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动态面板模型的初始条件：组内方程与组间方程AI 解读

Summary This paper investigates the quasi-maximum likelihood estimation of short dynamic panel data models. We consider their estimation on both fixed effects and random effects specifications and propose a Hausman test when exogenous variables are present. For a dynamic panel model, initial conditions play important roles in model structure and estimation, and they give rise to a between equation under the random effects framework. With the between equation properly…

非参数趋势推断的自回归野生自助法AI 解读

In this paper we propose an autoregressive wild bootstrap method to construct confidence bands around a smooth deterministic trend. The bootstrap method is easy to implement and does not require any adjustments in the presence of missing data, which makes it particularly suitable for climatological applications. We establish the asymptotic validity of the bootstrap method for both pointwise and simultaneous confidence bands under general conditions, allowing for general…

含零观测时间序列的动态建模AI 解读

Sometimes a significant proportion of observations in a time series are zero, but the remaining observations are positive and measured on a continuous scale. We propose a new dynamic model in which the conditional distribution of the observations is constructed by shifting a distribution for non-zero observations to the left and censoring negative values. The key to generalizing the censoring approach to the dynamic case is to have (the logarithm of) the location/scale…

通过动态因子模拟长期预测厄尔尼诺事件AI 解读

We propose a new forecasting procedure which particularly explores opportunities for improving the precision of medium and long-term forecasts of the Niño3.4 time series that is linked with the well-known El Niño phenomenon. This important climatic time series is subject to an intricate dynamic structure and is interrelated to other climatological variables. The procedure consists of three steps. First, a univariate time series model is considered for producing prediction…

全球南北半球气温与共同均值转移：向量均值转移自回归分析AI 解读

This paper examines local changes in annual temperature data for the northern and southern hemispheres (1850–2017) by using a multivariate generalization of the shifting-meanautoregressive model of González and Teräsvirta (2008). Univariate models are first fitted to each series by using the QuickShift methodology. Full information maximum likelihood estimates of a bivariate system of temperature equations are then obtained and asymptotic properties of the corresponding…

地球瞬态气候敏感度的计量估计AI 解读

How sensitive is Earth’s climate to a given increase in atmospheric greenhouse gas (GHG) concentrations? This long-standing question in climate science was recently analyzed by dynamic panel data methods using extensive spatio-temporal data of global surface temperatures, solar radiation, and GHG concentrations over the last half century to 2010 (Storelvmo et al, 2016). Those methods revealed that atmospheric aerosol effects masked approximately one-third of the continental…

似不相关协整多项式回归的完全修正OLS估计、推断与二氧化碳环境库兹涅茨曲线AI 解读

This paper develops two fully modified OLS (FM-OLS) estimators for systems of seemingly unrelated cointegrating polynomial regressions, i.e., systems of regressions that include deterministic variables, integrated processes, and integer powers of integrated processes as explanatory variables. The stationary errors are allowed to be serially correlated and the regressors to be endogenous. Furthermore, the errors and regressors are allowed to be dynamically cross-sectionally…

高维气候模型的统计近似AI 解读

We propose a general emulation method for constructing low-dimensional approximations of complex dynamic climate models. Our method uses artificially designed uncorrelated CO2 emissions scenarios, which are much better suited for the construction of an emulator than are conventional emissions scenarios. We apply our method to the climate model MAGICC to approximate the impact of emissions on global temperature. Comparing the temperature forecasts of MAGICC and our emulator,…

气候系统的计量建模：能量平衡模型与协整向量自回归的等价性AI 解读

Estimates of both the human impact on climate as well as the economic impacts of climate change are crucial to inform policy decisions. Econometric modelling allows us to quantify these impacts and their uncertainties, but models have to be consistent with the underlying physics and the time series properties of the data. Here I show that energy-balance models of climate are equivalent to an econometric cointegrated system and can be estimated in discrete time. This…

分布特征的趋势：全球变暖的存在性AI 解读

What type of global warming exists? This study introduces a novel methodology to answer this question, which is the starting point for all issues related to climate change analyses. Global warming is defined as an increasing trend in certain distributional characteristics (moments, quantiles, etc.) of global temperatures, in addition to simply examining the average values. Temperatures are viewed as a functional stochastic process from which we obtain distributional…

连续分段趋势多变量系统中的共同断点推断：全球与半球气温应用AI 解读

What transpires from recent research is that temperatures and radiative forcing seem to be characterized by a linear trend with two changes in the rate of growth. The first occurs in the early 60s and indicates a very large increase in the rate of growth of both temperature and radiative forcing series. This was termed as the “onset of sustained global warming”. The second is related to the more recent so-called hiatus period, which suggests that temperatures and total…

