Datasets
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Hours Worked and the U.S. Distribution of Real Annual Earnings 1976--2019 (re...
This dataset has no description
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Bayesian Collapsed Gibbs Sampling for a Stochastic Volatility Model with a Di...
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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Deep Distributional Time Series Models and the Probabilistic Forecasting of I...
This dataset has no description
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Identifying and Interpreting the Factors in Factor models via Sparsity: Diffe...
This dataset has no description
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Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty (re...
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,... -
Did earnings mobility change after minimum wage introduction? Evidence from p...
We analyze the evolution of earnings mobility in Germany between 2011 and 2018. We use transition matrices and parametric and semi-nonparametric copula models to assess the... -
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... -
General Bayesian time‐varying parameter vector autoregressions for modeling g...
US yield curve dynamics are subject to time-variation, but there is ambiguity about its precise form. This paper develops a vector autoregressive (VAR) model with time-varying... -
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... -
Bayesian estimation of multivariate panel probits with higher‐order network i...
This paper proposes a Bayesian estimation framework for panel data sets with binary dependent variables where a large number of cross-sectional units are observed over a short... -
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... -
Workplace Heterogeneity and Wage Inequality in Denmark (replication data)
Wage inequality is on the rise in most developed economies, and this phenomenon has fostered a growing body of research on its potential drivers. Using German data over the... -
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... -
Count Roy model with finite mixtures (replication data)
This paper develops the Finite Mixture Roy model for count variables and uses this semiparametric model to analyze the effect of supplemental Medigap private insurance on the... -
Do words hurt more than actions? The impact of trade tensions on financial ma...
We use machine learning techniques to quantify trade tensions between the United States and China. Our measure matches well-known events in the US-China trade dispute and is... -
Instrumental‐variable estimation of exponential‐regression models with two‐wa...
This paper introduces instrumental-variable estimators for exponential-regression models that feature two-way fixed effects. These techniques allow us to develop a... -
Trade openness and growth: A network‐based approach (replication data)
We propose a novel approach to the study of international trade based on a theory of country integration that embodies a broad systemic viewpoint on the relationship between... -
Identification of dynamic latent factor models of skill formation with transl...
In this paper, we highlight an important property of the translog production function for the identification of treatment effects in a model of latent skill formation. We show... -
Do rural banks matter that much? Burgess and Pande (2005) reconsidered (repli...
We replicate Burgess and Pande's (2005) analysis of the effect of India's state-led bank expansion on poverty. The authors instrument rural bank branch expansion by its trend... -
Macroeconomic forecasting in a multi‐country context (replication data)
In this paper, we propose a hierarchical shrinkage approach for multi-country VAR models. In implementation, we consider three different scale mixtures Normals priors and... -
Recurrent conditional heteroskedasticity (replication data)
We propose a new class of financial volatility models, called the REcurrent Conditional Heteroskedastic (RECH) models, to improve both in-sample analysis and out-of-sample... -
ARDL bounds test for cointegration: Replicating the Pesaran et al. (2001) res...
This paper replicates the UK earnings equation using the autoregressive distributed lag (ARDL) modeling approach and the bounds test for cointegration by Pesaran et al. (Journal... -
Extremal connectedness of hedge funds (replication data)
We propose a dynamic measure of extremal connectedness tailored to the short reporting period and unbalanced nature of hedge funds data. Using multivariate extreme value... -
Optimal forecast under structural breaks (replication data)
This paper develops an optimal combined estimator to forecast out-of-sample under structural breaks. When it comes to forecasting, using only the postbreak observations after... -
Oil prices, gasoline prices, and inflation expectations (replication data)
It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1-year inflation expectations. Assessing this view... -
Making text count: Economic forecasting using newspaper text (replication data)
This paper examines several ways to extract timely economic signals from newspaper text and shows that such information can materially improve forecasts of macroeconomic... -
How is machine learning useful for macroeconomic forecasting? (replication data)
We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how. The current forecasting literature has focused on matching specific variables and... -
Robust inference under time‐varying volatility: A real‐time evaluation of pro...
In many forecast evaluation applications, standard tests as well as tests allowing for time-variation in relative forecast ability build on... -
The role of precautionary and speculative demand in the global market for cru...
Contemporary structural models of the global market for crude oil jointly specify precautionary and speculative demand shocks as a composite shock, named a storage demand shock.... -
Generalized band spectrum estimation with an application to the New Keynesian...
This paper proposes a new method for estimating linear dynamic structural models. The proposed generalized band spectrum estimator (GBSE) generalizes band spectrum regression to... -
Nowcasting tail risk to economic activity at a weekly frequency (replication ...
This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information used to produce nowcasts on a weekly basis. We... -
Identifying factor‐augmented vector autoregression models via changes in shoc...
This study proposes a method to identify factor-augmented vector autoregression models without imposing uncorrelatedness or any timing restrictions among observed and unobserved... -
Small world: Narrow, wide, and long replication of Goyal, van der Leij and Mo...
I undertake a narrow, wide, and long replication of Goyal, van der Leij and Moraga-Gonzélez (2006, https://doi.org/10.1086/500990). Using social network analysis, they show that... -
Measuring real activity using a weekly economic index (replication data)
This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus... -
How to estimate a vector autoregression after March 2020 (replication data)
This paper illustrates how to handle a sequence of extreme observations-such as those recorded during the COVID?19 pandemic-when estimating a vector autoregression, which is the... -
A regularization approach to common correlated effects estimation (replicatio...
Cross-section average-augmented panel regressions introduced by Pesaran (2006) have been a popular empirical tool to estimate panel data models with common factors. However, the... -
Revisiting Sweden's comprehensive school reform: Effects on education and ear...
We revisit a Swedish comprehensive school reform first evaluated by Meghir and Palme (2005). This reform increased years of schooling and abolished tracking. We extend the... -
Early‐life famine exposure, hunger recall, and later‐life health (replication...
We use newly collected individual-level hunger recall information from the China Family Panel Survey to estimate the causal effect of undernourishment on later-life health. We... -
The impact of product and labour market reform on growth: Evidence for OECD c...
We examine the impact of labour and product market reforms on economic growth in 25 OECD countries between 1985 and 2013, and tests whether this impact is conditioned by the...
