СОВОКУПНАЯ ФАКТОРНАЯ ПРОИЗВОДИТЕЛЬНОСТЬ В РОССИИ: ВЛИЯНИЕ ЭКОНОМИКО-ГЕОГРАФИЧЕСКИХ УСЛОВИЙ И ЧЕЛОВЕЧЕСКОГО КАПИТАЛА (Total Factor Productivity in Russia: The Impact of Economic and Geographical Conditions and Human Capital)

Within the framework of this study, the stability of the aggregate factor productivity (TFP) in Russia to the estimation method was assessed. Approaches to assessing TFP were systematized, an approach was developed for analyzing TFP, taking into account the economic and geographical characteristics and the role of human capital.

Continuous cotton ( Gossypium hirsutum L.) production was examined using data from Alabama's long‐term Old Rotation experiment (c. 1896). Index values were used to examine trends in productivity and sustainability for 95 yr. Treatments studied were those receiving (i) no N fertilizers and no winter legumes for 95 yr, (ii) only winter legumes as a source of N, and (iii) chemical fertilizer N. Three sets of index numbers were calculated from all inputs and outputs involved in the production systems: (i) total factor productivity (TFP), which accounts for all direct production inputs, but which does not consider production externalities; (ii) productivity relative to a base plot;and (iii) total social factor productivity (TSFP), which accounts for all direct production inputs as well as externalities of soil erosion and pesticide use. Viewed from the 95‐yr perspective of the Old Rotation experiment, all three treatments fulfill at least one criterion required for a system to be considered sustainable. Output per unit of input is higher in 1991 than in 1896, even when externalities are valued. None of the systems showed a linear trend in output or TFP over the life of the experiment;productivity cycles are present in all three systems, despite a positive overall trend. An average annual rate of TSFP growth of 1.8%/yr was attained. Accounting for erosion and pesticide externalities reduced the annual productivity growth rate by 0.2%/yr. The system that has neither an organic nor a chemical source of added N was less productive and less sustainable than the two other systems, with a 0.3%/yr TSFP growth rate. The plots using organic and chemical sources of N had similar productivity impacts. Valuing soil erosion and pesticide externalities had only a modest effect on measured productivity. The most dramatic single event to affect the productivity of cotton farming was the introduction of the mechanical cotton picker. The impact of this technology was powerful enough to offset the effect of many other changes in the system. Research Question Is cotton production in the southeastern USA sustainable? How do we measure sustainability of a crop that has been produced for almost 200 yr in the same region but has a reputation for depleting the soil of nutrients, extensive soil erosion, and high pesticide use? The objective of this study was to use input and output indexes and a calculation of total factor productivity (TFP) to determine if cotton production using different management strategies is sustainable over nearly a century of continuous production. Literature Summary Most researchers agree that a sustainable system should maintain or enhance agricultural production, reduce the level of production risk for the farmer, protect natural resources, be economically viable, and be socially acceptable. Measuring all of these attributes of a production system is very difficult. However, using the extensive data available from historical, long‐term experiments should provide insight as to sustainability of certain production systems. Alabama's Old Rotation (c. 1896) is the oldest continuous cotton experiment in the world. Input and output (yield) records and estimates allow calculation of TFP indexes over the 95‐yr history of continuous cotton production. Different cotton production systems can be compared. Study Description Three continuous cotton systems from the Old Rotation were chosen for comparison: (i) No N and no winter legumes since 1896 (No N), (ii) winter legumes (crimson clover and/or vetch) as the only source of N since 1896 (winter legumes), and (iii) no winter cover crop and 120 lb N/acre as ammonium nitrate since 1956 (N fertilizer). Where input records were not recorded (e.g., labor, costs, machinery, etc.), they were estimated from USDA, Alabama Agricultural Experiment Station, and Alabama Cooperative Extension Service publications. Soil erosion estimates for the three cropping systems on a Pacolet fine sandy loam, were made using Erosion Productivity Index Calculator modeling. Input, output, TFP, and total social factor productivity (TSFP) indexes for 95 yr were calculated. Total social factor productivity includes estimated values for the negative offsite effects of soil erosion and pesticide use. Applied Questions Is continuous cotton production sustainable? Viewed from the 95‐yr perspective of the Old Rotation, the no N, winter legume, and N‐fertilized continuous cotton plots all fulfill at least one criterion required for a system to be sustainable. Output per unit of input is higher in 1991 than in 1896, even when externalities (erosion and pesticides) are valued. The average growth rates on the No N plot are 0.5%/yr for TFP and 0.3%/yr for TSFP. On the winter legume plot, TFP and TSFP grew at a rate of 2.0%/yr and 1.8%/yr, respectively. The plots using organic and chemical sources of N had similar productivity records. None of the systems shows a linear trend in TFP over the history of the experiment. Productivity cycles are present in all three systems, despite the positive overall trend. An important focus of future research will be to explain whether these cycles are related to weather, technology, or changes in the resource base. As one would expect, the system that has neither an organic or a chemical source of added N is less productive than the two other systems. This system compares even more poorly when externality costs are assigned. Organic and chemical sources of N have similar productivity impacts. How have externalities such as soil erosion and the negative impact of pesticide use on the environment affected TFP? Soil erosion and pesticide externalities have had only a modest effect on measured productivity. The no N plot indexes are not changed at all; TFP on the legume and N‐fertilized plots decreased by 4 and 6%, respectively. The main conclusions of the previous question are therefore unaffected. How have technological advancements affected long‐term productivity/sustainability of continuous cotton production? The most dramatic single event to affect productivity was the introduction of the mechanical cotton picker around 1960. The impact of this technology is powerful enough to offset the effect of many other changes in the system. This advancement allowed cotton production to move from a labor‐intensive environment with increasing labor costs per pound of yield to an environment where harvesting costs were not seriously affected by increasing yields. Because technological advancements cannot be predicted into the future, predicting the long‐term sustainability of a system becomes very difficult.

