Xiaojun Song
Biographic Data
| ID | 6274410 |
|---|---|
| NAME | Xiaojun Song |
| GIVEN NAMES | Xiaojun |
| FAMILY NAME | Song |
| SIGNATURE | SONG X |
| AFFILIATIONS | Peking University |
| ORCID | 0000-0002-7971-9696 |
| VERIFIED | Yes |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 5 |
| WORKS AS AUTHOR | 17 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
A Smooth Specification Test for the Propensity Score
This paper proposes a simple smooth specification test for the propensity score in the spirit of Neyman (1937). We derive a particular restriction on the propensity score and construct the specification test based on it. Using the density‐weighting method, we transform the original specification testing problem into a test of the joint significance of the generalized Fourier coefficients. We propose a novel projection method to eliminate the para…
Self-normalized tests for skewness, kurtosis, and normality for time series data
Testing for skewness, kurtosis, and normality for time series data is highly relevant for modeling and testing purposes in econometrics and statistics. It also affects our understanding of many economic and financial phenomena and the validity of the models developed to explain them. In this paper, we propose self-normalized tests for skewness, kurtosis, and normality that can eliminate the effect of the long-run variance (LRV). In particular, ou…
Multi‐Scenario Simulation of Land Use Changes and Their Ecological Risk in the Global Largest Inland Arid Urban Agglomeration
Rapid global urbanization had significantly altered land use (LU), threatening the ecology and sustainability of arid regions. Systematic and forward‐looking analyses of land use changes (LUCs) and ecological risks in Asia's arid zones, particularly the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM), remained limited. Herein, the LUCs in UANSTM under four scenarios, including the ecology‐economy balanced development …
Trending Time-Varying Coefficient Spatial Panel Data Models
This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ various GMM estimations for regression coefficients with both linear and quadratic moments. Time trend estimator based on these GMM estimations is also proposed. Monte Carlo experiments show that the finite sample performance of t…
Value‐at‐Risk under Measurement Error
We propose a method for estimating Value‐at‐Risk that corrects for the effect of measurement errors in stock prices. We show that the presence of measurement errors might pose serious problems for estimating risk measures. In particular, when stock prices are contaminated, existing estimators of Value‐at‐Risk are inconsistent and might lead to an underestimation of risk, which can result in extreme leverage ratios within the held portfolios. Usin…
Model Checking in Partially Linear Spatial Autoregressive Models
This article proposes two new classes of nonparametric tests for the correct specification of linear spatial autoregressive models based on the “integrated conditional moment” approach. Our test statistics are constructed as continuous functionals of a residual marked empirical process as well as its projected version. We derive asymptotic properties of the test statistics under the null hypothesis, the alternative hypothesis, and a sequence of l…
Land consolidation of dryland-to-paddy conversion in China
Testing for Trend Specifications in Panel Data Models
This article proposes a consistent nonparametric test for common trend specifications in panel data models with fixed effects. The test is general enough to allow for heteroscedasticity, cross-sectional and serial dependence in the error components, has an asymptotically normal distribution under the null hypothesis of correct trend specification, and is consistent against various alternatives that deviate from the null. In addition, the test has…
Covariate distribution balance via propensity scores
This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups. Heuristically, our proposed procedure attempts to estimate a propensity score model by making the underlying covariate distribution of different treatment groups as close to each other as possible. Our estimators are data‐driven and can be used to estimate different treatment effect parameters under…
Altered microbial resource limitation regulates soil organic carbon sequestration based on ecoenzyme stoichiometry under long‐term tillage systems
Soil microbial metabolism is critically important for regulating soil carbon (C) sequestration. However, how soil organic C (SOC) stock responds to the changes in microbial resource limitation and microbial C use efficiency (CUE) under long‐term tillage system remains uncertain. Soil samples were randomly collected from a long‐term (19 years) tillage experiment growing winter wheat with three treatments [i.e., moldboard‐plough without straw reten…
Nitrogen addition mediates the effect of soil microbial diversity on microbial carbon use efficiency under long‐term tillage practices
Tillage practices can influence soil microbial carbon use efficiency (CUE), which is critical for carbon cycling in terrestrial ecosystems. The effect of tillage practices could also be regulated by nitrogen (N) addition. However, the soil microbial mechanism relating to N fertilizer effect on microbial CUE under no‐tillage (zero‐tillage) is still unclear. We investigated how N fertilizer regulates the effect of tillage management on microbial CU…
