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Quantile Regression with Generated Regressors Econometrics Pub Date : 2021-04-12 Liqiong Chen, Antonio F. Galvao, Suyong Song
This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of the two-step estimator, namely, consistency and asymptotic normality are established. We show that the asymptotic variance-covariance matrix needs
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Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions Econometrics Pub Date : 2021-04-02 Jau-er Chen, Chien-Hsun Huang, Jia-Jyun Tien
In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous study (Chernozhukov et al. 2018) and is thus relatively insensitive to the estimation of the nuisance parameters
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Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables Econometrics Pub Date : 2021-03-17 Souvik Banerjee, Anirban Basu
We provide evidence on the least biased ways to identify causal effects in situations where there are multiple outcomes that all depend on the same endogenous regressor and a reasonable but potentially contaminated instrumental variable that is available. Simulations provide suggestive evidence on the complementarity of instrumental variable (IV) and latent factor methods and how this complementarity
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Integration and Disintegration of EMU Government Bond Markets Econometrics Pub Date : 2021-03-15 Christian Leschinski, Michelle Voges, Philipp Sibbertsen
It is commonly found that the markets for long-term government bonds of Economic and Monetary Union (EMU) countries were integrated prior to the EMU debt crisis. Contrasting this, we show, based on the interrelation between market integration and fractional cointegration, that there were periods of integration and disintegration that coincide with bull and bear market periods in the stock market. An
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New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and The Past? § Econometrics Pub Date : 2021-03-06 Boriss Siliverstovs
We assess the forecasting performance of the nowcasting model developed at the New York FED. We show that the observation regarding a striking difference in the model’s predictive ability across business cycle phases made earlier in the literature also applies here. During expansions, the nowcasting model forecasts at best are at least as good as the historical mean model, whereas during the recessionary
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Goodness-of-Fit Tests for Bivariate Time Series of Counts Econometrics Pub Date : 2021-03-04 Šárka Hudecová, Marie Hušková, Simos G. Meintanis
This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being entirely nonparametric and the second one being semiparametric computed under the corresponding null hypothesis. The asymptotic distribution of the
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Temperature Anomalies, Long Memory, and Aggregation Econometrics Pub Date : 2021-03-03 J. Eduardo Vera-Valdés
Econometric studies for global heating have typically used regional or global temperature averages to study its long memory properties. One typical explanation behind the long memory properties of temperature averages is cross-sectional aggregation. Nonetheless, formal analysis regarding the effect that aggregation has on the long memory dynamics of temperature data has been missing. Thus, this paper
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Hospital Emergency Room Savings via Health Line S24 in Portugal Econometrics Pub Date : 2021-02-20 Paula Simões, Sérgio Gomes, Isabel Natário
Hospital emergency departments are often overused by patients that do not really need urgent care. These admissions are one of the major factors contributing to hospital costs, which should not be allowed to compromise the response and effectiveness of the National Health Services (SNS). The aim of this study is to perform a detailed spatial health econometrics analysis of the non-urgent emergency
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Erratum: Hoover, K.D. 2020. The Discovery of Long-Run Causal Order: A Preliminary Investigation. Econometrics 8: 31 Econometrics Pub Date : 2021-02-18 Kevin D. Hoover
Note: In lieu of an abstract, this is an excerpt from the first page. The author would like to make the following correction to the article by Kevin D [...]
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Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing Econometrics Pub Date : 2021-02-08 Kyungsik Nam
This study proposes a nonlinear cointegrating regression model based on the well-known energy balance climate model. Specifically, I investigate the nonlinear cointegrating regression of the mean of temperature anomaly distributions on total radiative forcing using estimated spatial distributions of temperature anomalies for the Globe, Northern Hemisphere, and Southern Hemisphere. Further, I provide
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Direct and Indirect Effects under Sample Selection and Outcome Attrition Econometrics Pub Date : 2020-12-07 Martin Huber, Anna Solovyeva
This paper extends the evaluation of direct and indirect treatment effects, i.e., mediation analysis, to the case that outcomes are only partially observed due to sample selection or outcome attrition. We assume sequential conditional independence of the treatment and the mediator, i.e., the variable through which the indirect effect operates. We also impose missing at random or instrumental variable
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Regularized Maximum Diversification Investment Strategy Econometrics Pub Date : 2020-12-29 N’Golo Koné
The maximum diversification has been shown in the literature to depend on the vector of asset volatilities and the inverse of the covariance matrix of the asset return covariance matrix. In practice, these two quantities need to be replaced by their sample statistics. The estimation error associated with the use of these sample statistics may be amplified due to (near) singularity of the covariance
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Towards a New Paradigm for Statistical Evidence in the Use of p-Value Econometrics Pub Date : 2020-12-31 Muhammad Ishaq Bhatti, Jae H. Kim
Note: In lieu of an abstract, this is an excerpt from the first page. As the guest editors of this Special Issue, we feel proud and grateful to write the editorial note of this issue, which consists of seven high-quality research papers [...]
