Policy Choices and Economic Indicators’ Impacts on Income Inequality in G8 Countries

Abstract:

The issue of income inequality is one of the main problems arising from the modern trend toward globalization. Many countries are still struggling with unequal wealth distribution. In an extreme example, the Gini index for South Africa was 63.1 in 2011. In contrast, the G8 countries had an average Gini index of only 35.3 for the same year (World Bank). This study examines the relationship between governmental policies, economic growth, and income inequality in the G8 countries via an econometric analysis of panel data. Five independent variables were examined: a) real GDP per capita; b) net investment in non-financial assets; c) unemployment rate; d) tax revenue; e) inflation rate; and f) two control variables, TO (ratio of export and import to GDP), and consumer price index. This analysis was applied to data collected from The World Bank DataBank 2004–2015. The results confirm that inflation rate and the openness of an economy significantly affect the income gap, consistent with the reports of Al-Marhubi (2000) and Günaydin and Çetİn (2015). In practical terms, these results suggest that specific policy changes have the potential reduce income inequality, namely imposition of a contractionary monetary policy and encouragement of international trade.

Keywords: policy, economic growth, income inequality, G8 countries.

INTRODUCTION

An increasing number of studies have implicitly suggested that income inequality is increasing in advanced capitalist countries (Beckfield, 2006).

When an economy is growing, a larger share of the new prosperity goes to blue-collar workers than to agricultural and manual laborers. This in turn, widens the income gap. There are numerous ways for a government to prevent this from happening, or at least from becoming worse, starting from wise policy planning. The prudent approaches that this paper discusses on are those that have a more direct effect on citizens, rather than those more abstract or general policies that have subtle impacts on income inequality. A misstep in deciding what is right for a country could eventually lead to a wider income gap that can become harder to tackle as it grows over time. The wider the gap, the harder it is to help those below the poverty line, usually manual laborers, to increase their income and climb out of poverty.

Seeing the issue form both the perspective of government and the people, it is something that is always best avoided. To have a gap in income is inevitable, but it certainly is not impossible to lessen them, through ways that will be further discussed in this paper.

One of the most striking examples of income inequality is found in South Africa. South Africa is part of the Southern African Customs Union and is considered a developed country by the standards of international trade statistics, with a GDP of $384.31 billion in 2012. Regardless, the UN holds firm in considering South Africa a developing country due to their low life expectancy and high income inequality (World Bank). South Africa’s income inequality can be quantified by its Gini index of 63.1 in 2011 (World Bank), the highest in the world. In contrast, the average Gini index for the G8 countries was 35.3 in the same year (Figure 1).

This paper contributes to the literature around income inequality by presenting new empirical results based on a unique dataset from the G8 countries over the 2004–2015 period, which has not previously been analyzed through this lens. The author strongly believes that governmental policy choices and economic growth play a role in Gini index of a country.

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The objective of the study are as follows:

i. To determine the impact policy choices and economic growth have on income inequality in G8 countries.
ii. To determine if those variables are significant in terms of effects.
iii. To model the results as a guide for other countries in setting governmental policies.

ETHODOLOGY

Research Subject: The subject of this study is the economies of the G8 countries—Canada, France, Germany, Italy, Japan, Russia, the United Kingdom, and the United States—during the eleven-year period 2004–2015.

Variable Definitions: Policy choices includes policies that the author suspects contribute to income inequality: investment and inflation rate. Economic indicators are economic data that are often used to judge the health of an economy. In this study, indicators used include economic growth, unemployment rate and tax revenue. Beside these main independent variables, two control variables were included: TO (percent of GDP made up of exports and imports), included in this study because Tahir and Azid (2015) reported that there is a positive and statistically significant relationship between trade openness and economic growth; and CPI (consumer price index), included because the price stability indicator has also been shown to affect the real output (Tiwari, Shahbaz and Islam, 2013).

Table 1. Variable Descriptions

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Procedures: This research used pooled cross-sectional regression analysis, performed in STATA 14. The general functional form of the model is as follows:

Δ ln giniit = β0 + ln β1 gdp + ln β2 investment + ln β3 unemployment + ln β4 taxrev + ln β5 inflation + ln Xnit + ℇ it

Xnit ∈{X1export + X2import + X3cpi}

Data Collection: Data were collected by the World Bank; some missing data for certain variables in some years were included by author through imputation.

