Stylised fact or situated messiness? The diverse effects of increasing debt on national economic growth

This paper assesses the options available to researchers analysing multilevel (including longitudinal) data, with the aim of supporting good methodological decision-making. Given the confusion in the literature about the key properties of fixed and random effects (FE and RE) models, we present these models' capabilities and limitations. We also discuss the within-between RE model, sometimes misleadingly labelled a 'hybrid' model, showing that it is the most general of the three, with all the strengths of the other two. As such, and because it allows for important extensions-notably random slopes-we argue it should be used (as a starting point at least) in all multilevel analyses. We develop the argument through simulations, evaluating how these models cope with some likely mis-specifications. These simulations reveal that (1) failing to include random slopes can generate anticonservative standard errors, and (2) assuming random intercepts are Normally distributed, when they are not, introduces only modest biases. These results strengthen the case for the use of, and need for, these models.

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“…see Bell, Johnston, and Jones 2015). Most significantly for our present purposes is the possibility of omitted variable bias.…”

Section: Omitted Variable Bias In the Within-between Re Modelmentioning

confidence: 94%

Fixed and random effects models: making an informed choice

2018

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“…Statistical methods that attempt to consider reverse causality exist, -e.g. the multilevel distributed lag model (Bell et al, 2014) gives an indication of causality for multilevel data.…”

Section: Other Covariates and Their Interactions With Age/cohortmentioning

confidence: 99%

Life-course and cohort trajectories of mental health in the UK, 1991–2008 – A multilevel age–period–cohort analysis

Bell

2014

Social Science & Medicine

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103

121

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“…Mencinger et al (2014) argue that the result of Reinhart and Rogoff leads to unjustified adoption of austerity policies for countries with various levels of public debt. Bell et al (2015) argue that the nexus between debt and growth varies significantly between countries, implying that an average rule suggested by Reinhart and Rogoff, has little policy relevance.…”

Section: Resultsmentioning

confidence: 99%

Non-linear Growth-Determinants Nexus: The Role of Sovereign Debt

Wu¹,

Liu²,

Huang³

2017

HPE-RPE

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We expand the new growth model as a panel smooth transition regression specification to measure the effects of determinants on growth and the role of debt ratio in the growth-determinants nexus. In the model, we consider new determinants (FDI, export and tourism) and use a two-period lagged debt-GDP ratio as the transition variable. The effects of determinants on growth vary across countries and with time, depending on the value of the transition variable. The threshold of the debt-GDP ratio (73.019%) is a referenced index to set the ceiling of debt-GDP ratio for the fiscal stability. For countries with high debt ratios, the policies to accumulate human capital and promote tourism are more effective in boosting growth than to stimulate domestic physical investment and export. For countries with low debt ratios, the conclusion is opposite. Thus, lowering debt ratio is not always favorable for the contributions of individual determinants to growth.

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Stylised fact or situated messiness? The diverse effects of increasing debt on national economic growth

Cited by 46 publications

References 39 publications

Fixed and random effects models: making an informed choice

Fixed and random effects models: making an informed choice

Life-course and cohort trajectories of mental health in the UK, 1991–2008 – A multilevel age–period–cohort analysis

Non-linear Growth-Determinants Nexus: The Role of Sovereign Debt

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