Are the effects of subsidies on farm productivity heterogeneous? Does the direction and magnitude of subsidies impact depend on farm specialization? To address this question, I use farm-level data from Amur region in the Russian Far East for 2010–2014. The data set includes farms inputs and output as well as state subsidies and degree of farm specialization. The latter is defined as the share of crop production in total farm revenue. The sample of farms is not random but includes almost the entire set of corporate farms in the Amur Region. Using the data, I estimate the production function that allows me to study the relationships between total factor productivity (TFP), farms specialization and state subsidies. To test whether farm specialization moderates the impact of subsidies on TFP, an interaction term between specialization and subsidies was included in the model. So, I study how the marginal effects of subsidies change conditional on degree of specialization. My findings support the heterogeneous effect of subsidies on TFP depending on the degree of farm specialization. High degree of specialization on livestock production is associated with negative effects of subsidies on TFP, while I don’t fine a statistically significant connection between subsides and TFP for farms specializing on crop production. The research contributes to the discussion about the effects of state supports and subsidies on agricultural development and productivity in Russia and particularly in the Russian Far East

The article valuates structural changes in the total factor productivity for the GDP of a number of world economies based on two samples in 1990–2010. These estimates are used to study structural changes in the total factor productivity in Russia.

The effects of openness, trade orientation, and human capital on total factor productivity

Comment

Human capital refers to the literacy rate and life expectancy on total factor productivity (TFP). This analysis is based on how total factor productivity is affected by human capital in Pakistan. The study was conducted in Pakistan. The ARDL method, based on data from 1980 to 2017, is used to test this relationship. Results indicated that human capital (health) in terms of life expectancy positively and significantly impacts total factor productivity in Pakistan. The available evidence also suggests that the effect of health (life expectancy) on total factor productivity (TFP) is superior to the effect of education on literacy rate. The association between gross fixed capital formation (GFCF) is statistically significant, and their impact is positive on total factor productivity (TFP). The outcome also demonstrates that GDP and LR have insignificant associations with TFP. It is recommended that the Pakistani government spend more on human capital to enhance skills and become more productive. High educational funds should be allocated to promote education. Therefore, Pakistan must increase the quality of education in both the short and long- run to attain the higher total factor productivity growth.

