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Best linear and quadratic moments for spatial econometric models with an application to spatial interdependence patterns of employment growth in US counties Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-16 Fei Jin, Lung‐fei Lee, Kai Yang
SummaryWe provide a novel analytic procedure to construct best linear and quadratic moments of the generalized method of moments estimation for a large class of cross‐sectional network and spatial econometric models. These moments generate an estimator that is asymptotically more efficient than the quasi‐maximum likelihood estimator when the disturbances follow a non‐normal and unknown distribution
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Statistical identification in panel structural vector autoregressive models based on independence criteria Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-13 Helmut Herwartz, Shu Wang
SummaryThis paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross‐sectional correlation and heterogeneity through simulation experiments. In an empirical application on monetary policy transmission in the Euro area, we find that
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Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-11 Frank C. Z. Wu
SummaryThis paper replicates the results of the stochastic volatility–Dirichlet process mixture (SV‐DPM) models proposed in Jensen and Maheu (2010) in both a narrow and a wide sense. By using a normal‐Wishart prior and the collapsed Gibbs sampling method, our algorithm can be applied for more general settings, and it is more efficient for sampling the Dirichlet process mixture. For the stochastic volatility
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-07
No abstract is available for this article.
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US fiscal policy shocks: Proxy‐SVAR overidentification via GMM Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-06 Allan W. Gregory, James McNeil, Gregor W. Smith
SummaryUsing external instruments, one can recover the effects of individual shocks without fully identifying a vector autoregression (VAR). We show that fully or almost fully instrumenting a VAR—that is, using an instrument for each shock—allows one to overidentify the model by incorporating the condition that the structural shocks are uncorrelated, via the generalized method of moments (GMM). We
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Should we trust cross‐sectional multiplier estimates? Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-03-05 Fabio Canova
SummaryI examine the properties of cross‐sectional estimators of multipliers, elasticities, or pass‐throughs when a conventional spatial macroeconomic specification generates the data. A number of important biases plague standard estimates; the most relevant one occurs when the units display heterogeneous dynamics. Methods that work well in this situation are suggested. An experimental setting shows
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Peer desirability and academic achievement Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-26 Adrian Mehic
Using the random assignment of university engineering students to peer groups during introductory freshmen weeks, this paper studies how a student's parental income and facial attractiveness affect the grade outcomes of peers. The results show that exposure to highly desirable peers with respect to socioeconomic background and beauty improves grades. The results operate chiefly through a direct spillover
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Empirical evidence on the Euler equation for investment in the US Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-27 Guido Ascari, Qazi Haque, Leandro M. Magnusson, Sophocles Mavroeidis
SummaryIs the typical specification of the Euler equation for investment employed in dynamic stochastic general equilibrium (DSGE) models consistent with aggregate macro data? The answer is yes using state‐of‐the‐art econometric methods that are robust to weak instruments and exploit information in possible structural changes. Unfortunately, however, there is very little information about the values
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How does the dramatic rise of nonresponse in the Current Population Survey impact labor market indicators? Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-26 Robert Bernhardt, David Munro, Erin L. Wolcott
SummaryWithin a decade, the share of households refusing to participate in the Current Population Survey (CPS) tripled. We show households that refuse 1 month but respond in an adjacent month account for an important part of the rise. Leveraging the labor force status of survey participants in the months surrounding their nonresponse, we find that rising refusals suppressed the measured labor force
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Advance layoff notices and aggregate job loss Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-15 Pawel M. Krolikowski, Kurt G. Lunsford
We collect data from Worker Adjustment and Retraining Notification (WARN) Act notices and establish their usefulness as an indicator of aggregate job loss. The number of workers affected by WARN notices (“WARN layoffs”) leads state-level initial unemployment insurance claims and unemployment rate (UR) and private employment changes. WARN layoffs comove with aggregate layoffs from Mass Layoff Statistics
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A high‐dimensional multinomial logit model Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-19 Didier Nibbering
SummaryThe number of parameters in a standard multinomial logit model increases linearly with the number of choice alternatives and number of explanatory variables. Because many modern applications involve large choice sets with categorical explanatory variables, which enter the model as large sets of binary dummies, the number of parameters in a multinomial logit model is often large. This paper proposes
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Identifying factors via automatic debiased machine learning Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-13 Esfandiar Maasoumi, Jianqiu Wang, Zhuo Wang, Ke Wu
Identifying risk factors that have significant explanatory power for the cross-sectional asset returns is fundamental in asset pricing. We adopt a novel automatic debiased machine learning (ADML) method proposed by Chernozhukov, Newey, and Singh (2022) to robustly estimate partial pricing effect of a certain factor controlling for a large number of confounding factors under a nonlinear stochastic discount
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Statistically identified structural VAR model with potentially skewed and fat-tailed errors Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-13 Jetro Anttonen, Markku Lanne, Jani Luoto
We introduce a structural vector autoregressive model in which the mutually independent errors follow skewed generalized t-distributions, whose flexibility compared with commonly considered Student's t-distributions diminishes the risk of misspecification and strengthens identification. Because of statistical identification due to non-Gaussianity, the plausibility of economic identifying restrictions
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-02-08
No abstract is available for this article.
