods. However, low farm productivity continues to plague the agricultural sector resulting in slow growth and widening of income inequality between rural and urban areas. One of key factors contributing to low farm productivity is lack of reliable farm electricity. High voltage and uninterrupted farm electricity supply is required to run irrigation equipment and farm tools. However, farm electricity in much of rural India continues to be highly subsidized creating financial pressures on public utility companies and consequently affecting transmission and distribution (T&D). The result has been unreliable, low voltage, and infrequent electricity to farms, which in turn affects productivity. A related issue is managing groundwater withdrawal for irrigation. Supplying unlimited farm electricity may not be desirable as it is likely to cause groundwater exploitation, which will also affect farm productivity in the medium- to long-run. To balance the two issues of supplying reliable farm electricity and sustainable use of groundwater, the state government of Gujarat launched the Jyotigram Yojana (JGY) in October 2003. Under JGY, farms received 8 hours of high quality and uninterrupted electricity supply as per a pre-determined schedule. It is yet unknown whether this policy change has indeed resulted in improved farm outcomes and greater welfare for farm households. By matching the exact village-level program rollout dates to the 2004-05 and 2011-12 India Human Development Survey (IHDS), we examine the impact of JGY on various investment decisions of farm households related to productivity and on farm profits. Using a difference-in-difference framework, we find that JGY has led to significant increase in net farm income and net animal income for small land owners. Farm households across land size significantly reduced hired labor. Our results suggest that improving reliability of farm electricity can result in significant welfare gains for farm households.

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