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大型需求系统的估计与福利分析AI 解读

We develop an approach for estimating individual or household level preferences for a large set of quality-differentiated goods and for constructing Hicksian welfare measures within the demand system framework. Our approach uses a maximum simulated likelihood procedure to recover estimates of the structural parameters and a multistage, Monte Carlo Markov chain algorithm for constructing Hicksian consumer surplus estimates. We illustrate our approach with a recreation dataset…

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利用全球误差修正宏观计量模型刻画地区间相互依赖AI 解读

Financial institutions are ultimately exposed to macroeconomic fluctuations in the global economy. This article proposes and builds a compact global model capable of generating forecasts for a core set of macroeconomic factors (or variables) across a number of countries. The model explicitly allows for the interdependencies that exist between national and international factors. Individual region-specific vector error-correcting models are estimated in which the domestic…

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改善多项Logit有限混合模型个体估计与预测的经验贝叶斯方法AI 解读

with by specifying either a multinomial or a normal distribution of the coefficients, leading to finite mixture logit and mixed logit models. Focusing on the former, we show that individual-level estimates and predictions of finite mixtures estimated by maximizing the likelihood function can be improved through integration over the estimation error of the hyperparameters, using an empirical Bayes approach. We investigate the conjecture that this approach is more robust…

波动减弱的美国经济AI 解读

Using a Bayesian model comparison strategy, we search for a volatility reduction in U.S. real gross domestic product (GDP) growth within the postwar sample. We find that aggregate real GDP growth has been less volatile since the early 1980s, and that this volatility reduction is concentrated in the cyclical component of real GDP.Sales and production growth in many of the components of real GDP display similar reductions in volatility, suggesting the aggregate volatility…

半参数持续时间模型AI 解读

estimation of the parameters in a non-iid environment. In contrast to classical time series models where innovations are assumed to be iid we show that in, for example, the often-used autoregressive conditional duration (ACD) model, the assumption of independent innovations is too restrictive to describe financial durations accurately. Therefore, we consider semiparametric extensions of the standard specification that allow for arbitrary kinds of dependencies between the…

行为假设如何影响结构推断？来自实验室实验的证据AI 解读

rational expectations has on structural inference in a dynamic discrete decision problem. Our design induces preferences up to the subjective rate of time preference, leaving unrestricted both this parameter and subjects' decision rules. We estimate subjects' discount rates under the assumption that all subjects use the rational expectations decision rule, and under weaker behavioral assumptions that allow decision rule heterogeneity. We find that certain sophisticated…

异质性模型的贝叶斯分析AI 解读

effects, which is also known as the heterogeneity model. First, we discuss the properties of various Markov chain Monte Carlo samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing. Whereas full conditional Gibbs sampling turns out to be sensitive to the parameterization chosen for the mean structure of the model, the alternative sampler is robust in this respect. However, the logical extension of the approach to the sampling of the group…

用于比较随机波动率模型的偏差信息准则AI 解读

stochastic volatility models for analyzing financial time series. Recent advances made it possible to fit stochastic volatility models of increasing complexity, including covariates, leverage effects, jump components, and heavy-tailed distributions. However, a formal model comparison via Bayes factors remains difficult. The main objective of this article is to demonstrate that model selection is more easily performed using the deviance information criterion (DIC). It…

抽样频率与匹配型号、特征回归价格指数的比较AI 解读

prices, because the price/performance ratio of models sold in consecutive periods is worse than that of new models. This "unrepresentativeness" of the sample potentially might be reduced by obtaining higher-frequency data, thus increasing the fraction of models that are matched. We propose a set of conformable indexes to test this hypothesis. Using computer prices from the Buy Direct press, we find, contrary to initial expectations, that the bias in the matched-model price…

融资约束与农场投资AI 解读

This study contributes to the q-based empirical investment literature by using a Bayesian approach to analyze the impact of internal financial variables on a q-based investment model, accounting specifically for variable selection and incorporating outliers explicitly within the advocated modeling framework. For the balanced panel analyzed, a farm's liquidity situation is found to affect its investment significantly. Incorporation of an outlier detection component changes…

若干稳健工具变量估计量的表现AI 解读

and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.

