Shadow prices of $$\hbox {CO}_{2}$$ emissions at US electric utilities: a random-coefficient,random-directional-vector directional output distance function approach

We estimate the shadow prices of \(\hbox {CO}_{2}\) emissions of electric utilities in the US over the period from 2001 to 2014, using a random-coefficient, random-directional-vector directional output distance function (DODF) model. The main feature of this model is that both its coefficients and directional vector are allowed to vary across firms, thus allowing different firms to have different production technologies and to follow different growth paths. Our Bayes factor analysis indicates that this model is strongly favored over the commonly used fixed-coefficient DODF model. Our results obtained from this model suggest that the average annual shadow price of \(\hbox {CO}_{2}\) emissions ranges from $61.62 to $105.72 (in 2001 dollars) with an average of $83.12. The results also suggest that the firm-specific average shadow price differs significantly across electric utilities. In addition, our estimates of the shadow price of \(\hbox {CO}_{2}\) emissions show an upward trend for both the sample electric utilities as a whole and the majority of the individual sample electric utilities.     

Fiscal Policy and $$\hbox {CO}_{2}$$ Emissions of New Passenger Cars in the EU

To what extent have national fiscal policies contributed to the decarbonisation of newly sold passenger cars? We construct a simple model that generates predictions regarding the effect of fiscal policies on average \(\hbox {CO}_{2}\) emissions of new cars, and then test the model empirically. Our empirical strategy combines a diverse series of data. First, we use a large database of vehicle-specific taxes in 15 EU countries over 2001–2010 to construct a measure for the vehicle registration and annual road tax levels, and separately, for the \(\hbox {CO}_{2}\) sensitivity of these taxes. We find that for many countries the fiscal policies have become more sensitive to \(\hbox {CO}_{2}\) emissions of new cars. We then use these constructed measures to estimate the effect of fiscal policies on the \(\hbox {CO}_{2}\) emissions of the new car fleet. The increased \(\hbox {CO}_{2}\)-sensitivity of registration taxes have reduced the \(\hbox {CO}_{2}\) emission intensity of the average new car by 1.3 %, partly through an induced increase of the share of diesel-fuelled cars by 6.5 percentage points. Higher fuel taxes lead to the purchase of more fuel efficient cars, but higher diesel fuel taxes also decrease the share of (more fuel efficient) diesel cars; higher annual road taxes have no or an adverse effect.     

A trend filtering method closely related to $$\ell _{1}$$ trend filtering

The filtering method developed by Kim et al. (SIAM Rev 51:339–360, 2009), \(\ell _{1}\) trend filtering, is attractive because it enables us to estimate a continuous piecewise linear trend. This paper introduces a new filtering method closely related to \(\ell _{1}\) trend filtering in order to contribute to the accumulation of knowledge on \(\ell _{1}\) trend filtering. We show that the piecewise linearity, which is the key feature of \(\ell _{1}\) trend filtering, is derived from the new filtering. For this reason, we refer to the filtering as ‘pure’ \(\ell _{1}\) trend filtering. We also demonstrate some other miscellaneous results concerning the new filtering.     

Is the Green Solow Model Valid for $$\hbox {CO}_{2}$$ Emissions in the European Union?

This paper addresses the \(\hbox {CO}_{2}\) emission patterns of the European Union from 1950 to 2010, and examines the validity of the Green Solow model, which simulates \(\hbox {CO}_{2}\) emissions growth by including only Solow forces and assuming emission intensity growth to be exogenous and constant. This study verifies that an environmental Kuznets curve (EKC) trajectory exists for per capita \(\hbox {CO}_{2}\) emissions in the European Union, that emission intensity growth is decreasing over time, and that the decreasing intensity growth reflects variations of the dependent variable in the specifications of the Green Solow model. The critique by Stefanski (On the mechanics of the Green Solow model. OxCarre Research Paper 47, OxCarre & Laval University, Oxford, 2013) of the Green Solow model assumption of exogenous and constant intensity growth is validated. The EKC is defined as the emissions plotted against income and emission intensity is defined as the ratio of emissions to income. The EKC and emission intensity share identical definitions and similar transition trajectories over time. The transition of the EKC trajectory and decline in emission intensity growth began before worldwide attention was focused on global warming.     

