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Announcement Econometric Reviews (IF 1.2) Pub Date : 2024-03-13
Published in Econometric Reviews (Ahead of Print, 2024)
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Doubly robust estimation of multivariate fractional outcome means with multivalued treatments Econometric Reviews (IF 1.2) Pub Date : 2024-03-08 Akanksha Negi, Wooldridge Jeffrey M.
This article suggests a doubly robust method of estimating potential outcome means for multivariate fractional outcomes when the treatment of interest is unconfounded and can take more than two val...
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Inferring inequality: Testing for median-preserving spreads in ordinal data Econometric Reviews (IF 1.2) Pub Date : 2024-03-04 Ramses H. Abul Naga, Christopher Stapenhurst, Gaston Yalonetzky
The median-preserving spread (MPS) ordering for ordinal variables has become ubiquitous in the inequality literature. We devise statistical tests of the hypothesis that a distribution G is not an M...
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Nonparametric estimation of mediation effects with a general treatment Econometric Reviews (IF 1.2) Pub Date : 2024-02-19 Lukang Huang, Wei Huang, Oliver Linton, Zheng Zhang
To investigate causal mechanisms, causal mediation analysis decomposes the total treatment effect into the natural direct and indirect effects. This article examines the estimation of the direct an...
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Confidence intervals for intentionally biased estimators Econometric Reviews (IF 1.2) Pub Date : 2024-02-11 David M. Kaplan, Xin Liu
We propose and study three confidence intervals (CIs) centered at an estimator that is intentionally biased to reduce mean squared error. The first CI simply uses an unbiased estimator’s standard e...
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A method to evaluate the rank condition for CCE estimators Econometric Reviews (IF 1.2) Pub Date : 2024-01-08 Ignace De Vos, Gerdie Everaert, Vasilis Sarafidis
We develop a binary classifier to evaluate whether the rank condition (RC) is satisfied or not for the Common Correlated Effects (CCE) estimator. The RC postulates that the number of unobserved fac...
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Post-averaging inference for optimal model averaging estimator in generalized linear models Econometric Reviews (IF 1.2) Pub Date : 2024-01-03 Dalei Yu, Heng Lian, Yuying Sun, Xinyu Zhang, Yongmiao Hong
This article considers the problem of post-averaging inference for optimal model averaging estimators in a generalized linear model (GLM). We establish the asymptotic distributions of optimal model...
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A unifying switching regime regression framework with applications in health economics Econometric Reviews (IF 1.2) Pub Date : 2023-11-29 Giampiero Marra, Rosalba Radice, David Zimmer
Motivated by three health economics-related case studies, we propose a unifying and flexible regression modeling framework that involves regime switching. The proposal can handle the peculiar distr...
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Model averaging for generalized linear models in diverging model spaces with effective model size Econometric Reviews (IF 1.2) Pub Date : 2023-11-29 Chaoxia Yuan, Fang Fang, Jialiang Li
While plenty of frequentist model averaging methods have been proposed, existing weight selection criteria for generalized linear models (GLM) are usually based on a model size penalized Kullback-L...
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Testing Granger non-causality in expectiles Econometric Reviews (IF 1.2) Pub Date : 2023-09-05 Taoufik Bouezmarni, Mohamed Doukali, Abderrahim Taamouti
This article aims to derive a consistent test of Granger causality at a given expectile. We also propose a sup-Wald test for jointly testing Granger causality at all expectiles that has the correct...
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Extremal quantiles and stock price crashes Econometric Reviews (IF 1.2) Pub Date : 2023-08-20 Panayiotis C. Andreou, Sofia Anyfantaki, Esfandiar Maasoumi, Carlo Sala
Abstract We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, idiosyncratic negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently imprecise and susceptible to misspecifications, especially for tail events. We instead propose new definitions
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In memory of Michael McAleer: special issue of Econometric Reviews Econometric Reviews (IF 1.2) Pub Date : 2023-08-17 Esfandiar Maasoumi, Robert Taylor
Published in Econometric Reviews (Vol. 42, No. 9-10, 2023)
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Time-dependent shrinkage of time-varying parameter regression models Econometric Reviews (IF 1.2) Pub Date : 2023-08-04 Zhongfang He
This article studies the time-varying parameter (TVP) regression model in which the regression coefficients are random walk latent states with time-dependent conditional variances. This TVP model i...
