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We show that foreign capital liberalization reduces capital misallocation and increases aggregate productivity for affected industries in India. The staggered liberalization of access to foreign capital across disaggregated industries allows us to identify changes in firms' input wedges, overcoming major challenges in the measurement of the effects of changing misallocation. Liberalization increases capital overall. For domestic firms with initially high marginal revenue products of capital (MRPK), liberalization increases revenues by 23%, physical capital by 53%, wage bills by 28%, and reduces MRPK by 33% relative to low MRPK firms. The effects of liberalization are largest in areas with less developed local banking sectors, indicating that inefficiencies in that sector may cause misallocation. Finally, we propose an assumption under which a novel method exploiting natural experiments can be used to bound the effect of changes in misallocation on treated industries' aggregate productivity. These industries' Solow residual increases by 3–16%.

Based on the analysis of the quantitative assessment of the influence of the factors of innovative activity on the dynamics of economic development and the endogenous determination of its contribution to the economic growth of the country, it is revealed that in foreign researches it is identified with the concept of the influence of scientific and technological progress. However, the impact of innovative factors on economic growth is not considered separately. Attempts of such a definition in Ukrainian researches are limited to well-known approaches: methods of integral assessment, methods of expert assessments, the method of multipliers, econometric models. Most of the approaches considered are focused on defining the innovative impact on economic development, rather than on economic growth. The main tool for assessing the role and innovative contribution to economic growth is the aggregate supply function model, usually based on the Cobb-Douglas production function. The analysis of the approaches used revealed a number of comments on econometric approaches. In contrast to this, an approach is proposed based on the neoclassical production function of Cobb-Douglas with a constant return to scale in the form of J. Tinbergen, with technical progress neutral according to J. Hicks, decreasing marginal productivity of macrofactors with limited interchangeability, which provides a causal functional (and not a statistical) relationship between input and output variables; does not require long time series. It is characterized by dynamic coefficients of elasticity, capital utilization rate and taking into account the innovation factor in each separate period. The innovation factor includes: the gross domestic expenditures on research and development, the expenditures on innovation, general expenditures on education. To define the contribution of formal innovation factor in economic growth applied "method of Solow residual", which by taking the logarithm and obtaining logarithmic derivatives in the production function, provides a formalized information about the contribution of each factor to economic growth and allows to develop the necessary regulatory measures. The method has been tested at the level of the country and old industrial regions of Ukraine: Dnepropetrovsk, Zaporozhye and Kirovograd regions of the Dnieper economic region of Ukraine. The role, importance and influence of the main factors of economic growth along with innovative ones on the part of the aggregate supply are considered and the cost-effectiveness of innovative factors is estimated.

PurposeIn response to the 2008 financial crisis, the performance of the Chinese construction industry seems to be more successful, especially in total factor productivity growth (TFPG) and its contribution (TFPGC). Hence, the purpose of this paper is to investigate and reveal the potential successful lessons in this regard.Design/methodology/approachThis study is conducted innovatively based on a special comparative analysis of TFPG and TFPGC between pre- and post-2008 financial crisis. Solow Residual Approach is used to measure TFPG and TFPGC for the period 2002–2016. Given that the crisis hit China at the end of 2008, the pre-2008 financial crisis period is from 2002 to 2008, and the post-2008 financial crisis period is limited to 2009–2016.FindingsThe results indicate that the industry indeed has better performance in promoting TFPG and TFPGC, TFP thus achieved significant accumulative growth before and after the crisis. However, from an evolutionary perspective, both TFPG and TFPGC presented an overall downward trend from before the crisis to after the crisis. Further, the game between the centrally planned economy and the market-oriented economy was identified and revealed as the essential reason behind the evolution of TFPG and TFPGC.Practical implicationsSome valuable lessons for policies and practices in promoting TFPG and TFPGC were summarized and learned from the Chinese experience, such as reducing administrative intervention and making the construction market play a decisive role.Originality/valueThis study provides some new empirical evidence to enrich the overall body of knowledge on growth theory, especially in promoting TFPG and TFPGC.

This paper proposes a small-scale general equilibrium model of structural transformation with a non-agricultural labour market characterized by search frictions. The model is used to investigate the role of sectoral TFPs as main drivers of structural change and a new growth accounting exercise allows a quantitative reassessment of the importance of the labour reallocation bonus in structural transformation in the presence of labour market frictions. The model is calibrated to data for post-war Spain and its transition from dictatorship to democracy. Counterfactual simulations point towards productivity improvements in agriculture as the main driver, while modifications in labour market institutions affect mainly the labour market itself, with only a modest effect on structural change.

