Inequality-growth Relationship Research Articles

The moderating effect of income inequality in fiscal policy efficiency: The case of Central and Eastern Europe

AbstractOne of the objectives of fiscal policy is to ensure a fair income distribution. In the literature there is no consensus on the income inequality – fiscal policy nexus. Unlike previous studies, this paper contributes to the literature by quantifying the moderating effect of income inequality in total tax revenues and gross national expenditures which are defined as fiscal policy tools. With the help of two moderator variables (income inequality*total tax revenues, and income inequality*gross national expenditures), the impact of income inequality and fiscal policy tools on economic growth are tested for 20 Central and Eastern European (CEE) countries from 1990 to 2019. Diagnostic tests are also carried out on the series before long-term relationships are determined. Our analysis finds that the inequality-growth relationship is negative, the moderator variable defined as income inequality * total tax revenues decreases the strength of the relationship, and the moderator variable defined as income inequality * gross national expenditures increases the strength of the relationship.

Inequality and Economic Growth: a Method-Dependent Relationship Driven by the Measure of Income Inequality?

This study re-examines the much studied inequality-growth relationship. An empirical analysis that covers over a hundred countries finds no clear evidence for inequality to boost or dampen the growth of per capita GDP. Furthermore, evidence is found for inequality to promote growth through physical investments and hurt economic development via lower accumulation of human capital. These two mechanisms seem to balance out one another. The conclusions are based on a thorough investigation using the World Income Inequality Database maintained by UNU-WIDER and considering different measures of inequality, various estimation techniques, different specifications of the growth regression, allowing for non-linearities in the relationship and separating the OECD members from the non-OECD countries. The properties of the much-used system GMM estimator are investigated in detail. Even though its use is motivated by disentangling causality from correlation, the technique is found to suffer from weak instrument variables and sensitivity to small changes in the econometric specification. The results from simpler panel techniques follow a predictable pattern, where the use of cross-country (time) variation is associated with negative (positive) estimates. More profoundly, a strong result stemming from a data set that combines information from several countries would be of limited use for policy purposes because the actions to curb or promote income inequality are controlled by national policy-makers.

The Role of Financial Development in the Relationship Between Income Inequality and Economic Growth: An Empirical Approach Using Cross-Country Panel Data

The study complements the existing literature on the role of credit constraints in the interplay between income inequality and economic growth. The question what type of financial development matters for inequality-growth relationship is answered empirically by adopting a multi-dimensional index of financial development. The analysis covers 35 OECD member countries and 34 non-OECD economies starting from the year 1980 with varying coverage across countries. The results of the panel estimation techniques suggest that in the non-OECD countries, income inequality is positively associated with subsequent growth of per capita GDP under sufficiently developed financial markets. If the markets are poorly developed, the partial correlation between inequality and growth is statistically insignificant. For OECD countries, the association seems to be non-existent although weak evidence for growth-dampening inequality is found if both the level of inequality is high and the financial markets are highly developed. The results imply that promoting the development of financial markets, rather than institutions, may alleviate the adverse effects of income inequality on economic growth in under-developed countries.

The inequality-growth link revisited with spatial considerations: the case of provinces in the Philippines

This study revisits the relationship between income inequality and economic growth using provincial-level data from the Philippines over a ten-year period (1991–2000). This study demonstrates that the magnitude and significance of the inequality-growth relationship is not stable across space and the magnitude can be overestimated when spatial considerations are excluded from analysis. Generally, existing literature on the relationship between income inequality and economic growth has largely overlooked spatial elements. To avoid this exclusion, geographically weighted regression (GWR) estimates were used in this study. Results using GWR showed the magnitude of the inequality-growth relationship varied over a range of 0.70–0.85. The results of this study reinforce the idea that previous studies that have excluded spatial variation have likely overestimated the inequality-growth relationship, particularly in differences between urban and rural provinces.

The absolute Gini is a more reliable measure of inequality for time dependent analyses (compared with the relative Gini)

I compare time series properties of relative and absolute Ginis to examine which one is better suited for time dependent analyses. In particular, I model Gini trends as a fractionally integrated process and find that there are more mean-reverting absolute Ginis than relative Ginis suggesting that absolute Ginis may be better suited than relative Ginis for time-dependent analyses. I then undertake an estimation of the inequality-growth relationship using popular panel regression methods and find that the absolute Gini is negatively and significantly associated with growth for most models estimated, but none for the relative Gini. I deduce that from an empirical point of view, the absolute Gini may be a better choice when undertaking time dependent analyses.

