Narrow Results

The role of social capital in economic development has been a subject of interest to both academics and practitioners of development for several decades. However, empirical evidence on social capital in the context of developing countries is still relatively scant. This study explores the effects of social capital on economic development in Indonesia, a large and multi-ethnic developing country. Using district-level data for 2006–2019, we find that the relationships between social capital and economic development are complex. There are both favorable and unfavorable effects of social capital on economic development, as well as nonlinear effects. Hence, we cannot draw unequivocal conclusions on the benefits or disadvantages of social capital for economic development. Nevertheless, this study finds that trust among people across different ethnic groups, participation in communal works and social activities, and trust in government are the most important forms of social capital needed to improve people’s welfare.

Despite recent intense interest, happiness studies have been impeded by some conceptual and methodological problems, including viewing happiness (well-being/welfare) as different over different persons, as relative, multi-dimensional, non-cardinally measurable, interpersonally non-comparable and using non-cardinal and interpersonally non-comparable methods of happiness measurement. Using the evolutionary biology of happiness, this paper argues that happiness is absolute, universal, and uni-dimensional and is also cardinally measurable and interpersonally comparable. This is needed to make choices motivated by reward (pleasure) and punishment (pain) consistent with fitness maximization. However, happiness indices obtained by virtually all existing methods of happiness measurement are largely non-cardinal and non-comparable, making the use of averaging in group happiness indices of dubious philosophical validity. A method of measuring happiness to give cardinal and interpersonally comparable indices is discussed. These may contribute towards the more scientific study of happiness that is based on sounder methodological grounds as well as yielding more useful results.

Poverty is an interlacement of income distribution below a threshold value and inequality within that boundary. To unthread the fabric of poverty and understand the dimensions of impoverishment below and around the poverty line, a deeper examination of different facets of deprived and starving households is required. This paper attempts to provide an additional tool in monitoring poverty reduction by computing density ratio and decile density trends by applying Kernel density function for the consumer expenditure distribution from the National Sample Survey Organization’s 55th (2000), 61st (2005), 66th (2009) and 68th (2012) quinquennial rounds. The progressive Indian state Kerala has exhibited a higher density ratio with the poverty tail flattening when compared with the backward State Bihar. The ways and means to succeed in reaching the end of the sea of hardship in Bihar are explored keeping in view some of the most impressive achievements of Kerala, a developed Indian state.

The difference in land use modeling approaches is an important uncertain factor in evaluating future climate scenarios in global economic models. We compare five widely used land use modeling approaches: constrained optimization, constant elasticity of transformation (CET), the additive form of constant elasticity of transformation (ACET), logit, and Ricardian. We demonstrate that the approaches differ not only by the extent of parameter uses but also by the definition of conversion cost and the consideration of comparative advantage implied by land heterogeneity. We develop a generalized hybrid approach that incorporates ACET/logit and Ricardian to account for both conversion cost and comparative advantage. We use this hybrid approach to estimate future climate impacts on agriculture. We find a welfare loss of about 0.38–0.46% of the global GDP. We demonstrate that ignoring land heterogeneity or land conversion costs underestimates climate impacts on agricultural production and welfare.

This paper presents the overall and distributional welfare effects of alternative multi-regional emissions trading coalitions relative to unilateral action. It focusses on meeting Paris Agreement pledges and more emissions reduction targets consistent with 2^∘C and 1.5^∘C temperature pathways in 2030. The results from seven computable general equilibrium (CGE) models are compared. Across all models, welfare gains are highest with a global market and increase with the stringency of targets. All regional coalitions also show overall welfare gains, although lower gains than the global market. The models show more variability in the gains by a participant. Depending on the model, participants may benefit more from some regional arrangements than from a global market or face modest losses compared to the domestic reductions alone, due to interactions between carbon targets and fossil fuel markets. The scenario with a joint China–European Union emissions trading system in all sectors is consistently favorable for participants and provides the highest economic gains per unit of emissions abated.