Estimation and Inference for Actual and Counterfactual Growth Incidence Curves
Different episodes of economic growth display widely varying distributional characteristics, both across countries and over time. Growth is sometimes accompanied by rising and sometimes by falling inequality. Applied economists have come to rely on the Growth Incidence Curve, which gives the quantile-specific rate of income growth over a certain period, to describe and analyze the incidence of economic growth. This paper discusses the identification conditions, and develops estimation and inference procedures for both actual and counterfactual growth incidence curves, based on general functions of the quantile potential outcome process over the space of quantiles. The paper establishes the limiting 0 distribution of the test statistics of interest for those general functions, and proposes resampling methods to implement inference in practice. The proposed methods are illustrated by a comparison of the growth processes in the United States and Brazil during 1995-2007. Although growth in the average real wage was disappointing in both countries, the distribution of that growth was markedly different. In the United States, wage growth was mediocre for the bottom 80 percent of the sample, but much more rapid for the top 20 percent. In Brazil, conversely, wage growth was rapid below the median, and negative at the top. As a result, inequality rose in the United States and fell markedly in Brazil.
Main Authors: | , , |
---|---|
Format: | Working Paper biblioteca |
Language: | English en_US |
Published: |
World Bank, Washington, DC
2017-01
|
Subjects: | growth incidence curve, potential outcome, inference, quantile process, economic growth, income distribution, inequality, wage growth, |
Online Access: | http://documents.worldbank.org/curated/en/953201483623365115/Estimation-and-inference-for-actual-and-counterfactual-growth-incidence-curves https://hdl.handle.net/10986/25942 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Different episodes of economic growth
display widely varying distributional characteristics, both
across countries and over time. Growth is sometimes
accompanied by rising and sometimes by falling inequality.
Applied economists have come to rely on the Growth Incidence
Curve, which gives the quantile-specific rate of income
growth over a certain period, to describe and analyze the
incidence of economic growth. This paper discusses the
identification conditions, and develops estimation and
inference procedures for both actual and counterfactual
growth incidence curves, based on general functions of the
quantile potential outcome process over the space of
quantiles. The paper establishes the limiting 0 distribution
of the test statistics of interest for those general
functions, and proposes resampling methods to implement
inference in practice. The proposed methods are illustrated
by a comparison of the growth processes in the United States
and Brazil during 1995-2007. Although growth in the average
real wage was disappointing in both countries, the
distribution of that growth was markedly different. In the
United States, wage growth was mediocre for the bottom 80
percent of the sample, but much more rapid for the top 20
percent. In Brazil, conversely, wage growth was rapid below
the median, and negative at the top. As a result, inequality
rose in the United States and fell markedly in Brazil. |
---|