Licheng Liu
Datos Biográficos
| ID | 4372285 |
|---|---|
| NOMBRE | Licheng Liu |
| NOMBRES | Licheng |
| APELLIDO | Liu |
| FIRMA | LIU L |
| AFILIACIONES | Massachusetts Institute of Technology |
| ORCID | 0000-0003-4891-9211 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 17 |
| TOTAL DE CITAS | 109 |
| TOTAL COMO AUTOR | 17 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2015 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 4 |
From Plate to Plow
Cropland soil erosion poses a significant environmental challenge globally, affecting efforts to achieve Sustainable Development Goals. While dietary transitions are recognized for their wide‐ranging environmental effects, their specific impact on soil erosion has received limited attention. To explore this relationship, this study combined a revised universal soil loss equation with a high‐sector‐resolution multi‐regional input–output model. Thi…
N 2 Onet
Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identi…
Assessing the impact of farmland fragmentation on green productivity in Yellow River Basin
Improving the quantification of global free-living and symbiotic nitrogen fixation in natural terrestrial ecosystems
Biological nitrogen fixation (BNF) is a critical natural nitrogen input that sustains terrestrial carbon cycling, yet it remains poorly represented in terrestrial ecosystem models (TEMs). Here, we refine the nitrogen cycle representation in a TEM by incorporating free-living and symbiotic nitrogen fixation (SNF) processes along with atmospheric nitrogen deposition effects. Our updated model provides a new assessment of present-day and future glob…
Bayesian Sensitivity Analysis for Unmeasured Confounding in Causal Panel Data Models
Despite the recent methodological advancements in causal panel data analysis, concerns remain about unobserved unit-specific time-varying confounders that cannot be addressed by unit or time fixed effects or their interactions. We develop a Bayesian sensitivity analysis (BSA) method to address the concern. Our proposed method is built upon a general framework combining Rubin’s Bayesian framework for model-based causal inference (Rubin [1978], The…
Grassland or Cropland? Land Use Dilemma and Ecological Solutions in Inner Mongolia
Inner Mongolia plays a critical role in both ecological conservation and food provision in China. However, some researchers have argued that focusing on and improving only one side of the equation necessarily threatens the functionality of the opposite side. To address this problem, we compared a “business‐as‐usual” scenario (BAU) with a “sustainable land use planning” scenario (SLU) constructed by simulating spatiotemporal changes in croplands a…
Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018
These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus
Understanding China's agricultural non‐carbon-dioxide greenhouse gas emissions
A Practical Guide to Counterfactual Estimators for Causal Inference with Time‐Series Cross‐Sectional Data
This paper introduces a simple framework of counterfactual estimation for causal inference with time‐series cross‐sectional data, in which we estimate the average treatment effect on the treated by directly imputing counterfactual outcomes for treated observations. We discuss several novel estimators under this framework, including the fixed effects counterfactual estimator, interactive fixed effects counterfactual estimator and matrix completion…
A Bayesian multifactor spatio-temporal model for estimating time-varying network interdependence
This paper proposes a Bayesian multilevel spatio-temporal model with a time-varying spatial autoregressive coefficient to estimate temporally heterogeneous network interdependence. To tackle the classic reflection problem, we use multiple factors to control for confounding caused by latent homophily and common exposures. We develop a Markov Chain Monte Carlo algorithm to estimate parameters and adopt Bayesian shrinkage to determine the number of …
Effect of increasing the rental housing supply on house prices
Monetary policy and corporate financing
Spatiotemporal characteristics and dynamic mechanism of rural settlements based on typical transects
A Bayesian Alternative to Synthetic Control for Comparative Case Studies
This paper proposes a Bayesian alternative to the synthetic control method for comparative case studies with a single or multiple treated units. We adopt a Bayesian posterior predictive approach to Rubin’s causal model, which allows researchers to make inferences about both individual and average treatment effects on treated observations based on the empirical posterior distributions of their counterfactuals. The prediction model we develop is a …
Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach
The high productivity in the US Corn Belt is largely enabled by the consumption of millions of tons of manufactured fertilizer. Excessive application of nitrogen (N) fertilizer has been pervasive in this region, and the unrecovered N eventually escaped from croplands in forms of nitrous oxide (N 2 O) emission and N leaching. Mitigating these negative impacts is hindered by a lack of practical information on where to focus and how much mitigation …
The Global Methane Budget 2000–2017
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential…
Source attribution of particulate matter pollution over North China with the adjoint method
We quantify the source contributions to surface PM2.5 (fine particulate matter) pollution over North China from January 2013 to 2015 using the GEOS-Chem chemical transport model and its adjoint with improved model horizontal resolution (1/4° × 5/16°) and aqueous-phase chemistry for sulfate production. The adjoint method attributes the PM2.5 pollution to emissions from different source sectors and chemical species at the model resolution. Winterti…
A Practical Guide to Counterfactual Estimators for Causal Inference with Time‐Series Cross‐Sectional Data
This paper introduces a simple framework of counterfactual estimation for causal inference with time‐series cross‐sectional data, in which we estimate the average treatment effect on the treated by directly imputing counterfactual outcomes for treated observations. We discuss several novel estimators under this framework, including the fixed effects counterfactual estimator, interactive fixed effects counterfactual estimator and matrix completion…
Spatiotemporal characteristics and dynamic mechanism of rural settlements based on typical transects
A Bayesian Alternative to Synthetic Control for Comparative Case Studies
