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Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions 从大数据量化回归透视宏观经济尾部风险的非线性因素
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-26 DOI: 10.1002/jae.3018
Jan Prüser, Florian Huber
{"title":"Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions","authors":"Jan Prüser,&nbsp;Florian Huber","doi":"10.1002/jae.3018","DOIUrl":"10.1002/jae.3018","url":null,"abstract":"<p>Modeling and predicting extreme movements in GDP is notoriously difficult, and the selection of appropriate covariates and/or possible forms of nonlinearities are key in obtaining precise forecasts. In this paper, our focus is on using large datasets in quantile regression models to forecast the conditional distribution of US GDP growth. To capture possible nonlinearities, we include several nonlinear specifications. The resulting models will be huge dimensional, and we thus rely on a set of shrinkage priors. Since Markov chain Monte Carlo estimation becomes slow in these dimensions, we rely on fast variational Bayes approximations to the posterior distribution of the coefficients and the latent states. We find that our proposed set of models produces precise forecasts. These gains are especially pronounced in the tails. Using Gaussian processes to approximate the nonlinear component of the model further improves the good performance, in particular in the right tail.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 2","pages":"269-291"},"PeriodicalIF":2.1,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139061916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Panel data nowcasting: The case of price–earnings ratios 面板数据预报：市盈率案例
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-26 DOI: 10.1002/jae.3028
Andrii Babii, Ryan T. Ball, Eric Ghysels, Jonas Striaukas
{"title":"Panel data nowcasting: The case of price–earnings ratios","authors":"Andrii Babii,&nbsp;Ryan T. Ball,&nbsp;Eric Ghysels,&nbsp;Jonas Striaukas","doi":"10.1002/jae.3028","DOIUrl":"10.1002/jae.3028","url":null,"abstract":"<p>The paper uses structured machine learning regressions for nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the problem of predicting corporate earnings for a large cross-section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse-group LASSO regularization which can take advantage of the mixed-frequency time series panel data structures. Our empirical results show the superior performance of our machine learning panel data regression models over analysts' predictions, forecast combinations, firm-specific time series regression models, and standard machine learning methods.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 2","pages":"292-307"},"PeriodicalIF":2.1,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139061854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Revisiting the analysis of matched-pair and stratified experiments in the presence of attrition 重新审视自然减员情况下的配对实验和分层实验分析
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-20 DOI: 10.1002/jae.3025
Yuehao Bai, Meng Hsuan Hsieh, Jizhou Liu, Max Tabord-Meehan
{"title":"Revisiting the analysis of matched-pair and stratified experiments in the presence of attrition","authors":"Yuehao Bai,&nbsp;Meng Hsuan Hsieh,&nbsp;Jizhou Liu,&nbsp;Max Tabord-Meehan","doi":"10.1002/jae.3025","DOIUrl":"10.1002/jae.3025","url":null,"abstract":"<p>In this paper, we revisit some common recommendations regarding the analysis of matched-pair and stratified experimental designs in the presence of attrition. Our main objective is to clarify a number of well-known claims about the practice of dropping pairs with an attrited unit when analyzing matched-pair designs. Contradictory advice appears in the literature about whether or not dropping pairs is beneficial or harmful, and stratifying into larger groups has been recommended as a resolution to the issue. To address these claims, we derive the estimands obtained from the difference-in-means estimator in a matched-pair design both when the observations from pairs with an attrited unit are retained and when they are dropped. We find limited evidence to support the claims that dropping pairs helps recover the average treatment effect, but we find that it may potentially help in recovering a convex-weighted average of conditional average treatment effects. We report similar findings for stratified designs when studying the estimands obtained from a regression of outcomes on treatment with and without strata fixed effects.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 2","pages":"256-268"},"PeriodicalIF":2.1,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138827035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sample selection in linear panel data models with heterogeneous coefficients 具有异质系数的线性面板数据模型中的样本选择
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-14 DOI: 10.1002/jae.3022
Alyssa Carlson, Riju Joshi
