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Inattention and the impact of monetary policy (replication data)
Replication material for “Inattention and the impact of monetary policy” by Zidong An, Salem Abo-Zaid and Xuguang Simon Sheng, published in Journal of Applied Econometrics. -
Global Financial Uncertainty (replication data)
Giovanni Caggiano and Efrem Castelnuovo's "Global Financial Uncertainty" dataset. It contains: i) the monthly volatility data used to estimate our global, region, and... -
Testing for multiple level shifts with an integrated or stationary noise comp...
We provide the MATLAB code and datasets to replicate the computation that are carried out in the empirical section of the paper -
Does Proactive Policing Really Increase Major Crime? A Replication Study of S...
In December 2014 and January 2015, police officers in New York City engaged in an organized slowdown of police work to protest the murder of two police officers who were... -
Inference in Difference-in-Differences: How Much Should we Trust in Independe...
Replication material for 'Inference in Difference-in-Differences: How Much Should we Trust in Independent Clusters?' by Bruno Ferman, published in Journal of Applied Econometrics. -
Hours Worked and the U.S. Distribution of Real Annual Earnings 1976--2019 (re...
This dataset has no description
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Real-time Macroeconomic Projection Using Narrative Central Bank Communication...
This dataset has no description
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Should We Trust Cross Sectional Multiplier Estimates (replication data)
This dataset has no description
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New Evidence on the Importance of Instruction Time for Student Achievement on...
This dataset has no description
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Equity‐premium prediction: Attention is all you need (replication data)
Predictions of stock returns are greatly improved relative to low-dimensional forecasting regressions when the forecasts are based on the estimated factor of large data sets,... -
Long‐run predictability tests are even worse than you thought (replication data)
We derive asymptotic results for the long-horizon ordinary least squares (OLS) estimator and corresponding -statistic for stationary autoregressive predictors. The... -
Forecasting low‐frequency macroeconomic events with high‐frequency data (repl...
High-frequency financial and economic indicators are usually time-aggregated before computing forecasts of macroeconomic events, such as recessions. We propose a mixed-frequency... -
Raiders of the Lost High‐Frequency Forecasts: New Data and Evidence on the Ef...
We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of... -
Reevaluating the evidence on seasonality in housing market match quality: Rep...
I revisit Ngai and Tenreyro (2014)'s empirical analysis of seasonal match quality in American Housing Survey (AHS) data. Using 1999 data only, Ngai and Tenreyro show that homes... -
Regression with an imputed dependent variable (replication data)
Researchers are often interested in the relationship between two variables, with no single data set containing both. A common strategy is to use proxies for the dependent... -
Reassessing the dependence between economic growth and financial conditions s...
Adrian, Boyarchenko and Giannone ((2019), ABG) adapt quantile regression (QR) methods to examine the relationship between US economic growth and financial conditions. We confirm... -
Normal but skewed? (replication data)
We propose a multivariate normality test against skew normal distributions using higher-order log-likelihood derivatives, which is asymptotically equivalent to the likelihood... -
The role of observed and unobserved heterogeneity in the duration of unemploy...
This paper studies the degree to which observable and unobservable worker characteristics account for the variation in the aggregate duration of unemployment. I model the... -
Covariate distribution balance via propensity scores (replication data)
This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups. Heuristically, our proposed... -
Matching theory and evidence on Covid‐19 using a stochastic network SIR model...
This paper develops an individual-based stochastic network SIR model for the empirical analysis of the Covid-19 pandemic. It derives moment conditions for the number of infected...
