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1
Ni, Zhehan, and Weilun Chen. "A Comparative Analysis of the Application of Machine Learning Algorithms and Econometric Models in Stock Market Prediction." BCP Business & Management 34 (December 14, 2022): 879–90. http://dx.doi.org/10.54691/bcpbm.v34i.3108.
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Forecasting the future price trend of a stock traded on a financial exchange is the aim of stock market prediction. In recent decades, stock market prediction has been a fascinating topic in the domain of Data Science and Finance. In reality, the stock movement is ambiguous and chaotic due to various influencing factors such as government policy, current events, interest rates Etc. At the same time, accurate enough forecasting of stock price movement leads to substantial benefits for investors. This paper provides a comprehensive review of the application and comparison of Machine Learning (ML) algorithms and Econometric Models in stock market prediction. The mentioned models are categorized into (i) ML algorithms, including Linear Regression (LR), K-nearest neighbors (KNN), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM). (ii) Econometric Models, including Autoregressive Integrated Moving Average (ARIMA) Model, Capital Asset Pricing Model (CAPM), and Fama-French (FF) Factor Model.
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Trofimov, Ivan. "Capital productivity in industrialised economies: Evidence from error-correction model and lagrange multiplier tests." Ekonomski anali 62, no. 215 (2017): 53–79. http://dx.doi.org/10.2298/eka1715053t.
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The paper re-examines the ?stylized facts? of the balanced growth in developed economies, looking specifically at capital productivity variable. The economic data is obtained from European Commission AMECO database, spanning 1961-2014 period. For a sample of 22 OECD economies, the paper applies univariate LM unit root tests with one or two structural breaks, and estimates error-correction and linear trend models with breaks. It is shown that diverse statistical patterns were present across economies and overall mixed evidence is provided as to the stability of capital productivity and balanced growth in general. Specifically, both upward and downward trends in capital productivity were present, while in several economies mean reversion and random walk patterns were observed. The data and results were largely in line with major theoretical explanations pertaining to capital productivity. With regard to determinants of the capital productivity movements, the structure of capital stock and the prices of capital goods were likely most salient.
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ALBIS, Manuel Leonard Friginal, Dennis Sioson MAPA, Dorcas Mae P. COMANDANTE, Josephine D. CURA, and Maureen P. LADAO. "Spatial Analysis of Income Growth in the Philippines. Evidence from Intra-Country Data." Theoretical and Practical Research in the Economic Fields 6, no. 1 (June 30, 2015): 1. http://dx.doi.org/10.14505/tpref.v6.1(11).01.
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This paper looks at the spatial relationship of the average per capita income growth using provincial data from 1988 to 2009. The results from the study provide insights on the geographical dimensions of provincial income growth and showed evidence on the role of spatial effects in the formal econometric analysis of intra-country income growth models. Despite data limitations, the study provides a strong empirical evidence of the presence of positive spatial dependence or degree of similarity in the average per capita income growth of the provinces, albeit the degree of positive spatial dependence weakens in the latter periods. This positive spatial correlation suggests the provinces may be converging in terms of their income growth and they do so in movements similar to their neighbors. Moreover, the study shows that spatial dependence weakened in the latter periods (1994-2000 and 2000-2009). The weakening of spatial dependence may provide insights on the uneven provincial/regional income growth experienced in the country. One possible explanation of the weak spatial dependence is that two or more groups of neighboring provinces are growing at similar rates within the group, but at different rates across groups. This opens the possibility of having different convergence clubs (of provinces) within the country.
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Sukharev, Oleg, and Ekaterina Voronchikhina. "Structural growth policy in Russia: Resources, technology-intensity, risk, and industrialisation." Journal of New Economy 21, no. 1 (March 27, 2020): 29–52. http://dx.doi.org/10.29141/2658-5081-2020-21-1-2.
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One way to overcome resource constraints in the Russian economy, which could boost its efficiency, is implementing measures of structural policy that affect resource movement. The paper studies opportunities of growth through the development of the manufacturing sector and movement of the resources between sectors. Methodologically the research relies on the Keynesian approach to economic growth, which is of structural nature and appears to be the most relevant for scrutinizing structural specifics of growth and resources distribution within the economy. In terms of methods, the paper applies structural analysis and uses elements of econometric modelling. General and special industrialisation criteria allow establishing whether the economy is industrial by structure or by the level of technological development. On the basis of the obtained models the authors judge how the sectors’ risk / profitability ratio impacts on the movement of capital and labour between them. The findings reveal that if the structural policy affects the ratio between risk and profitability, as well as the level of sector’s technology-intensity due to spurring investment into new technologies (under decrease in risk), the manufacturing sector will receive an additional resource, improve its dynamics, and increase its contribution to GDP growth. The scenario forecast of the industrialisation criteria depending on the risk in the manufacturing sector points to the conclusion that the risk is to be diminished to raise the contribution of the manufacturing sector to GDP growth and simultaneously intensify the tech nological industrialisation.
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Alyaseri, Nagham Hameed Abdulkhudhur. "Optimization of the challenges facing the Iraqi economy based on the values of returns in 2000-2020." Economic Annals-ХХI 194, no. 11-12 (December 27, 2021): 4–12. http://dx.doi.org/10.21003/ea.v194-01.
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In this paper, the situation in the Iraqi economy for the period of 2000-2020 has been analyzed using three hybrid models. The research hypothesis was launched from the necessity of interaction between the activity of the Iraqi market for securities and the local financial and economic institutions. The hypothesis has been verified accordingly using Kolmogorov-Smirnov Test, normality test and Multicollinearity Test. The statistical analysis was based on the three mathematical models to expect return and risk values of Iraqi money market. Three basic models (optimization (BO), Optimized Return Value (ORV), General Optimization Risk (GOR)) have been conducted to optimize and analyze the given data accordingly. The research reached several conclusions, the most prominent of which is the limited economic role of the Iraqi market for securities; the potential exposure to negative effects that could be produced by international crises because of the expected openness, due to the possibility of illegal capital movements resulting in irrational speculation; the difficulty of implementing monetary and financial policies, due to vulnerability to international challenges
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Dell’Anna, Federico. "What Advantages Do Adaptive Industrial Heritage Reuse Processes Provide? An Econometric Model for Estimating the Impact on the Surrounding Residential Housing Market." Heritage 5, no. 3 (July 6, 2022): 1572–92. http://dx.doi.org/10.3390/heritage5030082.
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When industrial relics, such as obsolete buildings, sites, and infrastructures, enter into a process of adaptive reuse, they become transformation engines capable of shaping the urban fabric. They provide tangible and intangible links to our past and have the potential to play a significant role in today’s cities’ futures. One unresolved issue is the quantification of the externalities of these transformation processes. If undertaken correctly, adaptive reuse can contribute to the development of social and cultural capital, environmental sustainability, urban regeneration, and, most importantly, economic benefits to the surrounding community. In this sense, understanding the value of heritage is particularly important in light of the new European urban environmental policy movement based on the circular economy, which aims to change the way Member States consume and produce materials and energy. After a review of the externalities generated by the adaptive reuse of disused industrial heritage, the paper will concentrate on the estimation of economic benefits given by a transformation process that affected Turin’s Aurora district (Northern Italy) during the last years. The hedonic pricing method (HPM) was used to investigate the effects of the construction of new headquarters and the redevelopment of an old power plant converted into a museum and conference center. This study used econometric models to identify a significant increase in market prices within 800 m of the site and calculated a EUR 16,650,445 capitalized benefit from the transformation on the surrounding residential building stock. The study thus contributed to the awareness that reused heritage not only improves the lives of residents, but it also has a positive impact on the real estate market, in terms of transactions, as well as market values.
