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Book part
Publication date: 19 December 2012

Shahram Amini, Michael S. Delgado, Daniel J. Henderson and Christopher F. Parmeter

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which…

Abstract

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

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Essays in Honor of Jerry Hausman
Type: Book
ISBN: 978-1-78190-308-7

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Book part
Publication date: 25 February 2016

Martha H. Stinson and Peter Gottschalk

We investigate the question of whether investing in a child’s development by having a parent stay at home when the child is young is correlated with the child’s adult…

Abstract

We investigate the question of whether investing in a child’s development by having a parent stay at home when the child is young is correlated with the child’s adult outcomes. Specifically, do children with stay-at-home mothers have higher adult earnings than children raised in households with a working mother? The major contribution of our study is that, unlike previous studies, we have access to rich longitudinal data that allows us to measure both the parental earnings when the child is very young and the adult earnings of the child. Our findings are consistent with previous studies that show insignificant differences between children raised by stay-at-home mothers during their early years and children with mothers working in the market. We find no impact of maternal employment during the first five years of a child’s life on earnings, employment, or mobility measures of either sons or daughters. We do find, however, that maternal employment during children’s high school years is correlated with a higher probability of employment as adults for daughters and a higher correlation between parent and daughter earnings ranks.

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Inequality: Causes and Consequences
Type: Book
ISBN: 978-1-78560-810-0

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Article
Publication date: 11 July 2016

Shuyun Ren and Tsan-Ming Choi

Panel data-based demand forecasting models have been widely adopted in various industrial settings over the past few decades. Despite being a highly versatile and…

Abstract

Purpose

Panel data-based demand forecasting models have been widely adopted in various industrial settings over the past few decades. Despite being a highly versatile and intuitive method, in the literature, there is a lack of comprehensive review examining the strengths, the weaknesses, and the industrial applications of panel data-based demand forecasting models. The purpose of this paper is to fill this gap by reviewing and exploring the features of various main stream panel data-based demand forecasting models. A novel process, in the form of a flowchart, which helps practitioners to select the right panel data models for real world industrial applications, is developed. Future research directions are proposed and discussed.

Design/methodology/approach

It is a review paper. A systematically searched and carefully selected number of panel data-based forecasting models are examined analytically. Their features are also explored and revealed.

Findings

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. A novel model selection process is developed to assist decision makers to select the right panel data models for their specific demand forecasting tasks. The strengths, weaknesses, and industrial applications of different panel data-based demand forecasting models are found. Future research agenda is proposed.

Research limitations/implications

This review covers most commonly used and important panel data-based models for demand forecasting. However, some hybrid models, which combine the panel data-based models with other models, are not covered.

Practical implications

The reviewed panel data-based demand forecasting models are applicable in the real world. The proposed model selection flowchart is implementable in practice and it helps practitioners to select the right panel data-based models for the respective industrial applications.

Originality/value

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. It is original.

Details

Industrial Management & Data Systems, vol. 116 no. 6
Type: Research Article
ISSN: 0263-5577

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Book part
Publication date: 15 April 2020

Badi H. Baltagi, Georges Bresson and Jean-Michel Etienne

This chapter proposes semiparametric estimation of the relationship between growth rate of GDP per capita, growth rates of physical and human capital, labor as well as…

Abstract

This chapter proposes semiparametric estimation of the relationship between growth rate of GDP per capita, growth rates of physical and human capital, labor as well as other covariates and common trends for a panel of 23 OECD countries observed over the period 1971–2015. The observed differentiated behaviors by country reveal strong heterogeneity. This is the motivation behind using a mixed fixed- and random coefficients model to estimate this relationship. In particular, this chapter uses a semiparametric specification with random intercepts and slopes coefficients. Motivated by Lee and Wand (2016), the authors estimate a mean field variational Bayes semiparametric model with random coefficients for this panel of countries. Results reveal nonparametric specifications for the common trends. The use of this flexible methodology may enrich the empirical growth literature underlining a large diversity of responses across variables and countries.

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Article
Publication date: 26 June 2009

Monjur Mourshed and Mohammed A. Quddus

Renewable energy (RE) is an important component to the complex portfolio of technologies that have the potential to reduce CO2 emissions and to enhance the security of…

Abstract

Purpose

Renewable energy (RE) is an important component to the complex portfolio of technologies that have the potential to reduce CO2 emissions and to enhance the security of energy supplies. Despite RE's potential to reduce CO2 emissions, the expenditure on renewable energy research, development, and demonstration (RERD&D) as a percentage of total government energy research, development, and demonstration (ERD&D) investment remains low in developed countries. The declining ERD&D expenditure prompted this research to explore the relationship between CO2 emissions per capita and RERD&D as opposed to ERD&D.

