The first four essays of this dissertation are single-authored – I am responsible for the formulation of the research problem, contextualizing the research to previous literature, the chosen econometric framework, data retrieval, data analysis, inter-pretation of the findings and writing in each of the four essays. I acknowledge the help I received in the title page of each chapter below. In the fifth essay, which is jointly written with Kari Heimonen, Juha Junttila and Teemu Pekkarinen, I am the main author. More precisely, I am the main liaison in the following elements:
previous literature, the chosen econometric framework (research design), data re-trieval, data analysis and writing. I am one of the main liaisons in the formulation of the research problem and interpretation of our findings. My role is auxiliary, but not negligible, in the theoretical analysis of the study.
1.2.1 Essay 1: Inequality and Economic Growth: Different Panel Estimators and Various Measures of Income Inequality
This essay lays the foundation for the dissertation by illustrating the choices that an empirical researcher faces in studying the interplay between inequality and growth. The sensitivity of the results to these choices is investigated in detail.
What remains fixed is the data source: the fourth version of the survey-based World Income Inequality Database (WIID) is used (UNU-WIDER, 2018). These data enable me to compare results between various measures of income inequal-ity. I pool data from 103 countries, of which 34 are OECD members.
First, different estimation techniques yield different results. After control-ling for unobserved time-invariant country-specific characteristics, and bias stem-ming from model dynamics and the endogeneity of the explanatory variables (sGMM), the estimated association between income inequality and subsequent
economic growth is predominantly negative but statistically insignificant across the different specifications. Moreover, the technique is found to suffer from iden-tification issues. Therefore, it is unclear whether it is an improvement on a pler class of estimators. The lack of statistical significance equally holds for sim-pler techniques that also account for country-specific unobservable characteris-tics (FE and dGMM). Conversely, assuming that these characterischaracteris-tics are not cor-related with the explanatory variables (POLS and RE) – meaning that inequality is not assumed to be driven by unobserved country-specific traits – yields statis-tically significant negative estimates. Thus, a cursory analysis suggests that a rise in inequality seems to be associated with lower subsequent growth, whereas ac-counting for country-specificity changes the conclusion and the association seems negligible.
Second, the patterns that are related to the different estimators do not de-pend critically on the measure of income inequality. The considered measures are the Gini coefficient, the Palma ratio, various other ratios, and top income shares.
However, if a data source that uses imputation methods to improve the coverage of the WIID is adopted, the estimates are typically much higher than the ones that rely on raw data.
Third, there are no clear differences between the FE, dGMM and sGMM results for OECD and non-OECD countries. However, the POLS and RE results are driven by the non-OECD subsample. Allowing for the relationship to vary conditionally on the level of inequality does not change these findings.
Fourth, to understand the roots of the results better, the estimated associa-tion is evaluated in terms of potential transmission channels. The findings sug-gest that inequality promotes growth through physical investments and that it hurts growth via lower accumulation of human capital. These two mechanisms seem to balance each other out.
1.2.2 Essay 2: The Role of Financial Development in the Relationship Be-tween Income Inequality and Economic Growth
Many seminal studies on the inequality-growth nexus have emphasized the role of financial frictions (see e.g. Galor and Zeira (1993), Aghion et al. (1999) and Galor and Moav (2004)). This essay evaluates the significance of financial devel-opment for the relationship between income inequality and growth. It employs standard panel regression analysis. Data compiled by Svirydzenka (2016) is used to allow the association between income inequality and the subsequent growth of per capita GDP to depend on multi-dimensional financial development. Finan-cial conditions are evaluated at the aggregate level, and institutions and markets are analyzed separately. Inequality data come from the survey-based World In-come Inequality Database maintained by UNU-WIDER (2018).
The findings highlight a difference between OECD and non-OECD coun-tries. When financial markets are sufficiently developed, the association between income inequality and growth is positive in non-OECD countries. If the finan-cial markets are poorly developed, the association is statistically insignificant.
The finding is robust to different measures of inequality and different estimation techniques. Such a dependency is not present when institutional development is considered or when the OECD member countries are analyzed.