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Enhanced Methods of Seasonal Adjustment Econometrics Pub Date : 2021-01-05 D. Stephen G. Pollock
The effect of the conventional model-based methods of seasonal adjustment is to nullify the elements of the data that reside at the seasonal frequencies and to attenuate the elements at the adjacent frequencies. It may be desirable to nullify some of the adjacent elements instead of merely attenuating them. For this purpose, two alternative sets of procedures are presented that have been implemented
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Acknowledgment to Reviewers of Econometrics in 2020 Econometrics Pub Date : 2021-01-21 Econometrics Editorial Office
Note: In lieu of an abstract, this is an excerpt from the first page. Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Econometrics maintains its standards for the high quality of its published papers [...]
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Searching for a Theory That Fits the Data: A Personal Research Odyssey Econometrics Pub Date : 2021-02-01 Katarina Juselius
This survey paper discusses the Cointegrated Vector AutoRegressive (CVAR) methodology and how it has evolved over the past 30 years. It describes major steps in the econometric development, discusses problems to be solved when confronting theory with the data, and, as a solution, proposes a so-called theory-consistent CVAR scenario. A number of early CVAR applications are motivated by the urge to find
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A Parameterization of Models for Unit Root Processes: Structure Theory and Hypothesis Testing Econometrics Pub Date : 2020-11-10 Dietmar Bauer, Lukas Matuschek, Patrick de Matos Ribeiro, Martin Wagner
We develop and discuss a parameterization of vector autoregressive moving average processes with arbitrary unit roots and (co)integration orders. The detailed analysis of the topological properties of the parameterization—based on the state space canonical form of Bauer and Wagner (2012)—is an essential input for establishing statistical and numerical properties of pseudo maximum likelihood estimators
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Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature Econometrics Pub Date : 2020-11-02 Eric Hillebrand, Søren Johansen, Torben Schmith
We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880–2001 and 1880–2013. We
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Reducing the Bias of the Smoothed Log Periodogram Regression for Financial High-Frequency Data Econometrics Pub Date : 2020-10-10 Erhard Reschenhofer, Manveer K. Mangat
For typical sample sizes occurring in economic and financial applications, the squared bias of estimators for the memory parameter is small relative to the variance. Smoothing is therefore a suitable way to improve the performance in terms of the mean squared error. However, in an analysis of financial high-frequency data, where the estimates are obtained separately for each day and then combined by
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On the Asymptotic Distribution of Ridge Regression Estimators Using Training and Test Samples Econometrics Pub Date : 2020-10-01 Nandana Sengupta, Fallaw Sowell
The asymptotic distribution of the linear instrumental variables (IV) estimator with empirically selected ridge regression penalty is characterized. The regularization tuning parameter is selected by splitting the observed data into training and test samples and becomes an estimated parameter that jointly converges with the parameters of interest. The asymptotic distribution is a nonstandard mixture
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Modeling I(2) Processes Using Vector Autoregressions Where the Lag Length Increases with the Sample Size Econometrics Pub Date : 2020-09-17 Yuanyuan Li, Dietmar Bauer
In this paper the theory on the estimation of vector autoregressive (VAR) models for I(2) processes is extended to the case of long VAR approximation of more general processes. Hereby the order of the autoregression is allowed to tend to infinity at a certain rate depending on the sample size. We deal with unrestricted OLS estimators (in the model formulated in levels as well as in vector error correction
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Long-Lasting Economic Effects of Pandemics:Evidence on Growth and Unemployment Econometrics Pub Date : 2020-09-17 C. Vladimir Rodríguez-Caballero, J. Eduardo Vera-Valdés
This paper studies long economic series to assess the long-lasting effects of pandemics. We analyze if periods that cover pandemics have a change in trend and persistence in growth, and in level and persistence in unemployment. We find that there is an upward trend in the persistence level of growth across centuries. In particular, shocks originated by pandemics in recent times seem to have a permanent
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Teaching Graduate (and Undergraduate) Econometrics: Some Sensible Shifts to Improve Efficiency, Effectiveness, and Usefulness Econometrics Pub Date : 2020-09-07 Jeremy Arkes
