Financial Deepening and Economic Growth in Advanced and Emerging Economies

The core of Shapley–Shubik games and general equilibrium models with a Venn diagram is applied for a theory on the role of real finance in economic growth among advanced economies. Then the dynamic computable general equilibrium (DCGE) models for Germany, France, the UK, Japan and the USA are constructed to assess the validity of the over-financing hypothesis that has reappeared after the financial crisis of 2008. Actual financial deepening ratios observed in the nonconsolidated balance sheet of the OECD exceeded by factors of 3.5, 2.4, 5.1, 11.6 and 4.8 than the optimal financial deepening ratios implied by DCGE models, respectively, in these countries because of excessive leveraging and bubbles up to 19 times of GDP which were responsible for this great recession. Containing such massive fluctuations for macroeconomic stability and growth in these economies are not possible in conventional fiscal and monetary policy models and require a DCGE analysis like this along with adoption of separating equilibrium strategy in line of Miller–Stiglitz–Roth mechanisms to avoid problem of asymmetric information in the process of financial intermediation so that the gaps between actual and optimal ratios of financial deepening remain as small as possible.

The paper investigates the role of infrastructure in promoting economic growth in China using ARDL and GMM techniques for the period 1975 to 2007. In this context, an attempt is made to understand growth accounting equations to investigate the impact of infrastructure development on output. Overall, the results reveal that infrastructure stock, labour force, public and private investment play an important role in economic growth in China. More importantly, the study finds that Infrastructure development in China has significant positive contribution to growth than both private and public investment. Further, there is unidirectional causality from infrastructure development to output growth justifying China's high spending on infrastructure development since the early nineties. The experience from China suggests that it is necessary to design an economic policy that improves the physical infrastructure as well as human capital formation for sustainable economic growth in developing countries.Keywords: China, Infrastructure Development, Investment, Output GrowthJEL classification: H4, H54, L9, O1(ProQuest: ... denotes formulae omitted.)1. INTRODUCTIONChina is the fastest growing country in the world for last few decades and accounts for nearly one fifth of the world population. Economic growth in China increased from 7.5% during 1970 to 1999 to over 10% per annum between 1999 to 2008. This has attracted many scholars to examine the major determinates of growth in China. Over the last two decades, academic research has devoted considerable attention to the role of trade and Foreign Direct Investment (FDI) in promoting growth. However, the role of infrastructure and human capital development has been neglected. Therefore, this paper offers an empirical assessment of the impact of infrastructure and human capital development on growth in the case of China.The role of infrastructure in enhancing economic development has been well documented both in the academic literature and in the policy debate (Aschauer, 1989; Munnell, 1990; World Bank, 1994; Calderon and Serven, 2003; Estache, 2006; Sahoo, 2006; Sahoo and Dash, 2010; and 2011). More recently, increasing attention has also been paid to the impact of infrastructure on poverty and inequality (World Bank, 2006). Further, it has been found that social infrastructure such as education, health, and housing are essential to promote better utilization of physical infrastructure and human resources, thereby leading to higher economic growth and improving quality of life (Hall and Jones, 1999).Over the past two decades, one of the defining features of China's growth has been investment led growth supported by domestic savings. China's sustained high economic growth and increased competitiveness has been underpinned by a massive development of physical infrastructure (Chatterjee, 2005; Stephane et al., 2007). The open economic policy made it possible for the inflow of foreign direct investment (FDI) mainly to the manufacturing sector. Cheap labour and better than adequate infrastructure were important pre-requisites that led to a successful the export-led growth strategy. With seemingly unlimited supply of cheap labour from the rural sector, public investment in infrastructure became the keystone in the strategy. A major focus by the government at all levels on infrastructure thus ensued.1Though infrastructure development certainly helped export-led economic growth in China, the Chinese economy started showing signs of overheating in recent years because of basic infrastructure constraints. Clearly, there is an increasing gap between the potential demand and the available supply of infrastructure to sustain high growth. Given the importance of infrastructure development for sustainable economic growth and poverty reduction in China, the present study examines the output elasticity of infrastructure development in China for the period 1970-2008. …