1.2.3 Essay 3: Income Inequality and Economic Growth: Difference Between Rising and Falling Top Income Shares
In this essay, the interplay between the income shares of the highest-earning 1 % and economic growth is analyzed on a country level. Data that rely on tax records originate from the World Inequality Database (World Inequality Lab, 2020), and the analysis covers Australia, Canada, France, India, Japan and the United States over the period between 1950 and 2010. The empirical results are based on a novel technique (Schorderet et al., 2003; Shin et al., 2014): the growth of per capita GDP is allowed to respond asymmetrically to rising and falling income shares.
The results suggest that the relationship between inequality and growth was characterized by cross-country heterogeneity and asymmetries between 1950 and 2010. First, in France and the United States, a decrease in the income share of the highest-earning percentile was associated with lower subsequent growth of per capita GDP while the growth-response to rising inequality was small and statis-tically insignificant. Second, in India, growth responded positively to rising in-equality but showed no significant response to falling inin-equality. Third, changes in the top income shares seemed not to significantly translate into the growth process in Australia, Canada and Japan. Though, in Japan, the statistically in-significant point estimates for both positive and negative changes are negative, and as a result, there is evidence for asymmetry. In all countries, the short-run re-sponses are larger than the long-run ones. Moreover, the adjustments took place in two to seven years depending on the country, which suggests that the empir-ical approach captures mechanisms that are related to relatively direct economic mechanisms rather than factors that change slowly.
Moreover, the essay also revisits two previously used panel estimation ap-proaches. Herzer and Vollmer (2013) conducted a panel cointegration analysis and found that the concentration of income is bad for economic development.
Their finding does not generalize beyond their sample. First, there is only weak evidence for cointegration between economic development and the top income shares as opposed to the original study. Second, the estimates that I obtain for the top income shares on economic development are positive. When standard panel growth regressions are considered, the evidence is in line with previous stud-ies that have used similar data (Andrews et al., 2011; Thewissen, 2014): a small positive association between top income shares and growth emerges.
1.2.4 Essay 4: Integrated Capital Shares
This essay deviates from the other four, in that it does not include any analysis of the links between income distribution and economic growth. Instead, functional income distribution, that is, the division of income between capital and labor,
is introduced. Although many drivers of the documented decline in the share of national income paid to workers have been suggested (see e.g. Karabarbounis and Neiman (2013), Piketty (2014), Acemoglu and Restrepo (2018), Stansbury and Summers (2020), and Autor et al. (2020)), the cross-country inter-dependencies of functional income distributions have not been analyzed previously. To investi-gate whether the same latent factors drive fluctuations in capital shares of total national income in different countries, historical data (Bengtsson and Walden-ström, 2018) and a technique previously used to measure financial integration (Pukthuanthong and Roll, 2009) are employed.
Identifying common unobservable factors from cross-country correlations reveal that the changes in capital shares are mainly driven by a single factor in all sample countries. This primary factor is strongly correlated with both trade openness and total factor productivity (variables that have been documented to contribute to the observed changes in capital shares) in the majority of the coun-tries. Such cross-country integration is not visible to the naked eye in correlation matrices or in time series graphs. The results are robust across samples, where both the country and year coverage change, and to the way capital depreciation is taken into account.
1.2.5 Essay 5: When Aiyagari meets Piketty: Growth, Inequality and Capital Shares
While the first four essays of this doctoral dissertation are single-authored, the final one is the result of a collaboration with Kari Heimonen, Juha Junttila and Teemu Pekkarinen. We incorporate the division of income between capital and labor into our analysis on the relationship between inequality and growth. Using historical, "Pikettyan" (2014), data (Bengtsson and Waldenström, 2018) and stan-dard panel estimation techniques, we show that an increase in the top 1 % income share is associated with higher subsequent growth of per capita GDP when capi-tal share is low. Alternatively, under a high capicapi-tal share, the association between inequality and growth is negative. These findings are robust to several tests, and compatible with the predictions of our theoretical analysis, which builds on the seminal study by Aiyagari (1994).
Theoretically, we stress the importance of the interplay between precaution-ary saving motives and consumption smoothing. Crucially, this interplay de-pends on the share of capital income in total national income, which in turn trans-lates into changes in capital accumulation and economic growth. We demonstrate the theoretical predictions in a simple capital market equilibrium and using com-putational methods. The main findings hold when financial frictions are suffi-ciently low – a property that is also present in the data.