A panel data heterogeneous Bayesian estimation of environmental Kuznets curves for CO2 emissions

This article investigates the Environmental Kuznets Curves (EKC) for CO₂ emissions in a panel of 109 countries during the period 1959 to 2001. The length of the series makes the application of a heterogeneous estimator suitable from an econometric point of view. The results, based on the hierarchical Bayes estimator, show that different EKC dynamics are associated with the different sub-samples of countries considered. On average, more industrialized countries show evidence of EKC in quadratic specifications, which nevertheless are probably evolving into an N-shape based on their cubic specification. Nevertheless, it is worth noting that the EU, and not the Umbrella Group led by US, has been driving currently observed EKC-like shapes. The latter is associated to monotonic income–CO₂ dynamics. The EU shows a clear EKC shape. Evidence for less-developed countries consistently shows that CO₂ emissions rise positively with income, though there are some signs of an EKC. Analyses of future performance, nevertheless, favour quadratic specifications, thus supporting EKC evidence for wealthier countries and non-EKC shapes for industrializing regions.     

The carbon Kuznets curve: A cloudy picture emitted by bad econometrics?

We discuss several major econometric problems that have been ignored in the empirical environmental Kuznets curve (EKC) literature thus far. These are: First, the use of nonlinear transformations of integrated regressors and second, in a panel context, cross-sectional dependence in the data. Both problems fundamentally invalidate the use of widely applied time series and panel unit root and cointegration techniques. We use the important special case of the relationship between GDP and CO₂ (and SO₂) emissions to show and discuss in detail that the seemingly strong evidence for an inverted U-shaped relationship between these variables obtained with commonly used methods is entirely spurious and vanishes when resorting to estimation strategies that take the discussed problems into account.     

Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect

Over the past few decades, much progress has been made in semiparametric modelling and estimation methods for econometric analysis. This paper is concerned with inference (i.e. confidence intervals and hypothesis testing) in semiparametric models. In contrast to the conventional approach based on t‐ratios, we advocate likelihood‐based inference. In particular, we study two widely applied semiparametric problems, weighted average derivatives and treatment effects, and propose semiparametric empirical likelihood and jackknife empirical likelihood methods. We derive the limiting behaviour of these empirical likelihood statistics and investigate their finite sample performance through Monte Carlo simulation. Furthermore, we extend the (delete‐1) jackknife empirical likelihood toward the delete‐d version with growing d and establish general asymptotic theory. This extension is crucial to deal with non‐smooth objects, such as quantiles and quantile average derivatives or treatment effects, due to the well‐known inconsistency phenomena of the jackknife under non‐smoothness.     

Environmental Kuznets Curve with Adjusted Net Savings as a Trade‐Off Between Environment and Development

The Environmental Kuznets Curve (EKC) hypothesises that emissions first increase at low stages of development then decrease once a certain threshold has been reached. The EKC concept is usually used with per capita Gross Domestic Product as the explanatory variable. As others, we find mixed evidence, at best, of such a pattern for CO₂ emissions with respect to per capita GDP. We also show that the share of manufacture in GDP and governance/institutions play a significant role in the CO₂ emissions–income relationship. As GDP presents shortcomings in representing income, development in a broad perspective or human well‐being, it is then replaced by the World Bank's Adjusted Net Savings (ANS, also known as Genuine Savings). Using the ANS as an explanatory variable, we show that the EKC is generally empirically supported for CO₂ emissions. We also show that human capital and natural capital are the main drivers of the downward sloping part of the EKC.     

Revisiting the environmental kuznets curve hypothesis: evidence from the ASEAN-5 countries with structural breaks

This paper tests if the Environmental Kuznets Curve (EKC) hypothesis exists for ASEAN-5 countries in an annual sample data that covers 1971–2013, by utilizing Auto Regressive Distributed Lag (ARDL) methodology. The empirical findings give support for the EKC hypothesis for Thailand only, after considering the structural breaks. Furthermore, the paper tests the EKC hypothesis for a panel data of the ASEAN-5 by adopting the Pooled Mean Group (PMG) methodology. The results show that the long-run estimates provide no evidence for the EKC hypothesis. Finally, the paper examines the causality between the CO₂ emissions and GDP. For individual countries, bidirectional causality was found in the case of Thailand and Malaysia, plus unidirectional causality running from GDP and squared GDP to CO₂ emissions was found for Indonesia, but a unidirectional causality running from CO₂ emissions to GDP and squared GDP was found for the Philippines, however, no causality effect was found for Singapore. Furthermore, the pairwise Dumitrescu and Hurlin Panel Causality test show a bidirectional effect between CO₂ emissions and both GDP in addition to squared GDP.     