Man has always thought of efficient utilization of available potentials and sources. Today this subject drives more serious attention compared to the past. Limited available resources, increasing population and growing human needs and demands of those involved make the economy, politics and management and community organizations increase productivity in its priority programs. Productivity has positive effect on phenomena such as competition in international markets, equitable distribution of income, raising living standards, economic development and even political power of a government. However, the study in this field requires knowledge about its development process. So far there has been no comparison of total factor productivity factor in Iran with other countries in the cement industry with regard to position and valuable role in the economy. This research should be considered a step toward eliminating the deficiencies outlined. In this study, using the relative index of total factor productivity factor, the relative total factor productivity factor in Iran and Turkey, South Korea and the United States has been evaluated and analyzed between the years (2007 to 1990) in the cement industry. Also, using panel data approach, the effect of macro and institutional factors such as the role of government, the degree of openness, inflation, and human capital on total factor productivity factor is evaluated. The findings indicate that there is a wide gap between total factor productivity of Iran's cement industry and that of the United States and the trend is not a proper one. This is an alarm for Iran's policy makers and planning managers to plan and utilize proper policies and take necessary actions to close or reduce this wide gap. It is also adversely shown that interference of the government may negatively affect the total factor productivity but, developed human resources and an open economic environment will have positive effect on the productivity. It is also noted that inflation has an adverse effect on total productivity. Key words: Total productivity, cement industry board data, equal purchasing power.

The paper presents the results of research about specifics of gross domestic product production in Russia using the tool of econometrics – production functions apparatus. Also, there are quantitatively found answers on questions, which have theoretical and methodological significance. First question – what has a decisive influencing on the production of gross domestic product in Russia, whether it is stocks or investments into the main fund? It was found that the decisive influence on the production of gross domestic product in Russia comes from investments into the main fund. Weak dependency of gross domestic product in Russia on capital stocks explains the inappropriateness of using capital stocks as a parameter of fund in production functions. Second question – what is the exact type of indicators that is preferred to use for characterizing the components of production function in conditions of the Russian economy – cost or natural? It is defined that is it possible to use both – cost terms indicators and indexes of physical volume. However, mining specifics of Russian economy defines the preference of using indexes of physical volume. Third question – what is the quality of economic growth of Russian economy during the period between 1996 and 2013? The intensive character of economic growth was found and the input of main factors of production into economic growth of Russian economy was measured. DOI: 10.5901/mjss.2015.v6n5s3p265

This study uses the DEA-Malmquist method to measure total factor productivity by employing the provincial panel data from 1998 to 2017 in China and constructing a panel data model to test the relationship between birth rate and human capital and the influence of labour in different age groups on total factor productivity. It was found that the increase in the birth rate has a significantly negative effect on human capital accumulation, while the effect of the birth rate on human capital shows an inverted ‘U’ shape. That is, when birth rate decreases, human capital increases, and when birth rate increases, human capital decreases. Thus, too low or too high birth rates will reduce human capital. Ultimately, human capital accumulation will significantly promote the growth and decomposition of total factor productivity. The effect of the labour age structure on total factor productivity also shows an inverted ‘U’ shape. Labour between 40 and 49 years old contributes the most to the promotion of total factor productivity. Eventually, due to the low birth rates, the proportion of 50-59 years old will keep at high level. Therefore, total factor productivity will decline significantly.

The article considers digitalization as a new general purpose technology and its impact on economic growth and economic policy in the world and Russia against the background of the so-called “productivity paradoxes” and economic shocks of 2020—2023. The importance of accelerating the growth of total factor productivity in Russia through the introduction of advanced digital technologies is shown. The world experience in assessing the impact of digital information and communication technologies on economic growth is briefly described, and an adapted methodology for assessing macroeconomic effects of economic policy, previously used by experts from the OECD and the Ministry of Economic Development of Russia at the level of country groups, is proposed and tested on a panel of Russian regions. The authors calculated the original series of contributions of labor, capital and total factor productivity to the GRP growth of Russian regions for the period 2011—2020. This makes possible to compare the benefits of digitalization and the rate of accumulation of digital capital in Russia and in other countries . The article discusses the desirable parameters of short-term macroeconomic stabilization tools and some aspects of developing the national innovation system.