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Hao, Shengquan, Qinglu Jin, and Guochang Zhang. "Relative Firm Profitability and Stock Return Sensitivity to Industry-Level News." Accounting Review 86, no. 4 (April 1, 2011): 1321–47. http://dx.doi.org/10.2308/accr-10042.
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ABSTRACT This study provides theory and evidence to demonstrate how relative firm profitability within an industry affects stock return sensitivity to industry-level news. Extending the Cournot and Bertrand competition models, we predict that (1) the returns of less profitable firms in an industry are more sensitive to industry-level news than those of more profitable firms, and that (2) this inverse relation between relative profitability and return sensitivity is more pronounced when there is positive rather than negative industry news, especially in industries with high (versus low) capital intensity. Using industry returns to proxy for industry-level news, we obtain empirical results consistent with these predictions. We further find that the two fundamental factors that contribute to profitability—cost efficiency and market share—each exhibit an effect similar to that of relative profitability in affecting return sensitivity. Our results remain unchanged after controlling for stock price movements attributable to common risk factors and firm-specific accounting information, and they hold over a range of robustness tests.
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Vasiliev, Vladimir. "Leveling the American model of economic development in the context of globalization." Russia and America in the 21st Century, no. 3 (2021): 0. http://dx.doi.org/10.18254/s207054760017028-7.
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The article critically analyzes the American economic model, focusing on the historical strengths of the US economy. It is pointed out that among American economists there is a different understanding of the specifics of the American economic model, which, along with its strengths, has many weaknesses and vulnerabilities. At the same time, it is stated that the concept of the "American economic model" is predominantly ideological in nature, reflecting the historically formed ideology of the American exceptionalism applied to the economic sphere of society. In the context of globalization, there is a process of leveling out many elements of the American economic system, claiming to be elevated to a certain kind of absolute, which are becoming widespread in the economies of other highly developed countries, since the globalization of the world economy over the past 25-30 years was built on the premises of the maximum possible free movement of capital, labor, goods and services. As a result, many parameters of the American economic system undergo evolutionary changes in which they increasingly become similar to the parameters of the economies of other countries. In addition, the practice of compiling the system of national economic accounts, which has formed over the past 70 years under the auspices of the UN, is based on the idea of their unification and applicability to economies with different levels of economic development without highlighting specific qualitative characteristics inherent in the economies of different countries. In parallel, economic modeling, including using econometric methods, practiced in American universities and think tanks, is also based on abstract models, which are based solely on quantitative indicators omitting the specific qualitative properties of the economy of each country, including the US economy. The parameters of the American economic system that evolve over time are turning into a steady reduction in the dominant role of the United States in the world economy, taken in terms of their share in world GDP, which has almost halved since 1960, from 40% to 24%, and according to the American forecasts will tend to decline further in the near foreseeable future.
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Melesse, Wondemhunegn Ezezew. "Business cycles in Ethiopia under alternative monetary policy rules." African Journal of Economic and Management Studies 10, no. 3 (September 2, 2019): 299–313. http://dx.doi.org/10.1108/ajems-12-2018-0395.
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Purpose The purpose of this paper is to compare business cycle fluctuations in Ethiopia under interest rate and money growth rules. Design/methodology/approach In order to achieve this objective, the author constructs a medium-scale open economy dynamic stochastic general equilibrium (DSGE) model. The model features several nominal and real distortions including habit formation in consumption, price rigidity, deviation from purchasing power parity and imperfect capital mobility. The paper also distinguishes between liquidity-constrained and Ricardian households. The model parameters are calibrated for the Ethiopian economy based on data covering the period January 2000–April 2015. Findings The main result suggests that: the model economy with money growth rule is substantially less powerful or more muted for the amplification and transmission of exogenous shocks originating from government spending programs, monetary policy, technological progress and exchange rate movements. The responses of output to fiscal policy shocks are relatively stronger under autarky which appears to confirm the findings of Ilzetzki et al. (2013) who suggest bigger multipliers in self-sufficient, closed economies. With regard to positive productivity shock, however, the model with interest rate feedback rule generates a decline in output and an increase in inflation, which are at odds with conventional empirical regularities. Research limitations/implications The major implication is that a central bank regulating some measure of monetary stocks should not expect (fear) as much expansion (contraction) in output following currency devaluation (liquidity withdrawal) as a sister central bank that relies on an interest rate feedback rule. As emphasized by Mishra et al. (2010) the necessary conditions for stronger transmission of interest-rule-based monetary policy shocks are hardly existent in emerging and developing economies targeting monetary aggregates; hence the relatively weaker responses of output and inflation in the model economy with money growth rule. Monetary policy authorities need to be cautious when using DSGE models to analyze business cycle dynamics. Quite often, DSGE models tend to mimic the proverbial “crooked house” built to every man’s advise. Whenever additional modification is made to an existing baseline model, previously established regularities break down. For instance, this paper documented negative response of output to technology shock. Such contradictions are not uncommon. For example, Furlanetto (2006) and Ramayandi (2008) have also found similarly inconsistent responses to fiscal and productivity shocks, respectively. Originality/value Using DSGE models for research and teaching purposes is not common in developing economies. To the best of the author’s knowledge, only one other Ethiopian author did apply DSGE model to study business cycle fluctuation in Ethiopia albeit under the implausible assumption of perfect capital mobility and a central bank following interest rate rule. The contribution of this paper is that it departs from these two unrealistic assumptions by allowing international risk premium as a function of the net foreign asset position of the country and by applying money growth rule which closely mimics the behavior of central banks in low-income economies such as Ethiopia.
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Sixpence, Atanas, Olufemi P. Adeyeye, and Rajendra Rajaram. "Impact of relative and absolute financial risks on share prices: a Zimbabwe Stock Exchange perspective." Investment Management and Financial Innovations 17, no. 1 (January 22, 2020): 1–14. http://dx.doi.org/10.21511/imfi.17(1).2020.01.
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The impact of financial risks on share prices concerns investors, company executives and accounting standards developers. Investors need this information in delineating their equity valuation models while company executives need the information to make appropriate capital structure decisions. Accounting standards developers use this information in their policy to make accounting standards contemporary. The authors examine the link between relative and absolute financial risks and share prices using a dynamic panel of non-financial listed companies on the Zimbabwe Stock Exchange after dollarization. Equity investors incurred losses before dollarization, which prompted this investigation into the sphere of financial risks in order to explain share price movements so that investors can use it to minimize losses in the future. Absolute financial risk is measured by the total debt, while debt/equity ratio measures relative financial risk. Market capitalization as a proxy for equity and debt is measured by total liabilities. An average debt/equity ratio greater or equal to one qualifies a firm into the high-risk category while ratios below one imply low-risk firms. Results from two-step System Generalised Method of Moments (GMM) show negative and significant connection between relative risk and share prices across risk categories. The impact of absolute risk on share prices differs by risk category. Firm managers are advised to keep total liabilities below market capitalization in order to enjoy the benefits of low-risk categorization. Debt ratio is a reasonable indicator of value and investors can use it in equity valuation. Mandatory reporting of debt ratios should be considered by accounting standards developers.
