scholarly journals Heterogeneous Consumption Goods, Sectoral Change, and Economic Growth

Author(s):  
Thomas M. Steger
2015 ◽  
Vol 15 (1) ◽  
pp. 1-42 ◽  
Author(s):  
Jaime Alonso-Carrera ◽  
Jordi Caballé ◽  
Xavier Raurich

AbstractWe analyze the transitional dynamics of an economic model with heterogeneous consumption goods where convergence is driven by two different forces: the typical diminishing returns to capital and the dynamic adjustment in consumption expenditure induced by the variation in relative prices. We show that this second force affects the growth rate if the consumption goods are produced with technologies exhibiting different capital intensities and if the intertemporal elasticity of substitution is not equal to one. Because the aforementioned growth effect of relative prices arises only under heterogeneous consumption goods, the transitional dynamics of this model exhibits striking differences with the growth model with a single consumption good. We also show that these differences in the transitional dynamics can give raise to large discrepancies in the welfare cost of shocks.


2019 ◽  
Vol 15 (4) ◽  
pp. 790-808 ◽  
Author(s):  
Jian Yu ◽  
Xunpeng Shi ◽  
James Laurenceson

Purpose Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to investigate the factors that determine household consumption volatility, using urban household survey (UHS) data over the period 2002–2009 in 18 provinces in China. Design/methodology/approach Both a traditional variance decomposition method and an advanced variance decomposition method are used. Findings The traditional variance decomposition method suggests that heterogeneity of consumption goods is the key to analyze consumption volatility in China. Consumption of transportation makes the highest aggregate contribution and per-unit volatility in consumption volatility, whereas consumption of food makes the second highest aggregate contribution and the lowest per-unit volatility. Further investigation with the advanced variance decomposition method, which allows the authors to capture intertemporal dynamics and cross-household differences simultaneously, finds that the main factor determining the consumption volatility in China is intertemporal dynamics, rather than cross-household differences. Research limitations/implications Future research could fruitfully explore four issues. First, consumption upgrading has increased the volatility of China’s household consumption. How much will this affect economic growth in China under its “new normal” conditions, and how should the Chinese government respond? Second, differences between UHS data and aggregate data in the calculations of consumption risk sharing need to be investigated. Third, it is important to investigate the channels through which the Chinese government can enhance its ability to spread consumption risks and thus reduce consumer consumption volatility. Finally, further study could extend the current 18 provinces to a nation-wide sample and update the data beyond 2009 to estimate the impact of the global financial crisis. Practical implications The results suggest that when policy makers design macroeconomic policies to smooth consumption volatility, they should consider heterogeneity in household consumption goods, regional disparity and intertemporal dynamics simultaneously. Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world. Social implications Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world. Originality/value This paper fills this gap by using China’s UHS data to assess consumption volatility from the perspectives of heterogeneity in household consumption goods, cross-household differences and intertemporal dynamics. We make three contributions to the literature. The first contribution of this paper consists of demonstrating the contributions of heterogeneity in household consumption goods to consumption volatility. The second contribution consists of using the advanced variance decomposition method proposed by Crucini and Telmer (2012). This decomposition methodology allows the authors to examine whether household consumption volatility is due to cross-household differences or intertemporal dynamics. The third contribution is that this paper takes Chinese residents’ consumption fluctuations as the starting point to analyze the impact of consumption fluctuations on the future trend of China’s economy.


1998 ◽  
Vol 155 ◽  
pp. 479-511
Author(s):  
Lawrence C. Reardon

Social scientists always have been fascinated by cyclic theories, which not only parsimoniously describe and explain the underlying dynamics of world events, but, for the more adventurous, offer the possibility of prediction. This fascination has been especially true in the China field, where Chinese scholars and practitioners have used cyclic theories to explain Chinese politics since the Early Han. Among contemporary Western academics, sociologists have used “compliance” cycles to characterize the relationship between Chinese elites and the peasantry. Western economists have focused on variations of Chinese business cycles, such as the demand for consumption goods or harvest failures, to analyse China's economic growth. Political scientists have looked at the impact of various business, reform and factional cycles on Chinese political development.


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