分布时间序列的趋势评估：人类气候影响的空间指纹AI 解读

We analyze a time series of global temperature anomaly distributions to identify and estimate persistent features in climate change. We employ a formal test for the existence of functional unit roots in the time series of these densities, and we develop a new test to distinguish functional unit roots from functional deterministic trends or explosive behavior. Results suggest that temperature anomalies contain stochastic trends (as opposed to deterministic trends or explosive…

随机经济—气候模型中的期望效用与灾难性风险AI 解读

We analyze a stochastic dynamic finite-horizon economic model with climate change, in which the social planner faces uncertainty about future climate change and its economic damages. Our model (SDICE*) incorporates, possibly heavy-tailed, stochasticity in Nordhaus’ deterministic DICE model. We develop a regression-based numerical method for solving a general class of dynamic finite-horizon economy–climate models with potentially heavy-tailed uncertainty and general utility…

优势家庭儿童0—2岁日托的认知与非认知代价AI 解读

Exploiting admission thresholds to the Bologna day care system, we show using a regression discontinuity (RD) design that one additional day care month at age 0–2 reduces intelligence quotient by 0.5% (4.7% of a standard deviation) at age 8–14 in a relatively affluent population. The magnitude of this negative effect increases with family income. Similar negative impacts are found for personality traits. These findings are consistent with the hypothesis from psychology that…

双成分优于单成分？乘法成分GARCH-MIDAS模型的波动率预测AI 解读

Summary We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of generalized autoregressive conditional heteroskedasticity–mixed‐data sampling (GARCH‐MIDAS) models suggested in Engle, Ghysels, and Sohn ( Review of Economics and Statistics , 2013, 95 , 776–797). In those models volatility is decomposed into a short‐term GARCH component and a long‐term component that is driven by an explanatory variable. We…

加拿大银行工作人员经济预测数据库介绍AI 解读

Summary We present a new, publicly available database of real‐time data and forecasts from the Bank of Canada's staff economic projections, which will be updated on an annual basis. We describe the data construct, its variables, coverage, and frequency. We then provide a forecast evaluation for gross domestic product (GDP) growth, consumer price index (CPI) inflation and the policy rate since 1982: We compare the staff's forecasts with those from commonly used time series…

利用大型贝叶斯向量自回归估计并分解产出缺口AI 解读

Summary We consider how to estimate the trend and cycle of a time series, such as real gross domestic product, given a large information set. Our approach makes use of the Beveridge–Nelson decomposition based on a vector autoregression, but with two practical considerations. First, we show how to determine which conditioning variables span the relevant information by directly accounting for the Beveridge–Nelson trend and cycle in terms of contributions from different…

具有非对称尾部的金融收益条件分布建模AI 解读

Summary This paper proposes a conditional density model that allows for differing left/right tail indices and time‐varying volatility based on the dynamic conditional score (DCS) approach. The asymptotic properties of the maximum likelihood estimates are presented under verifiable conditions together with simulations showing effective estimation with practical sample sizes. It is shown that tail asymmetry is prevalent in global equity index returns and can be mistaken for…

对《描述性统计对结构估计的信息含量》的评论AI 解读

LET ME FIRST BRIEFLY RECALL the bias expressions in the paper.For simplicity, throughout I will fix a value η of the base model parameter.Let f η ζ be the density of the data D under the reader's model.Let f η denote the density of D under the base model.Given a quantity of interest c(η), the unrestricted bias of c is

摘要暂缺

对《描述性统计对结构估计的信息含量》的评论AI 解读

ANDREWS, GENTZKOW, AND SHAPIRO (2020), henceforth AGS, make important progress on a challenging and fundamental question. The authors consider a setting in which a researcher reports an estimate ĉn that is unbiased under the researcher’s model. The researcher also reports a statistic γ̂n and a measure of informativeness of γ̂n for ĉn, denoted by . AGS show can be related to properties of the distribution of ĉn under models larger than the one employed by the researcher. As a…

摘要暂缺

描述性统计对结构估计的信息含量AI 解读

We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimate ĉ of a structural quantity of interest c that is exactly or asymptotically unbiased under some base model. The researcher also reports descriptive statistics γ ˆ that estimate features γ of the distribution of the data that are related to c under the base model. A reader entertains a less restrictive model that is local to the base model,…

随机极限自助概率测度下的推断AI 解读

Asymptotic bootstrap validity is usually understood as consistency of the distribution of a bootstrap statistic, conditional on the data, for the unconditional limit distribution of a statistic of interest. From this perspective, randomness of the limit bootstrap measure is regarded as a failure of the bootstrap. We show that such limiting randomness does not necessarily invalidate bootstrap inference if validity is understood as control over the frequency of correct…