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Inference for the VEC(1) model with a heavy-tailed linear process errors* Econometric Reviews (IF 1.2) Pub Date : 2023-07-31 Feifei Guo, Shiqing Ling
Abstract This article studies the first-order vector error correction (VEC(1)) model when its noise is a linear process of independent and identically distributed (i.i.d.) heavy-tailed random vectors with a tail index α∈(0,2). We show that the rate of convergence of the least squares estimator (LSE) related to the long-run parameters is n (sample size) and its limiting distribution is a stochastic
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Improved tests for stock return predictability Econometric Reviews (IF 1.2) Pub Date : 2023-07-14 David I. Harvey, Stephen J. Leybourne, A. M. Robert Taylor
Abstract– Predictive regression methods are widely used to examine the predictability of (excess) stock returns by lagged financial variables characterized by unknown degrees of persistence and endogeneity. We develop a new hybrid test for predictability in these circumstances based on simple regression t-statistics. Where the predictor is endogenous, the optimal, but infeasible, test for predictability
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Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models Econometric Reviews (IF 1.2) Pub Date : 2023-07-12 H. Peter Boswijk, Giuseppe Cavaliere, Luca De Angelis, A. M. Robert Taylor
Abstract Standard methods, such as sequential procedures based on Johansen’s (pseudo-)likelihood ratio (PLR) test, for determining the co-integration rank of a vector autoregressive (VAR) system of variables integrated of order one can be significantly affected, even asymptotically, by unconditional heteroskedasticity (non-stationary volatility) in the data. Known solutions to this problem include
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Automatic variable selection for semiparametric spatial autoregressive model Econometric Reviews (IF 1.2) Pub Date : 2023-07-12 Fang Lu, Sisheng Liu, Jing Yang, Xuewen Lu
This article studies the generalized method of moment estimation of semiparametric varying coefficient partially linear spatial autoregressive model. The technique of profile least squares is emplo...
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Linear fixed-effects estimation with nonrepeated outcomes Econometric Reviews (IF 1.2) Pub Date : 2023-07-12 Helmut Farbmacher, Harald Tauchmann
We demonstrate that popular linear fixed-effects panel-data estimators are biased and inconsistent when applied in a discrete-time hazard setting, even if the data-generating process is consistent ...
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Forecasting Levels in Loglinear Unit Root Models Econometric Reviews (IF 1.2) Pub Date : 2023-07-12 Kees Jan van Garderen
Abstract This article considers unbiased prediction of levels when data series are modeled as a random walk with drift and other exogenous factors after taking natural logs. We derive the unique unbiased predictors for growth and its variance. Derivation of level forecasts is more involved because the last observation enters the conditional expectation and is highly correlated with the parameter estimates
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Robust nonparametric frontier estimation in two steps Econometric Reviews (IF 1.2) Pub Date : 2023-07-03 Yining Chen, Hudson S. Torrent, Flavio A. Ziegelmann
Abstract We propose a robust methodology for estimating production frontiers with multi-dimensional input via a two-step nonparametric regression, in which we estimate the level and shape of the frontier before shifting it to an appropriate position. Our main contribution is to derive a novel frontier estimation method under a variety of flexible models which is robust to the presence of outliers and
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An application of copulas to OPEC’s changing influence on fossil fuel prices Econometric Reviews (IF 1.2) Pub Date : 2023-07-03 C. Grazian, A. McInnes
Abstract This work examines how the dependence structures between energy futures asset prices differ in two periods identified before and after the 2008 global financial crisis. These two periods were characterized by a difference in the number of extraordinary meetings of OPEC countries organized to announce a change of oil production. In the period immediately following the global financial crisis
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Forecasting vector autoregressions with mixed roots in the vicinity of unity Econometric Reviews (IF 1.2) Pub Date : 2023-07-03 Yundong Tu, Xinling Xie
Abstract This article evaluates the forecast performance of model averaging forecasts in a nonstationary vector autoregression with mixed roots in the vicinity of unity. The deviation from unit root allows for local to unity, moderate deviation from unity and strong unit root, and the direction of such deviation could be from either the stationary or the explosive side. We provide a theoretical foundation
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Latent local-to-unity models Econometric Reviews (IF 1.2) Pub Date : 2023-06-29 Xiaohu Wang, Jun Yu
Abstract The article studies a class of state-space models where the state equation is a local-to-unity process. The parameter of interest is the persistence parameter of the latent process. The large sample theory for the least squares (LS) estimator and an instrumental variable (IV) estimator of the persistent parameter in the autoregressive (AR) representation of the model is developed under two
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Endogeneity in semiparametric threshold regression models with two threshold variables Econometric Reviews (IF 1.2) Pub Date : 2023-06-22 Chaoyi Chen, Thanasis Stengos, Yiguo Sun
This article considers a semiparametric threshold regression model with two threshold variables. The proposed model allows endogenous threshold variables and endogenous slope regressors. Under the ...
