印度高增长时期结构变化与经济增长的动态模式:面板数据分析

M. R. Singariya
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引用次数: 1

摘要

本文利用中央统计局收集的2004-05年至2013-14年期间印度32个邦和自治区的面板数据,以2004-05年的恒定价格为基础,强调了结构变化对经济增长的影响。我们在增强型切尼-西奎因模型中检验了这些关系,并检验了高收入州、EAG(授权行动组)州和人口密度高的州是否产生了结构性影响,以及在如此高增长时期,经济采用了哪种类型的结构性趋势。随机效应模型的结果表明,制造业和工业部门(采矿业、制造业和建筑业)份额的增加对经济增长(收入系数)有显著的正影响,而工业部门的格局对人口密度(规模系数)有显著的正影响。人口密度对制造业取向的影响不显著,但对制造业取向的影响为正。这些关系表明,人口最密集的国家更容易实现规模经济、资源禀赋和国内需求规模,因此人口密度在工业和制造业发展模式中起着重要作用。时间趋势与产业取向呈显著负相关,高收入州与服务业呈显著正相关,与农业和制造业呈显著负相关。
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Dynamic Patterns of Structural Change and Economic Growth during the High Growth Regime in India: A Panel Data Analysis
Using panel data collected from the CSO for thirty two states and UTs of India for the recent period of 2004-05 to 2013-14 at the constant 2004-05 prices, the present paper highlights the effect of structural change on economic growth. We examine these relationships in an augmented Chenery-Syrquin Model, and test whether the high income states, EAG (Empowered Action Group) States and high densely states have had any structural impact and what type of structural trends have been adopted by the economy in such a high growth period. Results of random effect model show that any increases in the shares of manufacturing sector and industrial sectors (mining and Quarrying, manufacturing and construction) have significant positive effect on economic growth (Income Coefficient), while the patterns of industrial sector has significant positive effects on population density (Size Coefficient). However, the coefficient of population density is insignificant yet positive for manufacturing orientation. These relationships suggest that most densely populated states can achieve economies of scale, resource endowments and scale of domestic demand easily and hence population density plays an important role in the patterns of industrial and manufacturing development. The time trend seems to have significant negative association with industrial orientation and dummy for high income states has significant positive association with service sector and significant negative association with agriculture and manufacturing sectors.
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