Testing for Asymmetric Comovements
This paper aims to provide non‐parametric tests for asymmetric comovements between random variables. We consider the popular Cramér‐von Mises and Kolmogorov–Smirnov test statistics based on the distance between positive and negative joint conditional exceedance distribution functions. These tests can capture both linear and nonlinear dependence in the data and do not require selecting kernel functions and bandwidths. We derive the asymptotic dist…
Pharmaceuticals and Personal Care Products across Different Water Bodies in Taihu Lake Basin, China
Although pharmaceuticals and personal care products (PPCPs) have attracted great attentions, their occurrence characteristics across different water bodies at a basin scale remain poorly understood. To grasp a more comprehensive understanding of PPCP pollution from the perspective of the whole basin, the occurrence, spatial and seasonal variation, source, and flux of thirteen PPCPs across the different environmental compartments of the northern T…
Factors governing soil water repellency under tillage management
Soil water repellency (SWR) has significant effects on soil degradation by changing some soil processes (e.g., carbon sequestration and soil erosion). Understanding the influence factors of SWR under conservation agriculture are playing a vital role in the sustainable development for improving soil quality. However, how soil pore structure influence on SWR remains unclear. We aim to assess the impact of hydrophobic substances and pore structure o…
Chemical profile of Cimicifuga heracleifolia Kom. And immunomodulatory effect of its representative bioavailable component, cimigenoside on Poly(I
Measuring Granger Causality in Quantiles
We consider measures of Granger causality in quantiles, which detect and quantify both linear and nonlinear causal effects between random variables. The measures are based on nonparametric quantile regressions and defined as logarithmic functions of restricted and unrestricted expectations of quantile check loss functions. They can consistently be estimated by replacing the unknown expectations of check loss functions by their nonparametric kerne…
Measuring Nonlinear Granger Causality in Mean
We propose model-free measures for Granger causality in mean between random variables. Unlike the existing measures, ours are able to detect and quantify nonlinear causal effects. The new measures are based on nonparametric regressions and defined as logarithmic functions of restricted and unrestricted mean square forecast errors. They are easily and consistently estimated by replacing the unknown mean square forecast errors by their nonparametri…
Measuring Nonlinear Granger Causality in Mean
We propose model-free measures for Granger causality in mean between random variables. Unlike the existing measures, ours are able to detect and quantify nonlinear causal effects. The new measures are based on nonparametric regressions and defined as logarithmic functions of restricted and unrestricted mean square forecast errors. They are easily and consistently estimated by replacing the unknown mean square forecast errors by their nonparametri…
Factors governing soil water repellency under tillage management
Soil water repellency (SWR) has significant effects on soil degradation by changing some soil processes (e.g., carbon sequestration and soil erosion). Understanding the influence factors of SWR under conservation agriculture are playing a vital role in the sustainable development for improving soil quality. However, how soil pore structure influence on SWR remains unclear. We aim to assess the impact of hydrophobic substances and pore structure o…
Chemical profile of Cimicifuga heracleifolia Kom. And immunomodulatory effect of its representative bioavailable component, cimigenoside on Poly(I
Measuring Granger Causality in Quantiles
We consider measures of Granger causality in quantiles, which detect and quantify both linear and nonlinear causal effects between random variables. The measures are based on nonparametric quantile regressions and defined as logarithmic functions of restricted and unrestricted expectations of quantile check loss functions. They can consistently be estimated by replacing the unknown expectations of check loss functions by their nonparametric kerne…
Covariate distribution balance via propensity scores
This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups. Heuristically, our proposed procedure attempts to estimate a propensity score model by making the underlying covariate distribution of different treatment groups as close to each other as possible. Our estimators are data‐driven and can be used to estimate different treatment effect parameters under…
Altered microbial resource limitation regulates soil organic carbon sequestration based on ecoenzyme stoichiometry under long‐term tillage systems
Soil microbial metabolism is critically important for regulating soil carbon (C) sequestration. However, how soil organic C (SOC) stock responds to the changes in microbial resource limitation and microbial C use efficiency (CUE) under long‐term tillage system remains uncertain. Soil samples were randomly collected from a long‐term (19 years) tillage experiment growing winter wheat with three treatments [i.e., moldboard‐plough without straw reten…