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Dynamic factor, leverage and realized covariances in multivariate stochastic volatility Econometric Reviews (IF 1.2) Pub Date : 2023-06-22 Yuta Yamauchi, Yasuhiro Omori
Abstract In the stochastic volatility models for multivariate daily stock returns, it has been found that the estimates of parameters become unstable as the dimension of returns increases. To solve this problem, we focus on the factor structure of multiple returns and consider two additional sources of information: first, the stock index associated with the market factor and, second, the realized covariance
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A unified unit root test regardless of intercept Econometric Reviews (IF 1.2) Pub Date : 2023-06-12 Bingduo Yang, Xiaohui Liu, Wei Long, Liang Peng
Abstract Using the augmented Dickey-Fuller test to verify the existence of a unit root in an autoregressive process often requires the correctly specified intercept, since the test statistics can be distinctive under different model specifications and lead to contradictory results at times. In this article, we develop a unified inference that not only unifies the specifications of the intercept but
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Optimal minimax rates of specification testing with data-driven bandwidth Econometric Reviews (IF 1.2) Pub Date : 2023-06-07 Kohtaro Hitomi, Masamune Iwasawa, Yoshihiko Nishiyama
Abstract This study investigates optimal minimax rates of specification testing for linear and non-linear instrumental variable regression models. The test constructed by non-parametric kernel techniques can be rate optimal when bandwidths are selected appropriately. Since bandwidths are often selected in a data-dependent way in empirical studies, the rate-optimality of the test with data-driven bandwidths
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A robust score-driven filter for multivariate time series Econometric Reviews (IF 1.2) Pub Date : 2023-06-06 Enzo D’Innocenzo, Alessandra Luati, Mario Mazzocchi
Abstract A multivariate score-driven filter is developed to extract signals from noisy vector processes. By assuming that the conditional location vector from a multivariate Student’s t distribution changes over time, we construct a robust filter which is able to overcome several issues that naturally arise when modeling heavy-tailed phenomena and, more in general, vectors of dependent non-Gaussian
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Monitoring the direction of the short-term trend of economic indicators Econometric Reviews (IF 1.2) Pub Date : 2023-06-05 Estela Bee Dagum, Silvia Bianconcini
Abstract Socioeconomic indicators have long been used by official statistical agencies to analyze and assess the current stage at which the economy stands via the application of linear filters used in conjunction with seasonal adjustment procedures. In this study, we propose a new set of symmetric and asymmetric weights that offer substantial gains in real-time by providing timely and more accurate
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Inference in a similarity-based spatial autoregressive model Econometric Reviews (IF 1.2) Pub Date : 2023-05-12 Offer Lieberman, Francesca Rossi
In this article, we develop asymptotic theory for a spatial autoregressive (SAR) model where the network structure is defined according to a similarity-based weight matrix, in line with the similar...