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The macroeconomy as a random forest Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-17 Philippe Goulet Coulombe
I develop the macroeconomic random forest (MRF), an algorithm adapting the canonical machine learning (ML) tool, to flexibly model evolving parameters in a linear macro equation. Its main output, generalized time-varying parameters (GTVPs), is a versatile device nesting many popular nonlinearities (threshold/switching, smooth transition, and structural breaks/change) and allowing for sophisticated
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Addressing sample selection bias for machine learning methods Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-17 Dylan Brewer, Alyssa Carlson
We study approaches for adjusting machine learning methods when the training sample differs from the prediction sample on unobserved dimensions. The machine learning literature predominately assumes selection only on observed dimensions. Common approaches are to weight or include variables that influence selection as solutions to selection on observables. Simulation results show that selection on unobservables
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Mandatory seatbelt laws and traffic fatalities: A reassessment Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-16 D. Mark Anderson, Yang Liang, Joseph J. Sabia
Using data from the Fatality Analysis Reporting System for the period 1983–1997, Cohen and Einav (Review of Economics and Statistics 2003; 85[4]: 828–843) found that mandatory seatbelt laws were associated with a 4–6% reduction in traffic fatalities among motor vehicle occupants. After successfully replicating their two-way fixed effects estimates, we (1) add 22 years of data (1998–2019) to capture
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A maximum likelihood bunching estimator of the elasticity of taxable income Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-18 Thomas Aronsson, Katharina Jenderny, Gauthier Lanot
This paper develops a maximum likelihood (ML) bunching estimator of the elasticity of taxable income (ETI). Our structural approach provides a natural framework to simultaneously account for unobserved preference heterogeneity and optimization errors and for measuring their relative importance. We characterize the conditions under which the parameters of the model are identified and show that the ML
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Did marginal propensities to consume change with the housing boom and bust? Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-14 Yunho Cho, James Morley, Aarti Singh
We extend a widely used semi-structural model to identify and estimate dynamic consumption elasticities with respect to transitory income shocks. Applying our model to household survey data, we find a structural break in marginal propensities to consume following the end of the housing market boom, with the average across households increasing significantly. There is important heterogeneity by different
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Forecasting GDP in Europe with textual data Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-13 Luca Barbaglia, Sergio Consoli, Sebastiano Manzan
We evaluate the informational content of news-based sentiment indicators for forecasting gross domestic product (GDP) and other macroeconomic variables of the five major European economies. Our dataset includes over 27 million articles for 26 major newspapers in five different languages. The evidence indicates that these sentiment indicators are significant predictors to forecast macroeconomic variables
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Disease and development—The predicted mortality instrument revisited Journal of Applied Econometrics (IF 2.46) Pub Date : 2024-01-12 David Kreitmeir, Thomas Überfuhr
This paper revisits Acemoglu-Johnson the predicted mortality instrument. Drawing on a unique historical data set of disease-specific mortality rates, we reconstruct several versions of the instrument that differ in terms of data usage and instrument relevance. Our findings confirm its predictive power on life expectancy. The replication analysis reveals a significant positive second-stage effect of
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Partial identification and inference in duration models with endogenous censoring Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-28 Shosei Sakaguchi
This paper studies identification and inference in transformation models with endogenous censoring. Many kinds of duration models, such as the accelerated failure time model, proportional hazard model, and mixed proportional hazard model, can be viewed as transformation models. We allow the censoring of a duration outcome to be arbitrarily correlated with observed covariates and unobserved heterogeneity
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Does paid parental leave affect children's schooling outcomes? Replicating Danzer and Lavy (2018) Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-27 Claudia Troccoli
