Nonparametric estimation and testing of fixed effects panel data models

Assessing nonlinearities and heterogeneity in debt sustainability analysis: a panel spline approach

This paper empirically studies public debt sustainability with the penalized panel splines approach for 25 EU economies from 2000 to 2019 by estimating the response of the primary surplus to lagged debt relative to GDP, respectively. A positive coefficient on average indicates sustainable policies, which is supported by all our results. Moreover, we show that this relationship is not homogeneous across the distribution of the debt ratios but varies with the magnitude of public debt to GDP. The estimations reveal a strongly increasing reaction for small and high debt ratios while it is rather flat for intermediate levels. This holds for normal times, too, whereas during years of economic crisis a monotonously increasing response can be observed. Additionally, for a cluster consisting of smaller EU economies, there is an indication of 'fiscal fatigue', meaning that the effort of active fiscal counter-steering peters out for high ratios of public debt to GDP. The same effect can be observed for the whole sample and a sample including the large EU economies, once Greece is removed.

Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding

Recently, machine learning (ML) methods have been used in causal inference to estimate treatment effects in order to reduce concerns for model mis-specification. However, many ML methods require that all confounders are measured to consistently estimate treatment effects. In this paper, we propose a family of ML methods that estimate treatment effects in the presence of cluster-level unmeasured confounders, a type of unmeasured confounders that are shared within each cluster and are common in multilevel observational studies. We show through simulation studies that our proposed methods are robust from biases from unmeasured cluster-level confounders in a variety of multilevel observational studies. We also examine the effect of taking an algebra course on math achievement scores from the Early Childhood Longitudinal Study, a multilevel observational educational study, using our methods. The proposed methods are available in the CURobustML R package.

Impact of renewable energy investment on carbon emissions in China - An empirical study using a nonparametric additive regression model

This study analyzed the comprehensive impact of renewable energy investment on carbon emissions in China. To achieve this, a nonparametric additive regression model was built. Using the STIRPAT model, we considered six influencing factors: economic growth, industrialization level, urbanization level, population aging, trade openness, and renewable energy investment. This enabled the exploration of the existence, direction, and intensity of the impact of renewable energy investment on carbon emissions. The results of the linear component of the model showed that renewable energy investment can slightly reduce carbon emissions. The results of the nonlinear component of the model showed that the impacts of renewable energy investment on carbon emissions were inconsistent at different stages of the investment. In the early stage, the renewable energy investment can increase carbon emissions. In the middle stage, the renewable energy investment begins to play a role in reducing emissions. In the later stage, renewable energy investment may be associated with increased carbon emissions again. The relationship between carbon emissions and the other five influencing factors can be represented by an inverted U-shaped curve, a U-shaped curve, or a slow rising curve. The results above provide useful references to adjust renewable energy investment and reduce carbon emissions.

On the search for environmental sustainability in Africa: the role of governance

Africa remains the most affected by environmental degradation, thereby exacerbating the negative effect of climate change in the region. Little empirical credence has been leaned to the institution-environmental sustainability relationship in Africa. This omission in the literature of environmental sustainability is abysmal, considering the role of institutions and government in ecological preservation. To inform policy and research on the subject matter, we estimated a unbalanced panel data of the indices of good governance and strong institutions to explain transformation to environmental sustainability using the dynamic system generalised method of moment estimator from 1996 through 2017. Findings suggested a positive relationship between the rule of law and regulatory quality and transformation to environmental sustainability. An inverse relationship between government effectiveness and environmental sustainability was established. We recommended concerted effort at an institutional level such that policy and punishment for violation of greenhouse strategies will be optimum.

The Environmental Kuznets Curve with Recycling: A Partially Linear Semiparametric Approach

This paper is the first to study a comparatively new Environmental Kuznets Curve which traces empirically the relationship between environmental abatement and real GDP. Our model is a partial linear semi parametric model that allows for two way fixed effects to eliminate the bias arising from two sources. We use data for recycling and real GDP, for fifty states of the United States for the years between 1988 and 2017. We find evidence that this relationship is characterized by an increasing curve which confirms the existence of a J curve, a finding that agrees with the predictions from recent theoretical models.