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Isabelle Mejean - One of the best experts on this subject based on the ideXlab platform.
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Trade Elasticities
Review of International Economics, 2017Co-Authors: Jean Imbs, Isabelle MejeanAbstract:Conventional aggregate trade elasticity estimates hardly vary across countries. We introduce an aggregate elasticity that is implied by theory: It is the value that equates the welfare gains from trade as implied by one- and multi-sector versions of the model in Arkolakis et al. (American Economic Review, 102 (2012):94–130). These estimates are predicated on sector-level values for trade elasticites, which we provide at three-digit levels for 28 developed and developing countries. The values for this aggregate elasticity vary greatly across countries, and they do so because of countries' patterns of production and because a given sector-level elasticity displays considerable cross-country heterogeneity.
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Elasticity Optimism
American Economic Journal: Macroeconomics, 2015Co-Authors: Jean Imbs, Isabelle MejeanAbstract:On average, estimates of trade Elasticities are smaller in aggregate data than at sector level. This is an artifact of aggregation. Estimations performed on aggregate data constrain sector Elasticities to homogeneity, which creates a heterogeneity bias. The paper shows such a bias exists in two prominent approaches used to estimate Elasticities, which has meaningful consequences for the calibration of the trade elasticity in one-sector, aggregative models. With Elasticities calibrated to aggregate data, macroeconomic models can have predictions at odds with the implications of their multi-sector counterparts. They do not when Elasticities are calibrated using a weighted average of sector Elasticities. (JEL C51, F13, F14, F41, O19)
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Elasticity Optimism
American Economic Journal: Macroeconomics, 2015Co-Authors: Jean Imbs, Isabelle MejeanAbstract:On average, estimates of trade Elasticities are smaller in aggregate data than at sector level. This is an artifact of aggregation. Estimations performed on aggregate data constrain sector Elasticities to homogeneity, which creates a heterogeneity bias. The paper shows such a bias exists in two prominent approaches used to estimate Elasticities, which has meaningful consequences for the calibration of the trade elasticity in one-sector, aggregative models. With Elasticities calibrated to aggregate data, macroeconomic models can have predictions at odds with the implications of their multi-sector counterparts. They do not when Elasticities are calibrated using a weighted average of sector Elasticities.
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trade Elasticities a final report for the european commission
European Economy - Economic Papers 2008 - 2015, 2010Co-Authors: Jean Imbs, Isabelle MejeanAbstract:In a demand system with conventional CES preferences, the price elasticitites of aggregate trade flows are weighted averages of sector-specific Elasticities of substitution. We describe a methodology that can be used to estimate country-specific values for the price Elasticities of aggregate imports and exports. We first use disaggregated trade data to compute structural estimates of international substitutability for a large cross section of countries. We aggregate up the estimates using model-implied, country-specific weights. We obtain structural estimates of the price Elasticities of aggregate exports and imports for more than 30 countries, including most developed and developing economies.
Roger Fouquet - One of the best experts on this subject based on the ideXlab platform.
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trends in income and price Elasticities of transport demand 1850 2010
Energy Policy, 2012Co-Authors: Roger FouquetAbstract:The purpose of this paper is to estimate trends in income and price Elasticities and to offer insights for the future growth in transport use, with particular emphasis on the impact of energy and technological transitions. The results indicate that income and price Elasticities of passenger transport demand in the United Kingdom were very large (3.1 and -1.5, respectively) in the mid-nineteenth century, and declined since then. In 2010, long run income and price elasticity of aggregate land transport demand were estimated to be 0.8 and -0.6. These trends suggest that future Elasticities related to transport demand in developed economies may decline very gradually and, in developing economies, where Elasticities are often larger, they will probably decline more rapidly as the economies develop. Because of the declining trends in Elasticities, future energy and technological transitions are not likely to generate the growth rates in energy consumption that occurred following transitions in the nineteenth century. Nevertheless, energy and technological transitions, such as the car and the airplane, appear to have delayed and probably will delay declining trends in income and price elasticity of aggregate land transport demand.
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Trends in income and price Elasticities of transport demand (1850–2010)
Energy Policy, 2012Co-Authors: Roger FouquetAbstract:The purpose of this paper is to estimate trends in income and price Elasticities and to offer insights for the future growth in transport use, with particular emphasis on the impact of energy and technological transitions. The results indicate that income and price Elasticities of passenger transport demand in the United Kingdom were very large (3.1 and -1.5, respectively) in the mid-nineteenth century, and declined since then. In 2010, long run income and price elasticity of aggregate land transport demand were estimated to be 0.8 and -0.6. These trends suggest that future Elasticities related to transport demand in developed economies may decline very gradually and, in developing economies, where Elasticities are often larger, they will probably decline more rapidly as the economies develop. Because of the declining trends in Elasticities, future energy and technological transitions are not likely to generate the growth rates in energy consumption that occurred following transitions in the nineteenth century. Nevertheless, energy and technological transitions, such as the car and the airplane, appear to have delayed and probably will delay declining trends in income and price elasticity of aggregate land transport demand.
Raymond Chan - One of the best experts on this subject based on the ideXlab platform.
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Stretching resources: sensitivity of optimal bus frequency allocation to stop-level demand Elasticities
Public Transport, 2014Co-Authors: Ömer Verbas, Charlotte Frei, Hani S. Mahmassani, Raymond ChanAbstract:Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where Elasticities are used in frequency allocation, a single across the board value or two respective values for peak and off-peak are used for the entire set of routes and stops throughout the day. With growing availability of ridership data, estimation of spatially and temporally disaggregated Elasticities is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of Elasticities cor- responding to varying levels of disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a transit network frequency setting framework: (1) temporal Elasticities based on time of day, (2) spatial Elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal Elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to Elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer. It is also important to capture longer-term effects—over a year or more—because seasonal activity patterns may bias elasticity estimates over shorter time horizons.