Table 2. Summary Statistics

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RESULTS AND DISCUSSION

The author proposes the hypothesis that there is a correlation between policy choices, economic growth, and Gini index. Below is the regression result of the model mentioned previously:

Table 3. Pooled OLS Regression

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*, ** and *** denote significance at the 1, 5 and 10 % level respectively

- As the F value is 0.0000, the variables above are statistically significant at all significance levels. Thus, we can reject the null hypothesis with extremely high confidence.
- The R2 value shows that the model explains 78.27% of the variation in Gini index, a satisfactory value. The remaining 21.73% is the error of the model.
- When the coefficients of all above-mentioned variables are zero, the value of gdpLn would be 4.020473.
- Ln β1 gdp = .0039683, which is insignificant. We would conclude that one percent change in GDP results in a change of .0039683 change in Gini index. This result is consistent with Barro (1999) in which the researcher, using a broad panel of roughly 100 countries observed from 1960 to 1990, shows evidence that there is little to no relationship between economic growth and income inequality. Delbianco et al. (2014) reached a similar conclusion in their study of 20 Latin American and Caribbean countries in the period 1980–2010; their analysis showed that in the upper tail of income distribution in richer countries, the relationship between income inequality and economic growth is positive.
- Ln β2 investment = -.0151641, which is statistically insignificant. We would conclude that one percent change of net investment in nonfinancial assets results in a change of -.0151641 in the Gini index. This result is consistent with Barro (1999), which reported that there is little to no relationship between investment and income inequality. The findings of Lin et al. (2013), though, contradict these findings; those researchers proved through empirical research that investment maintains a rather disproportionate positive impact on income distribution.; more investment causes a higher Gini index.
- Ln β3 unemployment = -.0223096, which is statistically insignificant. A one percent change in total unemployment rate then results in a change of -.0223096 in the Gini index. This result is consistent with the work of Jantti (1994), who reported that unemployment has a regressive effect that decreases as the unemployment rate rises. To be fair, it contradicts the work of Galbraith et al (1999), in which the researchers reported with confidence that unemployment causes income inequality.
- Ln β4 taxrev = .0328229, which is insignificant. Thus, a one percent change in tax revenue rate would result in a change of .0328229 in the Gini index. The lack of significance for this result is inconsistent with the findings of Duncan and Sabirianova (2016); they used measures of tax progressivity in the period 1981–2005 for a large panel of countries and found that a progressive tax did reduce the income gap.
- Ln β5 inflation = .0132117, which is significant at 5%. We would conclude that a one percent change in inflation rate results in a .0132117 change in the Gini index. This is consistent with a study by Al-Marhubi (2000), an empirical study that showed a statistically significant association between income inequality and higher inflation. Yet, this particular result contradicts Barugahara’s (2012) dynamic panel data study of 60 countries over a 29-year period (1980–2009), which showed that financial development does reduce income inequality, and as it becomes worse, inflation, which offsets financial development, stops reducing income inequality. Barugahara argues this results from the cutback and great variability of real returns, high levels of inflation boost credit rationing. As a result, the financial sector makes fewer loans, resource allocation is more inefficient, and intermediary activity downsizes with unfavorable implications for income inequality.
- Ln X1export = .1942737, significant at a 1% level; thus, we expect a one percentage change in the export rate to result in a .1942737 change in Gini index.
- Ln X2import = ‑.5256328, significant at 1%. We conclude that a one percentage change in the import rate results in a ‑.5256328 change in Gini index. Similar results were found by Günaydin and Çetİn (2015), who reported in the results of an empirical study that there is a long-run relationship between international trade activities and income inequality, among other variables. Their study using Turkish economy as the sample, found that trade openness decreases income inequality in the long run.
- Ln X3cpi = .1210056, significant at the 5% level; based on this value we conclude that a change of one percent in the consumer price index results in a change of .1210056 in the Gini index.

The present study sought to determine to what extent policy choices and economic growth affect income inequality in the case of the G8 countries. The findings indicate that GDP, investment rate, unemployment rate, and tax revenue rate have minimal effects on income inequality as measured by Gini index. On the other hand, the rate of inflation, export and import rates, as well as the CPI, play significant roles in determining the Gini index.

Despite the lack of statistical significance for the relationship, we can see by analyzing results from a scatter plot (Figure A1) that Gini and GDP are positively correlated; as Gini index increases, so does GDP. Similarly, inflation (Figure A5) and Gini index also have an insignificant positive relationship; the rate of inflation increases as the Gini index does. This can serve as a suggestion to governments that it could be economically advantageous to impose income-equalizing policies.