TESTING THE QUANTAL RESPONSE HYPOTHESIS

We develop a nonparametric test for consistency of player behavior with the quantal response equilibrium (QRE). The test exploits a characterization of the equilibrium choice probabilities in any structural QRE as the gradient of a convex function; thereby, QRE‐consistent choices satisfy the cyclic monotonicity inequalities. Our testing procedure utilizes recent econometric results for moment inequality models. We assess our test using lab experimental data from a series of generalized matching pennies games. We reject the QRE hypothesis in the pooled data but cannot reject individual‐level quantal response behavior for over half of the subjects.     

地方经济增长与环境质量——以山东省域为例的库兹涅茨曲线分析

对于不同地区、不同污染物而言,经济增长与环境质量之间的关系不尽相同,表现为环境库兹涅茨曲线呈现地域性和时间性差异。本文在回顾相关研究成果的基础上,采用山东省17个城市1995～2008年的面板数据,建立涵盖污染物排放指标和环境监测指标两大类、11种环境指标与人均GDP之间的计量经济模型,对环境质量变化与山东省经济增长的关系进行实证检验,比较污染排放指标与环境监测指标的检验结果,进而评估人口规模、产业结构、对外开放以及环境政策等控制变量对污染物排放和环境质量的影响。结果显示,尽管部分环境指标处于下行通道,但山东省环境目前整体状况和未来趋势不容乐观,应进一步加大节能减排力度,完善污染治理的体制机制,改善治理效果。     

A new unit root test based on F-statistic in ESTAR framework

This article proposes a new F-type unit test in the exponential smooth transition autoregressive framework. We derive the asymptotic nonstandard distribution of the proposed test and explore its finite sample properties; simulation results show our test has greater power than the t_kss test proposed by Kapetanios et al.(2003). Finally, an application on the real exchange rates further underpins its superiority.     

Empirical study on the determinants of CO2 emissions: evidence from OECD countries

This article empirically investigates the Environmental Kuznets Curve (EKC) for CO₂ emissions in the cases of 11 OECD countries by taking into account the role of nuclear energy in electricity production. The autoregressive distributed lag approach to cointegration is employed as the estimation method. Our results indicate that energy consumption has a positive impact on CO₂ emissions in most countries in the study. However, the impact of trade is not statistically significant. The results provide evidence for the role of nuclear power in reducing CO₂ emissions only in some countries. Additionally, although the estimated long-run coefficients of income and its square satisfy the EKC hypothesis in Finland, Japan, Korea and Spain, only Finland's EKC turning point is inside the sample period of the study, providing poor evidence in support of the EKC hypothesis.     

Unit Root Tests for Dependent Micropanels

This paper proposes a new test for the null hypothesis of panel unit roots for micropanels with short time dimensions (T) and large cross‐sections (N). There are several distinctive features of this test. First, the test is based on a panel AR(1) model allowing for cross‐sectional dependency, which is introduced by a factor structure of the initial condition. Second, the test employs the panel AR(1) model with AR(1) coefficients that are heterogeneous for finite N. Third, the test can be used both for the alternative hypothesis of stationarity and for that of explosive roots. Fourth, the test does not use the AR(1) coefficient estimator. The effectiveness of the test rests on the fact that the initial condition has permanent effects on the trajectory of a time series in the presence of a unit root. To measure the effects of the initial condition, the present paper employs cross‐sectional regressions using the first time‐series observations as a regressor and the last as a dependent variable. If there is a unit root in every individual time series, the coefficient of the regressor is equal to one. The t‐ratios for the coefficient are this paper's test statistics and have a standard normal distribution in the limit. The t‐ratios are based on the OLS estimator and the instrumental variables estimator that uses reshuffled regressors as instruments. The test proposed in this paper makes it possible to test for a unit root even at T = 2 as long as N is large. Simulation results show that test statistics have reasonable empirical size and power. The test is applied to college graduates' monthly real wage in South Korea. The number of time‐series observations for this data is only two. The null hypothesis of a unit root is rejected against the alternative of stationarity.     