Technical Synergies and Trade-Offs Between Abatement of Global and Local Air Pollution

In this paper, we explore the synergies and tradeoffs between abatement of global and local pollution. We build a unique dataset of Swedish combined heat and power plants with detailed boiler-level data 2001–2009 on not only production and inputs but also on emissions of \(\hbox {CO}_{2}\) and \(\hbox {NO}_{\mathrm{x}}\). Both pollutants are regulated by strict policies in Sweden. \(\hbox {CO}_{2}\) is subject to the European Union Emission Trading Scheme and Swedish carbon taxes; \(\hbox {NO}_{\mathrm{x}}\)—as a precursor of acid rain and eutrophication—is regulated by a heavy fee. Using a quadratic directional output distance function, we characterize changes in technical efficiency as well as patterns of substitutability in response to the policies mentioned. The fact that generating units face a trade-off between the pollutants indicates the need for policy coordination.     

Shaping the Relationship Between Economic Development and Carbon Dioxide Emissions at the Local Level: Evidence from Spatial Econometric Models

The debate over the correlation between economic growth and environmental pollution has attracted a great deal of attention from academic researchers and policy makers in recent years. There has been excessive use of spatial econometric models and too much emphasis on statistical procedures in empirical studies. In this study, we contribute to the existing literature by conducting a more rigorous analysis of the relationship between economic growth and \(\hbox {CO}_{2}\) emissions in Chinese cities using spatial Durbin models. Our results show that \(\hbox {CO}_{2}\) emissions increase monotonically in relation to economic growth at the city level and that the driving effects of economic growth are slightly smaller in central China than in eastern and western China. In addition to economic growth, industry’s share of the economy is a major driver of \(\hbox {CO}_{2}\) emissions, while technological improvement, measured by energy intensity per unit of gross domestic product (GDP), and the effectiveness of environmental governance flatten the shape of the environmental Kuznets curve. We provide evidence of local spillover effects of explanatory variables on \(\hbox {CO}_{2}\) emissions. Economic competition as well as technological diffusion are found to exist in Chinese cities in relation to \(\hbox {CO}_{2}\) emissions. We also find carbon leakage between cities only if the per capita GDP of a given city is less than $493 (in 2010 constant dollars). Results hold when robustness checks are performed. Policy makers should carefully consider regional differences and the inherent spatial interactions between factors when formulating carbon reduction policies.     

Offsetting Versus Mitigation Activities to Reduce $$\hbox {CO}_{2}$$ Emissions: A Theoretical and Empirical Analysis for the U.S. and Germany

This paper studies the voluntary provision of public goods that is partially driven by a desire to offset for individual polluting activities. We first extend existing theory and show that offsets allow a reduction in effective environmental pollution levels while not necessarily extending the consumption of a polluting good. We further discuss the impact of an increased environmental preference on purchases of offsets and mitigation activities. Several theoretical results are then econometrically tested using a novel dataset on activities to reduce \(\hbox {CO}_{2}\) emissions for the case of vehicle purchases in the U.S. and Germany. We show that environmental preference triggers the stated use of \(\hbox {CO}_{2}\) offsetting and mitigation channels in both countries. However, we find strong country differences for the stated purchase of \(\hbox {CO}_{2}\) offsets. While such activities are mainly triggered by a high general awareness of the climate change problem in the U.S., the perception that road travel is responsible for \(\hbox {CO}_{2}\) emissions to a large extent is more important for driver’s license holders in Germany.     