THE RELATIONSHIP BETWEEN ECONOMIC GROWTH AND INEQUALITY: EVIDENCE FROM THE AGE OF MARKET LIBERALISM

Mediante un panel de países selectos, este artículo muestra que la relación desigualdad crecimiento sigue una forma de U durante el periodo 1970-98, en el cual la desigualdad inicialmente decrece y posteriormente se incrementa con el crecimiento económico. La evidencia también muestra que este patrón creciente puede revertirse a mayores niveles de ingreso. Usando series de tiempos se ilustra que varios países presentan un punto mínimo en diversos años a lo largo del periodo, mientras que otros siguen una tendencia positiva permanente. Adicionalmente se observa que, un pequeño grupo de países revierte la tendencia de desigualdad creciente a niveles altos de ingreso y despliegan un punto máximo a finales del periodo. Estos países están asociados con estabilidad macroeconómica, eficiencia gubernamental y expansión moderada del comercio y la IED. Entonces, la relación desigualdad-crecimiento durante la era del liberalismo de mercado tiende a cambiar hacia una relación positiva, aunque puede revertirse posteriormente.

A refinement of the relationship between economic growth and income inequality

There is mixed evidence in the literature of a clear relationship between income inequality and economic growth. Most of that work has focused almost exclusively on developed economies. In what we believe to be a first effort, our emphasis is solely on developing economics, which we classify as high-income and low-income developing countries (HIDC and LIDC). We make such distinction on theoretical and empirical grounds. Empirically, the World Bank has classified developing economies in this manner since 1978. The data in our sample are also supportive of such classifications. We provide theoretical scaffolding that uses asymmetric credit constraints as a premise for separating developing economies in such a way. We find strong evidence of a negative relationship between income inequality and economic growth in LIDC to be in stark contrast with a positive inequality–growth relationship for HIDC. Both correlations are statistically significant across multiple econometric specifications. Using international data from 1960 to 2010, this article explores the effect of income inequality on economic growth using dynamic panel technique, such as system generalized method of moments (GMM) that is believed to mitigate endogenous problem. These results are strikingly contrasting to the previous estimation results of Forbes (2000) displaying significant positive correlation between two variables in the short to medium term.

Dynamic and Long-Term Linkages Among Growth, Inequality and Poverty in Developing Countries

Drawing upon a cross-country panel data for developing countries, the present study sheds new empirical light on dynamic and long-term linkages among growth, inequality and poverty. First, agricultural sector growth is found to be consistently the most important factor in reducing inequality and poverty not only through its direct effects but also through its indirect effects. Second, there is a significant and negative association between inequality and GDP per capita, with macro institutional quality as one of the important factors in determining the inequality-growth relationship. Third, policies designed to prevent conflicts and mitigate their disruptive effects and violence, stabilise commodity prices, and enhance institutional quality would help eliminate worst forms of deprivation. Our analysis points to a drastic shift away from rural-urban migration and urbanisation as main drivers of growth and elimination of extreme poverty, and towards revival of agriculture in the post-2015 policy discourse. Indeed, the case for urbanisation rests on not just shaky empirical foundations but could mislead policy makers and donors.

A Refinement of the Relationship between Economic Growth and Income Inequality in Developing Countries

There is mixed evidence in the literature of a clear relationship between income inequality and economic growth. Most of that work has focused almost exclusively on developed economies. In what we believe to be a first effort, our emphasis is solely on developing economics, which we classify as high-income and low-income developing countries (HIDC and LIDC). We make such distinction on theoretical and empirical grounds. Empirically, the World Bank has classified developing economies in this manner since 1978. The data in our sample is also supportive of such classifications. We provide a theoretical scaffolding that uses asymmetric credit constraints as a premise for separating developing economies in such a way. We find strong evidence of a negative relationship between income inequality and economic growth in LIDC to be in stark contrast with a positive inequality-growth relationship for HIDC. Both correlations are statistically significant across multiple econometric specifications. These results are robust to degree of persistence in the variables of interest as well as a measure threshold of income that is estimated endogenously for our sample.