Danzer and Lavy (2018) study how the duration of paid parental leave affects children's educational performance using data from PISA. An extension of the maximum duration from 12 to 24 months in Austria had no statistically significant effect on average, but the authors highlight the existence of large and statistically significant heterogenous effects that vary in sign depending on the education of
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Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-26 Jan Prüser, Florian Huber
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
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Panel data nowcasting: The case of price–earnings ratios Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-26 Andrii Babii, Ryan T. Ball, Eric Ghysels, Jonas Striaukas
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
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Revisiting the analysis of matched-pair and stratified experiments in the presence of attrition Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-20 Yuehao Bai, Meng Hsuan Hsieh, Jizhou Liu, Max Tabord-Meehan
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
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Heterogeneity and dynamics in network models Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-14 Enzo D'Innocenzo, André Lucas, Anne Opschoor, Xingmin Zhang
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
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Sample selection in linear panel data models with heterogeneous coefficients Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-14 Alyssa Carlson, Riju Joshi
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
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-10
No abstract is available for this article.
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Identifying oil price shocks with global, developed, and emerging latent real economy activity factors Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-12-07 Antoine A. Djogbenou
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
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Partial identification and inference for conditional distributions of treatment effects Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-11-23 Sungwon Lee
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
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Outlier robust inference in the instrumental variable model with applications to causal effects Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-30 Jens Klooster, Mikhail Zhelonkin
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
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Forecasting and stress testing with quantile vector autoregression Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-26 Sulkhan Chavleishvili, Simone Manganelli
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
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Risk, ambiguity, and misspecification: Decision theory, robust control, and statistics Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-23 Lars Peter Hansen, Thomas J. Sargent
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
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Penalized sieve estimation of zero-inefficiency stochastic frontiers Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-23 Jun Cai, William C. Horrace, Christopher F. Parmeter
Stochastic frontier models for cross-sectional data typically assume that the one-sided distribution of firm-level inefficiency is continuous. However, it may be reasonable to hypothesize that inefficiency is continuous except for a discrete mass at zero capturing fully efficient firms (zero-inefficiency). We propose a sieve-type density estimator for such a mixture distribution in a nonparametric
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Sectoral slowdowns in the United Kingdom: Evidence from transmission probabilities and economic linkages Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-17 Eva F. Janssens, Robin L. Lumsdaine
This paper studies spillovers across macroeconomic sectors in the United Kingdom, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of economic deterioration to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of spillovers between them. The combination
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The efficacy of ability proxies for estimating the returns to schooling: A factor model-based evaluation Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-16 Mohitosh Kejriwal, Xiaoxiao Li, Linh Nguyen, Evan Totty
A common approach to addressing ability bias is to augment the earnings-schooling regression with proxies for cognitive and non-cognitive skills. We evaluate this approach using a factor model framework, which allows consistent estimation of the returns to schooling without relying on proxies. The factor model estimators may be viewed as implicitly estimating proxy measurement error and/or accounting
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-10-10
No abstract is available for this article.