Controlling Episodic Air Pollution with a Seasonal Gas Tax: The Case of Cache Valley,Utah

Using daily data spanning 10 years, we establish a statistical relationship between episodic particulate-matter \((\hbox {PM}_{2.5})\) concentrations and vehicle trips in Cache Valley, Utah, and estimate an average gas-price elasticity for the region. We also estimate the benefits and costs associated with a seasonal gas tax set to reduce vehicle trips during the winter-inversion season and thereby lower health costs through concomitant decreases in the \(\hbox {PM}_{2.5}\) concentrations. We find a strong positive relationship between vehicle trips reduced and associated reductions in \(\hbox {PM}_{2.5}\) concentrations. Further, we estimate a mean gas price elasticity of approximately \(-\)0.3 in what we call a “high price variability environment.” Incorporating these results, cost-benefit analysis suggests that the social net benefit for Cache Valley associated with the imposition of a seasonal gas tax during the winter-inversion season is highly dependent upon the type of benefit estimation method used.     

Fractional Integration Versus Structural Change: Testing the Convergence of $$\hbox {CO}_{2}$$ Emissions

This paper assesses the stochastic convergence of relative \(\hbox {CO}_{2}\) emissions within 28 OECD countries over the period 1950–2013. Using the local Whittle estimator and some of its variants we assess whether relative per capita \(\hbox {CO}_{2}\) emissions are long memory processes which, although highly persistent, may revert to their mean/trend in the long run thereby indicating evidence of stochastic convergence. Furthermore, we test whether (possibly) slow convergence or the complete lack of it may be the result of structural changes to the deterministics of each of the relative per-capita emissions series by means of the tests of Berkes et al. (Ann Stat 1140–1165, 2006) and Mayoral (Oxford Bull Econ Stat 74(2):278–305, 2012). Our results show relatively weak support for stochastic convergence of \(\hbox {CO}_2\) emissions, indicating that only between 30 and 40% of the countries converge to the OECD average in a stochastic sense. This weak evidence disappears if we enlarge the sample to include 4 out of the 5 BRICS, indicating that our results are not robust to the inclusion of countries which are experiencing rates of growth which are far larger than those of the OECD members. Our results also decisively indicate that a slow or lack of convergence is not the results of a structural break in the relative \(\hbox {CO}_{2}\) emissions series.     

The Value of Air Quality in Chinese Cities: Evidence from Labor and Property Market Outcomes

Using a dual-market sorting model of workers’ location decisions, this paper studies the capitalization of air pollution in wages and property prices across Chinese cities. To account for endogeneity of air pollution in the determination of wages and property prices, we exploit quasi-experimental variation in air quality induced by a policy subsidizing coal-based winter heating in northern China, and document a discontinuity in average air quality for cities located north and south of the policy boundary. Using data for all 288 Chinese cities in 2011, we estimate an equilibrium relationship between wages and house prices for the entire system of Chinese cities, and specify a regression discontinuity design to quantify how variation in air quality induced by the policy affects this relationship locally. Our preferred estimates of the elasticity of wages and house prices with respect to \(\text {PM}_{10}\) concentration are 0.53 and \({-}\) 0.71 respectively. At the average of our sample, the willingness to pay for a unit reduction in \(\text {PM}_{10}\) concentration is CNY 261.28 (\(\simeq \) USD 40.50), with a significant share reflected in labor market outcomes.     

Tops-only domains

In this paper we consider the standard voting model with a finite set of alternatives A and n voters and address the following question: what are the characteristics of domains \({\mathcal D}\) that induce the property that every strategy-proof social choice function \({f: {\mathcal D}^n \rightarrow A}\) satisfying unanimity, has the tops-only property? We first impose a minimal richness condition which ensures that for every alternative a, there exists an admissible ordering where a is maximal. We identify conditions on \({\mathcal D}\) that are sufficient for strategy-proofness and unanimity to imply tops onlyness in the general case of n voters and in the special case, n = 2. We provide an algorithm for constructing tops-only domains from connected graphs with elements of A as nodes. We provide several applications of our results. Finally, we relax the minimal richness assumption and partially extend our results.     