According to Banerjee (2004), the presence of an income gap suggests that some people have higher income or wealth than others, and some of these individuals may over-invest, compensating for those who under-invest, making it hard to see if inequality reflects the aggregate investment rate. This paper’s results are in line with that finding; investment rate has an insignificant impact on income inequality.

Several policies have the potential to reduce the inflation rate. One is for a government to implement a contractionary monetary policy, reducing the money supply within an economy by decreasing bond prices and increasing interest rates. This can reduce spending, because, logically, when there is less money in circulation, those with money tend to save their money instead of spending it. Naturally, there would also be less credit available, further discouraging spending. These interventions will “tame” the economic growth, reducing the rate of inflation.

Broadly speaking there are three ways of implementing a contractionary policy. The first is by increasing interest rates. This power is held by central banks of each country. The “central bank” rate is the rate at which banks borrow money from the government, but for them to be able to make a profit, they lend it to businesses and consumers at higher rates. An increase in the central bank rate will force banks to increase their rates in response, and as a result, people will be reluctant to borrow money due to its higher cost. In short, spending and prices drop, and inflation slows.

The second is to increase the reserve requirement for banks to keep cash on hand, which holds them back from lending too much to clients. Like increasing the central bank rate, this intervention will decrease consumer spending.

The third is to reduce the money supply, which may or may not be direct, by enacting policies that support reduction of the money supply: for instance, calling in debts owed to the government and increasing the interest paid on bonds to increase investor interest. An increase in bond interest rates will raise the exchange rate of the currency due to higher demand and cause net import. Both an increase in bond rates and a reduction in the money supply will reduce the amount of cash in circulation; money will be moving from banks, companies, and investors and into the government’s pocket, where it can be spent or stockpiled at the government’s discretion.

This paper confirms that there is a positive relationship between the openness of an economy and income inequality (Figures A6 and A7). A number of policies can be implemented to encourage the international trade activities of a country and improve trade balance. The first is not a surprise; alter interest rates, the same as our proposed solution to reduce inflation, though in this case the intervention is to reduce rather than increase them. When the prime rate dips, it becomes more appealing for businesses to borrow, which will help them to expand. This expansion allows consumers to have increases—albeit temporary increases—in discretionary income.

The second technique plausible for the government to apply to improve trade balance is changes in tax policy to stimulate specific industries. This means offering tax incentives to certain kinds of industry and customers who indulge in certain industries, which can give emerging markets a powerful boost. A great example of this is the USA state of Arkansas, which provides targeted tax incentives to six emerging technology sectors: advanced materials and manufacturing systems; agriculture, food, and environmental science; bio-based products (e.g. adhesives, biodiesel, ethanol); biotechnology, bioengineering, and life sciences (e.g. genetics, geriatrics, oncology); information technology; and transportation logistics (Bundrick, 2016). Tax incentives encourage potential business owners to jump-start and further grow their company, and incentives to purchasers make it more appealing for small business and households to purchase the technologies and products produced by the industry.

The third point of control involves altering foreign trade policies, which includes lowering or eliminating tariffs and import quotas that would encourage foreign trade. Less-strict trade regulations and the creation of free-trade zones allow businesses to significantly lower costs, inevitably increasing their bottom lines. Having the ability to choose to outsource manufacturing and labor to cheaper markets helps businesses increase profit margins and expand their business.

The fourth solution is an increase in governmental outsourcing of responsibilities; creation of business contracts with private companies to perform governmental responsibilities. One example is infrastructure maintenance and creation by third-party construction contractors rather than government employees.

Since the government has the power to allocate the tax revenues from both individuals and businesses to affect the changes in the economy, loans and grants offer the fifth solution to income inequality. Providing funding access from the government to new or established entrepreneurs could be a way to utilize tax revenue to stimulate business activity.

LIMITATIONS OF THE STUDY

Findings of the study were intended to examine whether governmental policy choices and economic growth has any correlation with the recurring income inequality issue. However, the findings of this study cannot be generalized to all non-G8 countries, though it can be used for comparison or as a benchmark.

There are country-specific demographics and cultural characteristics that may affect the efficacy of each intervention for that country. For example, some countries may seem to have a higher unemployment rate because they have a small population. It would be close to impossible to lower the rates to compete with countries with a significantly bigger population. Thus, it is the researcher’s opinion that factors such as population size must be taken into consideration when drawing conclusions based on this study.

