The Experts below are selected from a list of 219555 Experts worldwide ranked by ideXlab platform
Edward Miguel - One of the best experts on this subject based on the ideXlab platform.
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using randomized controlled trials to estimate long run impacts in development Economics
Annual Review of Economics, 2019Co-Authors: Adrien Bouguen, Edward Miguel, Yue Huang, Michael KremerAbstract:We assess evidence from randomized controlled trials (RCTs) on long-run Economic Productivity and living standards in poor countries. We first document that several studies estimate large positive ...
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global non linear effect of temperature on Economic production
Nature, 2015Co-Authors: Marshall Burke, Solomon Hsiang, Edward MiguelAbstract:Economic Productivity is shown to peak at an annual average temperature of 13 °C and decline at high temperatures, indicating that climate change is expected to lower global incomes more than 20% by 2100. Temperature, and therefore climate change, can affect a country's Economic Productivity, but it has not been clear if rich and poor countries, or different aspects of Economic Productivity, show similar relationships. These authors use Economic data from 166 countries for the years 1960 to 2010 to uncover a universal nonlinear relationship that reconciles earlier results. Economic Productivity peaks at an annual average temperature of 13 °C, and the authors explore the likelihood of global Economic contraction under future warming scenarios. Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies1,2, but effects on Economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries3,4. In contrast, aggregate macroEconomic Productivity of entire wealthy countries is reported not to respond to temperature5, while poor countries respond only linearly5,6. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems7,8 and to anticipating the global impact of climate change9,10. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall Economic Productivity is non-linear in temperature for all countries, with Productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that Economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling Economic loss in response to climate change11,12, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.
Ashish Lall - One of the best experts on this subject based on the ideXlab platform.
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developing measures of airport Productivity and performance an application of data envelopment analysis
Transportation Research Part E-logistics and Transportation Review, 1997Co-Authors: David Gillen, Ashish LallAbstract:Many studies have investigated the financial results and Economic Productivity of airlines but few have investigated the Productivity or performance of airports, and how changes in the industry may have affected them. Most airports measure performance strictly in accounting terms by looking at only total costs and revenues and the resulting surpluses or deficits. Few utilize any type of Productivity measure or performance indicator. This paper applies Data Envelopment Analysis to assess the performance of airports. It is used to construct performance indices on the basis of the multiple outputs which airports produce and the multiple inputs which they utilize. In particular we develop Productivity measures for terminals and airside operations. The performance measures are then used in a second stage Tobit regression in which environmental, structural and managerial variables are included. The regression results provide a 'net' performance index and also identify which variables the managers have some control over and what the relative importance of each variable is in affecting performance. The data set contains a panel of 21 U.S. airports over a five-year period.
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developing measures of airport Productivity and performance an application of data envelopment analysis
Transportation Research Part E-logistics and Transportation Review, 1997Co-Authors: David Gillen, Ashish LallAbstract:Many studies have investigated the financial results and Economic Productivity of airlines but few have investigated the Productivity or performance of airports, and how changes in the industry may have affected them. Most airports measure performance strictly in accounting terms by looking at only total costs and revenues and the resulting surpluses or deficits. Few utilize any type of Productivity measure or performance indicator. This paper applies Data Envelopment Analysis to assess the performance of airports. It is used to construct performance indices on the basis of the multiple outputs which airports produce and the multiple inputs which they utilize. In particular we develop Productivity measures for terminals and airside operations. The performance measures are then used in a second stage Tobit regression in which environmental, structural and managerial variables are included. The regression results provide a 'net' performance index and also identify which variables the managers have some control over and what the relative importance of each variable is in affecting performance. The data set contains a panel of 21 U.S. airports over a five-year period.
Ming Zhang - One of the best experts on this subject based on the ideXlab platform.