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Islam, Tamanna, Ashfaque A. Mohib, and Shahnaz Zarin Haque. "Econometric Models for Forecasting Remittances of Bangladesh." Business and Management Studies 4, no. 1 (December 13, 2017): 1. http://dx.doi.org/10.11114/bms.v4i1.2860.
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At present, the remittance of Bangladesh (RB) is the largest source of foreign exchange earning of the country. The RB plays a critical role in alleviating the foreign-exchange constraint and supporting the balance of payments, enabling imports of capital goods and raw materials for industrial development. Remittance from overseas migrant workers certainly increases the income disparity between classes of the rural society. Therefore forecasting plays an important role to know the future situation of economic condition. This paper employed the prospective data on RB to derive a unique and suitable forecasting model. The data were collected from Bangladesh Bank (BB) during January, 1998 to December, 2003. The Autoregressive Integrated Moving Average (ARIMA) and the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models were used to find out the best one. The findings indicated that the ARIMA (0,1,1) (0,2,1)12 and the GARCH (2,1) models were appropriate for our data and the GARCH (2,1) model appeared to be the best one between these.
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Lazarides, Themistokles, Evaggelos Drimpetas, and George Kyriazopoulosr. "Mergers, liquidations and bankruptcies in the European banking sector." Risk Governance and Control: Financial Markets and Institutions 5, no. 2 (2015): 52–70. http://dx.doi.org/10.22495/rgcv5i2art6.
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The inactivity of banks may be the result of a number of events, such as merger & acquisition (M&A), liquidation, default-bankruptcy, etc. All these phenomena of inactivity contribute to the same result, the reform of the European banking sector and they may have the same causes. The paper will address the issue of inactivity and will try to detect its causes using econometric models. Six groups of indicators are examined: performance, size, ownership, corporate governance, capital adequacy or capital structure and loan growth. Three econometric methods (Probit, Logit, OLS) have been used to create a system that predicts inactivity. The results of the econometric models show that from the six groups of indicators, four have been found to be statistically important (performance, size, ownership, corporate governance). Two have a negative impact (ownership, corporate governance) on the probability of inactivity and two positive (performance, size). The paper’s value and innovation is that it has given a systemic approach to find indicators of inactivity and it has excluded two groups of indicators as non-statistically important (capital adequacy or capital structure and growth).
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Lupekesa, Chipasha Salome Bwalya, Johannes Tshepiso Tsoku, and Lebotsa Daniel Metsileng. "Econometric Modelling of Financial Time Series." International Journal of Management, Entrepreneurship, Social Science and Humanities 5, no. 2 (December 30, 2022): 52–70. http://dx.doi.org/10.31098/ijmesh.v5i2.622.
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This paper examines the relationship between assets, capital, liabilities and liquidity in South Africa using the Johansen cointegration analysis and the GARCH model using times data for the period 02/2005 to 06/2018. The results obtained from the study suggests that the time series are integrated of order one, I(1). The findings from the Johansen cointegration test indicated that the variables have a long run cointegrating relationship. Furthermore, the results from the GARCH model revealed that the estimated model has statistically significant coefficients at 5% significance level. Additionally, results revealed that assets have a positive relationship with capital, liabilities and liquidity. This implies that a percentage increase in assets will result to a percentage increase in capital, liabilities and liquidity. The results also revealed that shocks decay quickly in the future and that the conditional variance is explosive. The diagnostic tests revealed that the estimated models show the characteristics of a well specified model. The recommendations for future studies were formulated. Keywords: ARCH model; Cointegration; Financial time series; GARCH model; VECM; Volatility
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Басовский, Leonid Basovskiy, Басовская, and Elena Basovskaya. "Russian Regions’ Economy Research: Econometric Approach." Economics 2, no. 2 (April 17, 2014): 13–17. http://dx.doi.org/10.12737/3648.
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It is proposed a research program related to studying of economic development
of regions and country as a whole. It is suggested to build econometric models
of influence of factors which are able to affect indicators characterizing the
economic development. For this purpose it is proposed to use cross-sectional
data of the Federal State Statistics Service of Russia by region .On the basis of
obtained models it is possible to get partial regression equations. From these
equations it has been obtained equations for partial coefficients of influence of
studied factors by region. A use of described techniques has allowed estimate
an influence of capital-labor ratio, human capital, new technologies and private
property institution on labor efficiency in Russia. A higher education expansion
influence on salary level in Russia has been estimated. Estimates of private
property expansion influence on labor efficiency in the regions of Russia have
been obtained. Using these estimates it is possible to accomplish a costeffectiveness
analysis related to management of factors affecting the economic
development of country regions.
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Gonul, Dilcu, and Gulden Erkut. "Why do Skilled People Migrate to Cities? A Spatial Econometric Analysis for Understanding the Impact of the Social Environment on the Attraction of Human Capital to Cities in Turkey." European Spatial Research and Policy 26, no. 1 (July 11, 2019): 127–48. http://dx.doi.org/10.18778/1231-1952.26.1.07.
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The main focus of this study is on understanding the importance of social dynamics of cities for attracting human capital to urban regions. The principal research question of the article is “if there is a spatial dependency on neighbouring provinces’ social environmental qualities in human capital attraction for Turkey.” It is believed that developmental disparities among regions can be overcome with a balanced distribution of human capital. In this article, first the concept and importance of human capital and its evolution throughout economic history are explained in order to emphasize the relationship between development and human capital for urban regions. The literature review consists of migration models developed and used in previous studies and recent literature that together consider human capital and its flow with spatial analysis. A review of migration models helps structure the quantitative models’ building blocks, or the concepts to be quantified. Literature that discusses human capital and spatial analysis, at the same time, guides the study in implementing the most appropriate analysis technique. The literature discussed in the paper is focused on human capital migration and urban attractiveness. Its similarity with the current study work is the focus on the relationship between urban environment components and human capital. However, the cited studies lack the “spatial/relational” approach to urban regions which means that the effects of developments in settlements neighbouring the region were ignored. The contribution which we intend to make with the current study is to adapt the spatial econometric analysis to the problem of human capital attraction. Literature review is followed by data used in the empirical part of the study, and brief information on spatial econometric analysis. Next, findings of the empirical spatial econometric analysis of Turkey’s 81 urban regions are provided. Overall, the analysis indicated that undergraduate and post-graduate migrants care about the social prosperity of the neighbouring environment of destination province. The last part concludes with an interpretation of empirical study findings and discusses relevant urban and regional policy instruments.
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SKHVEDIANI, Angi E., Diana A. MAKSIMENKO, and Anastasiya A. MAIKOVA. "Econometric analysis of relationship between intellectual capital and gross profit margin of Russian IT companies from 2017 to 2020." Economic Analysis: Theory and Practice 21, no. 12 (December 28, 2022): 2272–92. http://dx.doi.org/10.24891/ea.21.12.2272.
