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G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when youestimate the
G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise). G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when youestimate the
G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise). G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: 2019
This too is pretty obvious if one looks at GDP growth data. For example, India's growth rate has been increasing over time (0.1% per year per year, p-value < 0.000) while the USA's growth rate has been declining (-0.043% per year per year, p-value = 0.018). G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. G-FEED: INTRODUCING SCYM Second is the ability to process the data at scale. Five years ago, for example, I would have to hire a research assistant to download imagery, make sure it was geometrically and radiometrically calibrated (i.e. properly lined up and in meaningful units), and then apply whatever algorithms we had. G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: 2014
Here's the relevant plot (R users will appreciate the near-unadulterated use of the ggplot defaults): Figure 1 from Gerland et al 2014, Science. So perhaps David should retitle his class, "11 is the new 9", or, "Feeding 9 billion in the next 20 years", or, "Feeding 11 billion (95% CI, 9 billion to 13 billion)". G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010). G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise).G-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010). G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise).G-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010).G-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: 2019
This too is pretty obvious if one looks at GDP growth data. For example, India's growth rate has been increasing over time (0.1% per year per year, p-value < 0.000) while the USA's growth rate has been declining (-0.043% per year per year, p-value = 0.018). G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. DO GDP GROWTH RATES HAVE TRENDS? EVIDENCE FROM Over the years, there have a been a handful of critiques of some of our prior research on GDP growth centering on the concern that we model country-specific time trends in growth rates. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whether G-FEED: DAILY OR MONTHLY WEATHER DATA? You can also see that the relationship isn’t exactly linear. So a model with yields vs. any of these monthly or growing season averages likely wouldn’t do as well as EDD if the monthly data entered in as a linear or quadratic response. G-FEED: DO GUNS KILL PEOPLE OR DO PEOPLE KILL PEOPLE? AN An economist's perspective. "Guns don't kill people, people kill people." I mulled over this a bit and got in a debate with my wife since it didn't seem immediately obvious to me what this statement meant and whether it was testable. I think the economist's take on the statement is that guns are a "technology" used to "produce" murder. G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise).G-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010). G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GOOD AND BAD OF FIXED EFFECTS Two things to note. First is that precipitation data seems to have a lot of measurement issues even before taking any fixed effects. Second is that temperature seems ok, at least until state fixed-effects are introduced (a correlation of 0.842 indicates some measurement error, but still more signal than noise).G-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE Here are a couple R functions to help you do this: # This function estimates time (in days) when temperature is # between t0 and t1 using sine curve interpolation. tMin and # tMax are vectors of day minimum and maximum temperatures over # range of interest. The sum of time in the interval is returned. # noGrids is number of grids in area G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: THE COST OF PARIS WITHDRAWAL The cumulative US GDP losses over time from withdrawal, discounted back to 2010 at 3%, are also impressive - I calculate them to be $8.2 trillion dollars (right plot above). That is, withdrawing from the Paris agreement costs the US economy $8.2 trillion dollars in present discounted value. That is a large pile of money. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010).G-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: 2019
This too is pretty obvious if one looks at GDP growth data. For example, India's growth rate has been increasing over time (0.1% per year per year, p-value < 0.000) while the USA's growth rate has been declining (-0.043% per year per year, p-value = 0.018). G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. DO GDP GROWTH RATES HAVE TRENDS? EVIDENCE FROM Over the years, there have a been a handful of critiques of some of our prior research on GDP growth centering on the concern that we model country-specific time trends in growth rates. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whether G-FEED: DAILY OR MONTHLY WEATHER DATA? You can also see that the relationship isn’t exactly linear. So a model with yields vs. any of these monthly or growing season averages likely wouldn’t do as well as EDD if the monthly data entered in as a linear or quadratic response. G-FEED: DO GUNS KILL PEOPLE OR DO PEOPLE KILL PEOPLE? AN An economist's perspective. "Guns don't kill people, people kill people." I mulled over this a bit and got in a debate with my wife since it didn't seem immediately obvious to me what this statement meant and whether it was testable. I think the economist's take on the statement is that guns are a "technology" used to "produce" murder. G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION Hannah Druckenmiller and I wrote a paper on a new method we developed that allows you to do cross-sectional regressions while eliminating a lot (or all) omitted variables bias.We are really excited about it and it seems to be performing well in a bunch of cases.. Since people seem to like watching TV more than reading math, here's a recent talk I gave explaining the method to the All NewG-FEED: ABOUT US