This study aims to analyze the effect of financial deepening on economic growth, income inequality, and poverty rates in 73 countries during the period 1991–2015. Panel data regression and the interaction of dummy variables are used to measure the effect. The results indicate that financial deepening has positive effects on economic growth, but negative effects on income inequality and poverty rates; has significant effect on economic growth in advanced economies (AEs) and significant effect on income equality and poverty rates in emerging markets and developing economies (EMDEs). These findings show that countries have to be selective in developing their financial sectors as it either can have positive or negative effect.

Based on the perspectives of both China (home country) and host countries (economies), a financial deepening indicator system and an economic growth indicator system are constructed, the mutual influence mechanism between financial deepening (FD), outward foreign direct investment flows (OFDI) and economic growth (EG) are studied. Firstly, from the perspective of China, based on Error Correction Model (ECM) and Vector Error Correction Model (VECM), the conclusions received are as follows. (i) China's financial deepening and OFDI have a long-run positive impact on China's economic growth. (ii) Further analysis also confirms that reforms related to financial deepening have positive policy effects on promoting OFDI in China. Secondly, from the perspective of the interaction between China and host countries (economies), based on Time-varying Spatial Durbin Model (TVSDM), the conclusions received are as follows. (i) In general, China's OFDI to host countries plays a positive intermediary role in the process of financial deepening for economic development in host countries. (ii) Three aspects (FD, OFDI, EG) have different degrees of spatial autocorrelation and spatial spillover effects on each other, which are positive in general. (iii) Further analysis also found heterogeneity in the above conclusions for high-income and low-income host countries individually. In a word, a comprehensive analysis framework of three aspects (financial deepening, OFDI and economic growth) is finally constructed, which has important implications for overseas investments and financial support to the real economy.

Measuring the impacts of the two-child policy on industrial structure and economic growth in china using a CGE model

Assessing the economic impact of public investment in Malaysia: a case study on MyRapid Transit project using a dynamic computable general equilibrium model

A study of the impact of military expenditures on economic growth and development examines the differences in the results of previous studies which led to contradictory conclusions. The authors find that these differences are due to sample variations, specificational choices, and the different time periods examined. The data indicate that there is no consistent, statistically significant connection between military spending and economic growth. Augmentation of the models suggests that military expenditures neither help nor hurt economic growth to any significant extent. 2 tables.

This paper analyses the long-run growth rates of advanced economies, based on demographic factors. To this end, growth is broken down into two components: growth in productivity (GDP per working-age person) and the projected rate of growth of the working-age population. Productivity is assumed to grow in the long-run at a constant rate equal to that of the technology leader, whereas the demographic projections are those of the United Nations. This simple methodology abstracts from other factors normally considered in the literature on long-term growth, such as the convergence process (we focus on advanced economies) and heterogeneity in participation and employment rates. However, the results do not differ much from those obtained using these other approaches (which are richer, but also more speculative), although the growth rates turn out to be somewhat lower in most cases. They indicate a general deceleration of growth in advanced economies in the coming two decades, due to a slowdown in working-age population growth. Japan, Germany, Italy and Spain face the least favourable growth dynamics in our sample, as these countries face reductions in the size of their workforces. By 2050 France and the United Kingdom could have overtaken Germany to become the largest economies in Europe. In the case of Spain (whose working-age population is expected to peak in 2024) the growth rate of GDP will progressively decline to just below 2% over the following decade.

