Quantile regression for longitudinal data
TLDR
In this paper, a general approach to estimating quantile regression models for longitudinal data is proposed employing l 1 regularization methods, based on the penalized least squares interpretation of the classical random effects estimator.About:
This article is published in Journal of Multivariate Analysis.The article was published on 2004-10-01 and is currently open access. It has received 1516 citations till now. The article focuses on the topics: Quantile regression & Quantile.read more
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Returns to Capital in Microenterprises: Evidence from a Field Experiment
TL;DR: In this article, the authors used a randomized experiment to measure the return to capital for the average microenterprise in their sample, regardless of whether they apply for credit and found that the average real return to be 5.7 percent a month, substantially higher than the market interest rate.
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A simple approach to quantile regression for panel data
TL;DR: In this article, the authors provide sufficient conditions that point identify a quantile regression model with fixed effects and propose a simple transformation of the data that gets rid of the fixed effects under the assumption that these effects are location shifters.
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Returns to Capital in Microenterprises: Evidence from a Field Experiment
TL;DR: In this paper, the authors used a randomized experiment to measure the return to capital for the average microenterprise in their sample, regardless of whether they apply for credit and found that the average real return to be 5.7 percent a month, substantially higher than the market interest rate.
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Quantiles via Moments
TL;DR: The methods proposed are not meant to replace the well-established quantile regression estimator, but provide an additional tool that can allow the estimation of regression quantiles in settings where otherwise that would be difficult or even impossible.
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The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression
TL;DR: In this paper, the authors investigated the impact of foreign direct investment, economic growth and energy consumption on carbon emissions in five selected member countries in the Association of South East Asian Nations (ASEAN-5), including Indonesia, Malaysia, the Philippines, Singapore and Thailand.
References
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Regression Shrinkage and Selection via the Lasso
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
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Atomic Decomposition by Basis Pursuit
TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
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R: A Language for Data Analysis and Graphics
Ross Ihaka,Robert Gentleman +1 more
TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
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