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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...
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Citations
... The SPF model has been used to examine sources of economic growth across countries (Kumbhakar and Wang, 2005) and regions (Brock and Ogloblin, 2014). Brock and Ogloblin (2018) employed the method to examine Russia's growth in 1998Russia's growth in -2007 These studies decompose growth based on the formulation of the SPF model suggested by Kumbhakar and Wang (2005), which focuses on growth convergence (technological catch-up) and parametrizes the inefficiency term as a function of time with a constant rate of change. ...
The study uses industry-level data to examine the drivers of Russia’s economic growth in 2000–2008, when the average annual growth rate was 6.45%, in comparison with 2010–2016, when it fell to 1.75%. We apply the stochastic frontier method to quantify input-driven, technology-driven, and efficiency-driven growth. The influence of the world oil price on Russia’s growth is estimated from the perspective of its effects on both expansion of inputs (extensive growth) and production efficiency (intensive growth). The oil price movements affected capital and labor growth, but the government used a rent management system to mitigate these effects. As a result, the rate of extensive growth in 2000–2008, when the oil price was rising, was about the same (around 3%) as in 2010–2016 when the oil price was falling. The intensive (TFP-driven) growth rate fell from an average of 2.7% per year in 2000–2008 to − 1% in 2010–2016 due to a substantial decline in production efficiency during the latter period. Although the world price of oil could be partly responsible for this trend, we found the evolution of Russia’s economic system from generally market-oriented to largely controlled by kleptocracy to be the main factor behind it. Despite some changes in the economy’s industrial structure that occurred during both periods, the structural transformation had a negligible effect on growth.
... Méon, Schneider, and Weill (2011) analysed the impact of adding the shadow economy to official output figures on estimated production functions and technical efficiency. While Brock and Ogloblin (2014) by studying how technical efficiency, technological progress, and returns to scale contributed to American economic growth during the period 1979-2000, found that efficiency is positively affected by wealth and human capital. ...
... Technical inefficiency is measured by the distance from countries' actual frontier to the optimal one as in Farrell (1957). The SFA technique was first developed to investigate firms' efficiency but was later used to measure technical efficiency at an aggregate level as applied, among others, by Weill (2005 and2010), Méon et al. (2011) and Brock and Ogloblin (2014), Moroney and Lovell (1997). ...
The relationship between government size and economic growth has been widely debated. Revisiting the subject from a distinct angle with respect to the mainstream approach, we provide an empirical analysis of the impact of government size on technical efficiency. The aim of this paper is to estimate the impact of public sector's size and of public expenditure components on 15 European countries’ technical efficiency from 1996 to 2014 by using a True Random Effect model. Using the total public expenditure as a proxy for the government size we estimate simultaneously national optimal production function and technical efficiency by controlling for income distribution and institutional quality. Our main findings show that the effect of public sector's size on efficiency is positive while the type of public expenditures may have both positive and negative impact. In more details, results suggest that education and health expenditures have a positive effect on technical efficiency, while others have a negative impact.
... We apply the model of Kumbhakar and Wang (2005) used by them to examine the world economy and recently applied to the U.S. as well (Brock and Ogloblin 2014). It allows a more thorough examination of TFP growth than many other production function models because it goes beyond a simple a simple dichotomy of extensive versus intensive growth. ...
Using a recently developed stochastic Translog production function frontier model, technical inefficiency, technological progress and returns to scale are examined during Russia’s 1998–2007 cyclical expansion at the branch level including both the market and non-market economy. The service sector plus high skill-intensive goods production is shown to be relatively more efficient than traditional Soviet era goods sectors. Technical efficiency decreases markedly over the expansion while technological progress is quite high (23 %) suggesting an expanding frontier leaving many branches behind as the economy adjusts away from the early transition era. Much greater attention to human capital policies are suggested to foster intensive growth in an environment of low oil and gas prices.
... Additionally, applied researchers have become increasingly interested in the analysis of regional efficiency over the last few decades (Ulltveit-Moe 2007; Ezcurra et al. 2008;Enflo and Hjertstrand 2009;Kline and Moretti 2013;Brock and Ogloblin 2014). Regional efficiency, understood as increases in terms of output or income growth at the aggregate regional level (Eleftheriou and Alexiadis 2011), is at the center of the ongoing debate regarding the effectiveness of growth-related regional policies (McCann and Ortega-Argilés 2013; Becker et al. 2012; Monastiriotis and Psycharis 2014). ...
