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Occupational Classifications : A Machine Learning Approach

Ikudo, Akina - 2018

, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to …

Persistent link: https://www.econbiz.de/10012480604

Health Inequality and Health Types

Borella, Margherita; Bullano, Francisco; De Nardi, … - National Bureau of Economic Research - 2024

While health affects many economic outcomes, its dynamics are still poorly understood. We use k means clustering, a machine learning technique, and data from the Health and Retirement Study to identify health types during middle and old age. We identify five health types: the vigorous resilient,...

Persistent link: https://www.econbiz.de/10015056123

Group Testing in a Pandemic : The Role of Frequent Testing, Correlated Risk, and Machine Learning

Augenblick, Ned - 2020

with intra-group risk correlation, which is expected in natural test groupings based on proximity. Third, because optimal … groupings depend on uncertain risk and correlation, we show how better estimates from machine learning can drive large …

Persistent link: https://www.econbiz.de/10012481312

Estimating the Covariates of Historical Heights

Trussell, James - 1984

Data on human height can provide an index that may measure more accurately changes in the standard of living than the more conventional real wage index. Height data, like those on real wages, are relatively abundant and extend back to the seventeenth century. In a previous paper, we developed...

Persistent link: https://www.econbiz.de/10012477633

Identification and Estimation of 'Irregular' Correlated Random Coefficient Models

Graham, Bryan S. - 2008

In this paper we study identification and estimation of a correlated random coefficients (CRC) panel data model. The outcome of interest varies linearly with a vector of endogenous regressors. The coefficients on these regressors are heterogenous across units and may covary with them. We...

Persistent link: https://www.econbiz.de/10012464178

A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations

Brandt, Michael W. - 2003

We extend range-based volatility estimation to the multivariate case. In particular, we propose a range-based covariance estimator motivated by a key financial economic consideration, the absence of arbitrage, in addition to statistical considerations. We show that this estimator is highly...

Persistent link: https://www.econbiz.de/10012469034

How Much Should We Trust Differences-in-Differences Estimates?

Bertrand, Marianne - 2002

almost all these papers ignore the bias in the estimated standard errors that serial correlation introduce4s. This is …

Persistent link: https://www.econbiz.de/10012469874

Selection on Observed and Unobserved Variables : Assessing the Effectiveness of Catholic Schools

Altonji, Joseph G. - 2000

We develop estimation methods that use the amount of selection on the observables in a model as a guide to the amount of selection on the unobservables. We show that if the observed variables are a random subset of a large number of factors that influence the endogenous variable and the outcome...

Persistent link: https://www.econbiz.de/10012470912

The Forecasting Ability of Correlations Implied in Foreign Exchange Options

Campa, Jose M. - 1997

This paper evaluates the forecasting accuracy of correlation derived from implied volatilities in dollar-mark, dollar …-yen, and mark-yen options from January 1989 to May 1995. As a forecast of realized correlation between the dollar-mark and … dollar-yen, implied correlation is compared against three alternative forecasts based on time series data: historical …

Persistent link: https://www.econbiz.de/10012472847

Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?

Bali, Turan G. - 2013

We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...

Persistent link: https://www.econbiz.de/10012459202

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