In this study we investigate the performance of Brazilian industry based on productivity and efficiency indicators. We associate productivity with the concept of total factor productivity (TFP) while efficiency is measured based on the stochastic frontier production model that indicates how far the actual production deviates from the optimal level. This methodology allows to take into consideration the effect of non-manageable factors o. Both models make use of Annual Industrial Survey (AIP) data for 29 Brazilian industrial sectors for the period 2007 to 2019. The results derived from TFP show that between 2010 and 2016, Brazilian industry experienced a productivity loss of 15.7%. Our frontier model allows to identify the evolution of efficiency over time. The results indicate there was also a downward trend in efficiency in the Brazilian industry. Among the exceptions is the Oil and Natural Gas Extraction sector that jumped from 29th place in 2007 to second place in 2019. This rise, which begins to happen in 2010, is possibly due to exploration and production (pre-salt) and in the refining area, resulting in the large increase in investment in the sector.

We study technical change for multi-product technologies to examine its effect on economic growth for 27 OECD (Organization for Economic Cooperation and Development) countries during 1951–2014. We review the Malmquist index and reexamine von Neumann’s model of an expanding economy. We estimate the coefficient of uniform expansion via DEA (Data Envelopment Analysis) and use it to measure technical change via a Solow residual and an alternative von Neumann technical change index which equals the difference between the growth rates of the slowest growing output and the fastest growing input. We also exploit a property of constant returns to scale in order to examine technical change of the average technology. During 2005–2014 the Solow residual shows relatively fast technical change. In contrast, the Malmquist, average technology and alternative von Neumann technical change indexes show negative or stagnant technical change.

The concern that an economy could experience persistent stagnation, caused by a structural weakness of aggregate demand, goes back to Alvin Hansen’s (1939) thesis of ‘secular stagnation’. Hansen’s thesis has been revived in recent times, when it became clear that productivity and potential growth in the OECD countries have been declining for decades. However, in line with deep-rooted theoretical beliefs, that inadequate demand can only affect growth in the short run, secular stagnation (of potential growth) is treated as an exclusively supply-side problem, the root of which is a worrying steady decline in productivity growth. This paper argues that it is a mistake to dismiss secular demand stagnation as main cause of declining potential growth in the OECD. We argue that the theoretical case for demand-caused secular stagnation is strong and empirical evidence that it has affected the U.S. economy after the mid-1970s is entirely convincing. Demand is leading supply, also in the long run. Hansen had it right, after all.

Purpose This study aims to estimate total factor productivity (TFP) growth for the post-2008 period for selected industries in the manufacturing sector at NIC 3-digit. Total factor productivity growth (TFPG) estimates are based on the theoretical framework provided by studies such Hall (1988), Abraham et al. (2009) and Crepon et al. (2005) that incorporate market imperfection in labour and product market, thereby modifying the traditional TFP estimation as Solow Residual. Design/methodology/approach Based on the theoretical model that incorporates market imperfections in labour as well as product market in modifying the TFP estimates using the Levinsohn–Petrin framework of empirical estimation, the authors have calculated industry wise TFPG for 62 industries at NIC 3-digit level. Findings The study finds three distinct trends: first, there are considerable industrial disparities in productivity growth in terms of TFP. The estimates have been found to be higher than the conventional Solow Residual for most industries, indicating the role played by market imperfections in affecting the conventional measure of productivity growth. Second, estimates of bargaining power are found to be lower than those compared to the earlier estimates in Maiti (2013) for the Indian organised manufacturing case for 1998-2005. This observation is commensurate with the observation in recent years of a falling share in labour wage in total output in organised manufacturing sector. Finally, the study also found a statistically significant contribution of greater mechanisation on TFPG while an adverse effect of the rising dependence of organised manufacturing on contractual labour. Originality/value The role of market imperfections in measuring TFPG has been undertaken, and it has been found to be an important factor, as the estimated measures vary from the conventional measures of TFPG. Moreover, the study has considered a very recent period from 2008-2015 in estimating TFPG, as well as analysing the factors behind the trends in TFPG at industrial level.

In this paper, we respectively decompose and study different effects of technological progress on carbon emissions in China based on the combination of the logarithmic mean Divisia index method, the Solow residual model, and spatial econometrics. Furthermore, we propose an improved approach to estimate the rebound effect index. By comparing the different effects of technological progress on carbon emissions, our results indicate that China's overall domestic technological progress reduced its carbon emissions over this period. As for the rebound effect index, the estimated results are higher than in previous studies because of the spatial rebound effect, which was ignored by previous studies. Regionally, although the eastern region had high rebound effects, the western region is at the greatest risk from the rebound effects. Finally, we present specific environmental policy proposals for China's sustainable development based on empirical results.