This paper analyses region-level technical efficiency in nine European countries over the 1995–2007 period. We propose the application of a nonparametric conditional frontier approach to account for the presence of heterogeneous conditions in the form of geographical externalities. Such environmental factors are beyond the control of regional authorities, but may affect the production function. Therefore, they need to be considered in the frontier estimation. Specifically, a spatial autoregressive term is included as an external conditioning factor in a robust order-m model. Thus we can test the hypothesis of non-separability (the external factor impacts both the input–output space and the distribution of efficiencies), demonstrating the existence of significant global interregional spillovers into the production process. Our findings show that geographical externalities affect both the frontier level and the probability of being more or less efficient. Specifically, the results support the fact that the spatial lag variable has an inverted U-shaped non-linear impact on the performance of regions. This finding can be interpreted as a differential effect of interregional spillovers depending on the size of the neighboring economies: positive externalities for small values, possibly related to agglomeration economies, and negative externalities for high values, indicating the possibility of production congestion. Additionally, evidence of the existence of a strong geographic pattern of European regional efficiency is reported and the levels of technical efficiency are acknowledged to have converged during the period under analysis.
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Springer Nature SharedIt link: http://rdcu.be/qrEN
... If Chechen data availability improves, the SFM aggregate production function literature (e.g. Brock & Ogloblin, 2014) offers an array of additions to the core production function used here that would facilitate a more nuanced analysis of the region. ...
The economic performance of Chechnya is examined for the first time
using an aggregate stochastic frontier production function method.
The 15 sectors of the economy are found to be quite inefficient in
the use of capital and labour to produce aggregate output. Extensive
growth is likely to continue though at a lower rate as federal subsidies
from Moscow end. Intensive growth is unlikely given the lack of foreign
investment and the authoritarian political system. Some evidence
for the emergence of a market economy is found, suggesting that
Kadyrov has overseen an economic transition.
Counterfactual estimates of excess deaths in Russian regions in the period 2020–21 are compared with officially reported COVID deaths to analyze underreporting. COVID mortality levels at the end of years 2020 and 2021 as well as annual growth during 2021 and the first half of 2022 reveal that COVID is a real threat to high labour productivity regions and those with relatively bigger defence and civilian sectors. Corruption lowers COVID mortality growth, suggesting a public health system where
better care is obtained informally. Improved access to a doctor just before the pandemic lowered the level of mortality during the worst year (2021) but did not impact the mortality growth or the mortality level in 2020. Better prevention of any virus including COVID in the future would include more regionally decentralised vaccine and testing initiatives to boost compliance plus a fundamentally reformed health system that includes access to foreign-made vaccines and higher quality mortality data.
This chapter analyses the effect of innovation encouraged by climate change challenges on European farmers’ technical efficiency. Using the stochastic frontier approach, we estimate the impact of agricultural patents on farmers’ technical efficiency by taking into account both unobservable heterogeneity and heteroscedasticity in the inefficiency term. Our findings suggest that European farmers remain quite far from the maximum frontier and irrespective of the country in which they reside; farmers who innovate are more efficient than those who do not. Thus, the inefficiency of agricultural agents in the European context leaves space for policies that incentivise firms to adopt climate change adaptation strategies through technological innovation.KeywordsClimate changeAgricultureAdaptationPatentStochastic frontier approach
Counterfactual estimates of excess deaths in Russian regions in 2020 are compared with actual deaths to measure the initial COVID impact. COVID is a real threat to high labor productivity regions and those with relatively bigger defense sectors. Corruption is surprisingly found to lower excess deaths. Legacy Soviet human capital and early Putin era democracy don’t appear to impact excess deaths. Urban males are most threatened with an even greater negative impact on the economy as COVID moves into working age brackets in the medium term. Living in rural areas and/or in regions far from Moscow was relatively safer in 2020.
This paper presents updated estimates for state‐level private capital and investment for 1950–2015. We improve upon the procedure of Garofalo and Yamarik (2002) and Yamarik (2013) using quantity measures to apportion the mining capital stock and a geometric pattern of depreciation to derive investment data. We provide a brief overview of our new estimates, discuss their reliability, and present the website where the data are posted and updated annually.
This study investigates the potential role of variations in technical efficiency as a contributing factor in providing explanation for convergence or divergence in West-Europe. To control for spatial dependence among regions, the paper uses a spatial stochastic frontier framework that integrates spatial econometric techniques with stochastic frontier panel data models. The empirical analysis reveals that there is a strong geographic pattern of regional efficiency while the degree of average regional efficiency has increased steadily year by year. From a European regional policy perspective, we can conclude that differentiated development strategies seem more appropriate that homogeneous or best-practice investment approaches.
