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This article analyzes a growing group of fixed T dynamic panel data estimators with a multifactor error structure. We use a unified notational approach to describe these estimators and discuss their properties in terms of deviations from an underlying set of basic assumptions. Furthermore, we consider the extendability of these estimators to practical situations that may frequently arise, such as their ability to accommodate unbalanced panels and common observed factors. Using a large-scale simulation exercise, we consider scenarios that remain largely unexplored in the literature, albeit being of great empirical relevance. In particular, we examine (i) the effect of the presence of weakly exogenous covariates, (ii) the effect of changing the magnitude of the correlation between the factor loadings of the dependent variable and those of the covariates, (iii) the impact of the number of moment conditions on bias and size for GMM estimators, and finally (iv) the effect of sample size. We apply each of these estimators to a crime application using a panel data set of local government authorities in New South Wales, Australia; we find that the results bear substantially different policy implications relative to those potentially derived from standard dynamic panel GMM estimators. Thus, our study may serve as a useful guide to practitioners who wish to allow for multiplicative sources of unobserved heterogeneity in their model.

The Clean Development Mechanism (CDM) is one of the three greenhouse gas emission reduction and trading instruments of the Kyoto Protocol (KP). The CDM allows governments and business entities from developed countries to offset their emissions liabilities by reducing or avoiding emissions in developing countries, where it is often cheaper to do so. Our results reveal that the majority of the CDM projects utilise local sources of technology. We attempt to explain technology sourcing patterns in CDM projects through the use of knowledge based determinants. Our empirical analysis indicates that in countries with a stronger knowledge base in climate friendly technologies, CDM project implementers tend to use local, as well as a combination of local and foreign technologies, more than foreign technologies.

Intro -- Acknowledgement -- Abstract -- Zusammenfassung -- Contents -- List of Figures -- List of Tables -- List of Algorithms -- Acronyms -- Glossary -- 1 Introduction -- 1.1 Controlling traffic lights -- 1.2 Data acquisition methods -- 1.3 Airborne sensors -- 1.4 Self-Organizing Traffic Lights -- 1.5 Traffic optimization goals -- 1.6 Greenhouse gas -- 1.7 Vehicles' emissions -- 1.8 Hypothesis and the research questions -- 1.9 Organization of the thesis -- 2 Comparison of travel time es-timations using intelligent in-frastructure and floating car data -- 2.1 Introduction -- 2.2 State of the art -- 2.3 Simulation environment -- 2.4 Methods -- 2.5 Measurements -- 2.6 Results -- 2.7 Summary -- 3 Integration of cellular automata traffic simulation with carbon dioxide emission model -- 3.1 Traffic simulators -- 3.2 Greenhouse gases and carbon dioxide emis-sion -- 3.3 CO2 emission model -- 3.4 Microscopic traffic simulator -- 3.5 Cellular automata traffic simulator -- 3.6 Integration of cellular automata traffic sim-ulation with emission model -- 3.6.1 Data acquisition -- 3.6.2 Data preparation -- 3.6.3 Vehicles' acceleration rate -- 3.6.4 Data analysis -- 3.6.5 Distribution of the acceleration -- 3.6.6 Deceleration -- 3.6.7 Adaptation of Rule 184 -- 3.7 Rule 184-based CO2 traffic emission model -- 3.7.1 Implementation note -- 3.8 NaSch-based CO2 traffic emission model -- 3.9 Critics, discussion and future work -- 4 The impact of dynamic route guidance system driven by travel time measurements on carbon dioxide emission -- 4.1 Introduction -- 4.2 Dynamic route guidance system architec-ture -- 4.2.1 Shortest Paths Algorithm -- 4.2.2 Cost function -- 4.2.3 Path with minimal cost -- 4.3 Methodology and measurements -- 4.4 Simulation -- 4.4.1 Virtual cities -- 4.5 Test scenarios and results -- 4.5.1 First scenario -- 4.5.2 Second scenario.

The clean development mechanism (CDM) is often seen as providing the financial benefits and transfers of cutting-edge green technology that enable developing countries to reduce emissions and achieve their sustainable development goals. The process of implementing the mechanism is, however, fraught with challenges. The absence of the United States in the carbon market has induced the low price of certified emissions reductions through the CDM, while host countries desire to ensure the sustainable development benefits of the CDM is likely to result in a complex approval process, which would further increase transaction costs. This article examines the CDM implementation environment in the context of a South African case study. It is argued that a fine balance needs to be struck between the spirit of the CDM, as encapsulated in its mandate to promote sustainable development in host countries, and its economic rationale when host countries approve those projects they deem beneficial.

U.S.Environmental Protection Agency (EPA) set the nationwide emission standard policy, but each state in the U.S. has an option to follow the higher emission standard policy set by CARB (California Air Resources Board) in 2004. There are 14 &ldquo ; CARB states&rdquo ; that follow California&rsquo ; s more restrictive standards. The purpose of this paper is to examine the impact of CARB&rsquo ; s tailpipe emission standard policy. Using the panel dataset for 49 U.S. states over a 28-year study period (1987&ndash ; 2015), this paper found the long-term policy effect in reducing CO2 emission from CARB&rsquo ; s tailpipe standard, and its long-run effect is 5.4 times higher than the short-run effect. The equivalent policy effect of the CARB emission standard in CO2 reduction can be achieved by raising gasoline price by 145.43%. Also, if 26.0% of petroleum consumed for transportation is substituted by alternative clean fuels (natural gas or electricity), it will have a comparable policy effect in CO2 reduction. Findings in this study support to continue the collaborative efforts among the EPA, National Highway Traffic Safety Administration (NHTSA), and California in order to achieve the CO2 reduction goal set by CARB and adopted by the EPA in 2012. The packaged policy approach rooted in persistent public and political support is necessary for successful policy implementation.

