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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... -
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... -
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... -
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...