In a 1957 paper, Robert Solow exploited the mathematical properties of the aggregate production function to isolate the role of disembodied “technical change” in economic growth. Solow’s method allowed to disentangle the role of technical change from that of production factors, with the residual serving as a measure of total factor productivity growth. His method and results were equally met with praise and criticism, some focused on the use of an aggregate production function, the residual composition and measurement errors. The interrogations around the residual gave rise to an abundant literature from the late 1950s which made it possible to improve the technique of calculation and refine the results. In this paper, I argue that in the 1980s, debates around the Solow residual were not essentially different from those which took place in the 1950s and 1960s (measurement issues, increasing returns to scale or procyclical productivity). They both have blossomed within the National Bureau of Economic Research (NBER), they both highlight and are central to the macroeconomics controversies of the decade and its resolution in a 1990s consensus. Though, these debates have been accompanied by a change in the “epistemic status of shocks” (Duarte and Hoover 2009, 228) in economics, which redesigned the Solow residual from a source of secular growth to be quantified to the initial impulse of short-term economic fluctuations. I allege that it was the ability to decompose the residual theoretically and empirically that made it a weapon in the war between those believed the business cycle was driven by supply-side factors (Freshwater) vs demand-side factors (Saltwater).

The energy rebound effect is regarded as an obstacle of achieving the expected target of energy-saving policies, especially under a rapid urbanization background in developing counties, such as China. This has become a substantial drag of sustainable development in some cities. Shanghai is the economic center of China, and it is also a typical energy import-dependent mega-city. Investigating the evolution of Shanghai’s energy-saving performance and the energy rebound effect is significant for the implementation of energy-saving policies in other similar cities of China and other developing countries. Using the state space model with time-varying parameters and based on the IPAT identity and the Solow residual approach, this paper is the first study to present a specific estimation on Shanghai’s energy rebound effect caused by technological progress. The results show that, during the period of 1991–2016, the average energy rebound effect of overall economy and secondary industry in Shanghai was 93.96% and 73.10%, respectively, indicating a high partial rebound effect. Most of expected energy saving caused by improved energy efficiency is offset by extra energy consumption caused by technological progress. Regarding tertiary industry, the average rebound effect was 146.61%, indicating a backfire effect. However, the average energy rebound amount of tertiary industry is less than that of secondary industry. In particular, there is an increasingly negative impact of the rebound effect of tertiary industry on energy conservation in recent years, with the sector’s rapid expansion and corresponding increase in energy demand. Furthermore, we estimate the carbon rebound amount (i.e., carbon emissions caused by the energy rebound effect) and find that, on average, the energy rebound effect caused 13.1% and 0.41% increases in carbon emissions in Shanghai and China, respectively. Therefore, mitigating the energy rebound effect can significantly reduce carbon emissions. Due to the substantial impact of the rebound effect, technological progress and energy efficiency improvement should not be the only way to achieve energy-saving target, especially in energy import-dependent mega-cities like Shanghai. Some supporting policies should be implemented to ensure that the expected outcome of energy-saving effort can be realized as far as possible.

When capacity constraints limit the production of heterogeneous firms, demand shocks can endogenously generate a number of important business cycle regularities: recessions are deeper than booms, economic volatility is countercyclical, the aggregate Solow residual is procyclical and the fiscal multiplier is countercyclical. The model's main mechanism is that the share of firms at their production limit is strongly procyclical. A baseline calibration of a basic New Keynesian DSGE model with capacity constraints delivers more than 25% of the empirically observed asymmetry in output, 18% of the additional cross-sectional dispersion in recessions and around 25% of the additional aggregate volatility, and more than 50% of the fluctuations in the Solow residual. The model implies fluctuations in the fiscal multiplier of around 0.12 between expansions and recessions.

Energy plays no role in the standard Cobb-Douglas Production Function (CDPF), and a trivial role in a three-factor CDPF where it is treated as a third input, independent of labour and capital. Starting from an epistemological perspective, we treat energy as an input to both labour and capital, without which production is impossible. We then derive an energy-based CPDF (EBCDPF) in which energy plays a critical role. We argue for the redefinition and measurement of real GDP in terms of exergy. We conclude that the “Solow Residual” measures the contribution of exergy to growth, and that the exponents in the EBCDPF should be based on cross-country comparative data as suggested by Mankiw (1995) rather than the “cost-share theorem”.