This article examines the impact of human capital and openness on total factor productivity (TFP) for five South Asian countries—India, Pakistan, Sri Lanka, Bangladesh, and Nepal—during the period from 1980 to 2011. The empirical results derived from the panel cointegration techniques provide evidence of a long-run relationship among the variables. The dynamic ordinary least squares (DOLS) results show that the long-run elasticities of TFP with respect to human capital and openness are positive. The results, however, suggest that the impact of human capital on TFP is relatively weaker than the impact of openness on TFP for the South Asian countries. The study also examines the long-run and short-run Granger causality between these three variables in a panel framework. The results indicate that there is a long-run Granger causality running from trade openness and human capital to TFP. Similarly, in the short-run, there exists a bi-directional Granger causality between trade openness and total factor productivity and between total factor productivity and human capital. The study suggests that by improving trade policy reforms, such as, licensing policies, and removing trade barriers, the low-income countries in South Asia can increase their level of openness, which would boost the TFP in the short run.

The objectives of this paper were to study effects of human capital and international trade orientation on the output and total factor productivity in Pakistan. The output and Total factor productivity have been estimated using Cobb-Douglas Production function linking per worker output, per worker capital as well as labor force including and excluding the human capital stock for the period of more than five decades from 1961 to 2013. The data was taken from various secondary sources including Pakistan Bureau of Statistics, State Bank of Pakistan and from various issues of Economic Surveys published by Ministry of Finance and was analyzed using SPSS. The role of potential determinants of output as well as total factor productivity such as human capital, exports, imports, FDI, Government consumption expenditure, education expenditure, capital labor ratio, GDP per capita, life expectancy and population have also been analyzed. According to the results the prevalence of decreasing return to scale was observed in all specification of the estimated production functions. Results also exhibit that the physical capital and employed labor force as significant determinants of output. Human capital becomes significant determinant of output when it is interacted with physical capital and employed labor force. An increasing trend in the output and productivity over time has been observed except during the 1970s. Human capital alone as well as its interaction with physical capital has been emerged as significant determinants of total factor productivity. The capital-labor ratio has also been found as significant determinant of productivity. The findings of the study advocate for more investment in both physical as well as human capital in order to increase the output and productivity in the long run.

Because of several policy distortions, including import‐substitution industrialization, widespread government intervention, and both domestic and international competitive barriers, there has been a general presumption that Latin America has been much less productive than the leading economies in the last decades. In this paper we show, however, that until the late 1970s Latin American countries had high productivity levels relative to the United States. It is only after the late 1970s that we observe a fast decrease of relative total factor productivity (TFP) in Latin America. We also show that the inclusion of human capital in the production function makes a crucial difference in the TFP calculations for Latin America. (JEL O11, O47, O54)

Foreign direct investment (FDI), human capital, infrastructure, and governance have been argued to enhance Total Factor Productivity (TFP). However, their low levels in Africa raise doubts about their effectiveness in boosting the TFP. This study investigates the dynamic relationship between TFP, FDI, human capital, infrastructure, and governance in 30 selected African countries from 1996 to 2019 using a Panel Vector Autoregression (PVAR) approach. The results show that FDI positively correlates with TFP, while governance initially decreases TFP, indicating the need for stable institutions to mitigate the negative impacts on productivity. The PVAR-Granger causality analysis reveals a significant bidirectional causality between FDI and TFP, signifying the mutual importance of FDI and TFP growth. Governance also influences TFP, emphasizing the role of efficient governance in enhancing TFP. The forecast error variance decomposition shows that TFP is mainly influenced by innovations in the short term, with FDI and human capital becoming more influential over longer horizons. The impulse response functions indicate that FDI shocks boost TFP significantly, whereas the effects of governance on TFP vary. These findings suggest that improving human capital, governance, and infrastructure is essential to creating a conducive environment for FDI and driving TFP growth in Africa.