Long-Run Convergence in Manufacturing and Innovation-Based Models

Most studies of comparative productivities fail to find evidence of convergence in OECD manufacturing despite major economic growth theories predicting convergence. Using manufacturing data for 19 OECD countries over the period from 1870 to 2006 this study finds strong evidence of unconditional B-convergence as well as o-convergence. Panel data estimates suggest that the convergence has been driven by domestic R&D, international R&D spillovers and financial development as predicted by Schumpeterian growth theoriesConvergence, second-generation endogenous growth models

Long-run economic growth in OECD countries: a century of evidence

This thesis examines three important issues in growth economics. These issues are productivity catch-up in the manufacturing sector, the direction of causality between schooling and economic growth, and the role of fiscal policy in explaining long-run growth. The main contribution of this thesis is to provide new empirical evidence on productivity growth in OECD countries using an extensive dataset going back to 1870, with important implications for growth researchers and policy makers around the world. Each chapter also makes significant contributions to the literature. The first contribution is to provide conclusive evidence of both β-convergence and σ- convergence in the manufacturing sector. The results in Chapter 2 suggest that the convergence has been driven by domestic research intensity, technology spillovers through the channel of imports, distance to the technology frontier, and catching up to the technology frontier through the channel of financial development. The empirical estimates are consistent with the predictions of Schumpeterian growth theory since domestic research intensity and foreign research intensity spillovers are found to have permanent growth effects. A clear policy implication is that innovation and R&D are essential for manufacturing productivity advances and governments must therefore ensure that appropriate legislations and institutions are in place to encourage innovation. The second contribution is to provide new empirical evidence showing that reverse causality does not appear to exist between schooling and growth. The results presented in Chapter 3 suggest that schooling is not affected by expected growth and most other variables linked to the present value of schooling. Furthermore, even if feedback effects from growth to schooling are allowed for in the growth regressions, the growth effects of schooling are not reduced. The most important implication of this result is that human capital driven growth models are still valid – schooling is indeed one the main drivers of long-run growth. The third contribution is to provide significant evidence that an increase in personal income taxation hinders the growth rate, while the long-run growth effects of corporate income taxation are found to be insignificant. Furthermore, consumption taxation is found to be positively correlated with the economic growth, suggesting that a reduction in income taxation financed by a higher consumption tax can be growth enhancing. Taken as a whole, this thesis suggests that technological progress, financial development and schooling have been among the strongest predictors of economic growth in OECD countries over the last century. Identifying these important growth determinants can help governments design sound economic policies to ensure sustained growth in the future

Long-run economic growth in OECD countries: a century of evidence

This thesis examines three important issues in growth economics. These issues are productivity catch-up in the manufacturing sector, the direction of causality between schooling and economic growth, and the role of fiscal policy in explaining long-run growth. The main contribution of this thesis is to provide new empirical evidence on productivity growth in OECD countries using an extensive dataset going back to 1870, with important implications for growth researchers and policy makers around the world. Each chapter also makes significant contributions to the literature. The first contribution is to provide conclusive evidence of both β-convergence and σ- convergence in the manufacturing sector. The results in Chapter 2 suggest that the convergence has been driven by domestic research intensity, technology spillovers through the channel of imports, distance to the technology frontier, and catching up to the technology frontier through the channel of financial development. The empirical estimates are consistent with the predictions of Schumpeterian growth theory since domestic research intensity and foreign research intensity spillovers are found to have permanent growth effects. A clear policy implication is that innovation and R&D are essential for manufacturing productivity advances and governments must therefore ensure that appropriate legislations and institutions are in place to encourage innovation. The second contribution is to provide new empirical evidence showing that reverse causality does not appear to exist between schooling and growth. The results presented in Chapter 3 suggest that schooling is not affected by expected growth and most other variables linked to the present value of schooling. Furthermore, even if feedback effects from growth to schooling are allowed for in the growth regressions, the growth effects of schooling are not reduced. The most important implication of this result is that human capital driven growth models are still valid – schooling is indeed one the main drivers of long-run growth. The third contribution is to provide significant evidence that an increase in personal income taxation hinders the growth rate, while the long-run growth effects of corporate income taxation are found to be insignificant. Furthermore, consumption taxation is found to be positively correlated with the economic growth, suggesting that a reduction in income taxation financed by a higher consumption tax can be growth enhancing. Taken as a whole, this thesis suggests that technological progress, financial development and schooling have been among the strongest predictors of economic growth in OECD countries over the last century. Identifying these important growth determinants can help governments design sound economic policies to ensure sustained growth in the future