{"title":"Sample selection in linear panel data models with heterogeneous coefficients","authors":"Alyssa Carlson,&nbsp;Riju Joshi","doi":"10.1002/jae.3022","DOIUrl":"10.1002/jae.3022","url":null,"abstract":"<p>We propose a parametric estimation procedure for linear panel data models with sample selection and heterogeneous coefficients that are present in both outcome model and selection model. Our two-step estimation procedure accounts for endogeneity from the selection process and endogeneity from correlation between the individual unobserved heterogeneity and the observed covariates using control function like methods. Conditional linear projections are used to establish a tractable approach that builds upon the original Heckman correction to sample selection. Monte Carlo simulations illustrate the finite sample properties of our estimator and demonstrate that our proposed estimator outperforms standard estimators. We apply the proposed approach to estimate gender differences in high-stakes time-constrained decisions using Elo ratings data from the World Chess Federation. When addressing both sources of endogeneity, we find a much larger gender skill gap and substantial differences across the genders in strategically selecting into time-constrained matches.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 2","pages":"237-255"},"PeriodicalIF":2.1,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138679993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Heterogeneity and dynamics in network models 网络模型中的异质性和动态性
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-14 DOI: 10.1002/jae.3013
Enzo D'Innocenzo, André Lucas, Anne Opschoor, Xingmin Zhang
{"title":"Heterogeneity and dynamics in network models","authors":"Enzo D'Innocenzo,&nbsp;André Lucas,&nbsp;Anne Opschoor,&nbsp;Xingmin Zhang","doi":"10.1002/jae.3013","DOIUrl":"10.1002/jae.3013","url":null,"abstract":"<div>\u0000 \u0000 <p>We propose an empirical spatial modeling framework that allows for both heterogeneity and dynamics in economic network connections. We establish the model's stationarity and ergodicity properties and show that the model's implied filter is invertible. While highly flexible, the model is straightforward to estimate by maximum likelihood. We apply the model to three datasets for Eurozone sovereign credit risk over the period Dec-2009 to Dec-2022. Accounting for both heterogeneity and time-variation turns out to be empirically important both in-sample and out-of-sample. The new model uncovers intuitive patterns that would go unnoticed in either homogeneous and/or static spatial financial network models.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 1","pages":"150-173"},"PeriodicalIF":2.1,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138679747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identifying oil price shocks with global, developed, and emerging latent real economy activity factors 利用全球、发达和新兴潜在实体经济活动因素识别石油价格冲击
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-12-07 DOI: 10.1002/jae.3017
Antoine A. Djogbenou
{"title":"Identifying oil price shocks with global, developed, and emerging latent real economy activity factors","authors":"Antoine A. Djogbenou","doi":"10.1002/jae.3017","DOIUrl":"10.1002/jae.3017","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes an identification strategy for international oil price shocks while accounting for the heterogeneous sources of oil demand from global, developed, and emerging economies. Unlike existing works, we isolate global oil demand shocks, associated with a global real economic activity factor, from oil demand shocks originating specifically from developed and emerging economies, associated with real economic activity factors within these two groups of economies. The paper uses a structural factor-augmented vector autoregression (FAVAR) model with latent global and specific factors to model crude oil demand and supply. To identify the shocks, we extract real economic activity factors from a large panel of emerging and developed economies' real activity variables using a two-level factor model. The paper shows how structural shocks can be identified by solving equations that arise from economically meaningful zero restrictions on the impact matrix of the reduced-form FAVAR model innovations. The empirical application shows that identifying the international oil demand shocks based on the global and specific latent factors is essential to appropriately quantify their heterogeneous impacts on these factors, the crude oil production, and the real oil price.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 1","pages":"128-149"},"PeriodicalIF":2.1,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138547765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Partial identification and inference for conditional distributions of treatment effects 治疗效果条件分布的部分识别与推断
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-11-23 DOI: 10.1002/jae.3014
Sungwon Lee