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Panel cointegrating polynomial regressions: group-mean fully modified OLS estimation and inference Econometric Reviews (IF 1.2) Pub Date : 2023-05-05 Martin Wagner, Karsten Reichold
Abstract We develop group-mean fully modified OLS (FM-OLS) estimation and inference for panels of cointegrating polynomial regressions, i.e., regressions that include an integrated process and its powers as explanatory variables. The stationary errors are allowed to be serially correlated, the integrated regressors – allowed to contain drifts – to be endogenous and, as usual in the panel literature
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Bandwidth selection for nonparametric regression with errors-in-variables Econometric Reviews (IF 1.2) Pub Date : 2023-04-22 Hao Dong, Taisuke Otsu, Luke Taylor
Abstract We propose two novel bandwidth selection procedures for the nonparametric regression model with classical measurement error in the regressors. Each method evaluates the prediction errors of the regression using a second (density) deconvolution. The first approach uses a typical leave-one-out cross-validation criterion, while the second applies a bootstrap approach and the concept of out-of-bag
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Inference and extrapolation in finite populations with special attention to clustering Econometric Reviews (IF 1.2) Pub Date : 2023-04-22 Richard Startz, Douglas G. Steigerwald
Abstract Statistical inference in economics is commonly based on formulas assuming infinite populations. We present appropriate formulas for use when sampling from finite populations, with special attention given to issues of treatment effects and to issues of clustering. Issues of whether to apply finite population corrections are often subtle, and appropriate corrections may depend on difficult to
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GLS estimation and confidence sets for the date of a single break in models with trends Econometric Reviews (IF 1.2) Pub Date : 2023-03-16 Eric Beutner, Yicong Lin, Stephan Smeekes
Abstract We develop a Feasible Generalized Least Squares estimator of the date of a structural break in level and/or trend. The estimator is based on a consistent estimate of a T-dimensional inverse autocovariance matrix. A cubic polynomial transformation of break date estimates can be approximated by a nonstandard yet nuisance parameter free distribution asymptotically. The new limiting distribution
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The two-way Mundlak estimator Econometric Reviews (IF 1.2) Pub Date : 2023-03-16 Badi H. Baltagi
Abstract Mundlak shows that the fixed effects estimator is equivalent to the random effects estimator in the one-way error component model once the random individual effects are modeled as a linear function of all the averaged regressors over time. In the spirit of Mundlak, this paper shows that this result also holds for the two-way error component model once the individual and time effects are modeled
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Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings Econometric Reviews (IF 1.2) Pub Date : 2023-03-13 Federico Belotti, Alessandro Casini, Leopoldo Catania, Stefano Grassi, Pierre Perron
Abstract We consider the derivation of data-dependent simultaneous bandwidths for double kernel heteroscedasticity and autocorrelation consistent (DK-HAC) estimators. In addition to the usual smoothing over lagged autocovariances for classical HAC estimators, the DK-HAC estimator also applies smoothing over the time direction. We obtain the optimal bandwidths that jointly minimize the global asymptotic
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Indirect inference estimation of higher-order spatial autoregressive models Econometric Reviews (IF 1.2) Pub Date : 2023-03-08 Yong Bao
Abstract This paper proposes estimating parameters in higher-order spatial autoregressive models, where the error term also follows a spatial autoregression and its innovations are heteroskedastic, by matching the simple ordinary least squares estimator with its analytical approximate expectation, following the principle of indirect inference. The resulting estimator is shown to be consistent, asymptotically
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Estimating flow data models of international trade: dual gravity and spatial interactions Econometric Reviews (IF 1.2) Pub Date : 2023-03-04 Fei Jin, Lung-fei Lee, Jihai Yu
Abstract This article investigates asymptotic properties of quasi-maximum likelihood (QML) estimates for flow data on the dual gravity model in international trade with spatial interactions (dependence). The dual gravity model has a well-established economic foundation, and it takes the form of a spatial autoregressive (SAR) model. The dual gravity model originates from Behrens et al., but the spatial
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Nonparametric identification and estimation of heterogeneous causal effects under conditional independence Econometric Reviews (IF 1.2) Pub Date : 2023-02-23 Sungho Noh
Abstract In this article, I propose a nonparametric strategy to identify the distribution of heterogeneous causal effects. A set of identification restrictions proposed in this article differs from existing approaches in three ways. First, it extends the random coefficient model by allowing potentially nonlinear interactions between distributional parameters and the set of covariates. Second, the causal
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Efficient estimation with missing data and endogeneity Econometric Reviews (IF 1.2) Pub Date : 2023-02-23 Bhavna Rai
Abstract I study the problem of missing values in the outcome and endogenous covariates in linear models. I propose an estimator that improves efficiency relative to a complete cases 2SLS. Unlike traditional imputation, my estimator is consistent even if the model contains nonlinear functions – like squares and interactions – of the endogenous covariates. It can also be used to combine data sets with