Inequality and the Process of Economic Growth: Threshold Effects of Human Capital to Physical Capital Ratio

This paper explores the relationship between inequality and growth in the context of a unified empirical approach suggested by the theoretical model of Galor and Moav (2004). Based on that model, we construct a new measure, the human capital to physical capital ratio, which is used to study threshold effects in the inequality-growth relationship. Methodologically, we use threshold regression with instruments, developed by Caner and Hansen (2004), which allows us to endogenously identify the threshold human capital to physical capital ratio that alters the inequality-growth relationship. Using data on 82 countries, our results show that there exist significant threshold effects, with a level of the human capital to physical capital ratio below which the effect of inequality on growth is positive and significant, whereas it is negative and significant above it. We also test the robustness of our results using different measures of the human capital to physical capital ratio. These results are consistent with the theoretical predictions of Galor and Moav (2004).

Did Higher Inequality Impede Growth in Rural China?

This paper estimates the relationship between initial village inequality and subsequent household income growth for a large sample of households in rural China. Using a rich longitudinal survey spanning the years 1987-2002, and controlling for an array of household and village characteristics, the paper finds that households located in higher inequality villages experienced significantly lower income growth through the 1990s. However, local inequality’s predictive power and effects are significantly diminished by the end of the sample. The paper exploits several advantages of the household-level data to explore hypotheses that shed light on the channels by which inequality affects growth. Biases due to aggregation and heterogeneity of returns to own-resources, previously suggested as candidate explanations for the relationship, are both ruled out. Instead, the evidence points to unobserved village institutions at the time of economic reforms that were associated with household access to higher income activities as the source of the link between inequality and growth. The empirical analysis addresses a number of pertinent econometric issues including measurement error and attrition, but underscores others that are likely to be intractable for all investigations of the inequality-growth relationship.

Inequality and Growth: The Neglected Time Dimension

The empirical literature on the relationship between inequality and growth offers a contradictory assessment: Estimators based on time-series variation indicate a positive link while estimators (also) exploiting the cross-sectional variation suggest a negative relationship. The present paper (i) confirms this conflicting pattern in an expanded dataset; (ii) proposes a simple theoretical framework to highlight the biases associated with the different techniques. We argue that mechanisms generating a positive inequality-growth relationship work mainly in the short-run and are reflected in difference-based estimators. In contrast, mechanisms generating a negative relationship work over the longer term and are reflected in level-based estimators.

The Macroeconomics of Model T

We study a model of endogenous growth where firms invest both in product and process innovations. Product innovations (that open up completely new product lines) satisfy the advanced wants of the rich. Subsequent process innovations (that decrease costs per unit of quality) transform the luxurious products of the rich into conveniences of the poor. A prototypical example for such a product cycle is the automobile. Initially an exclusive product for the very rich, the automobile became affordable to the middle class after the introduction of Ford's Model T, the car that put America on wheels. We show that an egalitarian society creates strong incentives for process innovations (such as the Model T) whereas an unequal society creates strong incentives for product innovations (new luxuries). We show that the inequality-growth relationship depends on which type of innovative activity drives technical progress, analyzing both the characteristics of and the transition to the balanced growth path.

Inequality and Growth in Rural China: Does Higher Inequality Impede Growth?

We explore the relationship between the level of village inequality in 1986, and the subsequent growth of household incomes from 1986 to 1999. Using a detailed household-level data set from rural China, we find robust evidence that initial inequality is negatively related to subsequent household income growth. We are able to address a number of econometric issues that affect the use of aggregate data for this exercise, especially measurement error and aggregation: Our results strongly suggest that village inequality has an external adverse impact on household-level income trajectories. However, once we account for possibly fixed village-level unobserved heterogeneity, we find no evidence that changes in inequality are correlated with household income growth: Whatever factor drives the inequality-growth relationship only operates in the “long run.” We explore several possible avenues by which initial inequality – or an unobserved variable correlated with it – affects household income growth. While we do not find the precise mechanism, our findings point toward a class of explanations based on collective choice (like the provision of public goods or determination of local taxes), and away from credit-market based explanations.