Estimation of dynamic panel data models with both individual and time-specific effects

Hsiao, Chêng; Tahmiscioglu, A. Kamil

doi:10.1016/j.jspi.2008.03.009

Cited by 49 publications

(33 citation statements)

References 13 publications

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“…As Hsiao andTahmiscioglu (2008, p. 2698) point out, panel data offer rich potential for investigating the complexity of social phenomena by "blending inter-individual differences and intra-individual dynamics". We use…”

Section: Methodsmentioning

confidence: 99%

Poverty Reduction in Urban China: The Impact of Cash Transfers

Ramesh

2014

Social Policy & Society

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Section: Methodsmentioning

confidence: 99%

Poverty Reduction in Urban China: The Impact of Cash Transfers

Ramesh

2014

Social Policy & Society

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“…We adopt the standard panel data models in our study. According to Hsiao and Tahmiscioglu (, p. 2698), “panel data, by blending inter‐individual differences and intra‐individual dynamics, have greater capacity for capturing the complexity of human behavior than data sets with only a temporal or a cross‐sectional dimension.” Social scientists are very much interested in dynamic relationships; nonetheless, they cannot be detected in a single cross‐section analysis (Wooldridge, , p. 191). Panel data analysis is strong at investigating dynamics in social sciences.…”

Section: Model Specificationsmentioning

confidence: 99%

Urbanization, Land Development, and Land Financing: Evidence from Chinese Cities

2014

Journal of Urban Affairs

182

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China's urbanization is significant worldwide. This process is characterized by underurbanization of population and fast urban land expansion. The driving forces behind this expansion and their rationale are not fully understood and empirically tested. This study fills this gap by analyzing panel data from 1999–2009 for all 286 prefecture‐level cities in China. The findings reveal that land financing, using different measures, significantly contributed to land urbanization in China. Economically stronger cities with higher real estate investment more aggressively pushed for land urbanization. The true purpose of urbanization should be improving the living standard, not to generate revenue. It is suggested that urbanization can serve its justified goals only if fiscal and political relations between central and local governments can be adjusted. As more data become available, future studies are encouraged to further explore the subject by investigating additional factors and the latest trend of urbanization in China.

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“…For example, the prediction that risk averse agents will make insurance contracts allowing them to smooth idiosyncratic shocks implies dependence in consumption across individuals. Ignoring cross-sectional dependence can lead to inconsistent estimators, in particular, when T is finite (e.g., Hsiao and Tahmiscioglu 2005). Unfortunately, contrary to the time series data in which the time label gives a natural ordering and structure, general forms of dependence for cross-sectional dimension are difficult to formulate.…”

Section: Modeling Cross-sectional Dependencementioning

confidence: 99%