Replication data for: Long-Run Convergence in Manufacturing and Innovation-Based Models

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Replication data for: Long-Run Convergence in Manufacturing and Innovation-Based Models

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Long-Run Convergence in Manufacturing and Innovation-Based Models

Most studies of comparative productivities fail to find evidence of convergence in OECD manufacturing despite major economic growth theories predicting convergence. Using manufacturing data for nineteen OECD countries over the period from 1870 to 2006, this study finds strong evidence of unconditional β-convergence as well as σ-convergence. Panel data estimates suggest that the convergence has been driven by domestic R&D, international R&D spillovers, and financial development as predicted by Schumpeterian growth theories. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

THE ROBUSTNESS OF ESTIMATORS FOR DYNAMIC PANEL DATA MODELS TO MISSPECIFICATION

Transition from economic theory to a testable form of model invariably involves the use of certain "simplifying assumptions." If, however, these are not valid, misspecified models result. This article considers estimation of the dynamic linear panel data model, which often forms the basis of testable economic hypotheses. The estimators of such a model are frequently similarly based on certain assumptions which appear to be often untenable in practice. Here, the performance of these estimators is analyzed in scenarios where the theoretically required conditions are not met. Specifically, we consider three such instances of serial correlation of the idiosyncratic disturbance terms; correlation of the idiosyncratic disturbance terms and explanatory variables; and, finally, cross-sectional dependence (as a robustness check to these findings, we also consider correlations between observed and unobserved heterogeneity terms). The major findings are that the limited tests readily available tend to have poor power properties and that estimators' performance varies greatly across scenarios. In such a wide array of experiments, it is difficult to pick-out just one "winner." However, a robust estimator across all experiments and parameter settings was a variant of the Wansbeek–Bekker estimator. This is a significant finding, as this estimator is infrequently used in practice. When the experiments are extended to include correlations between observed and unobserved heterogeneity terms, one might also consider, for across-the-board performance, the Blundell and Bond estimator. </jats:p

THE ROBUSTNESS OF ESTIMATORS FOR DYNAMIC PANEL DATA MODELS TO MISSPECIFICATION

Transition from economic theory to a testable form of model invariably involves the use of certain "simplifying assumptions." If, however, these are not valid, misspecified models result. This article considers estimation of the dynamic linear panel data model, which often forms the basis of testable economic hypotheses. The estimators of such a model are frequently similarly based on certain assumptions which appear to be often untenable in practice. Here, the performance of these estimators is analyzed in scenarios where the theoretically required conditions are not met. Specifically, we consider three such instances of serial correlation of the idiosyncratic disturbance terms; correlation of the idiosyncratic disturbance terms and explanatory variables; and, finally, cross-sectional dependence (as a robustness check to these findings, we also consider correlations between observed and unobserved heterogeneity terms). The major findings are that the limited tests readily available tend to have poor power properties and that estimators' performance varies greatly across scenarios. In such a wide array of experiments, it is difficult to pick-out just one "winner." However, a robust estimator across all experiments and parameter settings was a variant of the Wansbeek–Bekker estimator. This is a significant finding, as this estimator is infrequently used in practice. When the experiments are extended to include correlations between observed and unobserved heterogeneity terms, one might also consider, for across-the-board performance, the Blundell and Bond estimator.Dynamic panel data, misspecification, IV/GMM estimation, C13, C15, C23