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high speed rail impacts on travel times accessibility and Economic Productivity a benchmarking analysis in city cluster regions of china
Journal of Transport Geography, 2018Co-Authors: Liwen Liu, Ming ZhangAbstract:Abstract The direct and wider impacts of high-speed rail (HSR) have long been the interest of academia and policy makers. Studies on China's experience just began to accumulate but remain inadequate given the size and speed of the country's HSR and regional growth. This paper reports a benchmark analysis of HSR impacts on travel times, accessibility, Economic Productivity, and regional disparity in the context of China's current growth initiative centered at city-cluster regions. The study utilized data from year 2006 without HSR and 2014 with HSR for 266 prefectural level cities and analyzed HSR's impacts at the spatial scales of nationwide, territorial regions, and city-cluster regions. In the study, travel times measured the city-to-city average travel times by rail, whereas accessibility analysis applied a gravity model of total employment. Three indicators of Economic Productivity were calculated: Gross Regional Product (GRP) per capita, per worker, and per square kilometer of built-up land. Finally, regression models framed around Economics production theory were estimated. The main findings are: HSR contributed to travel times savings, accessibility enhancement, and Productivity gain but with limitations. HSR reduced city-to-city travel times at a national average by 45% or 589 min. City-clusters in Western China, where the starting level of travel times were long, enjoyed a greater rail time reduction than other regions. HSR increased accessibility of all cities and regions; a simplified decomposition analysis estimated HSR's contribution being 25–45% of total accessibility change. Access disparity within most city-cluster regions decreased, whereas the between-region gaps remained during the study period. The study estimated HSR elasticity of GRP per capita being 0.28 nationwide. Responses to HSR varied greatly among city-clusters when measured in GRP per worker and per built-up area terms. As China's HSR network continues to expand, optimizing HSR impacts should focus on integrating fully with other transportation modes and fitting well with national and local development initiatives.
David Gillen - One of the best experts on this subject based on the ideXlab platform.
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developing measures of airport Productivity and performance an application of data envelopment analysis
Transportation Research Part E-logistics and Transportation Review, 1997Co-Authors: David Gillen, Ashish LallAbstract:Many studies have investigated the financial results and Economic Productivity of airlines but few have investigated the Productivity or performance of airports, and how changes in the industry may have affected them. Most airports measure performance strictly in accounting terms by looking at only total costs and revenues and the resulting surpluses or deficits. Few utilize any type of Productivity measure or performance indicator. This paper applies Data Envelopment Analysis to assess the performance of airports. It is used to construct performance indices on the basis of the multiple outputs which airports produce and the multiple inputs which they utilize. In particular we develop Productivity measures for terminals and airside operations. The performance measures are then used in a second stage Tobit regression in which environmental, structural and managerial variables are included. The regression results provide a 'net' performance index and also identify which variables the managers have some control over and what the relative importance of each variable is in affecting performance. The data set contains a panel of 21 U.S. airports over a five-year period.
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developing measures of airport Productivity and performance an application of data envelopment analysis
Transportation Research Part E-logistics and Transportation Review, 1997Co-Authors: David Gillen, Ashish LallAbstract:Many studies have investigated the financial results and Economic Productivity of airlines but few have investigated the Productivity or performance of airports, and how changes in the industry may have affected them. Most airports measure performance strictly in accounting terms by looking at only total costs and revenues and the resulting surpluses or deficits. Few utilize any type of Productivity measure or performance indicator. This paper applies Data Envelopment Analysis to assess the performance of airports. It is used to construct performance indices on the basis of the multiple outputs which airports produce and the multiple inputs which they utilize. In particular we develop Productivity measures for terminals and airside operations. The performance measures are then used in a second stage Tobit regression in which environmental, structural and managerial variables are included. The regression results provide a 'net' performance index and also identify which variables the managers have some control over and what the relative importance of each variable is in affecting performance. The data set contains a panel of 21 U.S. airports over a five-year period.
Johan W. Joubert - One of the best experts on this subject based on the ideXlab platform.
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inferring commercial vehicle activities in gauteng south africa
Journal of Transport Geography, 2011Co-Authors: Johan W. Joubert, Kay W. AxhausenAbstract:To address the underreporting of freight from a transport geography point of view, we present a novel analysis of the time and spatial characteristics of disaggregated commercial vehicle activities. The activities were extracted from raw global positioning system (GPS) data collected in South Africa over a six-month period for more than 30,000 commercial vehicles. The analyses of the activity chains provide useful characteristics such as activity and chain durations, number of activities per chain, and the spatial extent of the activity chains. Key results indicate that about 60% of activity chains have between 5 and 15 activities per chain while 25% of the chains have 4 or less; 89% of the chains have a duration of 24 hours or less; and approximately 75% of all activities start between 08:00 and 17:00. The paper’s contribution is twofold: it firstly demonstrates a methodology to extract and evaluate vehicle activities and activity chains from raw GPS data. Novel results and characteristics about transport geographies in Gauteng, the Economic centre of South Africa, are presented. We also report on the sensitivity of the analyses to certain parameters. Secondly, we introduce new metrics to evaluate a geographical area’s Economic Productivity based on commercial activity.