Developing a de-capacity scheme that is economical, fair, and efficient, has become a key problem affecting the smooth achievement of coal de-capacity targets. It is also an important policy issue with regard to the overall implementation of China's supply-side structural reforms. In this study, we use the production function method as well as the panel variable coefficient model to calculate the 25 provinces' boundary production functions for the coal industry, which leads to the estimation of the coal capacity and capacity utilization rate of each province. Taking into account the labor resettlement cost and disposal cost of fixed assets, a total cost function of coal de-capacity is established. The growth rate function of total factor productivity (TFP) in the coal industry is constructed by the Solow residual value method. An allocation model of coal de-capacity is then proposed, based on multi-objective nonlinear optimization with constraint conditions on the total reduction amount and minimum output of coal in each region. Finally, using the relevant data of China's 25 coal-producing provinces in 1990–2015, the allocation of coal de-capacity is obtained under the goal of minimizing the total cost and maximizing the TFP growth rate. The results show that the capacity utilization rate of China's coal industry is much lower than the lower limit of the reasonable utilization ratio, while TFP shows negative growth over a long period. The comparative analytical results indicate that in terms of total cost, the optimal allocation scheme is 44.5335 billion yuan lower than the government allocation scheme. The disposal cost of fixed assets and labor resettlement costs decrease by 29.2749 billion yuan and 15.2586 billion yuan respectively. In terms of TFP growth, the optimal allocation scheme has a 1.54% higher TFP growth rate compared with the government allocation scheme. In terms of fairness, the Gini coefficients of the optimal scheme calculated by various indexes are all smaller than 0.3, placing the scheme within the category of considerable or absolute fairness. In addition, we calculate the optimal allocation ratio of coal de-capacity in the situation where cost preference and quality preference of central government are considered, to verify the intrinsic consistency of the model. In brief, the optimal allocation scheme proposed in this study effectively realizes the integration of economy, efficiency, and fairness. © 2018 Elsevier B.V.

The contribution rate of technological progress is an indicator to measure the contribution of technological progress to agricultural production, which is important for analyzing the interrelationship between economic growth and scientific and technological progress, labor and capital. This paper uses the Solow residual method to measure and analyze the contribution rate of agricultural technological progress in Guizhou Province and makes suggestions for agricultural development. The research results show that the elasticity coefficient of capital for agriculture in Guizhou province during 2000–2019 is 0.52, the elasticity coefficient of labor is 0.38, and the elasticity coefficient of arable land area is 0.1. Capital inputs are currently the main driving force to promote agricultural production, and the contribution of labor and the arable land inputs to the growth of agricultural output is at a low level. The overall contribution rate of technological progress in agriculture is 40.35%, but it shows unstable changes from year to year. The capital contribution rate has an inverse alternating relationship with the contribution rate of technological progress.

Social capital has been credited with playing a role in many desirable economic outcomes. We analyze how these potentially beneficial effects translate into the macro-performance of economies by developing a dynamic stochastic general equilibrium (DSGE) model featuring the role of social capital in the explanation of the Solow residual. We then simulate and estimate the model with Bayesian techniques using Italian data. Our framework fits actual data better than a standard DSGE model, suggesting that social capital may improve the economic performance via its impact on total factor productivity.

Магістерська дисертація: 100 с., 24 рис., 23 табл., 16 джерел. Об’єкт дослідження – закон еволюційного розвитку технологій та інноваційних процесів. Предмет дослідження: моделювання та прогнозування росту економіки та зміни технологій на прикладі s-функції Річардса. Мета роботи – дослідження зростання економіки країни за допомогою узагальненої моделі Солоу на основі s-функції Річардса та залишку Солоу. Актуальність теми: в умовах інтенсивно мінливих зовнішніх і внутрішніх умов особливої актуальності для країн набула проблема вироблення стратегії економічного зростання і постійного вдосконалення власної методології довгострокового планування, яка б враховувала особливості соціально-економічної ситуації, що склалася в країні. У рамках цієї проблеми найскладніші завдання пов'язані з оцінкою перспектив якісного вдосконалення процесу відтворення та виявлення вкладу факторів його інтенсифікації у кінцеві результати економічного зростання. Подальший розвиток предмету дослідження – розгляд більш складних s- функції для дослідження росту економіки та вибір ефективних стратегій економічної політики. Master’s Thesis 100 pp., 24 Fig., 23 tables, 16 sources. Object of a research – the law of evolutionary technological development and innovation processes. Topic of a research: modelling and forecasting the growth of economy and changes in technology on the example of Weibull s-function. The aim of the work – research of the country's economic growth using a generalized Solow model based on Richards s-function Richards and Solow residual. Relevance of the topic: in the conditions of intensively changing external and internal conditions the problem of developing a strategy of economic growth and constantly improving their own methodology of long-term planning, which would take into account the socio-economic situation in the country. Within the framework of this problem, the most difficult tasks are related to assessing the prospects for qualitative improvement of the reproduction process and identifying the contribution of factors of its intensification to the final results of economic growth. Further development of the subject of research - consideration of more complex s-functions for the study of economic growth and the choice of effective economic policy strategies.

