scholarly journals The Impact of Foreign Direct Investment on Income Convergence in China - A Spatial Panel Data Analysis

2021 ◽  
Vol 4 (4) ◽  
pp. p1
Author(s):  
Di Zhu ◽  
Yefei Li ◽  
Ejimofor Bruno Chiedozi ◽  
Hui Pan
Keyword(s):  
Economic Growth ◽  
Growth Factors ◽  
Panel Data ◽  
Population Growth ◽  
Regional Economic Growth ◽  
Income Convergence ◽  
Fixed Asset ◽  
Spatial Durbin Model ◽  
Regional Economic ◽  
Fixed Asset Investment

After taking into account the spatial dependence effects in the panel data consisting of all 31 provinces, direct-controlled municipalities, and autonomous regions in China between the years 1998 and 2017, it found significant spatial autocorrelation effects in both traditional absolute and conditional β income convergence models. At the national level, using the spatial econometric models (Spatial Error Model for absolute convergence and Spatial Durbin Model for conditional convergence), the analysis shows that in the past 19 years from 1999 to 2017, there is no absolute β income convergence. However, there is conditional β income convergence after controlling for all growth factors, while the positive effect of fixed asset investment on regional economic growth is significant, and the effect of population growth is significantly negative. The other growth factors such as FDI inflow, export, and higher education enrollment were surprisingly found no statistically significant effects on regional economic growth. From regional level (Spatial Durbin Model and Spatial Lag Model), there is no conditional β income convergence within each four economic regions. Nonetheless, the northeast region showed an income divergence trend, where only the fixed asset investment is positively significant. This study results imply that China should continue to improve fixed asset investment and control population growth to stimulate regional economic growth and income convergence.

Assessing the Impact of the Factors in the Digital Transformation on the Regional Economic Growth

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (3) ◽  
pp. 486-510
Author(s):  
Tatyana V. Mirolyubova ◽  
Marina V. Radionova
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Digital Transformation ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
The Russian Federation ◽  
Regional Product ◽  
The Impact ◽  
Regions Of Russia

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.

scholarly journals Model Pertumbuhan Ekonomi Indonesia: Peranan Ketergantungan Spasial

2019 ◽  
Vol 19 (1) ◽  
pp. 62-83
Author(s):  
Aspiansyah Aspiansyah ◽  
Arie Damayanti
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Growth Model ◽  
Spatial Dependence ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
Spatial Spillover ◽  
Economic Growth Model ◽  
Per Capita

This study aims to examine the role of spatial dependence on Indonesia’s regional economic growth based on panel data of all provinces in Indonesia during 1990–2015. By using spatial durbin model, the authors found that spatial dependence plays an important role in achieving regional economic growth in Indonesia. Indonesia’s regional economic growth model that controls spatial dependence, yields better estimates than growth model that does not control spatial dependence. The researchers also found positive spatial spillover to Indonesia’s regional economic growth sourced from other region’s economic growth and initial per capita incomes, as well as population growth in other regions. ============================ Penelitian ini bertujuan untuk mengkaji peranan ketergantungan spasial terhadap pertumbuhan ekonomi regional Indonesia berdasarkan data panel seluruh provinsi di Indonesia selama tahun 1990–2015. Dengan menggunakan model durbin spasial, penulis menemukan bahwa ketergantungan spasial berperan penting dalam pencapaian pertumbuhan ekonomi regional di Indonesia. Model pertumbuhan ekonomi regional Indonesia yang mengontrol ketergantungan spasial menghasilkan estimasi yang lebih baik daripada model pertumbuhan ekonomi regional Indonesia yang tidak mengontrol ketergantungan spasial. Peneliti jugamenemukan terjadinya spatial spillover yang positif terhadap pertumbuhan ekonomi regional Indonesia yang bersumber dari pertumbuhan ekonomi wilayah lain, pendapatan per kapita awal dari wilayah lain dan pertumbuhan penduduk wilayah lain.

scholarly journals Human Capital and Regional Economic Growth in Russia

2021 ◽  
Vol 17 (2) ◽  
pp. 57-80
Author(s):  
Boris Alekhin
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Panel Data ◽  
Capital Accumulation ◽  
Positive Impact ◽  
Regional Economic Growth ◽  
Human Capital Accumulation ◽  
Regional Economic ◽  
Long Run ◽  
Per Capita

This study examines the contribution of human capital accumulation to regional economic growth using panel data for 82 subjects of the Russian Federation over 2002–2019. This paper aims to test the hypothesis that in the long-run equilibrium there exists a connection between economic growth and human capital accumulation in the regions of Russia. From the point of view of econometrics, it would mean that we should refute the hypothesis that there is no cointegration of time series describing the aforementioned variables. General theoretical framework was drawn from the neoclassical growth theory, and panel data econometrics suggested the appropriate empirical methodology. Pooled mean group and fully modified least squares estimators were applied to an autoregressive distributed lags model based on the Solow model. The results indicate that accumulation of human capital has a positive and statistically significant long-term impact on the rate of growth of per capita income and that these variables are cointegrated. Such calculations allow us to make the following conclusions: per capita GRP is cointegrated with physical and human capital on the regional level. The cointegrating equation ‘explained’ more than 90% of per capita GRP variance. Human capital accumulation had a significant positive impact on per capita GRP growth in the long run; such impact exceeded the impact of physical capital accumulation. The positive impact of human capital accumulation on per capita GRP growth surpassed the negative elasticity of growth GRP by the amount of resource excluded from the real sector to provide support to students and maintain the regional education system. The paces at which regional economies were heading towards the steady state differed which is an evidence that there exist an incredible manifold of ways and means for regions to adjust to disbalancies

scholarly journals Vertical Fiscal Imbalance and Regional Economic Growth

2020 ◽  
Vol 12 (6) ◽  
pp. 39-53
Author(s):  
B.I. Alekhin ◽  
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fiscal Federalism ◽  
Fiscal Decentralization ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
Fiscal Imbalance ◽  
Vertical Fiscal Imbalance ◽  
The Impact

This study examines the impact of fiscal decentralization on regional economic growth using panel data for 82 subjects of the Russian Federation for the period 2005-2018. General theoretical framework was drawn from the second-generation theory of fiscal federalism, and panel data econometrics suggested the appropriate empirical model and estimation method. The pooled mean group method was used to estimate an autoregressive distributed lags model based on Solow-Swan theory of economic growth. The results indicate that vertical fiscal gap has a negative and significant long-term impact on regional economic growth while vertical fiscal imbalance has a positive and significant long-term effect. The study is consistent with the modern theory of fiscal federalism, W.E. Oates’ matching hypothesis and previous empirical work using Russian data. The study also found evidence of conditional convergence of regional economies.

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