Forecasting with Panel Data

By Badi H. Baltagi. Social Science Research Network, 2008

599 citations recorded by the source corpus.

This paper gives a brief survey of forecasting with panel data. Starting with a simple error component regression and surveying best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper also surveys how these forecasts have been used in panal data applications, running horse races between heterogeneous and homogeneous panel data models using out of sample forecasts.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/8ab04c55ba047f0dcb9526538722e68991c60190

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In Economics and Econometrics

Citations in the corpus

The Role of ICT in Modulating the Effect of Education and Lifelong Learning on Income Inequality and Economic Growth in Africa (2019, unknown): “Besides this, it restricts over-identification (or the proliferation of instruments) and controls for cross-sectional dependence (Baltagi, 2008; Love & Zicchino, 2006).”
Constructing a Global Fear Index for the COVID-19 Pandemic (2020, background): “Some of the advantages of using panel data over cross-section as well as time series data in estimation and testing has been well documented in Hsiao (2003), Baltagi (2008a, 2008b) and Baltagi (2013), among others.”
The Impact of Terrorism on Governance in African Countries (2017, methodology): “The estimation strategy has been documented to restrict over-identification (or limit instrument proliferation) and account for cross sectional dependence (see Love & Zicchino, 2006; Baltagi, 2008).”
Does age structure forecast economic growth (2007, unknown): “The presence of such fixed effects could be addressed by the use of panel data forecasting methods as discussed in Baltagi (2006). For the naive SDM0 (constant only), we reject the null hypothesis of no serial correlation, indicating that a country’s relative growth rate over the period 1960–1980 ha”
Education, lifelong learning, inequality and financial access: evidence from African countries (2020, background): “Moreover, it controls for crosssectional dependence and restricts the proliferation of instruments (or over-identification) (see Love & Zicchino, 2006; Baltagi, 2008).”
Quantile regression for dynamic panel data with fixed effects (2011, background): “There is an emerging literature on forecasting with panel data, see for instance Baltagi (2008) for a survey.”
Forecasting With Dynamic Panel Data Models (2017, unknown): “Baltagi, B. H. (2008): “Forecasting with Panel Data,” Journal of Forecasting, 27(2), 153–173. Blundell, R., and S. Bond (1998): “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models,” Journal of Econometrics, 87(1), 115–143. Brown, L. D., and E. Greenshtein (2009): “Nonparametric ”
Environmental Degradation, ICT and Inclusive Development in Sub-Saharan Africa (2017, methodology): “In this study, we adopt the Roodman (2009a, 2009b) extension of Arellano and Bover (1995), which has been established to restrict over-identification and limit the proliferation of instruments (Love & Zicchino, 2006; Baltagi, 2008).”
The Role of Information Sharing in Modulating the Effect of Financial Access on Inequality (2019, background): “…extension of Arellano and Bover (1995) is preferred in this inquiry because it has been acknowledged to take into account crosssectional dependence and restrict instrument proliferation (or over-identification) (see Baltagi, 2008; Boateng, Asongu, Akamavi, & Tchamyou, 2018; Love & Zicchino, 2006).”
The Mobile Phone in the Diffusion of Knowledge for Institutional Quality in Sub-Saharan Africa (2016, unknown): “The estimation approach has been documented to: (i) control for cross-country dependence and (ii) limit the proliferation of instruments or restrict over-identification (see Love & Zicchino, 2006; Baltagi, 2008).”
Information Sharing and Financial Sector Development in Africa (2017, background): “The specification is the Roodman (2009ab) extension of Arellano and Bover (1995) which has been documented to limit instrument proliferation and control for cross sectional dependence (see Love & Zicchino, 2006; Baltagi, 2008).”
Mobile phones, institutional quality and entrepreneurship in Sub-Saharan Africa (2017, methodology): “In this study, we opt for the Roodman (2009a, 2009b) extension of Arellano and Bover (1995) because it has been documented to restrict the proliferation of instruments and control for dependence among cross-sections (see Love & Zicchino, 2006; Baltagi, 2008; Boateng et al., 2016).”
Foreign Aid, FDI and Economic Growth in South-East Asia and South Asia (2020, background): “Such a specification is more efficient in the presence of cross-sectional dependence to avoid bias in estimated coefficients (Baltagi, 2008).”
Information Asymmetry and Financial Development Dynamics in Africa (2016, unknown): “This strategy is an extension by Roodman (2009ab) of Arellano and Bover (1995) which has the positive sides of : (i) restricting the proliferation of instruments and (ii) controlling for cross-sectional dependence (Love & Zicchino, 2006; Baltagi, 2008).”
Inequality, ICT and financial access in Africa (2019, unknown): “distribution (Cobham et al., 2015). Consistent with Efobi et al. (2018); Sassi and Goaied (2013); and Chavula (2013), we employ mobile phone penetration rate per 100 people, internet penetration rate per 100 people and fixed broadband subscription per 100 people as proxies for ICT.”
Information Asymmetry and Market Power in the African Banking Industry (2017, methodology): “…of this inquiry, we prefer the Roodman (2009ab) extension of Arellano and Bover (1995) because it has been documented to: (i) account for cross-sectional dependence and (ii) restrict over-identification or instrument proliferation (see Love & Zicchino, 2006; Baltagi, 2008; Asongu & De Moor, 2016).”
Foreign Aid and Inclusive Development: Updated Evidence from Africa, 2005-2012 (2017, unknown): “Such a specification is more efficient in the presence of cross-sectional dependence to avoid bias in estimated coefficients (Baltagi, 2008).”
Environmental degradation and inclusive human development in sub-Saharan Africa (2018, unknown): “In this study, we adopt the Roodman (2009a, 2009b) extension of Arellano and Bover (1995) which has been established to restrict over-identification and limit the proliferation of instruments (Love & Zicchino, 2006; Baltagi, 2008; Tchamyou, 2018).”
The Role of Governance in Mobile Phones for Inclusive Human Development in Sub-Saharan Africa (2016, unknown): “Roodman (2009ab) and has been documented to account for cross-sectional independence and limit over-identification or instrument proliferation (Love & Zicchino, 2006; Baltagi, 2008).”