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What is Dynamic Panel Model

Handbook of Research on Economic, Financial, and Industrial Impacts on Infrastructure Development
In the context of panel data, we usually must deal with unobserved heterogeneity by applying the within transformation, as in one-way fixed effects models, or by taking first differences if the second dimension of the panel is a proper time series.
Published in Chapter:
Trends of FDI and Production in Service Sectors: A Dynamic Panel Exercise with Indian Data
Madhabendra Sinha (National Institute of Technology Durgapur, India) and Partha Pratim Sengupta (National Institute of Technology Durgapur, India)
DOI: 10.4018/978-1-5225-2361-1.ch017
Abstract
The chapter investigates the role of foreign direct investment (FDI) on performances of Indian services at sector level. Service sector is marked as one of the fastest growing sectors in India, contributing more than 65 percent of GDP. The maximum share of FDI inflows in India is also captured by service sectors. So FDI inflows can have significant impacts on services. We collect quarterly data of components of services from GDP estimates of Central Statistical Office (CSO) and monthly data of sector wise FDI inflows from DIPP over the period January 2009 to March 2016 in India. After matching the data series, we form a balanced panel for four basic service sectors as classified by CSO. The stochastic properties are looked into by carrying out LLC and IPS panel unit root tests. Empirical results from the estimate of Generalised Method of Moments (GMM) suggest that FDI Inflows enhance performances of Indian services.
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Defense Expenditure and Economic Performance in SAARC Countries
The model with dynamic panel data uses the lags of the dependent variable as explanatory variables. That means dynamic panel data models are useful when the dependent variable depends on its own past realizations: Although the coefficients on lagged dependent variables might be far from our interest, the introduction of these lags becomes crucial to control for the dynamics of the process.
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