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Reassessing growth vulnerability Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-09-25 Dooyeon Cho, Seunghwa Rho
This paper replicates the results of Adrian et al. (American Economic Review, 2019) that GDP growth volatility is mainly driven by the lower quantiles of the distribution which is predicted by the financial condition. It extends their study by estimating the model with the IVX-QR estimator of Lee (Journal of Econometrics, 2016) and double weighted estimator of Cai et al. (Journal of Econometrics, 2022)
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Narrow and wide replication of Chalfin and McCrary (REStat, 2018) Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-09-15 Federico Crudu, Advait Moharir
We undertake a narrow and wide replication of "Are US Cities Underpoliced? Theory and Evidence" by Chalfin and McCrary. Using data from medium to large cities in the United States from 1960 to 2010, the authors estimate the effect of police on crime. To correct for the presence of measurement error, they propose to combine the information from two proxies of the police variable within the generalized
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Recent changes in the nature of the distribution dynamics of the US county incomes Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-09-13 Seonyoung Park, Donggyun Shin
We study the evolution of the cross-sectional distributions of county-level per capita income in the United States from 1970 to 2017. We confirm previous findings of convergence in pre-transfer income during the 1970s and 1980s but present new evidence of rising inequality since the early 1990s, which is characterized by bipolarization. Cross-county differences in education and industry composition
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The Federal Reserve's output gap: The unreliability of real-time reliability tests Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-08-24 Josefine Quast, Maik H. Wolters
Output gap revisions can be large even after many years. Real-time reliability tests might therefore be sensitive to the choice of the final output gap vintage that the real-time estimates are compared to. This is the case for the Federal Reserve's output gap. When accounting for revisions in response to the global financial crisis in the final output gap, the improvement in real-time reliability since
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Was Harold Zurcher myopic after all? Replicating Rust's engine replacement estimates Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-08-21 Christopher Ferrall
Rust (1987) studies the dynamic decision making under uncertainty made by Harold Zurcher to replace bus engines. In the decades since, the model has been applied, extended, and used as an example multiple times. This paper resolves some discrepancies in how data were transformed in the original and subsequent archives. Using a package that standardizes computation of estimated dynamic programming,
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Featured Cover Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-08-03 James G. MacKinnon, Morten Ørregaard Nielsen, Matthew D. Webb
The cover image is based on the Research Article Fast and reliable jackknife and bootstrap methods for cluster-robust inference by James G. MacKinnon et al., https://doi.org/10.1002/jae.2969.
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-08-03
No abstract is available for this article.
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Heterogeneous responses to corporate marginal tax rates: Evidence from small and large firms Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-07-31 Ruhollah Eskandari, Morteza Zamanian
Do small and large firms respond differently to tax cuts? Using new narrative measures of the exogenous variation in corporate marginal tax rates and a unique dataset of US manufacturing firms, we find that the investment of large firms is more sensitive to a marginal tax cut than that of small firms. Furthermore, we show that small firms finance their new investments almost entirely through debt,
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Monetary policy and exchange rate anomalies in set-identified SVARs: Revisited Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-07-25 Sebastian K. Rüth, Wouter Van der Veken
Set-identified vector autoregressions typically document violations of uncovered interest rate parity (forward discount puzzle) and gradual appreciation–depreciation cycles of exchange rates (delayed overshooting puzzle) following contractionary monetary policy shocks. We revisit both anomalies in a framework similar to Kim et al. (2017, JPE). We complement their identifying restrictions on how monetary
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Employment reconciliation and nowcasting Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-07-13 Eiji Goto, Jan P.A.M. Jacobs, Tara M. Sinclair, Simon van Norden
We construct a latent employment estimate for the United States, which both reconciles the information from separate payroll and household surveys and incorporates the preliminary data revision process of the payroll data. We find that our reconciled latent employment series looks somewhat different than the initial release of payroll employment and is closer to the fully revised data that is benchmarked
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Approximating grouped fixed effects estimation via fuzzy clustering regression Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-07-09 Daniel J. Lewis, Davide Melcangi, Laura Pilossoph, Aidan Toner-Rodgers
We propose a new, computationally efficient way to approximate the “grouped fixed effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the clustering exponent m $$ m $$ approaches 1, the fuzzy clustering objective converges to the GFE objective, which we recast
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Identifying exchange rate effects and spillovers of US monetary policy shocks in the presence of time-varying instrument relevance Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-07-09 Wenting Liao, Jun Ma, Chengsi Zhang
We propose a novel econometric approach to estimating time-varying policy effects using external instruments in the presence of time-varying instrument relevance in a factor-augmented VAR model with data on the United States, Canada, Germany, Japan, and the United Kingdom. We find that US monetary policy shocks are an important driver of the exchange rate movements, with no delayed overshooting. We
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A direct approach to Kilian–Lewis style counterfactual analysis in vector autoregression models Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-06-27 Shiu-Sheng Chen
This paper proposes a direct approach to Kilian–Lewis style counterfactual analysis in structural vector autoregression models. The proposed approach is easy to implement, and the procedure of counterfactual construction is more transparent than the indirect approach. Practitioners conducting Kilian–Lewis style counterfactual analysis should find the proposed approach novel and useful.