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Subject. The article addresses relationship between intellectual capital and operating efficiency of IT companies. Objectives. Our aim is to conduct econometric analysis of the impact of intellectual capital and its individual elements on the profit margin of Russian IT companies. Methods. We employ methods of econometric analysis. The sample comprised 323 IT companies operating in Russia from 2016 to 2020. Results. We built two blocks of linear regression models with random and fixed annual and panel effects. For models of the first block, were selected indicators of structural (SCE), human (HCE), relational (RCE) capital efficiency and capital employed efficiency (CEE) as exogenous variables. The regression analysis showed that CEE and SCE have a significant positive effect on profit marginality. For models of the second block, we used a complex indicator, combining SCE, HCE, and RCE. We established that intellectual capital in general is positively associated with gross profit marginality of Russian IT companies. Conclusions. The study revealed that Russian IT companies effectively use the supporting intangible infrastructure and total assets. However, human capital, being the most significant resource of this industry, is used inefficiently and provides no potential for profit. Relationships with counterparties (consumers, suppliers, and other stakeholders), expressed in RCE, did not show a significant relationship with profitability either. Practical application of the findings may help improve business processes and management of intangible resources of IT companies.
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Mohammadi, Hosein, Samira Shayanmehr, and Juan D. Borrero. "Does Freedom Matter for Sustainable Economic Development? New Evidence from Spatial Econometric Analysis." Mathematics 11, no. 1 (December 28, 2022): 145. http://dx.doi.org/10.3390/math11010145.
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Achieving sustainable economic development is always considered one of the main economic goals of countries. Therefore, researchers are interested in presenting new econometric models for more accurate identification of factors affecting economic growth. The current study evaluates the impact of various aspects of freedom (economic freedom, press freedom, civil freedom, and political rights) and an aggregated freedom index on economic growth in European countries from 2000 to 2019 using spatial panel econometric techniques. In addition, the effects of variables such as FDI, financial development (FD), human capital (HC), and capital stock on economic growth are examined. The findings of this research confirm the existence of spatial autocorrelation in economic growth. The results reveal that civil liberties, economic and press freedom, and aggregated freedom boost economic growth, whereas political rights have no significant effect on economic growth. Furthermore, the econometric model results indicate that FDI, FD, HC, and capital stock are positively and significantly associated with economic growth. This research is expected to provide policymakers with a thorough understanding of how to implement the best policies in European countries to achieve sustainable economic development.
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Bereskin, C. Gregory. "Estimating Maintenance-of-Way Costs for U.S. Railroads After Deregulation." Transportation Research Record: Journal of the Transportation Research Board 1707, no. 1 (January 2000): 13–21. http://dx.doi.org/10.3141/1707-02.
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The movement of freight on railroads, like most transportation services, is subject to a number of restrictions that make costing of specific traffic a complex process. Among these restrictions are conditions of joint production; economies of scale, scope, and density; and a lack of data on specific expenditures as related to individual freight movements. Yet costing of specific movements is a desirable activity for shippers, railroads, and regulatory bodies. Traditionally, movement costing has involved the use of accounting-based allocative costing models such as the Uniform Rail Costing System developed by the Interstate Commerce Commission for use in regulatory hearings. Most econometric studies have aimed at characterizing the underlying economic nature of costs with little or no application to the cost of providing a specific service, and as such they may be of little use in costing specific traffic. Moving beyond the historic econometric costing models’ application of economic analysis, cost behavior is evaluated for a single sector of railroad activity. The process involves four steps. First, a consistent econometric model of total railroad expenditures is developed by applying a translog function within a multidimensional definition of railroad output. Second, the model is decomposed into individual partial-elasticity estimates relative to each of the several related intermediate output measures within the framework of a total differential of the cost function. Next, specific traffic movements are defined relative to the measures of rail output. Finally, the total differential is applied using several simplifying assumptions to yield estimates of incremental (marginal) costs for the specific traffic definition.
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Li, Xing, Liang Wang, and Bang Yuan Wu. "Research on Efficiency of Physical Capital and Human Capital in China's Economic Growth." Advanced Materials Research 468-471 (February 2012): 2970–73. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.2970.
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Research on economic growth in the past concerns only with physical capital and human capital in the absolute amount of effects at the expense of the efficiency of the present situation, we use the 1981-2008 China's annual time-series data, with uniform measurement to build econometric models to study China's economic growth in the efficiency of physical capital and human capital. Our research results indicate that in the long term, human capital is of much higher output efficiency than physical capital; In the short term, increased input ratio of human capital causes average labour output to grow sustainably, and increased input ratio of physical capital only between the 1th and 2nd period dues to rapid increase in average labour output and then declined rapidly.
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Комарова and Anna Komarova. "Human Capital Influence on Labor Productivity in Far Eastern Federal District." Economics 3, no. 1 (February 16, 2015): 48–50. http://dx.doi.org/10.12737/7812.
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A technique based on development of econometric models related to labor
productivity in regions of the Far Eastern Federal District of Russia has been
realized. It has been shown that such a factor as an employed population’s
education level is the important one in determining the labor productivity in the
regions of the Far Eastern Federal District of Russia.
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Ismagilova, Larisa, and Elvira Arylbaeva. "Labor productivity management: cognitive models of contradictions." Vestnik BIST (Bashkir Institute of Social Technologies), no. 2(55) (June 30, 2022): 154–61. http://dx.doi.org/10.47598/2078-9025-2022-2-55-154-161.
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The analysis of the research, demonstrating the interrelation between the efficiency of human resources management and economic results of the enterprise has been conducted. Causal relationship between human resource management and productivity is shown. Contradictions in the formation of human and labor resources are revealed. The defining role of human capital in the structure of intangible resources. The procedure of substantiation of the choice of HR-practices that involves the construction of a generalized cognitive model of the impact of intangible resources on productivity was formed. The structure of the system of labor productivity management is developed. The structure of the blocks of imitation model on the basis of econometric research data, the procedure of selection of the most important HR-factors is proposed. The possibility of substantiating the choice of control actions based on modeling results is shown. Causal scheme of labor productivity management through intangible resources of industrial enterprise is proposed. A set of econometric models built on the basis of generalization of empirical research and statistical data of specific enterprises was used to develop the model.
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Комарова and Anna Komarova. "Human Capital and Labor Productivity in the North-West Federal District of Russia." Economics 2, no. 6 (December 17, 2014): 12–14. http://dx.doi.org/10.12737/6728.
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A technique based on implementing of labor productivity’s econometric models
in regions of the North-West Federal District of Russia has been realized. It has
been shown that such a factor as employed population’s education level is
significant in labor productivity determining in the regions of the North-West
Federal District of Russia.
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Ruffin, Roy J., and Young Deak Yoon. "International Capital Movements In the Solow and Overlapping Generations Growth Models." Review of International Economics 1, no. 2 (June 1993): 123–35. http://dx.doi.org/10.1111/j.1467-9396.1993.tb00010.x.
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Sievka, Victoria, Igor Shevchuk, Aleksey Stepanov, and Oksana Tykhankina. "Application of cluster models in forecasting housing construction economic potential in the region." E3S Web of Conferences 217 (2020): 11006. http://dx.doi.org/10.1051/e3sconf/202021711006.
