States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India
This paper takes a fresh look at growth convergence in India, combining insights from macroeconomics and urban economics. It departs from the existing literature in three ways. First, the paper assesses growth patterns across districts and across p...
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okr-10986-309822021-06-08T14:42:45Z States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India Li, Yue Rama, Martin Zhao, Qinghua GROWTH DRIVERS CITY DEVELOPMENT STRATEGY CONVERGENCE BAYESIAN MODEL URBANIZATION LIVING STANDARDS LOCAL ECONOMIC DEVELOPMENT MARKET ACCESS ELECTRIFICATION TRANSPORT INFRASTRUCTURE LOCAL GOVERNANCE This paper takes a fresh look at growth convergence in India, combining insights from macroeconomics and urban economics. It departs from the existing literature in three ways. First, the paper assesses growth patterns across districts and across places below the district level instead of taking the state as the unit of analysis. Second, it relies on household expenditures per capita, instead of gross domestic product per capita, to measure living standards. And third, it uses a Bayesian model averaging approach to identify the key drivers of local growth, instead of the classical econometric approach. The paper finds absolute convergence in living standards across districts and places below the district level, with locations in the gray area between rural and urban growing fastest. In assessing conditional convergence, it finds that geography is a strong predictor of local growth, but population density is not. Market access, electrification and transport infrastructure matter, but irrigation and housing investments do not. The quality of state-level governance has a significant impact on local growth, but variations in city governance are only mildly relevant. The share of medium and large firms plays a role, but the sectoral structure of economic activity does not. And the coverage of primary education is an important predictor of subsequent growth, but not that of other levels of education. Strong convergence at the local level can be reconciled with lack of convergence at the state level if low-income states fail to generate enough locations with the "right" characteristics. 2018-12-11T18:06:43Z 2018-12-11T18:06:43Z 2018-12 Working Paper http://documents.worldbank.org/curated/en/862901543851042872/States-Diverge-Cities-Converge-Drivers-of-Local-Growth-Catch-up-in-India http://hdl.handle.net/10986/30982 English Policy Research Working Paper;No. 8660 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research South Asia India |
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Digital Repository |
institution_category |
Foreign Institution |
institution |
Digital Repositories |
building |
World Bank Open Knowledge Repository |
collection |
World Bank |
language |
English |
topic |
GROWTH DRIVERS CITY DEVELOPMENT STRATEGY CONVERGENCE BAYESIAN MODEL URBANIZATION LIVING STANDARDS LOCAL ECONOMIC DEVELOPMENT MARKET ACCESS ELECTRIFICATION TRANSPORT INFRASTRUCTURE LOCAL GOVERNANCE |
spellingShingle |
GROWTH DRIVERS CITY DEVELOPMENT STRATEGY CONVERGENCE BAYESIAN MODEL URBANIZATION LIVING STANDARDS LOCAL ECONOMIC DEVELOPMENT MARKET ACCESS ELECTRIFICATION TRANSPORT INFRASTRUCTURE LOCAL GOVERNANCE Li, Yue Rama, Martin Zhao, Qinghua States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
geographic_facet |
South Asia India |
relation |
Policy Research Working Paper;No. 8660 |
description |
This paper takes a fresh look at growth
convergence in India, combining insights from macroeconomics
and urban economics. It departs from the existing literature
in three ways. First, the paper assesses growth patterns
across districts and across places below the district level
instead of taking the state as the unit of analysis. Second,
it relies on household expenditures per capita, instead of
gross domestic product per capita, to measure living
standards. And third, it uses a Bayesian model averaging
approach to identify the key drivers of local growth,
instead of the classical econometric approach. The paper
finds absolute convergence in living standards across
districts and places below the district level, with
locations in the gray area between rural and urban growing
fastest. In assessing conditional convergence, it finds that
geography is a strong predictor of local growth, but
population density is not. Market access, electrification
and transport infrastructure matter, but irrigation and
housing investments do not. The quality of state-level
governance has a significant impact on local growth, but
variations in city governance are only mildly relevant. The
share of medium and large firms plays a role, but the
sectoral structure of economic activity does not. And the
coverage of primary education is an important predictor of
subsequent growth, but not that of other levels of
education. Strong convergence at the local level can be
reconciled with lack of convergence at the state level if
low-income states fail to generate enough locations with the
"right" characteristics. |
format |
Working Paper |
author |
Li, Yue Rama, Martin Zhao, Qinghua |
author_facet |
Li, Yue Rama, Martin Zhao, Qinghua |
author_sort |
Li, Yue |
title |
States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
title_short |
States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
title_full |
States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
title_fullStr |
States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
title_full_unstemmed |
States Diverge, Cities Converge : Drivers of Local Growth Catch-up in India |
title_sort |
states diverge, cities converge : drivers of local growth catch-up in india |
publisher |
World Bank, Washington, DC |
publishDate |
2018 |
url |
http://documents.worldbank.org/curated/en/862901543851042872/States-Diverge-Cities-Converge-Drivers-of-Local-Growth-Catch-up-in-India http://hdl.handle.net/10986/30982 |
_version_ |
1764473320906948608 |