Design/methodology/approach

An econometric analysis of annual CO2 emissions per capita during the period 1990‐2004 for the 15 pre‐2004 European Union (EU15) countries was carried out. It was hypothesized that the impact of RERD&D expenditure on the reduction of CO2 emissions would be higher than that of ERD&D expenditure, primarily due to several RE technologies being close to carbon neutral. Country‐level gross domestic product per capita and an index of the ratio between industry consumption and industrial production were introduced in the analysis as proxies to control for activities that generate CO2 emissions. A number of panel data econometric models that are able to take into account both country‐ and time‐specific unobserved effects were explored.

Findings

It was found that random effect models were more appropriate to examine the study hypothesis. The results suggest that expenditure on RERD&D is statistically significant and negatively associated with CO2 emissions per capita in all models, whereas expenditure on ERD&D is statistically insignificant (ceteris paribus).

Originality/value

The findings of this paper provide useful insight into the effectiveness of RERD&D investment in reducing CO2 emissions and are of value in the development of policies for targeted research, development, and demonstration investment to mitigate the impacts of climate change.

Details

International Journal of Energy Sector Management, vol. 3 no. 2
Type: Research Article
ISSN: 1750-6220

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Article
Publication date: 30 September 2019

Joseph F. Hair Jr. and Luiz Paulo Fávero

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

Abstract

Purpose

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

Design/methodology/approach

The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation.

Findings

From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level.

Originality/value

Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used.

Details

RAUSP Management Journal, vol. 54 no. 4
Type: Research Article
ISSN: 2531-0488

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Abstract

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Panel Data Econometrics Theoretical Contributions and Empirical Applications
Type: Book
ISBN: 978-1-84950-836-0

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Book part
Publication date: 26 April 2014

Konstantinos Drakos, Ekaterini Kyriazidou and Ioannis Polycarpou

This paper seeks to explain the serial persistence as well as the substantial number of zeros characterizing global bilateral investment holdings. We explore the different…

Abstract

Purpose

This paper seeks to explain the serial persistence as well as the substantial number of zeros characterizing global bilateral investment holdings. We explore the different sources of serial persistence in the data (unobserved country pair effects, genuine state dependence, and transitory shocks) and examine the crucial factors affecting the decision to invest in a host country.

Methodology

Based on a gravity setup, we consider investment behavior at the extensive (participation) margin and employ dynamic first-order Markov probit models, controlling for unobserved cross-sectional heterogeneity and serial correlation in the transitory error component, in order to explore the sources of persistence. Within this modeling framework we explore the importance of institutional quality of the host country in attracting foreign investment.

Findings

The data support that the strong persistence is driven by true state dependence, implying that past investment experiences strongly impact on the trajectory of future investment holdings. Institutional quality appears to play a significant role to attract foreign investment.

Research implications

The empirical findings suggest that due to the existence of genuine state dependence, inward-investment stimulating policy measures could have a more pronounced effect since they are likely to induce a permanent change to the future trajectory of inward investment.

Originality

Both the substantial number of zeros and the salient persistence characterizing bilateral investment holdings decision have been previously overlooked in the literature. A study modeling jointly the levels and the selection mechanism could prove a fruitful direction for future research.

Details

Macroeconomic Analysis and International Finance
Type: Book
ISBN: 978-1-78350-756-6

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Abstract

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The Handbook of Road Safety Measures
Type: Book
ISBN: 978-1-84855-250-0

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Article
Publication date: 31 August 2012

William R. DiPeitro and Emmanuel Anoruo

The purpose of this paper is to examine the impact of the size of government and public debt on real economic growth, for a panel of 175 countries around the world.

Abstract

Purpose

The purpose of this paper is to examine the impact of the size of government and public debt on real economic growth, for a panel of 175 countries around the world.

Design/methodology/approach

The paper utilizes the fixed‐effects and randomeffects techniques to estimate the panel regressions.

Findings

The results indicate that both the size of government and the extent of government indebtedness have negative effects on economic growth.

Practical implications

The findings suggest that the authorities ought to take the necessary steps to curtail excessive government spending and public debts, in order to promote economic growth.

Originality/value

The contribution of the paper is its application of the fixed‐ and randomeffects techniques in modeling the relation of real economic growth to the size of government and public debt, for a panel of 175 countries around the world.

Details

Journal of Economic Studies, vol. 39 no. 4
Type: Research Article
ISSN: 0144-3585

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