Despite significant technological advances in emerging economies, the further development of clean energy technologies in developing countries remains crucial to reducing the greenhouse gas emissions associated with economic development. In this paper we address two significant gaps in the growing body of literature that has assessed the role of the Clean Development Mechanism in promoting the transfer of clean technologies to developing countries. First, we present a qualitative analysis of the governance of the Clean Development Mechanism in India. This provides a basis for understanding the extent to which and the ways in which governance may impact upon the likelihood that projects promote technology transfer. Second, we provide a novel quantification of the level and nature of technology transfer that has occurred in Indian Clean Development Mechanism projects, based on insights from literature on technological capability building. We find that the Clean Development Mechanism in India has produced a negligible number of projects that promote technology transfer if technology transfer is understood as a process of learning about technology. Together these qualitative and quantitative analyses show how politics and governance have contributed to the current form of the Clean Development Mechanism market in India, in which processes of building indigenous technological capabilities have been neglected.

Introduction / Badi H. Baltagi, Thomas B. Fomby, R. Carter Hill -- Testing for common cyclical features in nonstationary panel data models / Alain Hecq, Franz C. Palm, Jean-Pierre Urbain -- The local power of some unit root tests for panel data / J(c)·org Breitung -- On the estimation and inference of a cointegrated regression in panel data / Chihwa Kao, Min-Hsien Chiang -- Testing for unit roots in panels in the presence of structural change with an application to OECD unemployment / Christian J. Murray, David H. Papell -- Panel data limit theory and asymptotic analysis of a panel regression with near integrated regressors / Heikki Kauppi -- Stationarity tests in heterogeneous panels / Yong Yin, Shaowen Wu -- Instrumental variable estimation of semiparametric dynamic panel data models : Monte Carlo results on several new and existing estimators / M. Douglas Berg, Qi Li, Aman Ullah -- Small sample performance of dynamic panel data estimators in estimating the growth-convergence equation : a Monte Carlo study / Nazrul Islam -- Estimation in dynamic panel data models : improving on the performance of the standard GMM estimator / Richard Blundell, Stephen Bond, Frank Windmeijer -- Nonstationary panels, cointegration in panels and dynamic panels : a survey / Badi H. Baltagi, Chihwa Kao -- Fully modified OLS for heterogeneous cointegrated panels / Peter Pedroni. - This volume is dedicated to two recent intensive areas of research in the econometrics of panel data, namely nonstationary panels and dynamic panels. It includes a comprehensive survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration tests. In addition, it provides recent developments in the estimation of dynamic panel data models using generalized method of moments. The volume includes eleven chapters written by twenty authors. These chapters: investigate better methods of estimating dynamic panels; develop methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels; extend the concept of serial correlation common features analysis to nonstationary panel data models; study the local power of panel unit root test statistics; derive the asymptotic distributions of various estimators for the panel cointegrated regression model; propose a unit root test in the presence of structural change; develop a new limit theory for panel data that may be cross-sectionally heterogeneous; propose stationarity tests for a heterogeneous panel data model; derive instrumental variable estimators for a semiparametric partially linear dynamic panel data model; and conduct Monte Carlo experiments to study the small sample properties of a growth convergence equation. This collection of papers should prove useful for practitioners and researchers working with panel data

ABSTRACTThis paper studies the socio‐economic determinants of violence in the seven most important cities in Colombia. Derived from theories rooted in classic works, including Becker's paradigm, criminal inertia, social disorganisation, urbanism and strain, we formulate several hypotheses on the socio‐economic determinants of violence. To test these hypotheses, a dynamic panel data analysis is employed. The analysis shows that cities' deprivation and high population density are strong predictors of homicide rates. Comparing the results among Colombian cities, we find support indicating that city‐level homicide rates are influenced by the city's level of development. Moreover, we find evidence that economic growth, inequality, poverty and human capital influence violence in the cities studied, which could generate negative effects on the economic and social development of Colombia. Copyright © 2012 John Wiley & Sons, Ltd.

This article explores the ways in which the "global" governance of the Clean Development Mechanism (CDM) intersects with the "local" politics of resource regimes that are enrolled in carbon markets through the production and trade in Certified Emissions Reductions (CERs). It shows how political structures and decision-making procedures set up at the international level to govern the acquisition of CERs through the Kyoto Protocol's CDM interact with and transform national and local level political ecologies in host countries where very different governance structures, political networks, and state-market relations operate. It draws on literature within political ecology and field work in Argentina and Honduras to illustrate and understand the politics of translation that occur when the social and environmental consequences of decisions made within global governance mechanisms, such as the CDM, are followed through to particular sites in the global political economy. It also shows how the outcomes in those sites in turn influence the global politics of the CDM.