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Inference in an incomplete information entry game with an incumbent and with beliefs conditioned on unobservable market characteristics Econometric Reviews (IF 1.2) Pub Date : 2023-02-23 Andres Aradillas-Lopez
Abstract We consider a static entry game played between an incumbent and a collection of potential entrants. Entry decisions are made with incomplete information and beliefs are conditioned, at least partially, on a market characteristic that is unobserved by the econometrician. We describe conditions under which, even though the unobserved market characteristic cannot be identified, a subset of parameters
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Hamiltonian sequential Monte Carlo with application to consumer choice behavior Econometric Reviews (IF 1.2) Pub Date : 2023-02-11 Martin Burda, Remi Daviet
Abstract The practical use of nonparametric Bayesian methods requires the availability of efficient algorithms for posterior inference. The inherently serial nature of traditional Markov chain Monte Carlo (MCMC) methods imposes limitations on their efficiency and scalability. In recent years, there has been a surge of research activity devoted to developing alternative implementation methods that target
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Yet another look at the omitted variable bias Econometric Reviews (IF 1.2) Pub Date : 2023-02-08 Masayuki Hirukawa, Irina Murtazashvili, Artem Prokhorov
Abstract When conducting regression analysis, econometricians often face the situation where some relevant regressors are unavailable in the data set at hand. This article shows how to construct a new class of nonparametric proxies by combining the original data set with one containing the missing regressors. Imputation of the missing values is done using a nonstandard kernel adapted to mixed data
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Smooth structural changes and common factors in nonstationary panel data: an analysis of healthcare expenditures† Econometric Reviews (IF 1.2) Pub Date : 2022-12-21 Saban Nazlioglu, Junsoo Lee, Margie Tieslau, Cagin Karul, Yu You
Abstract This article suggests new panel unit root tests that allow for multiple structural breaks and control for cross-correlations in the panel. Breaks are modeled with a Fourier function, which allows for smooth or gradual change rather than abrupt breaks. Cross-correlations are corrected by using the PANIC procedure. The simulations show that our tests have good size and power properties and perform
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Forward detrending for heteroskedasticity-robust panel unit root testing Econometric Reviews (IF 1.2) Pub Date : 2022-11-28 Helmut Herwartz, Simone Maxand, Yabibal M. Walle
Abstract The variances of most economic time series display marked fluctuations over time. Panel unit root tests of the so-called first and second generation are not robust in such cases. In response to this problem, a few heteroskedasticity-robust panel unit root tests have been proposed. An important limitation of these tests is, however, that they become invalid if the data are trending. As a prominent
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Back Matter Econometric Reviews (IF 1.2) Pub Date : 2022-11-26
Published in Econometric Reviews (Vol. 41, No. 10, 2022)
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Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition Econometric Reviews (IF 1.2) Pub Date : 2022-10-22 Martin Huber, Lukáš Lafférs
Abstract Causal mediation analysis aims at disentangling a treatment effect into an indirect mechanism operating through an intermediate outcome or mediator, as well as the direct effect of the treatment on the outcome of interest. However, the evaluation of direct and indirect effects is frequently complicated by non-ignorable selection into the treatment and/or mediator, even after controlling for
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Nonparametric estimation of additive models with errors-in-variables Econometric Reviews (IF 1.2) Pub Date : 2022-10-10 Hao Dong, Taisuke Otsu, Luke Taylor
Abstract In the estimation of nonparametric additive models, conventional methods, such as backfitting and series approximation, cannot be applied when measurement error is present in a covariate. This paper proposes a two-stage estimator for such models. In the first stage, to adapt to the additive structure, we use a series approximation together with a ridge approach to deal with the ill-posedness
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Finite sample inference in multivariate instrumental regressions with an application to Catastrophe bonds* Econometric Reviews (IF 1.2) Pub Date : 2022-09-28 Marie-Claude Beaulieu, Lynda Khalaf, Maral Kichian, Olena Melin
Abstract We propose exact exogeneity tests and weak-instruments-robust tests on factor loadings for a system of regressions with possibly non-Gaussian disturbances. Our methodology is valid in finite samples and accounts for common cross-sectional factors. Analytical invariance results are derived, with companion simulation studies. Finally, a total-effect parameter is introduced that embeds the unobservable
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Testing rank similarity in the local average treatment effects model Econometric Reviews (IF 1.2) Pub Date : 2022-09-12 Ju Hyun Kim, Byoung G. Park
Abstract This paper develops a test for the rank similarity condition of the nonseparable instrumental variable quantile regression model using the local average treatment effect model. When the instrument takes more than two values or multiple binary instruments are available, there exist multiple complier groups for which the marginal distributions of potential outcomes are identified. A testable
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The variances of non-parametric estimates of the cross-sectional distribution of durations Econometric Reviews (IF 1.2) Pub Date : 2022-09-09 Maoshan Tian, Huw Dixon
