General Regional Economics
Does entrepreneurship cause urban economic growth and if so how large is the impact? Empirical analysis of such question is hampered by endogeneity. This paper uses two different sets of variables – the homestead exemption levels in state bankruptcy laws from 1975 and the share of MSA overlaying aquifers - to instrument for entrepreneurship and examine urban growth between 1993 and 2002. Despite using different sets of instrumental variables, the ranges of 2SLS estimates are similar, further supporting the significant impact of entrepreneurship on urban growth.
This paper examines the impact of government guaranteed small business loans on urban economic growth, and compares the growth impacts of government versus market financed entrepreneurship. OLS estimates indicate a significant and positive relation between the Small Business Administration’s guaranteed loans and metropolitan growth between 1993 and 2002. However, first-difference and instrumental variable regressions show no growth impact from government guaranteed loans. In contrast, market entrepreneurship significantly and positively contributes to local economic growth.
This paper examines how an autocratic regime domestically counters the impact of economic sanctions. A stylized model predicts that, as long as non-compliance is not too costly, the autocrat redistributes resources to the more valuable urban area when sanctions increase. Empirically, I examine the case of North Korea. I use the satellite night lights data to create average luminosity for each one minute by one minute cell between 1992 and 2010. I construct a sanctions index that varies based on the international response to North Korea’s nuclear pursuit.
Since the 1998 “wind of falsification and embellishment,” Chinese official GDP statistics have repeatedly come under scrutiny. This paper evaluates the quality of China’s GDP statistics in four stages. First, it reviews past and ongoing suspicions of the quality of GDP data and examines the evidence. Second, it documents the institutional framework for data compilation and concludes on the implications for data quality. Third, it asks how the National Bureau of Statistics could possibly go about credibly falsifying GDP data without being found out.
We propose a dynamic spatial theory to analyze the geographic impact of climate change. Agricultural and manufacturing firms locate on a hemisphere. Trade across locations is costly, firms innovate, and technology diffuses over space. Energy used in production leads to emissions that contribute to the global stock of carbon in the atmosphere, which affects temperature. The rise in temperature differs across latitudes and its effect on productivity also varies across sectors.
This paper studies the recent spatial development of India. Services, and to a lesser extent manufacturing, are increasingly concentrating in high-density clusters. This stands in contrast with the United States, where in the last decades services have tended to grow fastest in mediumdensity locations, such as Silicon Valley. India's experience is not common to all fast-growing developing economies. The spatial growth pattern of China looks more similar to that in the U.S. than to that of India.
China is the world’s second-largest economy and its output data are being closely watched. The release of the latest GDP data by China’s National Bureau of Statistics can be felt on stock markets around the globe, and may influence a broad range of economic decisions ranging from companies’ investment strategies to monetary policy. But China’s GDP data are poorly understood. GDP in one year may be revised upward by 16.8 percent, while rural household consumption falls by 26.6 percent and government consumption rises by 41.1 percent.
China has become a popular geographic area of research. Researchers make extensive use of Chinese official statistics, but these statistics are often not well understood. This article first clarifies three major issues that affect a wide range of Chinese statistics—from output and employment data to industry profitability—and then elaborates on data sources. The three data issues are changes over time to the sectoral classification system, changes to the ownership classification system, and changes to the coverage of the industry sector.
We study the validity of Zipf's Law in a data set of Chinese city sizes. Previous investigations are restricted to log-log rank-size regression for a fixed sample. In contrast, we use rolling sample regression methods in which the sample is changing with the truncation point. The intuition is that if the distribution is Pareto with a coefficient one (Zipf's law holds), rolling sample regressions should yield a constant coefficient regardless of what the sample is.