Jen is an assistant professor at the University of California, San Diego, in the School of Global Policy & Strategy (GPS). Her research focuses on climate impacts and adaptation, mechanisms for decarbonization, and the role that air pollutants play in the climateand food systems.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). G-FEED: THE GOOD AND BAD OF FIXED EFFECTS A common way to deal with omitted variable bias is to introduce dummy variables for space or time units. These “fixed effects” greatly reduce (but do not completely eliminate) the chance that a relationship is driven by an omitted variable. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GDP-TEMPERATURE RELATIONSHIP So, again, the paper's abstract is not consistent with its own stated results.They do find that the model with quadratic time trends (as used by BHM) is outperformed by models without country time trends -- but again, the purpose of those time trends is to remove potential confounding variation, not to perfectly predict GDP.G-FEED: BAD CONTROL
A standard conclusion would be that the effect of temperature is "not robust", but in this case that conclusion is likely wrong. The reason why is that temperature also affects economic productivity (see here and here), and so GDP is really an outcome variable.This means it doesn't make sense to "hold economic productivity constant" when exploring the relationship between temperature G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE w # weather data that includes a "fips" county ID, "gridNumber", "tMin" and "tMax". # rows of w span all days, fips, years and grids being aggregated tempDat # pulls the particular fips/year of w being aggregated. Trows # = expand.grid( fips.index, year.index ), rows span the aggregated data set T # a vector of integer temperatures. I'm approximating the distribution with # the time in each G-FEED: THE COST OF PARIS WITHDRAWAL Lots of discussion today about the potential ramifications of the US withdrawing from the Paris Accords. Folks have already done some nice calculations looking at the climate consequences of US withdrawal, but there's a lot of interest in the potential economic consequences and I hadn't seen anyone take a heroic stab at that yet. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN What we do know is this: black carbon is the second or third largest contributor to present warming (after CO 2 and perhaps methane, depending on how you partition its impact – it is part LLGHG and part SLCP, since it’s also an ozone precursor). And the four main warming SLCPs combined (BC, tropospheric ozone, methane, and HFCs) have contributed around half of present warming (again, it G-FEEDABOUT USCLIMATEAGRICULTUREECONOMICSCONFLICTADAPTATION Hannah Druckenmiller and I wrote a paper on a new method we developed that allows you to do cross-sectional regressions while eliminating a lot (or all) omitted variables bias.We are really excited about it and it seems to be performing well in a bunch of cases.. Since people seem to like watching TV more than reading math, here's a recent talk I gave explaining the method to the All NewG-FEED: ABOUT US
Jen is an assistant professor at the University of California, San Diego, in the School of Global Policy & Strategy (GPS). Her research focuses on climate impacts and adaptation, mechanisms for decarbonization, and the role that air pollutants play in the climateand food systems.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). G-FEED: THE GOOD AND BAD OF FIXED EFFECTS A common way to deal with omitted variable bias is to introduce dummy variables for space or time units. These “fixed effects” greatly reduce (but do not completely eliminate) the chance that a relationship is driven by an omitted variable. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: THE GDP-TEMPERATURE RELATIONSHIP So, again, the paper's abstract is not consistent with its own stated results.They do find that the model with quadratic time trends (as used by BHM) is outperformed by models without country time trends -- but again, the purpose of those time trends is to remove potential confounding variation, not to perfectly predict GDP.G-FEED: BAD CONTROL
A standard conclusion would be that the effect of temperature is "not robust", but in this case that conclusion is likely wrong. The reason why is that temperature also affects economic productivity (see here and here), and so GDP is really an outcome variable.This means it doesn't make sense to "hold economic productivity constant" when exploring the relationship between temperature G-FEED: SEARCHING FOR CRITICAL THRESHOLDS IN TEMPERATURE w # weather data that includes a "fips" county ID, "gridNumber", "tMin" and "tMax". # rows of w span all days, fips, years and grids being aggregated tempDat # pulls the particular fips/year of w being aggregated. Trows # = expand.grid( fips.index, year.index ), rows span the aggregated data set T # a vector of integer temperatures. I'm approximating the distribution with # the time in each G-FEED: THE COST OF PARIS WITHDRAWAL Lots of discussion today about the potential ramifications of the US withdrawing from the Paris Accords. Folks have already done some nice calculations looking at the climate consequences of US withdrawal, but there's a lot of interest in the potential economic consequences and I hadn't seen anyone take a heroic stab at that yet. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN What we do know is this: black carbon is the second or third largest contributor to present warming (after CO 2 and perhaps methane, depending on how you partition its impact – it is part LLGHG and part SLCP, since it’s also an ozone precursor). And the four main warming SLCPs combined (BC, tropospheric ozone, methane, and HFCs) have contributed around half of present warming (again, itG-FEED: 2020