Abstract This paper focuses on the link between non-parametric survival analysis and three distributions. The delta method is applied to derive the variances of the non-parametric estimators of three distributions: the distribution of durations (DD), the cross-sectional distribution of ages (CSA) and the cross-sectional distribution of (completed) durations (CSD). The non-parametric estimator of the
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Finite-sample results for lasso and stepwise Neyman-orthogonal Poisson estimators Econometric Reviews (IF 1.2) Pub Date : 2022-09-01 David M. Drukker, Di Liu
Abstract High-dimensional models that include many covariates which might potentially affect an outcome are increasingly common. This paper begins by introducing a lasso-based approach and a stepwise-based approach to valid inference for a high-dimensional model. It then discusses several essential extensions to the literature that make the estimators more usable in practice. Finally, it presents Monte
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Two-step series estimation and specification testing of (partially) linear models with generated regressors Econometric Reviews (IF 1.2) Pub Date : 2022-08-02 Yu-Chin Hsu, Jen-Che Liao, Eric S. Lin
Abstract This paper studies three semiparametric models that are useful and frequently encountered in applied econometric work—a linear and two partially linear specifications with generated regressors, i.e., the regressors that are unobserved, but can be nonparametrically estimated from the data. Our framework allows for generated regressors to appear in linear or nonlinear components of partially
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Income and democracy: a semiparametric approach Econometric Reviews (IF 1.2) Pub Date : 2022-07-25 Shunan Zhao, Yiguo Sun, Subal C. Kumbhakar
Abstract We examine heterogeneous nonlinear effects of income on democracy using country-level data from 1960 to 2000. Existing studies mainly focused on a linear relationship or restricted nonlinear ones and find mixed findings about the effects of income on democracy. The strong positive cross-country correlation between income and democracy is often found to disappear after controlling country specific
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Determining the number of factors in constrained factor models via Bayesian information criterion Econometric Reviews (IF 1.2) Pub Date : 2022-07-23 Jingjie Xiang, Gangzheng Guo, Jiaolong Li
Abstract This paper estimates the number of factors in constrained and partially constrained factor models (Tsai and Tsay, 2010 Tsai, H., Tsay, R. (2010). Constrained factor models. Journal of the American Statistical Association 105(492):1593–1605. doi:10.1198/jasa.2010.tm09123[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) based on constrained Bayesian information criterion (CBIC)
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Comprehensively testing linearity hypothesis using the smooth transition autoregressive model Econometric Reviews (IF 1.2) Pub Date : 2022-07-21 Dakyung Seong, Jin Seo Cho, Timo Teräsvirta
Abstract This article examines the null limit distribution of the quasi-likelihood ratio (QLR) statistic for testing linearity condition against the smooth transition autoregressive (STAR) model. We explicitly show that the QLR test statistic weakly converges to a functional of a multivariate Gaussian process under the null of linearity, which is done by resolving the issue of identification problem
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A robust test for serial correlation in panel data models Econometric Reviews (IF 1.2) Pub Date : 2022-07-15 Bin Chen
Abstract We consider a new nonparametric test for serial correlation of unknown form in the estimated residuals of a panel regression model, where individual and time effects can be fixed or random, and the panel data can be balanced or unbalanced. Our test is robust against potential weak error cross-sectional dependence and error serial dependence in higher-order moments. This is in contrast to existing
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Rotation group bias and the persistence of misclassification errors in the Current Population Surveys Econometric Reviews (IF 1.2) Pub Date : 2022-07-12 Shuaizhang Feng, Yingyao Hu, Jiandong Sun
Abstract We develop a general misclassification model to explain the so-called “Rotation Group Bias (RGB)” problem in the Current Population Surveys, where different rotation groups report different labor force statistics. The key insight is that responses to repeated questions in surveys can depend not only on unobserved true values, but also on previous responses to the same questions. Our method
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Testing for time-varying factor loadings in high-dimensional factor models Econometric Reviews (IF 1.2) Pub Date : 2022-05-30 Wen Xu
Abstract This paper proposes a test for structural changes in factor loadings in high-dimensional factor models under weak serial and cross-sectional dependence. The test is an aggregate statistic in the form of the maximum of the variable-specific statistics whose asymptotic null distribution and local power property are studied. Two approaches including extreme value theory and Bonferroni correction
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Estimation of a partially linear seemingly unrelated regressions model: application to a translog cost system Econometric Reviews (IF 1.2) Pub Date : 2022-05-30 Xin Geng, Kai Sun
Abstract This article studies a partially linear seemingly unrelated regressions (SUR) model to estimate a translog cost system that consists of a partially linear translog cost function and input share equations. The parametric component is estimated via a simple two-step feasible SUR estimation procedure. We show that the resulting estimator achieves root-n convergence and is asymptotically normal