Intranational Risk Sharing and its Determinants

Ho, Chun‐Yu; Ho, Wai-Yip Alex; Li, Dan

doi:10.2139/ssrn.1549330

Cited by 5 publications

(11 citation statements)

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“…More recently, Du et al (2011) find that only about 40 percent of the income shocks at the provincial level are smoothed between regions between 1980 and 2007. Ho et al (2015) find that income components account for a large share of consumption variation in Chinese cities, which confirms a low degree of risk sharing. Contrary to this, Skoufias (2003) and Notten and de Crombrugghe (2012) report a relatively high importance of risk sharing in Russia.…”

Section: Intra-national Risk Sharingmentioning

confidence: 65%

Temporal and Spatial Dependence of Interregional Risk Sharing: Evidence From Russia

Fidrmuc

Degler

2019

Macroecon. Dynam.

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We present an analysis of interregional consumption risk sharing in Russia between 1999 and 2009 using novel estimation methods. In addition to standard fixed-effects panel estimations, we use system and difference GMM estimators to reflect time dynamic properties and possible endogeneity between output and consumption. Furthermore, we apply spatial models that control for spatial dependence across regions. The results show that regional consumption deviations from the national average are highly persistent in time and space. Nevertheless, the regional consumption risk sharing in Russia is relatively high with 70%–90% of idiosyncratic risk being smoothed. Finally, fiscal policy and the degree of financial development appear to contribute to the consumption smoothing.

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Section: Intra-national Risk Sharingmentioning

confidence: 65%

Temporal and Spatial Dependence of Interregional Risk Sharing: Evidence From Russia

Fidrmuc

Degler

2019

Macroecon. Dynam.

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“…With regards to estimating domestic capital mobility, Ho et al. (2015) shed light on the aggregate bias issue by comparing the level of consumption risk‐sharing and smoothing estimated with city‐level and province‐level data (with spatial aggregation also present). Using a dataset of 24 Chinese provinces and 196 prefecture‐level cities from 1990 to 2010, they find that the degree of perfect risk‐sharing in the province level is much higher than that at the city level, suggesting an upward aggregation bias when the province‐level data is employed.…”

Section: Discussionmentioning

confidence: 99%

The economics of domestic market integration

Gunessee

Zhang

2021

Journal of Economic Surveys

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This paper reviews the literature that evidences the extent of the integration and fragmentation of domestic markets from measuring internal border effects. The empirical evidence from three main approaches—trade flows‐related, capital flows‐related, and price‐related—are reviewed. They are evaluated with emphasis on the role of recent methodological developments that adequately deals with the spatial and data aggregation problems and use disaggregated (micro) data, refined distance measures, and fine‐grained geographical areas. In particular, it enables distinguishing trade costs due to informal administrative impediments (border effects) and geographical barriers (distance effect). These allow for better inferences about internal border effects and domestic market integration to be drawn. They reveal that traditional approaches, which fail to tackle these inadequacies, have over‐estimated the size of the internal border effects and in effect domestic markets are more integrated than earlier documented. This addresses the reported mixed evidence found in earlier studies.

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“…He et al (2014) used aggregate consumption data at the province level in China from 1985 to 2011 and found that consumption risk sharing in China is limited, that is, China has high volatility of consumption. Ho et al (2015) used a data set of 24 Chinese provinces and 196 prefecture-level cities in those provinces from 1990 to 2010 and found that the ability to smooth consumption depends on initial economic development and the share of GDP contributed by tertiary industry.…”

Section: Literature Reviewmentioning

confidence: 99%

Will the Chinese economy be more volatile in the future? Insights from urban household survey data

Shi

Laurenceson

2019

IJOEM

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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.

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Intranational Risk Sharing and its Determinants

Cited by 5 publications

References 0 publications

Temporal and Spatial Dependence of Interregional Risk Sharing: Evidence From Russia

Temporal and Spatial Dependence of Interregional Risk Sharing: Evidence From Russia

The economics of domestic market integration

Will the Chinese economy be more volatile in the future? Insights from urban household survey data

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