How Much Does Wind Power Reduce $$\text {CO}_{2}$$ Emissions? Evidence from the Irish Single Electricity Market

This paper evaluates the effect of wind generation on \(\text {CO}_{2}\) emissions using 2008–2012 historical data for the Irish Single Electricity Market. Wind generation displaces \(\text {CO}_{2}\) emissions, as expected, in line with the average system emissions. Over the whole period, wind generation avoided about 8.8 million tons of \(\text {CO}_{2}\), equivalent to about 12% of total system emissions. To understand what drives the level of abatement we evaluate the results by technology and determine that wind generation has similar effects on total emissions from CCGT and coal plants, due to the higher carbon content of coal. Each MWh of wind, however, replaces more generation from CCGTs than from coal plants, in proportion to their generation. We also test the hypothesis that as wind displaces baseload plants it pushes them to generate less efficiently, but find no evidence of a strong negative effect of wind on CCGT or coal plant efficiency. Finally wind displaces about 2.5% fewer emissions when the pumped storage plant is on outage, suggesting that wind is more effective when paired with a flexible system.     

Nonparametric measures of efficiency in the presence of undesirable outputs: a by-production approach

In empirical research on productivity measurement adjusted for undesirable outputs on the side, the good and the bad outcomes are treated as joint products of the underlying production process. In the present paper, following Murty, Russell, and Levkoff, we conceptualize the good output as technologically separable from the bad output. Joint disposability is assumed between the bad output and the polluting input, rather than weak disposability and null jointness between the good and bad outputs. Moreover, we set up an integrated DEA optimization problem over the intersection of these two subtechnologies to measure the efficiency of a firm that produces a bad output alongside the good output. In an empirical illustration of our methodology, we use country-level data for an unbalanced panel of 64 countries over the years 1986 through 2011 where per capita GDP is the good and per capita \(\hbox {CO}_{2}\) emission is the bad output. We then utilize our DEA results to compute opportunity costs of a targeted reduction in \(\hbox {CO}_{2}\) emission in terms of required dollar amounts of reduction in per capita GDP for the individual countries in selected years.     

Origins of knowledge and innovation in R&D alliances: a contingency approach

Innovative performance is influenced both by the origins of the existing knowledge that is combined to generate innovation and by how economic actors search for new knowledge. Drawing on a sample of inter-firm dyadic R&D alliances, we found that whereas the integration of geographically distant knowledge and of organisationally proximate knowledge in R&D alliances are negatively related to the alliance innovative performance, search span positively moderates both relationships. We conclude that, in order to make the most of broad-span searching, firms participating in R&D alliances should integrate geographically distant but organisationally proximate knowledge. By doing so, firms take advantage of the diversity and novelty that characterises geographically distant knowledge, while preserving considerable levels of relative absorptive capacity that are needed for them to understand, internalise, and effectively use partners’ knowledge from different domains.     

Does FDI Bring Environmental Knowledge Spillovers to Developing Countries? The Role of the Local Industrial Structure

This paper examines the environmental knowledge externalities of FDI within and across cities in an emerging economy context. It argues that the extent of these environmental externalities is contingent upon local industrial agglomeration. Using a panel dataset of 280 Chinese prefectural cities from 2003 to 2012, we employ a spatial economic approach. Although limited to evidence from soot and \(\hbox {SO}_{2}\) pollutants, our results suggest that FDI brings overall positive environmental knowledge externalities to a region, and also spillovers to nearby regions. Specialised cities may lock into a particular technological path, attenuating the absorption and diffusion of a variety of FDI environmental knowledge. Conversely, diversified cities promote cross-fertilisation of environmental knowledge and mitigate local pollution intensity at the aggregated city level. This study adds to the literature by highlighting the importance of considering both the spatiality of FDI and industrial structure in understanding FDI environmental knowledge spillovers.     