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The article introduces the first econometric modeling of the needs in new housing construction, reconstruction, capital repairs and finishing of uncompleted construction objects in the region on the basis of cluster models. Forecasting diagrams of gaps between the existing economic potential of housing construction and a normative need in sector housing as well as the need in introducing sector housing to reach mean European standards of housing are plotted.
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Shetty, Soumya, Janet Jyothi Dsouza, and Iqbal Thonse Hawaldar. "Rolling regression technique and cross-sectional regression: A tool to analyze Capital Asset Pricing Model." Investment Management and Financial Innovations 18, no. 4 (November 25, 2021): 241–51. http://dx.doi.org/10.21511/imfi.18(4).2021.21.
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The Capital Asset Pricing Model (henceforth, CAPM) is considered an extensively used technique to approximate asset pricing in the field of finance. The CAPM holds the power to explicate stock movements by means of its sole factor that is beta co-efficient. This study focuses on the application of rolling regression and cross-sectional regression techniques on Indian BSE 30 stocks. The study examines the risk-return analysis by using this modern technique. The applicability of these techniques is being viewed in changing business environments. These techniques help to find the effect of selected variables on average stock returns. A rolling regression study rolls the data for changing the windows for every 3-month period for three years. The study modifies the model with and without intercept values. This has been applied to the monthly prices of 30 BSE stocks. The study period is from January 2009 to December 2018. The study revealed that beta is a good predictor for analyzing stock returns, but not the intercept values in the developed model. On the other hand, applying cross-section regression accepts the null hypothesis. α, β, β2 ≠ 0. Therefore, a researcher is faced with the task of finding limitations of each methodology and bringing the best output in the model.
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Zheng, Xing You, and Peng Wang. "Research on the Effects of the Geographical Adjacency and Informatization Level on Input and Output of Regional Innovation - Based on a Spatial Econometrical Analysis of the 21 Cities in Guangdong Province." Advanced Engineering Forum 6-7 (September 2012): 459–67. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.459.
Full textAbstract:
Based on the diffusing theories of knowledge, this paper uses the data between 2006-2008 of the 21 cities in Guangdong province to conduct the exploratory data analysis, constructs the input-output model of innovation which take the informatization level of a region into account, and uses the common econometric model and spatial econometric models based on geographical adjacency between two regions, then compared the estimation results of these models. The systematic analysis shows that the innovation output of the 21cities is spatially correlated to each other, the result of the econometric model considered about the adjacency element is more precise than the common one, the accumulation of capital for innovation is the domain engine of innovation creating, the input of human and the enhancement of informatization level stimulate innovation weakly. However, when take the informatization level into account, the results of the new model are more precise. Based on the empirical research, this paper proposes several policy recommendations.
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Zhao, Guo Jie, Li Jie Jia, and Tie Feng Ma. "The Role of the Cities in the Western Economic Development." Advanced Materials Research 267 (June 2011): 227–29. http://dx.doi.org/10.4028/www.scientific.net/amr.267.227.
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Based on an annual panel for the western cities in China and system GMM method, this paper build the spatial econometric models to analyze if the same factors have the different impacts between the capital cities and the prefecture-level cities on their economic development. The results show that the capital cities more rely on their development path and less dependent on other cities of the same level; while the prefecture-level cities on the contrary.
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Juhl, Sebastian. "Measurement Uncertainty in Spatial Models: A Bayesian Dynamic Measurement Model." Political Analysis 27, no. 3 (November 9, 2018): 302–19. http://dx.doi.org/10.1017/pan.2018.35.
Full textAbstract:
According to spatial models of political competition, parties strategically adjust their ideological positions to movements made by rival parties. Spatial econometric techniques have been proposed to empirically model such interdependencies and to closely convert theoretical expectations into statistical models. Yet, these models often ignore that the parties’ ideological positions are latent variables and, as such, accompanied by a quantifiable amount of uncertainty. As a result, the implausible assumption of perfectly measured covariates impedes a proper evaluation of theoretical propositions. In order to bridge this gap between theory and empirics, the present work combines a spatial econometric model and a Bayesian dynamic item response model. The proposed model accurately accounts for measurement uncertainty and simultaneously estimates the parties’ ideological positions and their spatial interdependencies. To verify the model’s utility, I apply it to recorded votes from the sixteen German state legislatures in the period from 1988 to 2016. While exhibiting a notable degree of ideological mobility, the results indicate only moderate spatial dependencies among parties of the same party family. More importantly, the analysis illustrates how measurement uncertainty can lead to substantively different results which stresses the importance of appropriately incorporating theoretical expectations into statistical models.
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Басовская and Elena Basovskaya. "The Factor Productivity in the Pre-crisis Russian Economy." Economics 3, no. 3 (June 17, 2015): 19–23. http://dx.doi.org/10.12737/11578.
Full textAbstract:
To evaluate the factor productivity in the pre-crisis economy the econometric models were built. From the general level determination of the labor productivity models of 77.8%, the share of capital is 67%, the share of human capital — 8.4%, the share of new technologies — 1.4%. Effect of changes in the level of human capital on productivity surpasses the effect of changes in capital and the degree of diffusion of new technologies. In the pre-crisis period, the influence of the main production factors on the labor productivity was significantly decreased. The new tecnology have ceased to influence on productivity in general. The recession factor productivity in the country in the period 2010- 2013 may due to the formation under the impact of the adopted laws for the economic growth adverse institutional environment.
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Tkach, E. S., M. A. Firsova, and D. A. Fedotov. "Assessment of the Impact of Local Budgets on Regional Human Capital:Historical and Contemporary Aspects." Economy of regions 18, no. 1 (2022): 237–51. http://dx.doi.org/10.17059/ekon.reg.2022-1-17.
Full textAbstract:
Considering the need for sustainable human capital development in Russia, as well as interdisciplinary research challenges, the present study examines historical and contemporary aspects of the impact of the budget on regional human capital. For this purpose, budgetary mechanisms implemented in the period from 1969 to 2020 were retrospectively analysed. Based on archival materials and data from statistical collections of the Soviet period, the dynamics and structure of budget revenues and expenditures in the 1970s were compared with those in the period from 2000 to 2017. A quantitative assessment was performed to test a hypothesis about a relationship between the volume of social budget expenditures and increase in the return on human capital in the form of tax revenues to the budget. The study employed methods of comparative, structural, correlation and econometric analysis and statistical grouping. Constructed econometric models demonstrated the nature and degree of influence of various social expenditures on the resulting indicator of human capital development. Then, comparative analysis was conducted to interpret the econometric modelling results and data on the state of local budgets in the Soviet and post-Soviet period. Taking into account the established relationship between social expenditures and the indicator of human capital development, public authorities can most efficiently allocate budget funds, ensuring the maximum socio-economic effect from their investment. The research findings can be used for creating socio-economic development strategies of particular regions, as well as for comparing their social development in the historical and geographical context. In this regard, future studies can systematically assess the impact of local budgets of the largest Russian regions on the resulting indicators of human capital.
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Vidanage, Thushari N., Fabrizio Carmignani, and Tarlok Singh. "Predictability of Return Volatility Across Different Emerging Capital Markets: Evidence from Asia." South Asian Journal of Macroeconomics and Public Finance 6, no. 2 (October 23, 2017): 157–77. http://dx.doi.org/10.1177/2277978717727172.