Quantitative macroeconomics is often portrayed as a science—because of its intensive use of high-powered mathematics—with the possible limitation of being unable to conduct controlled experiments. To qualify as a science, however, theories in that discipline must meet a minimum number of criteria: (i) It has explanatory power to explain phenomena; (ii) it has predictive power to yield quantifiable and falsifiable statements about new phenomenon; and (iii) it has operational power to change the world. A scientific theory consists of axioms and working hypotheses that facilitate the derivation of contestable statements from the axioms.2 Hence, simply laying out a list of contradictions between a theory’s implications and the data is often insufficient to disqualify a theory as science; it may have just challenged its working hypotheses, not its axioms. But, challenging a theory’s working hypotheses is a crucial step to improve or falsify a theory. This is why Isaac Newton spent so much effort in his Principia Mathematica to deal with the law of motion under air friction. This article discusses one of the working hypotheses of the Arrow-Debreu paradigm and its dynamic stochastic general equilibrium reincarnation in quantitative macroeconomics—the supply curve and its embodiment in the neoclassical production function. The supply curve is a much stronger pillar than the demand curve in holding up the Arrow-Debreu paradigm, but we argue in this article that the neoclassical production function embodying the supply curve is full of cracks. More specifically, we show that the neoclassical production function is not quantifiable as a working hypothesis to support the Arrow-Debreu DSGE model, unlike the chemical reaction equations based on Lavoisier’s oxygen theory of combustion. The neoclassical production function relies on the unobservable and unmeasurable Solow residual to explain the quantity of output produced at the firm, industry, or national level, and the hypothetical factors of production (capital and labor) are much like “fire, air, water, and earth” in the ancient Greek theory of the universe. Because the working hypotheses of quantitative macroeconomics are not themselves quantifiable, the neoclassical theory is not yet a science. And this explains the lack of power for DSGE models to predict the 2008 Financial Crisis and the inability of economic theory to change the world by engineering or recreating economic prosperity in developing countries.

This chapter reevaluates inter-regional network economies in Japan based on cost-based Solow residuals, a novel analytical approach. In most studies, inter-regional network economies have been measured as elements of technological progress in production functions. However, the conventional approach based on perfect competition raises concerns that measurements of geographical externalities depend on the behavior of economic agents. One way to mitigate this concern is to construct a model based on imperfect competition. The cost-share Solow residual approach provides reliable evidence of the geographical externalities uncovered by the conventional approach. That is, by applying this approach to geographical analysis, we can precisely identify inter-regional network economies under imperfect economies. Furthermore, by using this approach, we perform a sensitivity analysis on the installation of the Linear-Chuo Shinkansen (magnetic levitation train) to measure the economic impact of high-quality transportation infrastructure. The results show that the Linear-Chuo Shinkansen provides a significant time-saving effect not only in the region of origin but also in local regions other than those along the railway lines. That is, the results reveal that the formation of inter-regional networks can increase productivity not only in large metropolitan areas but also in local areas. The results of this chapter suggest that inter-regional networks via high-quality transportation infrastructure significantly enhance regional economic performance. This chapter provides empirical evidence for the national land plan in Japan.

Using the data of Chongqing Statistical Yearbooks from 2015 to 2020 and based on the Cobb-Douglas production function of Solow residual method, this paper constructs a functional relationship model among GDP, employment number, fixed asset investment, and economic growth. The contribution rate of independent innovation in Changshou District of Chongqing City is improved by using polynomial distributed lag model. Besides, the contribution rate of independent innovation in Shapingba District, Yuzhong District, Jiangbei District, and Beibei District of Chongqing City is compared with that in Changshou District. The research shows that, overall, independent innovation contributes a lot to the economic growth of Changshou District, but its contribution rate is in a slowly declining state. The government needs to take active measures to improve the level of independent innovation and promote the regional economic growth.

This study uses the Solow Residual method which is a tool to measure the productivity growth other than capital investment and labor input, and this productivity growth which can represent technological progress in long-term to construct a panel regression model for the four China’s first-tier cities in Beijing, Shanghai, Guangzhou and Shenzhen from 1992 to 2017 to measure the contribution rate of technological progress to economic growth, and conclude that the economic growth of first-tier cities mainly depends on technological progress.