nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2018‒09‒10
eight papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Knowledge-Driven Economic Growth: The Case of Sub-Saharan Africa By Stephen Oluwatobi; Isaiah Olurinola; Philip Alege; Adeyemi Ogundipe
  2. Technological change and economic development: endogenous and exogenous fluctuations By Marianna Epicoco
  3. Income Segregation and Rise of the Knowledge Economy By Enrico Berkes; Ruben Gaetani
  4. Economic Growth in Transition Economies: Does investments matter? By Sulkhan Tabaghua
  5. Financial and economic mechanisms of promoting innovative activity in the context of the digital economy formation By Mikhail Yakovlevich Veselovsky; Tatiana Vitalievna Pogodina; Raisa Vasilyevna Ilyukhina; Tatyana Anatolyevna Sigunova; Nina Fedorovna Kuzovleva
  6. Putting China in perspective: a comparative exploration of the ascent of the Chinese knowledge economy By Rodríguez-Pose, Andrés; Wilkie, Callum
  7. TECHNOLOGY NETWORK, INNOVATION AND GROWTH By Jingong Huang
  8. Innovation, Knowledge Diffusion, and Selection By Danial Lashkari

  1. By: Stephen Oluwatobi (Covenant University, Nigeria); Isaiah Olurinola (Covenant University, Nigeria); Philip Alege (Covenant University, Nigeria); Adeyemi Ogundipe (Covenant University, Nigeria)
    Abstract: The experience of South Korea, India, China and Singapore reveals that developing economies can fasttrack development, leapfrog the stages of development and catch up with advanced economies by putting knowledge capital as the driver of development. If the knowledge economy is therefore an accelerant of development for both advanced and developing economies, it is possible for Sub-Saharan African (SSA) economies to also catch up with advanced economies. It was on this basis that this study assessed the knowledge capacity of SSA and the effect it has on its economic advancement. Given the importance of the interrelatedness among the knowledge economy elements, this study, thus, examined how the interaction effect between the elements of the knowledge economy affects economic growth in 32 SSA countries, for which data were available, over the period of 17 years (1996-2012). Using the System Generalized Method of Moments (SGMM), the study found out that institutions and human capital in SSA mitigate the effect of innovation on economic growth in the region, thus, making it a lean knowledge economy.
    Keywords: Economic Growth; Human Capital; ICT; Innovation; Institutions; Knowledge Economy
    JEL: O10 O30 O38 O55 O57
    Date: 2018–01
    URL: http://d.repec.org/n?u=RePEc:agd:wpaper:18/030&r=knm
  2. By: Marianna Epicoco
    Abstract: This paper aims at exploring the endogenous and exogenous forces that determine long-run fluctuations of innovative and economic activity. It proposes that technological paradigm shifts, structural change and major fluctuations of production are the result of the same endogenous process. This is defined as a co-evolutionary process between technological and economic variables based on cumulative multiplier and accelerator feedback effects between investments in innovation and demand. Exogenous factors are supposed to act upon this endogenous process, influencing the length and amplitude of fluctuations. This framework contributes to extant literature as it envisages an explicit endogenous mechanism explaining cyclical fluctuations of innovative and economic activity, and, at the same time, incorporates exogenous factors. Moreover, by combining the Schumpeterian analyses of innovation dynamics with the multiplier and accelerator effects coming from Keynesian theories, the framework integrates the impact of technological variables on economic activity and vice versa. To provide a preliminary supporting evidence, we have fitted the ICT cycle and the economic cycle to patent and productivity data, respectively. Our results suggest that the growth potential of ICT could be declining. This situation may represent an important opportunity, for public policy and socioinstitutional actors, to orient future development toward socially desirable directions.
    Keywords: technological paradigm shift, structural change, economic fluctuations, co-evolution, productivity slowdown, ICT.
    JEL: O33 O40 O11 E32
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:ulp:sbbeta:2018-34&r=knm
  3. By: Enrico Berkes (Northwestern University); Ruben Gaetani (University of Toronto)
    Abstract: We analyze the effect of the rise of knowledge-based activities on spatial inequality within U.S. cities, exploiting the network of patent citations to instrument for local trends in innovation. We find that innovation intensity is responsible for 20% of the overall increase in urban segregation between 1990 and 2010. This effect is mainly driven by the clustering of employment and residence of workers in knowledge-based occupations. We develop and estimate a spatial equilibrium model to quantify the contribution of productivity and residential externalities in explaining the observed patterns. Endogenous amenities account for two thirds of the overall effect. We illustrate the relevance of the model for policy analysis by studying the impact of four proposed projects for Amazon’s HQ2 on the structure of Chicago.