Full textAbstract:
The importance of return volatility forecasts in policy formation and investment decision-making in emerging countries is growing considerably. However, from an operational perspective, there is no consensus in the literature on which econometric model has the best forecasting performance. To shed new light on this issue, this article compares forecasting models for a selected group of emerging Asian economies: India, Malaysia, Pakistan, Sri Lanka, Singapore and Thailand. Model’s performance is tested using both in-sample and out-of-sample forecasting methods. It is found that a relatively simple asymmetric EGARCH model clearly outperforms other models. JEL Classification: G12, G17
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Басовский, Leonid Basovskiy, Басовская, and Elena Basovskaya. "The Influence of the Factors of Production on Labor Income in the Pre-crisis Economy of Russia." Economics 3, no. 3 (June 17, 2015): 9–13. http://dx.doi.org/10.12737/11576.
Full textAbstract:
The econometric models constructed in work have established the basic production factors determining the level of the labor income in the country. Capital-labor, human capital and new technologies in 2010-2013 explained 71.6% of the labor income in the country. The effect of changes in the level of human capital on labor income surpasses the impact of changes and the degree of capital-diffusion of new technologies. In the pre-crisis period, the influence of the main production factors on the income of the employed population of Russia has declined under the influence of pass laws that formed unfavorable for economic development institutional environment.
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Cristea, Mirela, Graţiela Georgiana Noja, Nicu Marcu, Marian Siminică, and Diana-Mihaela Ţîrcă. "MODELLING EU BIOECONOMY CREDENTIALS IN THE ECONOMIC DEVELOPMENT FRAMEWORK: THE ROLE OF INTELLECTUAL CAPITAL." Technological and Economic Development of Economy 26, no. 6 (August 25, 2020): 1139–64. http://dx.doi.org/10.3846/tede.2020.13159.
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Given the global importance of bioeconomy for sustainable development and its trendiness in the knowledge driven literature, our research aims to develop a general assessment framework for several shaping factors of bioeconomy fundamentals within the European Union under the decisive impact of the intellectual capital credentials, namely educational attainment, research and development activities and innovation patterns. Considering that there is a high heterogeneity among Member States (MS), selectively regarding the implementation of the intellectual capital in the knowledge economy, but also a differential degree of bioeconomy advances, we have compiled distinct panels on the two groups of EU-28 MS, namely EU-15 (old MS) and EU-13 (new MS). The purpose is to examine the inferences of the intellectual capital in the context of economic development and to shape its role in achieving a sustainable bioeconomy. We have applied several macro-econometric procedures for each considered group, namely: multifactorial macro-econometric models, structural equation modelling (SEM) and Gaussian Graphical Models (GGM), for the period 1995-2016. The results highlight that education, innovation and research, along with main bioeconomy credentials, are at the core of economic development of both EU-13 and EU-15 countries, having distinctive dissimilarities between them, particularly enhanced for the new EU-13 MS.
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Gaweł, Krzysztof. "The amount of fair remuneration determined on the basis of the theory of measuring human capital." INTERNATIONAL JOURNAL OF EXPERIMENTAL RESEARCH AND REVIEW 17 (December 30, 2018): 1–7. http://dx.doi.org/10.52756/ijerr.2018.v17.001.
Full textAbstract:
The aim of the article is to compare the amount of remuneration expected by employees with the salary determined on the basis of the economic constant of potential growth. Using the theory of human capital, we are able to carry out a research consisting in a combination of remuneration resulting from the minimum wage. To achieve this, an econometric model containing three variables is introduced – the experience factor [Q(T)], the component of maintenance costs [K] and the cost element of education [E]. For the sake of clarity, individual measurement models of human capital are presented along with models of fair remuneration. The obtained results prove that the model of human capital presented in the study can be used to determine the level of fair wage.
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Mirolubova, Tatyana V., and Marina V. Radionova. "Assessing the Impact of the Factors in the Digital Transformation on the Regional Economic Growth." REGIONOLOGY 29, no. 3 (September 30, 2021): 486–510. http://dx.doi.org/10.15507/2413-1407.116.029.202103.486-510.
Full textAbstract:
Introduction. The scientific problem under consideration is of particular relevance due to the need to assess the impact of the factors in the digital transformation of the regional economy and in the economic growth on the economic development of the regions of the Russian Federation. Based on the research conducted, the article presents an econometric assessment of the dependence of the level of the gross regional product per capita in the regions of Russia on such factors as digital labor and digital capital. Materials and Methods. The authors analyzed panel data from the Federal State Statistics Service covering 87 regions of Russia for the period from 2010 to 2018. The research methodology is based on the use of the Cobb–Douglas production function, statistical and correlation data analysis, as well as on econometric methods for studying panel data. Results. To analyze the impact of the digital transformation of the economy on the regional economic growth of the regions of Russia, various models based on panel data have been considered, such as the pooled model, fixed effects models, random effects models, as well as time-varying effects models using dummy variables. Based on statistical criteria, the best model has been chosen and conclusions have been drawn about the nature of the impact of the digital transformation indicators on the gross regional product per capita in the regions of Russia. Discussion and Conclusion. The results of econometric modeling have demonstrated that digital factors in economic growth (digital labor, digital capital), along with common factors in economic growth (labor and capital), affect the regional economic growth. According to the regional data for the period from 2010 to 2018, the time fixed effects model has proved to be the best model of the impact of the factors in economic growth and digital transformation on the economic development of the regions of the Russian Federation. The research results can be used when developing a public policy aimed at stimulating the digital transformation of the regional economy.
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COOKE, STEPHEN C. "Wage and Industry Effects in U.S. Regional Incomes, 1840 to 1987: A CES Wage Index Method." Journal of Economic History 63, no. 4 (December 2003): 1131–46. http://dx.doi.org/10.1017/s0022050703002559.
Full textAbstract:
The Solow growth and the Heckscher-Ohlin trade models describe two competing processes through which regional incomes converge over time. Solow's model attributes rising productivity of labor to additional regional capital investments. Heckscher-Ohlin's trade model ascribes the relocation of high value industries to regions with low wage rates. On the other hand Paul Krugman expects incomes to diverge over time as regions with an initial advantage maintain it through ever increasing external economies of scale. The Solow and Heckscher-Ohlin models imply that incomes converge through the movement of high quality labor and capital and high value goods and services into low income regions respectively.
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Boshoff, Douw Gert Brand. "Empirical analysis of space and capital markets in South Africa: A review of the REEFM- and FDW models." South African Journal of Economic and Management Sciences 16, no. 4 (November 29, 2013): 383–94. http://dx.doi.org/10.4102/sajems.v16i4.359.
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This paper assesses the different models, in conjunction with the different theories surrounding the distinction and interdependencies between space- and capital markets. First, the theory of space- and capital markets is discussed with reference to two models, the FDW and the REEFM models. The FDW model provides a diagrammatic explanation of the behaviour of the property market, while the REEFM is an econometric model based on statistical principles that are able to forecast property-market behaviour by interpreting specific given variables. The REEFM model as the perceived more sophisticated model, un-tested in South Africa, was then analysed to test its applicability in the South African context. The findings confirmed the applicability of the model, although one part is not confirmed and is suggested for further research.