Aspects of Governance and $$\hbox {CO}_2$$Emissions: A Non-linear Panel Data Analysis

The reduction of \(\hbox {CO}_2\)emissions has been at the centre of worldwide debates on environmental issues, though its inclusion as one of the millennium development goals (MDGs) by the United Nations has changed the focus of relative literature. Among many, one of the World Bank’s “recipes” to achieve a higher position toward MDGs has been to undertake reforms for a better governance. While, the majority of researches’ focus has been on one single aspect and its relationship with the environment, some studies, have simultaneously considered two governance dimensions. In this paper, we focus on the role of several aspects of governance on \(\hbox {CO}_2\)emissions. This provides us with a chance to explore the possible impacts of all aspects of governance on a more direct measure of emissions, that is different to previous researches which have focused on the indirect transmission and considered the maximum of two. Using the IV method within panel data analysis, we show that only one single aspect of governance, Control of Corruption, has a negative significant effect on \(\hbox {CO}_2\)emissions and its effect has a non-linear relationship. The non-linearity exists in both parametric and nonparametric analysis after controlling for endogeneity.     

Export,R&D and new products. a model and a test on European industries

In this article we extend the model developed by Bogliacino and Pianta (Industrial and Corporate Change 22 649, 2013, b) on the link between R&D, innovation and economic performance, considering the impact of innovation on export success. We develop a simultaneous three equation model in order to investigate the existence of a ‘virtuous circle’ between industries’ R&D, share of product innovators and export market shares. We investigate empirically – at the industry level – three key relationships affecting the dynamics of innovation and export performance: first, the capacity of firms to translate their R&D efforts in new products; second, the role of innovation as a determinant of export market shares; third, the export success as a driver of new R&D efforts. The model is tested for 38 manufacturing and service sectors of six European countries over three time periods, from 1995 to 2010. The model effectively accounts for the dynamics of R&D efforts, innovation and international performance of European industries. Moreover, important differences across countries emerge when we split our sample into a Northern group – Germany, the Netherlands and the United Kingdom – and a Southern group – France, Italy and Spain. We find that the ‘virtuous circle’ between innovation and competitiveness holds for Northern economies only, while Southern industries fail to translate innovation efforts into export success.     

Bootstrap LM tests for higher-order spatial effects in spatial linear regression models

This paper first extends the methodology of Yang (J Econom 185:33–59, 2015) to allow for non-normality and/or unknown heteroskedasticity in obtaining asymptotically refined critical values for the LM-type tests through bootstrap. Bootstrap refinements in critical values require the LM test statistics to be asymptotically pivotal under the null hypothesis, and for this we provide a set of general methods for constructing LM and robust LM tests. We then give detailed treatments for two general higher-order spatial linear regression models: namely the \(\mathtt{SARAR}(p,q)\) model and the \(\mathtt{MESS}(p,q)\) model, by providing a complete set of non-normality robust LM and bootstrap LM tests for higher-order spatial effects, and a complete set of LM and bootstrap LM tests robust against both unknown heteroskedasticity and non-normality. Monte Carlo experiments are run, and results show an excellent performance of the bootstrap LM-type tests.     

Technological and geographical proximity effects on knowledge spillovers: evidence from the US patent citations

The purpose of this paper is to investigate the pattern of knowledge flows as indicated by the patent citations in three areas: USA, Japan and Europe. In each economic area, we use information from United States Patent and Trademarks Office data to assess empirically the impact of the technological and geographical proximities for 530 international firms. In particular, the contribution to the existing literature is twofold: first, we use an international sample in such a way that we may compare the empirical results among different economic markets; second, we extend the analysis of the determinants of knowledge spillovers, taking into account the time dimension of the effects of the proximities. In order to compute the technological proximity, we follow the methodology developed by A.B. Jaffe (1986 Jaffe, A. B. 1986. Technological opportunity and spillovers of R&D: Evidence from firms’ patents, profits and market value. American Economic Review, 76(5): 984–1001. [Web of Science ®] , [Google Scholar]. Technological opportunity and spillovers of R&D: Evidence from firms’ patents, profits and market value. American Economic Review 76, no. 5: 984–1001), where a technological vector is based on the distribution of patents of each firm across technology classes. As far as the geographic proximity is concerned, we use the latitude and the longitude coordinates of the city in which each firm is situated to obtain the distance, in miles, between the firms. The empirical results, in line with results from previous studies, indicate that there is a statistically significant relationship between the knowledge flows, proxied by the patent citations, and the proximities, but the effects are rather differentiated according to the proximity type.