线性条件异方差模型的矩与记忆性质及一种新模型AI 解读

conditional heteroscedasticity models in which the conditional variance is a linear function of squared lags of the process. GARCH, IGARCH, FIGARCH, and a newly proposed generalization, the HYGARCH model, belong to this class. Conditions are derived for the existence of second and fourth moments, and for the limited memory condition of near-epoch dependence. The HYGARCH model is applied to 10 daily dollar exchange rates, and also to data for Asian exchange rates over the…

动态二元混合模型的估计AI 解读

Watanabe estimated the dynamic bivariate mixture models introduced by Tauchen and Pitts and modified by Andersen using a Bayesian method via Markov chain Monte Carlo techniques. Based on a maximum likelihood method via efficient importance sampling, Liesenfeld and Richard obtained estimates that are significantly different from those of Watanabe. This note corrects the error in the multimove sampler used by Watanabe and reproduces all analyses in the work of Watanabe using a…

可能协整序列中马尔可夫趋势的贝叶斯估计AI 解读

Stylized facts show that average growth rates of U.S. per capita consumption and income differ in recession and expansion periods. Because a linear combination of such series does not have to be a constant mean process, standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid. To model the changing growth rates in both series, we introduce a multivariate Markov trend model that accounts for different growth rates in…

动态二元混合模型的估计AI 解读

This note compares a Bayesian Markov chain Monte Carlo approach implemented by Watanabe with a maximum likelihood ML approach based on an efficient importance sampling procedure to estimate dynamic bivariate mixture models. In these models, stock price volatility and trading volume are jointly directed by the unobservable number of price-relevant information arrivals, which is specified as a serially correlated random variable. It is shown that the efficient importance…

方差突变、结构断裂与平稳性检验AI 解读

stochastic stationarity in time series characterized by variance shifts at some (known or unknown) point in the sample. It is shown that existing stationarity tests can be severely biased in the presence of such shifts, either oversized or undersized, with associated spurious power gains or losses, depending on the values of the breakpoint parameter and on the ratio of the prebreak to postbreak variance. Under the assumption of a serially independent Gaussian error term with…

含多元 t 创新的条件异方差动态回归模型：极大似然估计与推断AI 解读

Hessian, and information matrix of conditionally heteroscedastic dynamic regression models when the conditional distribution is multivariate t. We also derive one-sided and two-sided Lagrange multiplier tests for multivariate normality versus multivariate t based on the first two moments of the squared norm of the standardized innovations evaluated at the Gaussian pseudo-maximum likelihood estimators of the conditional mean and variance parameters. Finally, we illustrate our…

结构非自适应模型的迭代与递归估计AI 解读

appears well suited for econometric models where the structural relationships of interest define the observed endogenous variables as a known function of unobserved state variables and unknown parameters. This nonlinear state-space specification paves the way for iterative or recursive EM-like strategies. In the E steps, the state variables are forecasted given the observations and a value of the parameters. In the M steps, these forecasts are used to deduce estimators of…

再论经济周期的持续时间依赖性AI 解读

Economic Research business cycle chronology and found evidence of duration dependence only for prewar expansions and postwar contractions. The article updates the postwar sample through the end of the most recent expansion and uses a generalized Weibull model that provides much greater flexibility at the expense of one additional parameter. This model finds evidence of duration dependence for all samples and is statistically superior to the conventional Weibull model for all…

变换模型的成对差分秩估计AI 解读

coefficient vector in a transformation model. These estimators, like other existing rank estimators, require no subjective bandwidth choice. Monte Carlo simulations, numerical asymptotic efficiency comparisons, and two empirical applications suggest that the proposed estimators perform well in comparison with existing semiparametric estimators.