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Fitri, Nurul, and Sasqia Putri. "Effect of Capital Expenditure and Personnel Expenditure on Regional Economic Growth: Empirical evidence from Western Indonesia." Jurnal EMT KITA 3, no. 1 (June 25, 2019): 34. http://dx.doi.org/10.35870/emt.v3i1.94.
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This study aims to analyze the effect of capital expenditure and personnel expenditure on regional economic growth in western Indonesia. The data used is a panel data of 10 provinces during the period 2008-2015. The econometric models used to analyze the functional relationship of these variables consisted of the fixed effect method of panel regression, and the Granger causality test. The study found that capital expenditure has a positive but not significant effect on regional economic growth. Conversely, personnel expenditure has a positive and significant effect. Granger causality test results indicate a one-way causality from personnel expenditure and capital expenditure to economic growth and from personnel expenditure to capital expenditure.Keywords: Economic Growth, Capital Expenditure, Personnel Expenditure, Panel Regression and Granger causality test
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Басовская and Elena Basovskaya. "Impact of Production Factors on Labour Income in Modern Russia." Economics 4, no. 1 (February 18, 2016): 29–33. http://dx.doi.org/10.12737/17718.
Full textAbstract:
The paper builds econometric models that allow us to evaluate the influence
of the main productionfactors, defining the level of labour income in the country.
Capital/labour ratio, human capital and new technology explain over 70%
of earned income. The effect of changes in the level of human capital on labor
income surpasses the effect of changes in capital/labour ratio.The impact
of capital/labour ratio has been steadily declining, whereas the influence of human
capital and new technologies has been increasing. These arenew factors, the
most important ones for the development of post-industrial economy. The growth
of their influence shows that the economic system of the country adapts to the
prevailing institutional conditionsunfavorable for Russia’s industrial economy.
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Baranova, Nina, Sergey Larin, and Evgeny Khrustalyov. "Econometric models for estimating current and forecast values of the level of human capital development in the Russian economy." InterCarto. InterGIS 26, no. 1 (2020): 52–67. http://dx.doi.org/10.35595/2414-9179-2020-1-26-52-67.
Full textAbstract:
Studies of factors of sustainable economic development in modern conditions are highly relevant for Russia due to the constant increase and tightening of sanctions restrictions. They have a negative impact on the introduction of innovative developments and economic growth, and reduce the competitiveness of Russian enterprises and their products on world markets. Human capital can become one of the key factors for countering sanctions restrictions, improving the efficiency of economic development and gaining additional competitive advantages for domestic enterprises and the economy as a whole. Assessing the impact of human capital on the sustainable development of the economy is difficult, since it is one of the specific forms of capital. When making appropriate measurements, economic scientists rely on a number of developed theoretical methods and practical tools that support them, which allow us to obtain fairly accurate values of the human capital development index (HDI) based on statistical data. First of all, this is the current UN methodology for calculating the HDI indicator, as well as modern software systems OriginPro-8.6 and Eviews-10.0, which have sufficiently advanced functionality for performing calculations. Russia today has all the necessary prerequisites and opportunities for progressive social and economic development. However, the formation of econometric models will help to timely determine the current and forecast values of the level of human capital development for individual enterprises, industries, and the country’s economy as a whole. This paper shows the practical application of the econometric tools of all the above approaches to obtain the calculated values of the HDI indicator for different time periods and different scenarios for the development of the Russian economy. The results obtained confirmed the high practical significance of the tools used and the acceptable accuracy of the calculations. However, the current and forecast values of the level of human capital development alone will not be able to ensure the effective development of the Russian economy. On the contrary, the effective use of human capital in the implementation of import substitution strategies and national projects will allow our country to become one of the world’s leading economic development countries.
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Fernández, Viviana. "Determinants of Firm Leverage in Chile: Evidence from Panel Data." Estudios de Administración 12, no. 1 (February 5, 2020): 41. http://dx.doi.org/10.5354/0719-0816.2005.56455.
Full textAbstract:
There is an extensive literature on the determinants of capital structure for developed countries, but little has been said about emerging economies. This article analyzes the driving forces of capital structure in Chile for the period 1990-2002. We study interest-bearing liabilities for firms classified by economic sectors. Our results give more support to the trade-off theory than to the pecking-order hypothesis.
The contribution of our work is also methodological. Our econometric specification is based on a random-effects panel data model for censored data developed by Anderson (1986) and extended by Kim and Maddala (1992). We extend Anderson-Kim-Maddala’s work to panel data models for uncensored data, and devise specification tests for non-nested random-effects models. Most literature on capital structure focuses on the cross-section variation of the data by averaging observations over time.
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Комарова, Anna Komarova, Кальянов, and Aleksandr Kalyanov. "Human Capital and Labor Productivity in North Caucasian Federal District of Russia." Economics 3, no. 1 (February 16, 2015): 31–35. http://dx.doi.org/10.12737/7810.
Full textAbstract:
A technique based on Russia regions’ economic development analysis (on the
example of human capital and labor productivity in the North Caucasian Federal
District of Russia) by means of creation of econometric models related to labor
productivity in regions of the North Caucasian Federal District of Russia has
been realized. It has been shown that such a factor as an employed population’s
education level is the important one in determining the labor productivity in the
regions of the North Caucasian Federal District of Russia.
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Басовская and Elena Basovskaya. "Impact of Human Capital, Science and Innovation on Labour Productivity in Russia." Economics 3, no. 4 (August 10, 2015): 37–41. http://dx.doi.org/10.12737/12777.
Full textAbstract:
A program and methodology of the empirical study of the effect of human
capital, science and innovation on productivity and economic growth are
exemplified on modern Russian economy. To identify and quantify the impact of
factors related to human capital, innovation, science, labor productivity in the
country and its regions the author proposes to build econometric models using
cross-sectional data of regional statistics. It makes possible to obtain data and
forecast sizes of elasticity of labor productivity on the factors connected with
the human capital, science and innovations, the country and its regions. This
will generate a reasonable economic policy, policy of education and science
aimed at economic growth.
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Biørn, Erik. "VAR INTERPRETATIONS OF HAAVELMO’S MARKET MODEL OF CAPITAL AND INVESTMENT." Econometric Theory 31, no. 2 (June 27, 2014): 195–212. http://dx.doi.org/10.1017/s0266466614000267.
Full textAbstract:
In the paper attempts are made to integrate two parts of Trygve Haavelmo’s work: investment theory and dynamic econometric models of interrelated markets. Specifically, the duality in the representation of the capital service price and the capital quantity in relation to the investment price and quantity are brought to the forefront and confronted with elements from simultaneous equation modeling of vector autoregressive systems containing exogenous variables (VARX), using linear four-equation models. The role of the interest rate and the modeling of the expectation element in the capital service price and the capital’s retirement pattern, and their joint effect on the model’s investment quantity and price dynamics are discussed. Stability conditions are illustrated by examples. Extensions relaxing geometric decay and ways of accounting for forward-looking behavior, including rational expectations, are outlined. Some remarks on the theory-data confrontation of this kind of model are given.
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Mumtaz, Haroon, and Francesco Zanetti. "THE EFFECT OF LABOR AND FINANCIAL FRICTIONS ON AGGREGATE FLUCTUATIONS." Macroeconomic Dynamics 20, no. 1 (December 29, 2014): 313–41. http://dx.doi.org/10.1017/s1365100514000406.
