Search Results

Showing results 1 to 4 of approximately 4.

(refine search)
SORT BY: PREVIOUS / NEXT
Author:Brennan, Connor M. 

Working Paper
Measuring Job Loss during the Pandemic Recession in Real Time with Twitter Data

We present an indicator of job loss derived from Twitter data, based on a fine-tuned neural network with transfer learning to classify if a tweet is job-loss related or not. We show that our Twitter-based measure of job loss is well-correlated with and predictive of other measures of unemployment available in the official statistics and with the added benefits of real-time availability and daily frequency. These findings are especially strong for the period of the Pandemic Recession, when our Twitter indicator continues to track job loss well but where other real-time measures like ...
Finance and Economics Discussion Series , Paper 2023-035

Working Paper
Measuring Job Loss during the Pandemic Recession in Real Time with Twitter Data

We present an indicator of job loss derived from Twitter data, based on a fine-tuned neural network with transfer learning to classify if a tweet is job-loss related or not. We show that our Twitter-based measure of job loss is well-correlated with and predictive of other measures of unemployment available in the official statistics and with the added benefits of real-time availability and daily frequency. These findings are especially strong for the period of the Pandemic Recession, when our Twitter indicator continues to track job loss well but where other real-time measures like ...
Finance and Economics Discussion Series , Paper 2023-035

Working Paper
Measuring Job Loss during the Pandemic Recession in Real Time with Twitter Data

We present an indicator of job loss derived from Twitter data, based on a fine-tuned neural network with transfer learning to classify if a tweet is job-loss related or not. We show that our Twitter-based measure of job loss is well-correlated with and predictive of other measures of unemployment available in the official statistics and with the added benefits of real-time availability and daily frequency. These findings are especially strong for the period of the Pandemic Recession, when our Twitter indicator continues to track job loss well but where other real-time measures like ...
Finance and Economics Discussion Series , Paper 2023-035

Working Paper
Monetary Policy Shocks: Data or Methods?

Different series of high-frequency monetary shocks can have a correlation coefficient as low as 0.5 and the same sign in only two-thirds of observations. Both data and methods drive these differences, which are starkest when the federal funds rate is at its effective lower bound. Methods that exploit the differential responsiveness of short- and long-term asset prices can incorporate additional information. After documenting differences in monetary shocks, we explore their consequence for inference. We find that empirical estimates of monetary policy transmission from local projections and ...
Finance and Economics Discussion Series , Paper 2024-011

FILTER BY year

FILTER BY Content Type

FILTER BY Author

FILTER BY Jel Classification

J63 3 items

E31 1 items

E32 1 items

E52 1 items

E58 1 items

PREVIOUS / NEXT