China has experienced rapid urban expansion and agricultural land loss, and the land conversion has accelerated in central provinces since the mid-1990s. The goal of this paper is to examine the relative importance of socioeconomic and policy factors on the urban conversion of agricultural land in Henan Province, China. Using panel econometric models, we examine how socioeconomic and policy factors affect agricultural land conversion at the county level across three time periods, 1995–2000, 2000–2005, and 2005–2010. The results show that both urban land rent and urban wages are essential factors that positively contribute to the conversion of agricultural land. It is also found that per capita GDP is correlated with more urban development and agricultural land loss. Consistent with expectations, agricultural financial support is negatively correlated with agricultural land conversion, suggesting a policy success. Finally, the decomposition analysis illustrates that urban wages are the most influential positive factor and agricultural financial support is the most influential negative factor affecting the urban conversion of agricultural land.

The aim of this article is to empirically identify convergence clubs in energy intensity among 109 countries from 1971 to 2010 by using a recently developed methodology, i.e., a new regression-based convergence test, introduced by Phillips and Sul (2007). This log t test allows us to endogenously identify the groups of countries that converge to different equilibriums and those that do not converge to any convergence clubs. We mainly find that, first, world countries do not seem to converge at the same steady-state level; instead, they form four separate clubs converging to their own steady-state paths and few countries are found to converge to no group at all. In addition, although the world as a whole shows the evidence of convergence, economic and geographic groups seem to converge at different speeds. Last, estimates from an ordered-logit model reveal that initial energy intensity level and openness are mainly responsible for the formation of the world convergence clubs, whereas industry share and R&D share are not.