This paper proposes a Bayesian alternative to the synthetic control method for comparative case studies with a single or multiple treated units. We adopt a Bayesian posterior predictive approach to Rubin’s causal model, which allows researchers to make inferences about both individual and average treatment effects on treated observations based on the empirical posterior distributions of their counterfactuals. The prediction model we develop is a …
Understanding China's agricultural non‐carbon-dioxide greenhouse gas emissions
Effect of increasing the rental housing supply on house prices
A Bayesian multifactor spatio-temporal model for estimating time-varying network interdependence
This paper proposes a Bayesian multilevel spatio-temporal model with a time-varying spatial autoregressive coefficient to estimate temporally heterogeneous network interdependence. To tackle the classic reflection problem, we use multiple factors to control for confounding caused by latent homophily and common exposures. We develop a Markov Chain Monte Carlo algorithm to estimate parameters and adopt Bayesian shrinkage to determine the number of …
Source attribution of particulate matter pollution over North China with the adjoint method
We quantify the source contributions to surface PM2.5 (fine particulate matter) pollution over North China from January 2013 to 2015 using the GEOS-Chem chemical transport model and its adjoint with improved model horizontal resolution (1/4° × 5/16°) and aqueous-phase chemistry for sulfate production. The adjoint method attributes the PM2.5 pollution to emissions from different source sectors and chemical species at the model resolution. Winterti…
The Global Methane Budget 2000–2017
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential…
Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach
The high productivity in the US Corn Belt is largely enabled by the consumption of millions of tons of manufactured fertilizer. Excessive application of nitrogen (N) fertilizer has been pervasive in this region, and the unrecovered N eventually escaped from croplands in forms of nitrous oxide (N 2 O) emission and N leaching. Mitigating these negative impacts is hindered by a lack of practical information on where to focus and how much mitigation …
Effect of increasing the rental housing supply on house prices
Monetary policy and corporate financing
Spatiotemporal characteristics and dynamic mechanism of rural settlements based on typical transects
A Bayesian Alternative to Synthetic Control for Comparative Case Studies
This paper proposes a Bayesian alternative to the synthetic control method for comparative case studies with a single or multiple treated units. We adopt a Bayesian posterior predictive approach to Rubin’s causal model, which allows researchers to make inferences about both individual and average treatment effects on treated observations based on the empirical posterior distributions of their counterfactuals. The prediction model we develop is a …
A Bayesian multifactor spatio-temporal model for estimating time-varying network interdependence
This paper proposes a Bayesian multilevel spatio-temporal model with a time-varying spatial autoregressive coefficient to estimate temporally heterogeneous network interdependence. To tackle the classic reflection problem, we use multiple factors to control for confounding caused by latent homophily and common exposures. We develop a Markov Chain Monte Carlo algorithm to estimate parameters and adopt Bayesian shrinkage to determine the number of …
Grassland or Cropland? Land Use Dilemma and Ecological Solutions in Inner Mongolia
Inner Mongolia plays a critical role in both ecological conservation and food provision in China. However, some researchers have argued that focusing on and improving only one side of the equation necessarily threatens the functionality of the opposite side. To address this problem, we compared a “business‐as‐usual” scenario (BAU) with a “sustainable land use planning” scenario (SLU) constructed by simulating spatiotemporal changes in croplands a…
Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018
These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus
Understanding China's agricultural non‐carbon-dioxide greenhouse gas emissions
A Practical Guide to Counterfactual Estimators for Causal Inference with Time‐Series Cross‐Sectional Data
This paper introduces a simple framework of counterfactual estimation for causal inference with time‐series cross‐sectional data, in which we estimate the average treatment effect on the treated by directly imputing counterfactual outcomes for treated observations. We discuss several novel estimators under this framework, including the fixed effects counterfactual estimator, interactive fixed effects counterfactual estimator and matrix completion…
Improving the quantification of global free-living and symbiotic nitrogen fixation in natural terrestrial ecosystems
Biological nitrogen fixation (BNF) is a critical natural nitrogen input that sustains terrestrial carbon cycling, yet it remains poorly represented in terrestrial ecosystem models (TEMs). Here, we refine the nitrogen cycle representation in a TEM by incorporating free-living and symbiotic nitrogen fixation (SNF) processes along with atmospheric nitrogen deposition effects. Our updated model provides a new assessment of present-day and future glob…
Bayesian Sensitivity Analysis for Unmeasured Confounding in Causal Panel Data Models
Despite the recent methodological advancements in causal panel data analysis, concerns remain about unobserved unit-specific time-varying confounders that cannot be addressed by unit or time fixed effects or their interactions. We develop a Bayesian sensitivity analysis (BSA) method to address the concern. Our proposed method is built upon a general framework combining Rubin’s Bayesian framework for model-based causal inference (Rubin [1978], The…
From Plate to Plow
Cropland soil erosion poses a significant environmental challenge globally, affecting efforts to achieve Sustainable Development Goals. While dietary transitions are recognized for their wide‐ranging environmental effects, their specific impact on soil erosion has received limited attention. To explore this relationship, this study combined a revised universal soil loss equation with a high‐sector‐resolution multi‐regional input–output model. Thi…
N 2 Onet
Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identi…
Assessing the impact of farmland fragmentation on green productivity in Yellow River Basin
China (7 obras) · Ecology (6 obras) · Environmental Science (6 obras) · Geography (6 obras) · Agriculture (5 obras) · Advanced Causal Inference Techniques (4 obras) · Computer Science (4 obras) · Economics (4 obras) · Greenhouse gas (4 obras) · Mathematics (4 obras)