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Short T dynamic panel data models with individual, time and interactive effects Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-06-21 Kazuhiko Hayakawa, M. Hashem Pesaran, L. Vanessa Smith
This paper proposes a transformed quasi-maximum likelihood (TQML) estimator for short T $$ T $$ dynamic fixed effects panel data models allowing for interactive effects through a multifactor error structure. The proposed estimator is robust to the heterogeneity of the initial values and common unobserved effects, while at the same time allowing for standard fixed and time effects. It is applicable
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Correction to “Exogenous uncertainty and the identification of structural vector autoregressions with external instruments” Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-06-16
This correction fixes the following errors in the paper: (i) the necessary identification order condition in Proposition 1.b; (ii) one statement about the asymptotic distribution of the quantity ◂⋅▸◂◽˙▸T1/2(◂◽.▸ζ^T−ζ0),$$ {T}^{1/2}\left({\hat{\zeta}}_T-{\zeta}_0\right), $$ where ◂◽.▸ζ^T$$ {\hat{\zeta}}_T $$ is the estimator of a nonlinear transformation of the reduced form parameters that
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Issue Information Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-06-02
No abstract is available for this article.
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Multiple testing with covariate adjustment in experimental economics Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-26 John A. List, Azeem M. Shaikh, Atom Vayalinkal
This paper provides a framework for testing multiple null hypotheses simultaneously using experimental data in which simple random sampling is used to assign treatment status to units. Using general results from the multiple testing literature, we develop under weak assumptions a procedure that (i) asymptotically controls the familywise error rate—the probability of one or more false rejections—and
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Nowcasting from cross-sectionally dependent panels Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-23 Jack Fosten, Shaoni Nandi
This paper builds a mixed-frequency panel data model for nowcasting economic variables across many countries. The model extends the mixed-frequency panel vector autoregression (MF-PVAR) to allow for heterogeneous coefficients and a multifactor error structure to model cross-sectional dependence. We propose a modified common correlated effects (CCE) estimation technique which performs well in simulations
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Oil prices in the real economy Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-21 Haicheng Shu, Peter Spencer
This paper presents a macro-finance model of the US economy and the spot and futures markets for oil. The performance of the model is greatly enhanced by using the Kalman filter to model latent variables representing the inflation asymptote, the real price of oil and the slope of the futures curve. We find that these are dominated by innovations in observed futures prices, reflecting the importance
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Exchange rates and macroeconomic fundamentals: Evidence of instabilities from time-varying factor loadings Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-12 Eric Hillebrand, Jakob Guldbæk Mikkelsen, Lars Spreng, Giovanni Urga
We examine the relationship between exchange rates and macroeconomic fundamentals using a two-step maximum likelihood estimator through which we compute time-varying factor loadings. Factors are obtained as principal components, extracted from vintage macro-datasets that combine FRED-MD and OECD databases. Using 14 currencies over 1990–2021, we show that the loadings on the factors vary considerably
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US weekly economic index: Replication and extension Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-10 Philipp Wegmüller, Christian Glocker
We revisit the US weekly economic index (WEI) put forth by Lewis, Mertens, Stock and Trivedi (2021). In a narrow sense, we replicate their main results with data gathered from its original sources. In a wide sense, we apply the methodology established in Wegmüller, Glocker and Guggia (2023) to adjust the weekly input series for seasonal patterns, calendar day effects, and excess volatility. In a long
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The demand for money at the zero interest rate bound Journal of Applied Econometrics (IF 2.46) Pub Date : 2023-05-01 Tsutomu Watanabe, Tomoyoshi Yabu
This paper undertakes both a narrow and wide replication of the estimation of a money demand function conducted by Ireland (American Economic Review, 2009). Using US data from 1980 to 2013, we show that the substantial increase in the money-income ratio during the period of near-zero interest rates is captured well by the log–log specification but not by the semi-log specification, contrary to the