Building on arguments by Joshua Angrist and Jörn-Steffen Pischke arguments for how the teaching of undergraduate econometrics could become more effective, I propose a redesign of graduate econometrics that would better serve most students and help make the field of economics more relevant. The primary basis for the redesign is that the conventional methods do not adequately prepare students to recognize
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Linear Stochastic Models in Discrete and Continuous Time Econometrics Pub Date : 2020-09-04 D. Stephen G. Pollock
The econometric data to which autoregressive moving-average models are commonly applied are liable to contain elements from a limited range of frequencies. If the data do not cover the full Nyquist frequency range of [0,π] radians, then severe biases can occur in estimating their parameters. The recourse should be to reconstitute the underlying continuous data trajectory and to resample it at an appropriate
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Indirect Inference Estimation of Spatial Autoregressions Econometrics Pub Date : 2020-09-03 Yong Bao, Xiaotian Liu, Lihong Yang
The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the properly recentered OLS estimator and proposes a new estimator that is based on the indirect inference (II) procedure
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Climate Disaster Risks—Empirics and a Multi-Phase Dynamic Model Econometrics Pub Date : 2020-08-18 Stefan Mittnik, Willi Semmler, Alexander Haider
Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback effects on the macroeconomy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the
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Maximum Likelihood Estimation for the Fractional Vasicek Model Econometrics Pub Date : 2020-08-12 Katsuto Tanaka, Weilin Xiao, Jun Yu
This paper estimates the drift parameters in the fractional Vasicek model from a continuous record of observations via maximum likelihood (ML). The asymptotic theory for the ML estimates (MLE) is established in the stationary case, the explosive case, and the boundary case for the entire range of the Hurst parameter, providing a complete treatment of asymptotic analysis. It is shown that changing the
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The Discovery of Long-Run Causal Order: A Preliminary Investigation Econometrics Pub Date : 2020-08-03 Kevin D. Hoover
The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending variables to a set of causally ordered variables that would not themselves display nonstationary behavior
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Dynamic Panel Modeling of Climate Change Econometrics Pub Date : 2020-07-28 Peter C. B. Phillips
We discuss some conceptual and practical issues that arise from the presence of global energy balance effects on station level adjustment mechanisms in dynamic panel regressions with climate data. The paper provides asymptotic analyses, observational data computations, and Monte Carlo simulations to assess the use of various estimation methodologies, including standard dynamic panel regression and
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Cointegration and Structure in Norwegian Wage–Price Dynamics Econometrics Pub Date : 2020-07-27 Marit Gjelsvik, Ragnar Nymoen, Victoria Sparrman
Wage coordination plays an important role in macroeconomic stabilization. Pattern wage bargaining systems have been common in Europe, but in different forms, and with different degrees of success in terms of actual coordination reached. We focus on wage formation in Norway, a small open economy, where it is custom to regard the manufacturing industry as the wage leader. We estimate a model of wage
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Frequency-Domain Evidence for Climate Change Econometrics Pub Date : 2020-07-20 Manveer Kaur Mangat, Erhard Reschenhofer
The goal of this paper is to search for conclusive evidence against the stationarity of the global air surface temperature, which is one of the most important indicators of climate change. For this purpose, possible long-range dependencies are investigated in the frequency-domain. Since conventional tests of hypotheses about the memory parameter, which measures the degree of long-range dependence,
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Confidence Distributions for FIC Scores Econometrics Pub Date : 2020-07-01 Céline Cunen, Nils Lid Hjort
When using the Focused Information Criterion (FIC) for assessing and ranking candidate models with respect to how well they do for a given estimation task, it is customary to produce a so-called FIC plot. This plot has the different point estimates along the y-axis and the root-FIC scores on the x-axis, these being the estimated root-mean-square scores. In this paper we address the estimation uncertainty
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Gini Index Estimation within Pre-Specified Error Bound: Application to Indian Household Survey Data Econometrics Pub Date : 2020-06-18 Francis Bilson Darku, Frank Konietschke, Bhargab Chattopadhyay
The Gini index, a widely used economic