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Working Paper
A Robust Method for Microforecasting and Estimation of Random Effects
Giacomini, Raffaella; Lee, Sokbae; Sarpietro, Silvia (2023-08-02)
We propose a method for forecasting individual outcomes and estimating random effects in linear panel data models and value-added models when the panel has a short time dimension. The method is robust, trivial to implement and requires minimal assumptions. The idea is to take a weighted average of time series- and pooled forecasts/estimators, with individual weights that are based on time series information. We show the forecast optimality of individual weights, both in terms of minimax-regret and of mean squared forecast error. We then provide feasible weights that ensure good performance ...
Working Paper Series , Paper WP 2023-26

Working Paper
Selecting Primal Innovations in DSGE models
Ferroni, Filippo; León-Ledesma, Miguel A.; Grassi, Stefano (2017-08-01)
DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these non-existing shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select primal shocks and estimate model ...
Working Paper Series , Paper WP-2017-20

Working Paper
Self-employment and health care reform: evidence from Massachusetts
Becker, Thealexa; Tuzemen, Didem (2014-11-25)
We study the e ect of the Massachusetts health care reform on the uninsured rate and the self-employment rate in the state. The reform required all individuals to obtain health insurance, required most employers to o er health insurance to their employees, formed a private marketplace that o ered subsidized health insurance options and ex- panded public insurance. We examine data from the Current Population Survey (CPS)for 1994-2012 and its Annual Social and Economic (ASEC) Supplement for 1996-2013. We show that the reform led to a dramatic reduction in the state's uninsured rate due to ...
Research Working Paper , Paper RWP 14-16

Working Paper
Manufacturing Sentiment: Forecasting Industrial Production with Text Analysis
Cajner, Tomaz; Crane, Leland D.; Kurz, Christopher J.; Morin, Norman J.; Soto, Paul E.; Vrankovich, Betsy (2024-05-03)
This paper examines the link between industrial production and the sentiment expressed in natural language survey responses from U.S. manufacturing firms. We compare several natural language processing (NLP) techniques for classifying sentiment, ranging from dictionary-based methods to modern deep learning methods. Using a manually labeled sample as ground truth, we find that deep learning models partially trained on a human-labeled sample of our data outperform other methods for classifying the sentiment of survey responses. Further, we capitalize on the panel nature of the data to train ...
Finance and Economics Discussion Series , Paper 2024-026

Working Paper
A Local Projections Approach to Difference-in-Differences Event Studies
Jordà, Òscar; Girardi, Daniele; Dube, Arindrajit; Taylor, Alan M. (2023-04-20)
Many of the challenges in the estimation of dynamic heterogeneous treatment effects can be resolved with local projection (LP) estimators of the sort used in applied macroeconometrics. This approach provides a convenient alternative to the more complicated solutions proposed in the recent literature on Difference in-Differences (DiD). The key is to combine LPs with a flexible ‘clean control’ condition to define appropriate sets of treated and control units. Our proposed LP-DiD estimator is clear, simple, easy and fast to compute, and it is transparent and flexible in its handling of ...
Working Paper Series , Paper 2023-12

Working Paper
Approximating Time Varying Structural Models With Time Invariant Structures
Matthes, Christian; Ferroni, Filippo; Canova, Fabio (2015-10-23)
The paper studies how parameter variation affects the decision rules of a DSGE model and structural inference. We provide diagnostics to detect parameter variations and to ascertain whether they are exogenous or endogenous. Identifi cation and inferential distortions when a constant parameter model is incorrectly assumed are examined. Likelihood and VAR-based estimates of the structural dynamics when parameter variations are neglected are compared. Time variations in the financial frictions of Gertler and Karadi's (2010) model are studied.
Working Paper , Paper 15-10

Working Paper
Linear and nonlinear econometric models against machine learning models: realized volatility prediction
Kılıç, Rehim (2025-08-08)
This paper fills an important gap in the volatility forecasting literature by comparing a broad suite of machine learning (ML) methods with both linear and nonlinear econometric models using high-frequency realized volatility (RV) data for the S&P 500. We evaluate ARFIMA, HAR, regime-switching HAR models (THAR, STHAR, MSHAR), and ML methods including Extreme Gradient Boosting, deep feed-forward neural networks, and recurrent networks (BRNN, LSTM, LSTM-A, GRU). Using rolling forecasts from 2006 onward, we find that regime-switching models—particularly THAR and STHAR—consistently outperform ...
Finance and Economics Discussion Series , Paper 2025-061

Working Paper
Social Security and High-Frequency Labor Supply: Evidence from Uber Drivers
Beatty, Timothy K. M.; Weill, Joakim A. (2024-09-20)
We estimate the impact of anticipated transfers on labor supply using confidential driver-level data from Uber. Leveraging the staggered timing of Social Security retirement benefits within each month and a novel identification strategy, we find that the labor supply of older drivers declines by 2% on average in the week around benefit receipt—a precisely estimated but economically small effect. Individual-level analyses reveal that the average effect obscures heterogeneous micro-behavior: while the majority of drivers does not meaningfully adjust labor supply in response to social security ...
Finance and Economics Discussion Series , Paper 2024-079

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