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Despite being a global public–private partnerships (PPPs) leader, the Asian region is characterised by a wide PPP-divide, wherein select countries attract majority of PPP projects, while other countries fail to attract the requisite PPP investments. Against this background, the purpose of this study is to investigate the determinants of PPP projects in Asia.

Using quantitative methods on secondary data, this study analyses the macroeconomic determinants of value and number of PPPs in Asia for the period 2010–2019. The methodology relies on panel fixed effects, random effects, two-step system generalised method of moments and negative binomial regression.

Results underline the importance of the country’s experience with PPPs, physical infrastructure, financial sector development, market conditions, institutional quality and political stability in attracting PPP projects.

Identification of the determinants of PPPs will assist private investors in making informed decisions related to the selection of countries for PPP investments, thereby increasing the likelihood of a project’s success.

The results are expected to enable countries to formulate policies aimed at attracting higher PPP investments, thereby propelling economic development and improvement in the quality of life.

To the best of the authors’ knowledge, this is the first such study that comprehensively analyses the determinants of both value of PPP investments and number of PPP projects for Asian countries.

In view of the significance of public–private partnerships (PPPs) as a tool for bridging infrastructure deficits, it becomes imperative to study its determinants. The objective of this paper is to empirically study the determinants of PPPs in India at a subnational level, in terms of both number and value of PPP projects.

This study investigates the determinants of value and number of Indian PPPs at a subnational level for the period 2008–2017. The determinants are analyzed using two-step system generalized method of moments (GMM) and negative binomial regression. Select correlates examined are market size, fiscal compulsions, institutional quality, financial sector development and physical infrastructure.

The results indicate that fiscal compulsions, financial sector development and physical infrastructure influence PPPs favorably, whereas low institutional quality impacts PPPs adversely. A pertinent finding of this study is that the past value of PPPs lowers the current year's PPP value.

The findings are expected to assist subnational governments and policymakers in formulating policies that attract more PPP projects (in terms of both value and number).

This is the first study that analyzes the determinants of infrastructure PPPs at a subnational level in India.

Despite being a global public–private partnerships (PPPs) leader, India faces a vast PPP divide at a sub-national level, wherein a few states receive the majority of PPP projects, whereas other states face severe issues in attracting PPP investments. This necessitates the identification of factors that make some states attractive to PPP investors. The purpose of this study is to construct a “PPP readiness index” at the Indian state-level, which aims to assess the readiness of states for the diffusion of PPPs.

Using a quantitative method on secondary data, the study scores 17 Indian states on dimensions such as experience with PPPs, physical infrastructure, financial sector development, market conditions, institutional quality and political stability and fiscal constraints for each of the years during 2009–2018. Principal component analysis is used for assigning weights to the dimensions, thereby arriving at the composite index.

Results highlight that Tamil Nadu and Maharashtra offer the most favorable environment for PPPs to flourish. In contrast, Jharkhand and Bihar are laggards because they score the least and have limited PPP experience.

The index will assist the private sector in conducting a comparative analysis between state-specific PPP arrangements, thereby enabling them to make informed decisions prior to forging PPP arrangements. Further, the index will help the state governments in improving their PPP readiness by following the policies of the leading states.

Improvement in PPP readiness of the states will enable higher PPP investments in infrastructure, thereby reducing infrastructure deficits. This, in turn, will lead to economic growth, development and an improvement in the quality of life.

To the best of the authors’ knowledge, this is the first study that comprehensively analyzes the PPP readiness at a sub-national level in India.

Since finance is an efficacious instrument for economic development, social inclusion and women empowerment, the present paper examines the determinants of accessing institutional and non-institutional finance across male- and female-headed households in rural India.

Multinomial logistic regression is applied for categorizing households' accessing finance in four categories, namely Only Institutional Finance (IF), Only Non-institutional Finance (NIF), Both Sources of Finance (BF) and Neither Source of Finance (N). Both household and state-level determinants have been analysed. Household data set is sourced from the Situation Assessment Survey (NSSO, 70th round) and state-level data sets from Basic Road Statistics 2016, Agricultural Statistics at a Glance 2016, Rainfall Statistics of India 2014, database on Indian Economy RBI and Census 2011. Econometric regressions have been evaluated for female-headed households (FHHs), male-headed households (MHHs) and overall pooled households (HHs).

Four important findings emerge. First, FHHs have a lower probability of accessing IF and a higher probability of accessing NIF vis-a-vis MHHs. Second, in general, education levels, monthly household consumption expenditure, land size holding, irrigated area and penetration of scheduled commercial banks favourably influence FHHs accessing IF. Third, FHHs belonging to socially disadvantaged castes have a lower probability of accessing IF. Fourth, a substantial proportion of FHHs accesses neither IF nor NIF relative to MHHs.

The paper thoroughly addresses the issue of accessing finance by FHHs and MHHs, which will further assist policymakers in formulating holistic financial policies for rural India.

The paper recommends increasing women's access to financial services as an effective tool for reducing poverty and lowering income inequality in rural India.

This article contributes to the scant empirical literature on finance and gender.

The purpose of this study is to analyze and empirically test the impact of Economic Freedom [(EF) measured by size of the government] and inequality on environmental pollutants in addition to macroeconomic variables like per capita GDP, governance indicators, etc. along with existence of non-linear (Kuznets) postulation between economic growth and per capita emissions.

The paper examines the select Asian nations' data attributes, first qualitatively using correlation data technique, followed by empirical testing using differenced Generalized Methods of Moments (GMM). Using the data of selected Asian countries for the period from 1981 to 2016, the authors have applied a dynamic panel technique.

The key findings that emerge from the study are as follows: first, there is weak evidence for the existence of the Kuznets curve based on the empirical results; second, the results indicate that increased EF (by lower government size) could enable to contain carbon emissions; third, there is a negative relationship between democracy and environmental quality (corroborating to the existing studies on carbon emissions); and fourth, there is a strong statistical evidence that increasing income inequality pairs with greater emissions in the middle range of Gini.

The paper conforms to the universally held conviction that government interventions are essentially less productive and the desirability of a reduced size of the government in realizing sustainable green growth with equity.

In an era of liberalization and privatization, it is argued that the role of the government needs to be redefined if not necessarily truncated.

The current paper incorporates Gini (inequality measure) through its intercountry range dummies to study the differential effect of Gini on carbon emissions. Also, in some of the recent studies, distributional issues have surfaced explicitly in the discussion of income–climatic change relationship, but EF largely remains missing. The purpose of the current study is to investigate the same empirically.

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 CO₂ 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.

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 (CO₂), 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.

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.

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.