IV. Summary and Conclusion
In 1955 Kuznets (1955) identified the level of income or economic activity as the main determinant of income inequality. He asserted that at the early stages of development, income inequality gets worse and once labor migrates from rural to urban areas, it gets better. Since the pattern of movement of inequality over time resembles an inverted-U shape, it is known as the inverted-U hypothesis. Unfortunately, it has been a challenge for many researchers to verify the hypothesis empirically. Instead, what has been easy to verify in the literature is the unequalizing effect volatility of income or output. It has been argued that since income volatility introduces uncertainty into the economy, it redistributes income from workers to owners of capital or from poor to rich.
Previous research has tested and mostly verified unequalizing effects of income volatility on income distribution by using either cross-sectional data or panel that that is pooled from many countries over certain time period. One panel study has used a balanced panel data from 48 states of the continental U.S. from 1945 t0 2004 and concluded that in the U.S. income volatility worsens income inequality. The data in this study which comes from Frank (2009) has now been extended till 2013, yielding 69 time-series observations for each state. This allows us to introduce the first time-series study on the impact of income volatility on income distribution. Furthermore, our time-series approach removes the so called aggregation bias from the mentioned panel study. In other word, the conclusion that in the U.S. income volatility has worsened income inequality may hold in some states but not in all states.
