A Replication of “The Robust Relationship between Taxes and US State Income Growth” (National Tax Journal 2008)

Using state-level data from 1970 to 1999 and a five-year interval approach, Reed provides robust evidence that taxes have a negative effect on state economic growth. Subsequent work by Gale, Krupkin, and Rueben uses more recent data, ending with the five-year period around the Great Recession, and provides evidence that the relationship is not stable. We take a systematic approach to replicating and then updating Reed to include the most recent data possible to see whether the relationship is sensitive to the time period considered. Our analyses corroborate Reed’s findings of a consistently negative and often statistically significant effect of taxes on state economic growth but also suggest that the long-run effects no longer exist in more current years.

The Effects of Wireless Mobile Phone Technology on Economic Growth in Nigeria

The market in the telecom industry is often segmented into three categories namely long distance, local and wireless services. In their survey, Green and Teece (1998) used this approach to study the telecom market segmentations of the United Kingdom, Australia, United States and New Zealand. In line with its policy of openness, transparency, fairness and participatory regulation, the commission informed stakeholders in September 2012 of its intent to conduct a study on the level of competition in the relevant markets of Nigeria’s Telecommunications Industry. It held meetings with a cross section of industry operators. This study shows that as the availability of mobile phone technology increases, the volume of import increases and more technology is transferred. Thus, the findings by Freund and Weinhold (2002, 2004) and Arrow (1969) are reconfirmed by the study’s empirical result. Therefore, technology helps to reduce distributional inequality of economic benefits. In fact, this does not necessarily imply reduction in inequality among rich and poor classes of these societies in the respective rich and poor states. The finding suggests that the availability of mobile phone technology increases state economic growth by different marginal weights. However, these marginal weights statistical significance across the states in both 90% and 95% confidence intervals could not be ascertained because the covariance has to be estimated using bootstrap. It is therefore left for future research.