CONCLUSION

An impressive decrease in income gap can be achieved through governmental policies that minimize the inflation rate (also shown through consumer price index) and boost international trade activity.

It is a government’s duty to consider all arguments before imposing a policy. In this case, the ultimate goal is to lessen the income gap as much as possible in order to support a healthy economy and create a more fair and equitable society. As explained above, this can be achieved through monetary, fiscal, and supply-side policies, including encouraging international trade activities by domestic producers. All of these suggestions will help create and maintain positive developments in income distribution.

This paper may serve as a stepping-stone for further theoretical and empirical work. Further research will involve finding and examining other policies that may have more significant economic impacts on income inequality. In addition, examining different regions would be of benefit in seeking and recognizing patterns and determining if environment plays a large role in determining the efficacy and significance of each type of intervention.

REFERENCES

1. Al-Marhubi, F. (2000). Income Inequality and Inflation: The Cross-Country Evidence. Contemporary Economic Policy, 18(4), pp.428-439.

2. Banerjee, A. (2004). Inequality and Investment. Massachusetts Institute of Technology. Cambridge, Massachusetts.

3. Barro, R. J. (1999). Inequality, Growth, and Investment (No. w7038). National Bureau of Economic Research.

4. Barugahara, F. (2012). Financial Development and Income Inequality: Does Inflation Matter? Applied Economics Quarterly, 58(3), pp.193-212.

5. Brueckner, M., & Lederman, D. (2017). Inequality and GDP per capita: The Role of Initial Income, World Bank.

6. Bundrick, J. (2016). Tax Incentives and Subsidies: Two Staples of Economic Development – Arkansas Center for Research in Economics. [online] University of Central Arkansas. Available at: http://uca.edu/acre/2016/08/19/tax-incentives-and-subsidies-two-staples-of-economic-development/ [Accessed 25 Jan. 2018].

7. Delbianco, F., Dabús, C. and Caraballo, M. (2014). Income Inequality and Economic Growth: New Evidence from Latin America. Cuadernos de Economía, 33(63), pp.381-398.

8. Duncan, D. and Sabirianova Peter, K. (2016). Unequal Inequalities: Do Progressive Taxes Reduce Income Inequality? International Tax and Public Finance, 23(4), pp.762-783.

9. Galbraith, J. K., Conceicao, P., & Ferreira, P. (1999). Inequality and Unemployment In Europe: The American Cure.

10. Günaydin, D. and Çetİn, M. (2015). The Impact of Economic Growth and Trade Openness on Income Inequality: An Empirical Analysis for Turkish Economy. International Refereed Academic Social Sciences Journal, (20), pp.58-58.

11. Jantti, M. (1994). A More Efficient Estimate of the Effects of Macroeconomic Activity on the Distribution of Income. The Review of Economics and Statistics, 76(2), pp.372-378.

12. Lin, S., Kim, D. and Wu, Y. (2013). Foreign Direct Investment and Income Inequality: Human Capital Matters. Journal of Regional Science, 53(5), pp.874-896.

13. Mocan, H. (1999). Structural Unemployment, Cyclical Unemployment, and Income Inequality. Review of Economics and Statistics, 81(1), pp.122-134.

14. Tahir, M. and Azid, T. (2015). The Relationship between International Trade Openness and Economic Growth in the Developing Economies. Journal of Chinese Economic and Foreign Trade Studies, 8(2), pp.123-139.

15. Tiwari, A., Shahbaz, M. and Islam, F. (2013). Does financial development increase rural‐urban income inequality?. International Journal of Social Economics, 40(2), pp.151-168.

16. World Bank. “Income Inequality.” Beyond Economic Growth.

APPENDIX

Figure A1

Scatter of ln(Gini) against ln(GDP)

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Figure A2

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Scatter of ln(Gini) against ln(investment)

Figure A3

Scatter of ln(Gini) against ln(unemployment)

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Figure A4

Scatter of ln(Gini) against ln(tax revenue)

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Figure A5

Scatter of ln(Gini) against ln(inflation)

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Figure A6

Scatter of ln(Gini) against ln(exports)

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Figure A7

Scatter of ln(Gini) against ln(imports)

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Figure A8

Scatter of ln(Gini) against ln(CPI)

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