Dividend policy and earnings: a study of short- and long-term causality

This research examines whether earnings per share (EPS) and dividends per share (DPS) exhibit a short and long causality. The data employed in this study consist of quarterly EPS and DPS for 28 of the DJIA companies obtained from Bloomberg over a recent 10-year period. The companies under investigation all have EPS and DPS data available over the period studied. Dividends are generally paid out of earnings. The amount and timing of the dividend paid is a function of the respective company’s dividend policy. Therefore, the EPS_t can be expressed in terms of the DPS_t as follows: EPS_t = αDPS_t where α is a nonnegative constant. The equation suggests that there is a linear relationship between the EPS_t and the DPS_t. The results of this study indicate that bi-directional causality exists for some of the companies.     

RETURNS TO DEBT AND EQUITY IN FARM PRODUCER ORGANIZATIONS

While the capital structure irrelevance proposition is the point of departure in corporate finance, it is unknown if debt‐or‐equity decisions matter to farm producer organizations. To inform decisions of capital acquisition, a panel study is conducted to estimate the relationships of different types of debt (current, long‐term) and equity (allocated, unallocated) to the financial performance of 707 farm producer organizations in the United States during the 2005–2011 period. Using 3,120 observations, the panel analysis indicates net sales in period t is increased by $1.97, $9.59, and $4.01 with an addition of $1 in current debt, allocated equity, or unallocated equity in period t_‐1. Furthermore, the magnitude of the positive relationship of an additional dollar of allocated (unallocated) equity to net income is estimated at $0.32 ($0.14). We thus reject the notion managers and directors of farm producer organizations should decide to use debt or equity with a coin toss.     

Does economic growth and energy consumption drive environmental degradation in China’s 31 provinces? New evidence from a spatial econometric perspective

The panel data analysis points to economic and social factors contributing to NO_x, PM_2.5, PM₁₀, SO₂, and VOCs in China’s 31 provinces. The spatial correlation analysis using Global and Local Moran’s I values indicates the existence of a significant and positive spatial autocorrelation with respect to environment, economy and energy, and the high spatial correlation is evident in the eastern region, covering the northern part of Yangtze River Delta, Huaihai Economic Zone, and the lower reaches of the Yellow River Economic Belt. The empirical estimation is performed through spatial lag and spatial Durbin models. All emitted air pollutants in 31 provinces have significant spatial dependence and strong spillover effects. There is an inverted U-shaped relationship between emitted air pollutants (NO_x, PM₁₀, VOCs, and PM_2.5) and per capita GDP, which follows the EKC hypothesis. The relationship between SO₂ and per capita GDP does not follow the EKC hypothesis. There is a positive relationship between pollutant emissions and coal consumption, which is consistent with current studies for various countries like Canada, Denmark, UK and US and regions like New York State. However, the effects of science and technology investment on air pollutants are mostly positive, which is not as policy expected.     

DISCRIMINATING SHORT AND LONG MEMORY IN FINITE SAMPLES USING SENSITIVITY ANALYSIS: AN APPLICATION TO GROWTH CONVERGENCE

The standard linear model where u_t is generated from an ARFIMA process, is considered. The sensitivity of the predictor and sensitivity of variance estimates of the linear model to long memory are investigated by constructing the statistical measures B_L/S and D_L/S , respectively. B_L/S and D_L/S is interpreted as a sensitivity measure for the long‐memory process without the short‐memory effects. As an application, the memory characteristics of per capita GDP of 30 countries are investigated from the Maddison GDP dataset. It is found that per‐capita GDP exhibits long memory characteristics, and the long‐run growth estimates are sensitive to the long memory characteristics.     