{"title":"Partial identification and inference for conditional distributions of treatment effects","authors":"Sungwon Lee","doi":"10.1002/jae.3014","DOIUrl":"10.1002/jae.3014","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper considers identification and inference for the distribution of treatment effects conditional on observable covariates. Since the conditional distribution of treatment effects is not point identified without strong assumptions, we obtain bounds on the conditional distribution of treatment effects by using the Makarov bounds. We also consider the case where the treatment is endogenous and propose two stochastic dominance assumptions to tighten the bounds. We develop a nonparametric framework to estimate the bounds and establish the asymptotic theory that is uniformly valid over the support of treatment effects. An empirical example illustrates the usefulness of the methods.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 1","pages":"107-127"},"PeriodicalIF":2.1,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138511544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Outlier robust inference in the instrumental variable model with applications to causal effects 工具变量模型中的离群稳健推断与因果效应的应用
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-10-30 DOI: 10.1002/jae.3012
Jens Klooster, Mikhail Zhelonkin
{"title":"Outlier robust inference in the instrumental variable model with applications to causal effects","authors":"Jens Klooster,&nbsp;Mikhail Zhelonkin","doi":"10.1002/jae.3012","DOIUrl":"10.1002/jae.3012","url":null,"abstract":"<p>The Anderson-Rubin (AR) test is an important method that allows for reliable inference in the instrumental variable model when the instruments are weak. Yet, the robustness properties of this test have not been formally studied. As it turns out that the AR test is not robust to outliers, we show how to construct an outlier robust alternative—the robust AR test. We investigate the robustness properties of the robust AR test and show that the robust AR statistic asymptotically follows a chi-square distribution. The theoretical results are illustrated by a simulation study. Finally, we apply the robust AR test to three different case studies that are affected by different types of outliers.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 1","pages":"86-106"},"PeriodicalIF":2.1,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136068650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forecasting and stress testing with quantile vector autoregression 利用量子向量自回归进行预测和压力测试
IF 2.1 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-10-26 DOI: 10.1002/jae.3009
Sulkhan Chavleishvili, Simone Manganelli
{"title":"Forecasting and stress testing with quantile vector autoregression","authors":"Sulkhan Chavleishvili,&nbsp;Simone Manganelli","doi":"10.1002/jae.3009","DOIUrl":"10.1002/jae.3009","url":null,"abstract":"<div>\u0000 \u0000 <p>A quantile vector autoregressive (VAR) model, unlike standard VAR, traces the interaction among the endogenous random variables at any quantile. Quantile forecasts are obtained by factorizing the joint distribution in a recursive structure but cannot be obtained from reduced form estimation. Identification strategies and structural quantile impulse response functions are derived as generalization of the VAR model. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 1","pages":"66-85"},"PeriodicalIF":2.1,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136377185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Risk, ambiguity, and misspecification: Decision theory, robust control, and statistics 风险、模糊性和错误规范：决策理论、稳健控制和统计学
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2023-10-23 DOI: 10.1002/jae.3010
Lars Peter Hansen, Thomas J. Sargent
{"title":"Risk, ambiguity, and misspecification: Decision theory, robust control, and statistics","authors":"Lars Peter Hansen,&nbsp;Thomas J. Sargent","doi":"10.1002/jae.3010","DOIUrl":"10.1002/jae.3010","url":null,"abstract":"<p>What are “deep uncertainties” and how should their presence influence prudent decisions? To address these questions, we bring ideas from robust control theory into statistical decision theory. Decision theory has its origins in axiomatic formulations by von Neumann and Morgenstern, Wald, and Savage. After Savage, decision theorists constructed axioms that formalize a notion of ambiguity aversion. Meanwhile, control theorists constructed decision rules that are robust to some model misspecifications. We reinterpret axiomatic foundations of decision theories to express ambiguity about a prior over a family of models along with concerns about misspecifications of the corresponding likelihood functions.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 6","pages":"969-999"},"PeriodicalIF":2.3,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135368678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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