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stretching resources sensitivity of optimal bus frequency allocation to stop level demand Elasticities
Transportation Research Board 92nd Annual MeetingTransportation Research Board, 2013Co-Authors: Ömer Verbas, Charlotte Frei, Hani S. Mahmassani, Raymond ChanAbstract:Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where Elasticities are used in frequency allocation, a single across the board value is typically used for all routes and all times of the day. The most advanced applications might use two values, for peak and off-peak respectively. With growing availability of ridership data from many sources, estimation of spatially and temporally disaggregated Elasticities of demand with respect to service frequency is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of Elasticities corresponding to varying levels of spatial and temporal disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a Transit Network Frequency Setting framework: (1) temporal Elasticities based on time of day, (2) spatial Elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal Elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to Elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer to other modes. It is also important to capture longer term effects—over a year or more—in these models because seasonal activity patterns (e.g. school trips, vacation) may bias elasticity estimates over shorter time horizons. The experiments demonstrate that spatial detail in ridership elasticity estimation results in meaningful improvements in an objective function minimizing wait time and maximizing ridership, even when time periods are aggregated. Since much of this data is available at census tract level and collected by regional planning authorities, transit agencies could implement this frequency allocation formulation using rather coarse data.
Jean Imbs - One of the best experts on this subject based on the ideXlab platform.
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Trade Elasticities
Review of International Economics, 2017Co-Authors: Jean Imbs, Isabelle MejeanAbstract:Conventional aggregate trade elasticity estimates hardly vary across countries. We introduce an aggregate elasticity that is implied by theory: It is the value that equates the welfare gains from trade as implied by one- and multi-sector versions of the model in Arkolakis et al. (American Economic Review, 102 (2012):94–130). These estimates are predicated on sector-level values for trade elasticites, which we provide at three-digit levels for 28 developed and developing countries. The values for this aggregate elasticity vary greatly across countries, and they do so because of countries' patterns of production and because a given sector-level elasticity displays considerable cross-country heterogeneity.
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Elasticity Optimism
American Economic Journal: Macroeconomics, 2015Co-Authors: Jean Imbs, Isabelle MejeanAbstract:On average, estimates of trade Elasticities are smaller in aggregate data than at sector level. This is an artifact of aggregation. Estimations performed on aggregate data constrain sector Elasticities to homogeneity, which creates a heterogeneity bias. The paper shows such a bias exists in two prominent approaches used to estimate Elasticities, which has meaningful consequences for the calibration of the trade elasticity in one-sector, aggregative models. With Elasticities calibrated to aggregate data, macroeconomic models can have predictions at odds with the implications of their multi-sector counterparts. They do not when Elasticities are calibrated using a weighted average of sector Elasticities. (JEL C51, F13, F14, F41, O19)
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Elasticity Optimism
American Economic Journal: Macroeconomics, 2015Co-Authors: Jean Imbs, Isabelle MejeanAbstract:On average, estimates of trade Elasticities are smaller in aggregate data than at sector level. This is an artifact of aggregation. Estimations performed on aggregate data constrain sector Elasticities to homogeneity, which creates a heterogeneity bias. The paper shows such a bias exists in two prominent approaches used to estimate Elasticities, which has meaningful consequences for the calibration of the trade elasticity in one-sector, aggregative models. With Elasticities calibrated to aggregate data, macroeconomic models can have predictions at odds with the implications of their multi-sector counterparts. They do not when Elasticities are calibrated using a weighted average of sector Elasticities.
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trade Elasticities a final report for the european commission
European Economy - Economic Papers 2008 - 2015, 2010Co-Authors: Jean Imbs, Isabelle MejeanAbstract:In a demand system with conventional CES preferences, the price elasticitites of aggregate trade flows are weighted averages of sector-specific Elasticities of substitution. We describe a methodology that can be used to estimate country-specific values for the price Elasticities of aggregate imports and exports. We first use disaggregated trade data to compute structural estimates of international substitutability for a large cross section of countries. We aggregate up the estimates using model-implied, country-specific weights. We obtain structural estimates of the price Elasticities of aggregate exports and imports for more than 30 countries, including most developed and developing economies.
Matthew John Higgins - One of the best experts on this subject based on the ideXlab platform.
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estimating flight level price Elasticities using online airline data a first step toward integrating pricing demand and revenue optimization
Transportation Research Part A-policy and Practice, 2014Co-Authors: Stacey Mumbower, Laurie A Garrow, Matthew John HigginsAbstract:We estimate flight-level price Elasticities using a database of online prices and seat map displays. In contrast to market-level and route-level Elasticities reported in the literature, flight-level Elasticities can forecast responses in demand due to day-to-day price fluctuations. Knowing how Elasticities vary by flight and booking characteristics and in response to competitors’ pricing actions allows airlines to design better promotions. It also allows policy makers the ability to evaluate the impacts of proposed tax increases or time-of-day congestion pricing policies. Our elasticity results show how airlines can design optimal promotions by considering not only which departure dates should be targeted, but also which days of the week customers should be allowed to purchase. Additionally, we show how Elasticities can be used by carriers to strategically match a subset of their competitors’ sale fares. Methodologically, we use an approach that corrects for price endogeneity; failure to do so results in biased estimates and incorrect pricing recommendations. Using an instrumental variable approach to address this problem we find a set of valid instruments that can be used in future studies of air travel demand. We conclude by describing how our approach contributes to the literature, by offering an approach to estimate flight-level demand Elasticities that the research community needs as an input to more advanced optimization models that integrate demand forecasting, price optimization, and revenue optimization models.