Hannah Druckenmiller and I wrote a paper on a new method we developed that allows you to do cross-sectional regressions while eliminating a lot (or all) omitted variables bias.We are really excited about it and it seems to be performing well in a bunch of cases.. Since people seem to like watching TV more than reading math, here's a recent talk I gave explaining the method to the All New G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainly G-FEED: INTRODUCING SCYM Second is the ability to process the data at scale. Five years ago, for example, I would have to hire a research assistant to download imagery, make sure it was geometrically and radiometrically calibrated (i.e. properly lined up and in meaningful units), and then apply whatever algorithms we had. G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. DO GDP GROWTH RATES HAVE TRENDS? EVIDENCE FROM Over the years, there have a been a handful of critiques of some of our prior research on GDP growth centering on the concern that we model country-specific time trends in growth rates. G-FEED: BUILDING A BETTER DAMAGE FUNCTION Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using real-world data (if you're feeling skeptical, here's are two videos where Michael G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whether G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: DAILY OR MONTHLY WEATHER DATA? You can also see that the relationship isn’t exactly linear. So a model with yields vs. any of these monthly or growing season averages likely wouldn’t do as well as EDD if the monthly data entered in as a linear or quadratic response. G-FEED: DO GUNS KILL PEOPLE OR DO PEOPLE KILL PEOPLE? AN This is not the result we'd expect to see if "people kill people."The murder rate with non-gun technologies is almost totally unrelated to the presence of guns, and if anything it increases with gun ownership rather than decreases as we would expect if demand for murder were totally inelastic and people just swapped knives for guns seamlessly. This would suggest that "guns and knives are notG-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: COVID-19 REDUCES ECONOMIC ACTIVITY, WHICH REDUCES COVID-19 reduces economic activity, which reduces pollution, which saves lives. COVID-19 is a massive global economic and health challenge, having caused >3500 global deaths as of this writing (Mar 8) and untold economic and social disruption. This disruption is only likely to increase in coming days in regions where the epidemic isjust beginning.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whetherG-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: COVID-19 REDUCES ECONOMIC ACTIVITY, WHICH REDUCES COVID-19 reduces economic activity, which reduces pollution, which saves lives. COVID-19 is a massive global economic and health challenge, having caused >3500 global deaths as of this writing (Mar 8) and untold economic and social disruption. This disruption is only likely to increase in coming days in regions where the epidemic isjust beginning.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whetherG-FEED
In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: FOOD FIGHTS
Eoin McGuirk and I have a new NBER working paper out that (we argue) sheds important new light on the economic origins of conflict in Africa. This is a topic that has received a lot of scrutiny over the years, but one which has remained tricky to sort out empirically, as conflict could be both a cause and a consequence of deteriorating economic conditions. G-FEED: THE SHCIT LIST The SHCIT List. Just like George Lucas, I write my literature reviews out of order. But I'm happy to say that after several years of messing around in this field, in collaboration with great coauthors, I've finally finished the tetralogy that I've always wanted to complete. The latest installment (Episode I) just came out in the JEP (it's G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: DAILY OR MONTHLY WEATHER DATA? You can also see that the relationship isn’t exactly linear. So a model with yields vs. any of these monthly or growing season averages likely wouldn’t do as well as EDD if the monthly data entered in as a linear or quadratic response. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010). G-FEED: DO GUNS KILL PEOPLE OR DO PEOPLE KILL PEOPLE? AN An economist's perspective. "Guns don't kill people, people kill people." I mulled over this a bit and got in a debate with my wife since it didn't seem immediately obvious to me what this statement meant and whether it was testable. I think the economist's take on the statement is that guns are a "technology" used to "produce" murder.G-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: COVID-19 REDUCES ECONOMIC ACTIVITY, WHICH REDUCES COVID-19 reduces economic activity, which reduces pollution, which saves lives. COVID-19 is a massive global economic and health challenge, having caused >3500 global deaths as of this writing (Mar 8) and untold economic and social disruption. This disruption is only likely to increase in coming days in regions where the epidemic isjust beginning.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whetherG-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: ABOUT US
He is an applied econometrician working on the economic impacts of climate change on the agriculture and energy sectors of the economy. He is also keenly interested in how emissions forecasts are constructed and evaluated. He holds a B.S. and M.S. from UMass Amherst and a Ph.D. in Economics from UC San Diego (2003). Marshall is anassistant
G-FEED: COVID-19 REDUCES ECONOMIC ACTIVITY, WHICH REDUCES COVID-19 reduces economic activity, which reduces pollution, which saves lives. COVID-19 is a massive global economic and health challenge, having caused >3500 global deaths as of this writing (Mar 8) and untold economic and social disruption. This disruption is only likely to increase in coming days in regions where the epidemic isjust beginning.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: INDIRECT MORTALITY FROM RECENT WILDFIRES IN CA Indirect mortality from recent wildfires in CA. Wildfire activity in the US West coast has been unprecedented in the last month, with fires burning larger and faster than ever experienced. Multiple communities in the paths of these fires have been entirely destroyed, and wildfire smoke has blanketed huge swaths of the West Coast for weeks. G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: BAD CONTROL
But there is a particular case where throwing in a bunch of "control" variables might actually be a really bad idea: when these variables are themselves outcomes of the X variable of interest. That is, if X affects Y, and X also affects Z, then "controlling" for Z when you estimate the effect of X on Y is probably a mistake. G-FEED: NEW DAMAGE FUNCTIONS FOR THE AGRICULTURAL SECTOR Last week I had a new paper come out with some fantastic co-authors (Delavane Diaz, Tom Hertel, and Uris Baldos) on new damage functions in the agricultural sector. Since this covers a number of topics of interest to G-FEED readers (climate damages, agricultural impacts, SCC etc), I thought I’d dig a bit into what I see as some of the maincontributions.