Full textAbstract:
This paper embeds labor market search frictions into a New Keynesian model with financial frictions. The econometric estimation establishes that labor market frictions substantially improve the empirical fit of the model. The effect of the interaction between labor and financial frictions on aggregate fluctuations depends on the nature of the shock. For monetary policy, technology, and entrepreneurial wealth shocks, labor market frictions amplify the effect of financial frictions, because robust changes in hiring lead to persistent movements in employment and return on capital that reinforce the original effect of financial frictions. For cost-push, labor supply, marginal efficiency of investment, and preference shocks, labor market frictions dampen the effect of financial frictions by reducing the real cost of repaying existing debt, which lowers the external finance premium.
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Bauwens, Michel, and Vasilis Kostakis. "From the Communism of Capital to Capital for the Commons: Towards an Open Co-operativism." tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society 12, no. 1 (April 3, 2014): 356–61. http://dx.doi.org/10.31269/triplec.v12i1.561.
Full textAbstract:
Two prominent social progressive movements are faced with a few contradictions and a paradox. On the one side, we have a re-emergence of the co-operative movement and worker-owned enterprises which suffer from certain structural weaknesses. On the other, we have an emergent field of open and Commons-oriented peer production initiatives which create common pools of knowledge for the whole of humanity, but are dominated by start-ups and large multinational enterprises using the same Commons. Thus we have a paradox: the more communist the sharing license used in the peer production of free software or open hardware, the more capitalist the practice. To tackle this paradox and the aforementioned contradictions, we tentatively suggest a new convergence that would combine both Commons-oriented open peer production models with common ownership and governance models, such as those of the co-operatives and the solidarity economic models.
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Bauwens, Michel, and Vasilis Kostakis. "From the Communism of Capital to Capital for the Commons: Towards an Open Co-operativism." tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society 12, no. 1 (April 3, 2014): 356–61. http://dx.doi.org/10.31269/vol12iss1pp356-361.
Full textAbstract:
Two prominent social progressive movements are faced with a few contradictions and a paradox. On the one side, we have a re-emergence of the co-operative movement and worker-owned enterprises which suffer from certain structural weaknesses. On the other, we have an emergent field of open and Commons-oriented peer production initiatives which create common pools of knowledge for the whole of humanity, but are dominated by start-ups and large multinational enterprises using the same Commons. Thus we have a paradox: the more communist the sharing license used in the peer production of free software or open hardware, the more capitalist the practice. To tackle this paradox and the aforementioned contradictions, we tentatively suggest a new convergence that would combine both Commons-oriented open peer production models with common ownership and governance models, such as those of the co-operatives and the solidarity economic models.
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Barbosa, Natália. "Portuguese farming firms´ growth: do human capital and managerial capabilities matter?" New Medit 19, no. 1 (April 10, 2020): 101–16. http://dx.doi.org/10.30682/nm2001g.
Full textAbstract:
This paper examines the underlying factors that might shape firm’s growth in the farming sector. In par-ticular, we investigate the effects of human capital and managerial capabilities on growth of Portuguese farming firms during 2003-2007. Relying on econometric models that control for survivorship bias, the results indicate that younger and top-educated employees are likely to foster farming firm’s growth. On the other hand, the effect of managerial capabilities appears to be somewhat weak on firms without separation between ownership and management. The flexibility to hire specialised and multidisciplinary management teams with managerial capabilities appears to yield economic payoffs on the farming sector.
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Ivchenko, Yu S. "Determination of the main factors of the gross regional product level by econometric modeling methods for the totality of regions of the Russian Federation." Statistics and Economics 16, no. 6 (December 26, 2019): 4–18. http://dx.doi.org/10.21686/2500-3925-2019-6-4-18.
Full textAbstract:
The purpose of the research is to identify factors that determine the level of gross regional product, using the construction of econometric models. In terms of the economic theory the volume of gross added value of the region depends on existence of resources, efficiency of use of resources, level of effective demand for the consumption of gross added value, level of export, structure of the regional economy. In the article, by constructing econometric models with a different set of factors, the most essential and statistically significant factors determining the level of gross regional product were identified.Materials and methods. Official data of Federal State Statistics Service for 2016 formed empirical base of the research. The aggregate of the constituent entities of the Russian Federation was considered as a statistical aggregate as an object of study, and both the complete aggregate of subjects and the aggregate of entities with a gross regional product level of less than and more than a trillion rubles were studied. Research method is econometric modeling of gross regional product based on spatial data on constituent entities of the Russian Federation. The parameters of the multiple linear regression models in absolute values and in logarithms were estimated using the least squares method. To test the null hypotheses, a five percent significance level was adopted. Interval estimation of model parameters was carried out taking into account standard errors consistent under heteroskedasticity. The quality of models was defined by coefficient of determination, mean relative error of approximation, Ramsey’s test checking a null hypothesis about lack of the passed variables in model. Implementation of the research was carried out in the RStudio software product.Results. Eight qualitative models of multiple linear regression are constructed. Two models are constructed on the general set of constituent entities of the Russian Federation: 1) model in absolute values with three quantitative signs and one attributive sign characterizing group of entities on the level of a gross regional product; 2) three-factor model in logarithms. Two models are constructed on set of entities with a gross regional product less than one trillion rubles: 1) model in absolute values with seven quantitative signs, five of which were statistically significant; 2) four-factor model in logarithms. Four two-factor models are constructed on set of entities with a gross regional product more than one trillion rubles.Conclusion. In all constructed models the most significant factors of the level of gross regional product are: a) factor of fixed capital (average annual residual cost of fixed assets); b) factor of effective demand (expressed by one of the following indicators: social expenses of the budget, total income of the population, wage fund); c) factor of level of financial resources (expressed by the volume of average annual balances on ruble accounts of legal persons and balance of incomes and expenses of the enterprises and organizations). At creation of econometric models statistically insignificant were factors of resource efficiency (capital productivity, labor productivity, profitability), factors characterizing the volume of foreign economic activity and a share of the extractive industries. The economy of the regions in 2016 can be described as an economy of an extensive type, focusing on the use of domestic capital and financial resources.
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Басовская and Elena Basovskaya. "Effects of Human Capital on Profits of Russia’s Enterprises and Organizations." Economics 3, no. 5 (October 19, 2015): 17–19. http://dx.doi.org/10.12737/13589.
Full textAbstract:
Through econometric models construction the author evaluates the effects of
capital-labor ratio and human capital, where the latter is characterized by the
employees’ educational level, on profits of enterprises and organizations,
operating in Russia. In 2009 the capital-labor ratio and the human capital, as
estimated by the employees’ educational level, could be considered responsible
for no less, than 39% of profitability of enterprises and organizations. For the
most part this effect is due to the capital-labor ratio, while the lesser, though
essential part of the said effect is due to the employees human capital. It is
shown, that the elasticity of profit in terms of employees human capital exceeds
manifold the profit elasticity in terms of capital-labor ratio, meaning that the
effect of changes in human capital level on the labor productivity exceeds
manifold that of changes in capital-labor ratio. Therefore, to enhance the human
capital through better education of employees is more beneficial, than to
increase investments in basic capital assets.