SCALE EFFECT VERSUS INDUCED POLICY RESPONSE IN THE ENVIRONMENTAL KUZNETS CURVE: THE CASE OF U.S. WATER POLLUTION

The environmental Kuznets curve (EKC) could arise from the scale effect in abatement technology as emphasized by Andreoni and Levinson (2001) or from the induced policy response as suggested by Grossman and Krueger (1995). This paper incorporates these two contrary views into a model and quantitatively evaluates their relative importance in shaping the EKC of U.S. water pollution. Our main findings include: (a) some scale effect in abatement technology must exist, otherwise the turning point of the EKC will be unreasonably high; (b) the scale effect alone is not sufficient to explain the practical occurrence of the turning point of the EKC; and (c) the scale effect features critically in the induced policy response as well. (JEL H41, O40, Q20)     

Does urbanization increase pollutant emission and energy intensity? evidence from some Asian developing economies

This paper aims to investigate the effects of urbanization on pollutant emissions and energy intensity in selected Asian developing countries after controlling for the effects of disaggregated (renewable and non-renewable) energy consumption, trade liberalization, and economic growth. We use both linear and nonlinear panel data econometric techniques and employ recently introduced mean group estimation methods, allowing for heterogeneity and cross-sectional dependence. However, to check the robustness of our panel results, we also apply the autoregressive distributed lag (ARDL)-bound testing approach to country-level data. In addition, the relationship between affluence and CO₂ emissions is examined in the context of the Environmental Kuznets Curve (EKC) hypothesis. The estimation results identify the population, affluence, and non-renewable energy consumption as major factors in pollutant emissions in Asian countries. However, the results of the EKC hypothesis show that when countries achieve a certain level of economic growth, their emissions tend to decline. Whereas nonlinear results show that renewable energy, urbanization, and trade liberalization reduce emissions, linear estimations do not confirm these outcomes. Thus, substitution of non-renewable for renewable energy consumption, cautious and planned urbanization programs and more liberal trading regimes may be viable options for sustainable growth of these developing Asian economies.     

QUANTILE FORECASTS OF FINANCIAL RETURNS USING REALIZED GARCH MODELS*

This article applies the realized generalized autoregressive conditional heteroskedasticity (GARCH) model, which incorporates the GARCH model with realized volatility, to quantile forecasts of financial returns, such as Value‐at‐Risk and expected shortfall. Student's t‐ and skewed Student's t‐distributions as well as normal distribution are used for the return distribution. The main results for the S&P 500 stock index are: (i) the realized GARCH model with the skewed Student's t‐distribution performs better than that with the normal and Student's t‐distributions and the exponential GARCH model using the daily returns only; and (ii) using the realized kernel to take account of microstructure noise does not improve the performance.     

TESTING STRICT STATIONARITY WITH APPLICATIONS TO MACROECONOMIC TIME SERIES

We propose a model‐free test for strict stationarity. The idea is to estimate a nonparametric time‐varying characteristic function and compare it with the empirical characteristic function based on the whole sample. We also propose several derivative tests to check time‐invariant moments, weak stationarity, and pth order stationarity. Monte Carlo studies demonstrate excellent power of our tests. We apply our tests to various macroeconomic time series and find overwhelming evidence against strict and weak stationarity for both level and first‐differenced series. This suggests that the conventional time series econometric modeling strategies may have room to be improved by accommodating these time‐varying features.     

THE IMPACT OF MERGERS IN U.S. PETROLEUM INDUSTRY ON WHOLESALE GASOLINE PRICES

Starting in the mid‐1990s, the U.S. petroleum industry experienced a wave of mergers, several of them between large petroleum companies that were previously competitors. Using an econometric analysis of terminal city‐specific data, this study finds that the majority of the mergers led to higher wholesale gasoline prices in the United States in the mid‐1990s through 2000. (JEL L7, L13, L40)     

Econometrics and equilibrium models

In Rational Econometric Man, Edward Nell and Karim Errouaki present a welcome and timely case for the view that econometrics and econometric model-building may not be the magic tools to solve all empirical questions despite what many seem to have thought they were in the 1960s. Here I examine some possible problems with econometric models that have to do with their usually taking the form of equilibrium models. Some of these problems were recognized by Trygve Haavelmo decades ago. And as Aris Spanos has recently discussed, the problems are often the result of what we say in our textbooks. Some problems have to do with what we mean by econometric parameters and others with how we use probabilities.