نابرابری درآمد و مشوق های اقتصادی : آیا معاوضه بهره وری ـ عدالت وجود دارد؟

What is the basis and direction of relationship between income inequality and economic growth? The equity versus efficiency dictum which predicts a positive relationship between inequality, capital formation, and real GDP growth—emphasizes the importance of economic incentives. Subsequently, this was challenged by the incomplete markets and political outcomes theories, because of increasing empirical evidence of an inverse relationship between income inequality and economic growth. In this paper, we offer a further explanation of the basis and nature of the inequality–capital–growth relationship which emphasizes the divergence between savings and investment. For the United States over the period 1970–2006, we have found no empirical evidence for the support of the equity versus efficiency hypothesis—that economic incentives are necessary for capital accumulation and growth. In fact, it was discovered that in most cases, inequality has had little or no impact on movements in the US capital stock, net investment, and consequently, economic growth. Another interesting finding of this study was that inequality exhibits hysteresis—implying that any positive shock, such as the dot-com boom, can lead to persistent and enduring increases in inequality.

Can we have less inequality without reducing prosperity in the United States? In the US, the public finance literature has primarily focused on the measurement of “efficiency losses” associated with government programs and policies. According to Okun (1975), the efficiency cost of income redistribution or economic regulations may be large enough to result in less national income. Thus, the argument is that although inequality may be reduced, everyone will be worse-off because there would be less entrepreneurial-type or rent-seeking behavior and diminished labor/capital productivity-resulting in a lower standard of living. From 1990 to 2000, the United States has exhibited a high rate of economic growth (3.3%) as compared to other industrialized nations, and contemporaneously the greatest increase in inequality since the late 1970s. In contrast, many East Asian economies in the post-World War period experienced relatively low levels of inequality (for countries of comparable income levels), yet grew at extraordinary rates and many Latin American countries had higher levels of inequality and grew at a fraction of the average East Asian rate. These phenomena prompted an interest in the relationship between inequality and growth, and in particular to a conundrum regarding the correlation between inequality and economic growth: what is the direction of relationship between inequality and economic growth? There is ample lip service paid to the disincentives and/or inefficiencies associated with redistribution and the resultant adverse effect on economic growth in popular media writings.1 The notion that higher inequality is both a necessary and sufficient condition for increasing economic growth appears to be an uncontested truth. On the other hand, in contrast to the positive relationship posited by the equity–efficiency approach, a number of studies in the academic literature have found an inverse and statistically significant relationship between inequality and economic growth (Barro and Xavier, 1995). The theoretical construct behind these approaches is grounded in the notion that greater inequality either stimulates or discourages “productive investment” (depending on the policy involved) and ultimately GDP.2 In this paper, a Keynesian raison d’etre will be offered as an alternative explanation of the relationship between inequality and a country’s capital stock. Following this, the association between inequality and capital investment in the United States between 1970 and 2006 will be examined by using a time series approach incorporating both the effect of inequality on net investment (short-run) and capital formation (long-run). It is important to note that although policies changing inequality may also affect the labor market, only the impact on capital productivity will be studied here.3

Can equality in the United States be promoted without eliminating the “genie” of prosperity? It is clear that for over a quarter of a century, the higher the income quantile, the more income continued to grow and the rich-get-richer pattern has continued to prevail. Many have asked why prosperity is not spreading more equally, but when it came to hard policy decisions, the response has always been that there is a trade-off between equality and growth—if a country tries too hard to redistribute income to the lower quantiles, there would be fewer entrepreneurs, less capital investment, and therefore a lower standard of living.According to the results of this study, there is no empirical evidence over the past 30 years in the United States to support such a contention. In three of the five inequality measures, increases (decreases) in inequality have had no influence on net investment, the capital stock, and consequently economic growth. The three remaining inequality measures have had an inverse effect on capital formation — positing the existence of market failure in the capital markets due to credit rationing. 5.1. Study limitations There are some statistical/estimation issues regarding the model used for this study which could tend to temper the results. It is well known that although the Johansen (1988) estimators have less bias than other estimators, they exhibit more variation. However, this does not appear to be a considerable problem in this analysis, given the degree of statistical significance of the parameter estimators in Table 4. In addition, the following issues may be problematic and arise from Monte Carlo studies on the Johansen (1988) cointegration tests,19 1. the tabulated critical values based on asymptotic distributions may be inappropriate if sample sizes are small; 2. all tests can be misleading if too few variables are included; 3. insufficient lag length can lead to substantial size distortions, over-specification leads to loss of power; and 4. if a low-order VAR model is used, both the trace and View the MathML sourceλmax statistics are biased toward finding cointegration. This study could be criticized based upon any or all of these issues, but the use of detrending methods, as was done in this analysis, has been shown to improve the power of the Johansen tests.20