Nitrogen addition mediates the effect of soil microbial diversity on microbial carbon use efficiency under long‐term tillage practices
Tillage practices can influence soil microbial carbon use efficiency (CUE), which is critical for carbon cycling in terrestrial ecosystems. The effect of tillage practices could also be regulated by nitrogen (N) addition. However, the soil microbial mechanism relating to N fertilizer effect on microbial CUE under no‐tillage (zero‐tillage) is still unclear. We investigated how N fertilizer regulates the effect of tillage management on microbial CU…
Testing for Asymmetric Comovements
This paper aims to provide non‐parametric tests for asymmetric comovements between random variables. We consider the popular Cramér‐von Mises and Kolmogorov–Smirnov test statistics based on the distance between positive and negative joint conditional exceedance distribution functions. These tests can capture both linear and nonlinear dependence in the data and do not require selecting kernel functions and bandwidths. We derive the asymptotic dist…
Pharmaceuticals and Personal Care Products across Different Water Bodies in Taihu Lake Basin, China
Although pharmaceuticals and personal care products (PPCPs) have attracted great attentions, their occurrence characteristics across different water bodies at a basin scale remain poorly understood. To grasp a more comprehensive understanding of PPCP pollution from the perspective of the whole basin, the occurrence, spatial and seasonal variation, source, and flux of thirteen PPCPs across the different environmental compartments of the northern T…
Testing for Trend Specifications in Panel Data Models
This article proposes a consistent nonparametric test for common trend specifications in panel data models with fixed effects. The test is general enough to allow for heteroscedasticity, cross-sectional and serial dependence in the error components, has an asymptotically normal distribution under the null hypothesis of correct trend specification, and is consistent against various alternatives that deviate from the null. In addition, the test has…
Value‐at‐Risk under Measurement Error
We propose a method for estimating Value‐at‐Risk that corrects for the effect of measurement errors in stock prices. We show that the presence of measurement errors might pose serious problems for estimating risk measures. In particular, when stock prices are contaminated, existing estimators of Value‐at‐Risk are inconsistent and might lead to an underestimation of risk, which can result in extreme leverage ratios within the held portfolios. Usin…
Model Checking in Partially Linear Spatial Autoregressive Models
This article proposes two new classes of nonparametric tests for the correct specification of linear spatial autoregressive models based on the “integrated conditional moment” approach. Our test statistics are constructed as continuous functionals of a residual marked empirical process as well as its projected version. We derive asymptotic properties of the test statistics under the null hypothesis, the alternative hypothesis, and a sequence of l…
Land consolidation of dryland-to-paddy conversion in China
Multi‐Scenario Simulation of Land Use Changes and Their Ecological Risk in the Global Largest Inland Arid Urban Agglomeration
Rapid global urbanization had significantly altered land use (LU), threatening the ecology and sustainability of arid regions. Systematic and forward‐looking analyses of land use changes (LUCs) and ecological risks in Asia's arid zones, particularly the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM), remained limited. Herein, the LUCs in UANSTM under four scenarios, including the ecology‐economy balanced development …
Trending Time-Varying Coefficient Spatial Panel Data Models
This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ various GMM estimations for regression coefficients with both linear and quadratic moments. Time trend estimator based on these GMM estimations is also proposed. Monte Carlo experiments show that the finite sample performance of t…
A Smooth Specification Test for the Propensity Score
This paper proposes a simple smooth specification test for the propensity score in the spirit of Neyman (1937). We derive a particular restriction on the propensity score and construct the specification test based on it. Using the density‐weighting method, we transform the original specification testing problem into a test of the joint significance of the generalized Fourier coefficients. We propose a novel projection method to eliminate the para…
Self-normalized tests for skewness, kurtosis, and normality for time series data
Testing for skewness, kurtosis, and normality for time series data is highly relevant for modeling and testing purposes in econometrics and statistics. It also affects our understanding of many economic and financial phenomena and the validity of the models developed to explain them. In this paper, we propose self-normalized tests for skewness, kurtosis, and normality that can eliminate the effect of the long-run variance (LRV). In particular, ou…
Mathematics (8 works) · Econometrics (7 works) · Statistics (7 works) · Environmental Science (6 works) · Monte Carlo method (6 works) · Biology (5 works) · Chemistry (5 works) · Ecology (5 works) · Economics (5 works) · Estimator (5 works)