scholarly journals Economic Growth Convergence of Indonesia and 10 Main Trading Partner Countries

2021 ◽  
Vol 8 (5) ◽  
pp. 49-54
Author(s):  
Titin Siti Mahfudhotin Amin
Keyword(s):  
Economic Growth ◽  
Trading Partner ◽  
Growth Convergence

Overview of Global Development Patterns

2014 ◽  
pp. 1-23
Keyword(s):  
Economic Growth ◽  
Economic Theory ◽  
Income Distribution ◽  
Growth Trajectory ◽  
Future Trends ◽  
Global Development ◽  
Growth Trends ◽  
Development Patterns ◽  
Growth Convergence ◽  
Global Growth

This chapter introduces readers to growth economies and discusses why studies on economic growth are important. It proceeds to identifying global growth trends in the last four decades and provides a summary of world's income distribution. A concise survey of the convergence debate (which seems to have lost its prominence now) is also presented. The summary of some influential studies on income and growth convergence, however, states that the world's incomes have largely diverged, although convergence has been noted in at least two pockets of countries. Because the details are presented later in the text, only a brief summary of how theoretical economists view “sources of growth” is presented here. This chapter concludes with a discussion on the future trends in economic theory and global growth trajectory.

Indonesia in 2013

Asian Survey ◽  
2014 ◽  
Vol 54 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Geoffrey C. Gunn
Keyword(s):  
Economic Growth ◽  
Current Account ◽  
Current Account Deficit ◽  
Trading Partner ◽  
A Current ◽  
The U.S

Ahead of upcoming elections, expectations ran high in 2013 across the archipelago for a highly pluralistic electorate. With China as a leading trading partner, the backdrop for Indonesia was steady economic growth, albeit checked by a sliding currency, a current account deficit, and a depressing culture of corruption. Mixing commerce and geopolitics, China, the U.S., and Japan all turned to Indonesia to expand their influence.

scholarly journals Technological Spillover, Growth Convergence And Technical Progress: Does technology flow from rich to poor economies?

2020 ◽  
Vol 8 (4) ◽  
pp. 132-145
Author(s):  
Oladele O Aluko ◽  
B. Sabiu Sani
Keyword(s):  
Economic Growth ◽  
Technical Progress ◽  
Low Income ◽  
Generalized Method Of Moments ◽  
Low Income Countries ◽  
Dynamic Panel Model ◽  
Poor Countries ◽  
Growth Convergence ◽  
Using Data ◽  
The One

This study examines Technology spillover from rich to poor countries, the study used a model that, at the aggregate level, is similar to the one sector neoclassical growth model. The model was estimated using data on technical progress, Average Product Per-Worker, Capital Stock and Technology Intensive Goods in 25 countries which consist of rich and poor countries over the last decade. A dynamic panel model is formulated and estimated Using Generalized method of moments by Arelano and Bond; and the implications of the estimates were evaluated for aggregate total factor productivity and economic growth. The results reveal that, on average, technology have contributed more to economic growth in high income economies and on the contrary technology have made little or no contribution in low income countries. Consequently, there is substantial variation across technologies and economies

scholarly journals A σ-Convergence Model for Analyzing the Balance of Insurance Industry in China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zeyun Yang ◽  
Wendong Xiao ◽  
Qiaoling Fu
Keyword(s):  
Economic Growth ◽  
Labor Force ◽  
Spatial Correlation ◽  
Regional Differences ◽  
Insurance Industry ◽  
Balanced Development ◽  
Empirical Results ◽  
Growth Convergence ◽  
Convergence Model ◽  
Insurance Development

There are significant regional differences in the development of China’s insurance industry. An important question is that such regional differences are expanding or shrinking? Based on Barrow’s economic growth convergence model, this paper uses the σ convergence model to analyze the differences in the development of China’s insurance industry and its trends. It draws on the statistics data from 1990 to 2020. The empirical results show that the convergence of China’s insurance development is not obvious before 2006, but it shows a significant convergence after 2006. And, there are some differences between the Eastern, the Central, and the Western. Furthermore, when considering the spatial correlation, the convergence of insurance development among provinces in China is more obvious. This shows that the flowing of capital, technology, and labor force between regions may be beneficial to the balanced development of insurance among the regions.

Spatial Econometric Analysis of Urban and County-level Economic Growth Convergence in China

2016 ◽  
Vol 41 (4) ◽  
pp. 410-447 ◽  
Author(s):  
Guangdong Li ◽  
Chuanglin Fang
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Panel Data ◽  
Population Growth ◽  
Convergence Rates ◽  
Spatial Econometric ◽  
Cross Sectional ◽  
Growth Convergence ◽  
Savings Rate ◽  
Spatial Panel Data

Economic growth convergence, one of the classical assumption in regional economic growth, has been perplexing. There are many empirical studies trying to test if there is regional convergence in China. In this article, we bring new information of the finer spatial scale to the existing literature by using neoclassical convergence analysis, cross-sectional specifications, panel data models, and spatial econometric techniques to test the convergence hypothesis across 2,286 cities and counties in China. Empirical findings from cross-sectional data and spatial panel data show that significant absolute β and conditional β convergence are present in gross domestic product per capita after controlling for investment return rate, human capital, savings rate, population growth, technology advancement, capital depreciation rate, and initial technology level. We also find spatial agglomeration in urban and county economic growth is strong, and spatial effects are significant. Urban and county economic growth convergence rates for 1992–2010 show a gradually accelerated development trend. We present significant evidence that levels of investment, human capital, and initial technology impose significant facilitating effects on city and county economic growth, while savings and population growth have significant negative effects. And city and county economic growth differ in terms of convergence levels and influential factors.

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