A recently developed stochastic frontier production function methodology is used to estimate econometrically how technical efficiency, technological progress, and returns to scale contributed to US states’ economic growth in 1979–2000. Improved regional human capital data that are superior to the traditional “years of school” data are included. In support of the prior literature, overall technical inefficiency is found to be low but unlike earlier studies diverging over time with almost no shifting of the aggregate frontier. Efficiency is positively associated with relative historical wealth, human capital, relatively worse recession experience, greater market concentration, and a smaller informal economy
This paper creates a new data set on physical capital at the state level for the United States from ...
Chapter one presents a critical and detailed review of the stochastic frontier methodology from a ma...
We re-estimate the World Technology Frontier (WTF) non-parametrically, using the Data Envelopment An...
This paper estimates a translog stochastic frontier production function in the analysis of all 48 co...
U.S. states during the 1977-1986 business cycle are found to have small but significant technical in...
Abstract: U.S. states during the 1977-1986 business cycle are found to have small but significant te...
This paper investigates the process of GDP generation in Former Soviet Union (FSU) economies to prov...
This paper investigates the process of GDP generation in former Soviet Union (FSU) economies to prov...
It is broadly accepted that differences in efficiency and productivity growth are important contribu...
<p>Production of output and ideas: efficiency and growth patterns in the United States. <i>Regional ...
This paper investigates the process of GDP generation in Former Soviet Union (FSU) economies to prov...
Using data on the manufacturing sector for the 50 states during 1977-1996, we decompose labor produc...
This paper investigates the forces driving output growth, namely technological, efficiency, and inpu...
Growth is examined using a standard two input stochastic production function (SPF) that creates a me...
This paper applied a stochastic translog production function to examine the underlying causes of tec...
This paper creates a new data set on physical capital at the state level for the United States from ...
Chapter one presents a critical and detailed review of the stochastic frontier methodology from a ma...
We re-estimate the World Technology Frontier (WTF) non-parametrically, using the Data Envelopment An...
This paper estimates a translog stochastic frontier production function in the analysis of all 48 co...
U.S. states during the 1977-1986 business cycle are found to have small but significant technical in...
Abstract: U.S. states during the 1977-1986 business cycle are found to have small but significant te...
This paper investigates the process of GDP generation in Former Soviet Union (FSU) economies to prov...
This paper investigates the process of GDP generation in former Soviet Union (FSU) economies to prov...
It is broadly accepted that differences in efficiency and productivity growth are important contribu...
<p>Production of output and ideas: efficiency and growth patterns in the United States. <i>Regional ...
This paper investigates the process of GDP generation in Former Soviet Union (FSU) economies to prov...
Using data on the manufacturing sector for the 50 states during 1977-1996, we decompose labor produc...
This paper investigates the forces driving output growth, namely technological, efficiency, and inpu...
Growth is examined using a standard two input stochastic production function (SPF) that creates a me...
This paper applied a stochastic translog production function to examine the underlying causes of tec...
This paper creates a new data set on physical capital at the state level for the United States from ...
Chapter one presents a critical and detailed review of the stochastic frontier methodology from a ma...
We re-estimate the World Technology Frontier (WTF) non-parametrically, using the Data Envelopment An...