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:red:sed018:213&r=knm
  4. By: Sulkhan Tabaghua (Doctoral Student, Faculty of Economics and Business Ivane Javakhishvili Tbilisi State University (TSU))
    Abstract: Many countries from the beginning of transition period tried to find answer of Adam Smith fundamental question, ?how countries get rich??. Thus, main goals of all economic reforms, since 1989-1990 years until now in countries with transition economic for stimulation economic growth. All transition states have two way of development ?Shock Therapy? and ?Gradualism? for faster implementation free market based economic system.Countries that are characterized as transition economies, with the inefficient political or economical system investment will play a less prominent role in stimulating the economy than in the developed countries. Given these peculiarities, investments have lesser role in stimulation economic growth in countries with transition than macroeconomic policies, structural reforms, protection of property right.Countries? from the start of the transition period or from the time of became independent, economic policy focus on attracting investments for stimulation economic growth, but the height role of investment is not confirmed in examples of many countries, which indicates that the economic growth in countries of transition is not related to the number of invitations attracted by the country. Our research is developed based on Oleh Havrylyshyn, Ivailo Izvorski, Ron van Rooden study ?Recovery and Growth in Transition Economies 1990-97: A Stylized Regression Analysis?. IMF, 1998. Which include inflation rate, structural reform, share of government expenditure in GDP; investment; price liberalization index; competition index; exchange rate and privatization index as an independent variables, dependent variable is real economic growth (GDP). 31 countries as transition economic are selected based on World Economic Outlook, October 2000, IMF. Dates (1997-2014) used in econometric models came from different publications of IMF, EBRD and WB collected by author.Statistical characteristics of 12 models satisfy the necessary requirements for the evaluation, namely R2 are presented in 0.21 (minimum) and 0.43 (maximum) interval. Other statistics are also used for assessing the model: Akaike info criterion; Schwarz criterion; Hannan-Quinn Criter; Durban-Watson and F-statistics. In those models are analyzed different combination of independent variables.Panel model where the analyzed period is divided into two parts (1997-2004; 2004-2014), It is important to note that in these models all variables of investment are characterized by negative correlation with economic growth, statistical characteristics of models analyzed during the 2004-2014 data are considerably improved compared to the previous model.Inflation, governmental expenditures, price liberalization index, competition policy, exchange regime, investment has negative impact on economic growth, but structural reforms in important factor for stimulation economic growth rate in all models.
    Keywords: transition economy; economic growth, investment, structural reforms.
    JEL: C01 P20 P21
    Date: 2018–07
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:7809587&r=knm
  5. By: Mikhail Yakovlevich Veselovsky (University of Technology); Tatiana Vitalievna Pogodina (Financial University under the Government of the Russian Federation); Raisa Vasilyevna Ilyukhina (Moscow Technological University); Tatyana Anatolyevna Sigunova (Moscow Technological University); Nina Fedorovna Kuzovleva (Moscow Technological University)
    Abstract: The paper analyzes some financial, tax, information, communication, infrastructural, technological and organizational mechanisms of innovative activity promotion in conditions of transition to a digital economy. End-to-end technologies including "Big Data", "New Production Technologies", "Quantum Technologies", "Technologies of Virtual and Augmented Realities", the possibilities of their application in various sectors of the national economy were singled out and analyzed. The role of end-to-end technologies in the development of the Russian economy and promotion of innovative activities of companies was studied. A comparative analysis of the main indicators of informatization of the society of Russia and some leading foreign countries for the period of 2005-2015 was carried out. The conclusions were made about an insufficient use of the Internet in Russia, primarily in rural areas, which hindered the social progress of Russian society. The leading role of digital (information) technologies in solving social problems, including education, social services and healthcare, was defined. The necessity of development of electronic services in the sphere of education and health was proved. Ways of cluster development based on the example of the Kaluga Region in the development of digital technologies were studied. The influence of development institutions on stimulating innovation activity in Russia was analyzed.
    Date: 2018–03–30
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-01829712&r=knm
  6. By: Rodríguez-Pose, Andrés; Wilkie, Callum
    Abstract: This article traces the ascent of China from knowledge economy laggard to world leader over the last two decades, using a comparative perspective. Chinese trends in R&D and patenting are compared to those of the countries of the ‘triad’ (the European Union, Japan and the US), as well as to those of other large emerging economies (Brazil, India, Mexico and South Africa). The analysis demonstrates how both in innovation inputs and outputs China reflects an innovation reality closer to that of the most developed areas of the world than to that of other emerging countries. However, the rapid ascent of Chinese innovation has generated a distinct set of territorial dynamics, with innovation much more geographically concentrated than elsewhere in the world and more reliant on agglomeration forces than on more traditional ‘innovative’ drivers. Such a distinct geography of innovation may have until now facilitated the innovation surge in China, but poses serious future risks in terms of the sustainability of the system.
    Keywords: innovation; knowledge economy; R&D; patenting; regions; China
    JEL: N0
    Date: 2016–11–01
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:84294&r=knm
  7. By: Jingong Huang (University of Melbourne)
    Abstract: This paper develops a multi-sector endogenous growth model which embeds a technology network that captures heterogeneous intersectoral knowledge spillovers. Each sector serves both as a distributor and a consumer of knowledge: the former depends on a sector's position in the network; the latter depends on its efficiency in utilising knowledge. The interaction of these forces influences long-run economic growth, sectoral shares and the firm size distribution. The sparsity of the network imposes an upper bound on the impact of knowledge spillovers. In this model, sectors converge to the same growth rate if they belong to the same irreducible network. However, their contributions to economic growth differ substantially, depending on their positions in the technology network and their efficiency in conducting innovation. Consequently, the model has implications for the allocation of innovation subsidies. The gain in economic growth derived from promoting innovation in the sector that utilises knowledge most efficiently is over 10,000 times larger than gain derived from promoting innovation in the least efficient sector.
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:red:sed018:178&r=knm
  8. By: Danial Lashkari (Yale University)
    Abstract: This paper constructs a theory of industry growth through innovation and selection-driven creative destruction. Firms’ ideas determine their productivity and stochastically evolve over time. Firms innovate to improve their ideas and endogenously exit if unsuccessful. Entrants adopt the ideas of incumbents. In this model, when better ideas are innovated or adopted, they selectively replace worse ideas. Innovation externalities vary based on firm productivity: ideas generated by more productive firms create 1) longer-lasting positive externalities due to knowledge diffusion and 2) stronger negative externalities due to dynamic displacement of other firms. Therefore, the net external effect of innovation on aggregate productivity is heterogeneous and market equilibrium misallocates investments across firms. The solution to the social planner's problem suggests that optimal innovation policy instruments should depend on firm productivity. Quantitatively, the misallocations are large when the model is calibrated to firm-level data from US manufacturing and retail trade, and imply first-order considerations for the design of innovation policy.
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:red:sed018:337&r=knm

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