G-FEED: MEASURING TEMPERATURE FROM SPACE David, Marshall and I have a new paper that evaluates whether using temperature measures derived only from satellites can be used to estimate climate response functions. Several satellites measure surface emission of thermal energy, which can be converted into estimates of skin surface temperature (Ts) – a product that MODIS has provided at 1km resolution daily for nearly a decade. G-FEED: EVERYTHING WE KNOW ABOUT THE EFFECT OF CLIMATE ON Almost exactly ten years, Nick Stern released the his famous global analysis on the economics of climate change. At the time, I was in my first year of grad school trying to figure out what to do research on and remember fiercely debating all aspects of the study with Ram and Jesse in the way only fresh grad students can. Almost all the public discussion of the analysis revolved around whetherG-FEED
In version 1 you partial Z out of both X and Y, and generate residualized values Y_1 and X_1. In version 2 you partial W out of both X and Y, and generate residualized values Y_2 and X_2. This is in effect what NPS do, and then they want us to compare Y_1 = f (X_1) versus Y_2 = f (X_2).G-FEED: 2020
For most locations in CA, PM2.5 was 10-50ug/m3 higher than normal on many days, which is a massive increase above average (which in the Bay Area is typically ~ 10ug). For simplicity, we are going to attribute all the excess PM2.5 in Aug/Sept 2020 (relative to 2015-19 average) towildfires.
G-FEED: MARCH 2020
Putting these numbers together yields some very large reductions in premature mortality. Using the He et al 2016 estimates of the impact of changes in PM on mortality, I calculate that having 2 months of 10ug/m3 reductions in PM2.5 likely has saved the lives of 4,000 kids under 5 and 73,000 adults over 70 inChina.
G-FEED: PUBLIC DATABASE OF NON-PHARMACEUTICAL The hardest part of the study was actually putting together an original standardized dataset of all 1,717 NPIs. We have posted all the data here (alongside the code). We are hoping that people will use this new data set for other projects and welcome feedback and/or comments, especially if you think we missed something (much of this was collected by hand, so it is a dataset that will certainlyG-FEED: FOOD FIGHTS
Eoin McGuirk and I have a new NBER working paper out that (we argue) sheds important new light on the economic origins of conflict in Africa. This is a topic that has received a lot of scrutiny over the years, but one which has remained tricky to sort out empirically, as conflict could be both a cause and a consequence of deteriorating economic conditions. G-FEED: THE SHCIT LIST The SHCIT List. Just like George Lucas, I write my literature reviews out of order. But I'm happy to say that after several years of messing around in this field, in collaboration with great coauthors, I've finally finished the tetralogy that I've always wanted to complete. The latest installment (Episode I) just came out in the JEP (it's G-FEED: BUILDING A BETTER DAMAGE FUNCTION Building a better damage function. Bob Kopp, Amir Jina, James Rising, and our partners at the Climate Impact Lab, Princeton, and RMS, have a new paper out today. Our goal was to construct a climate damage function for the USA that is "micro-founded," in the sense that it is built up from causal relationships that are empirically measured using G-FEED: DAILY OR MONTHLY WEATHER DATA? You can also see that the relationship isn’t exactly linear. So a model with yields vs. any of these monthly or growing season averages likely wouldn’t do as well as EDD if the monthly data entered in as a linear or quadratic response. G-FEED: INDIAN CROPS AND AIR POLLUTION (GUEST POST BY JEN Indian crops and air pollution (Guest Post by Jen Burney) Greetings, loyal G-FEED Readers, My colleague (and former postdoctoral mentor!), V. "Ram" Ramanathan and I have a paper out this week in PNAS (here) on the impacts of short-lived climate pollutants (SLCPs) on Indian crop yields over the past 30 years (1980-2010). G-FEED: DO GUNS KILL PEOPLE OR DO PEOPLE KILL PEOPLE? AN An economist's perspective. "Guns don't kill people, people kill people." I mulled over this a bit and got in a debate with my wife since it didn't seem immediately obvious to me what this statement meant and whether it was testable. I think the economist's take on the statement is that guns are a "technology" used to "produce" murder.Details
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