The stability and sustainability of economic growth have always been a hot topic of concern in the academic and practical circles around the world. The purpose of this study is to examine the stability and sustainability of China's economic growth. For over 200 economies around the world, ensuring the stability and sustainability of their economic development in the face of sudden and catastrophic events is a great challenge. The COVID-19 epidemic in 2020 is just an emergency to test the economic development of each economy. The method adopted in this study is to observe the economic growth of more than 200 countries and regions in the world in 2020, visually measure the economic growth of each economy after being impacted by the COVID-19 epidemic, and then further explain the reason for the robustness of China's economic growth with the help of shock theory, statistical methods, including variance coefficient, nonlinear econometric model, shock entropy and other quantitative indicators. This study found that although the impact of the COVID-19 epidemic on China's economic growth is huge on the whole, the resilience of China's economic growth is significant, and the original trend of economic growth has not changed because of the impact of the COVID-19 epidemic. Its average variance coefficient is only 0.42, and the shock entropy is almost 0. The conclusion is that China's economic development is not only robust, but also sustainable. The practical significance of this study is that the perfect industrial economic structure and the Chinese style COVID-19 epidemic prevention and control model can still maintain the existing track of economic development at a certain cost of economic development, ensuring that the overall trend of economic growth remains strong, which lays a solid foundation for economic and social development after the COVID-19 epidemic.

This study empirically examines the role of research and development (R&D) in the universities on economic growth. Using yearly data over the period 1996-2013 for 32 advanced economies and 46 developing countries in the world, the empirical results are estimated by static- and dynamic-panel data to provide evidence in favor of the impact of academic research and development on economic growth. The empirical evidence suggests that the static- and dynamic-panel data analysis estimates well characterize how academic research and development (R&D) influences economic growth in advanced economies and developing countries. Static panel data analysis in the light of fixed effect method (FEM) suggest positive effect of academic research and development on economic growth both in advance economies and developing countries. Moreover, dynamic panel data (Arrelano-Bond and Blundell-Bond) analysis finds academic research and development has consistently positive effect on economic growth in advanced economies, unfortunately academic R&D has negative effect on economic growth in developing countries. Based on the results, this study recommends for developing countries especially Indonesia to pay specific attention to academic R&D at universities by commercialization of new inventions and knowledge to attract industry.

Elucidating the complex mechanism between urbanization, economic growth, carbon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997-2010, this study empirically examines the relationships among urbanization, economic growth and carbon dioxide (CO2) emissions at the national and regional levels using panel cointegration and vector error correction model and Granger causality tests. Results showed that urbanization, economic growth and CO2 emissions are integrated of order one. Urbanization contributes to economic growth, both of which increase CO2 emissions in China and its eastern, central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central regions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization, economic growth and CO2 emissions, indicating that in the long run, urbanization does have a causal effect on economic growth in China, both of which have causal effect on CO2 emissions. At the regional level, we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run, we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped relationship between CO2 emissions and economic growth in China, not supporting the environmental Kuznets curve (EKC) hypothesis. Our empirical findings have an important reference value for policy-makers in formulating effective energy saving and emission reduction strategies for China.

Publisher Summary This chapter discusses the financial development and economic growth in underdeveloped countries. An observed characteristic of the process of economic development over time, in a market-oriented economy using the price mechanism to allocate resources, is an increase in the number and variety of financial institutions and a substantial rise in the proportion not only of money but also of the total of all financial assets relative to GNP and to tangible wealth. Typical statements indicate that the financial system somehow accommodates—or, to the extent that it malfunctions, it restricts—growth of real per capita output. Such an approach places emphasis on the demand side for financial services; as the economy grows it generates additional and new demands for these services, which bring about a supply response in the growth of the financial system. In this view, the lack of financial institutions in underdeveloped countries is simply an indication of the lack of demand for their services.

The article presents a dynamic stochastic general equilibrium model (DSGE-model) for the Russian economy. The model describes the behavior of the following macroeconomic agents: households, real sector, banking sector, Central Bank, as well as the interactions between them and the world. Household modeling uses the external habit formation approach to account for the inertia of preferences. To model the real sector, we abandoned the most common approach which assumes that the decision on investments is made by the households as the owners of production factors. Instead, we took the firm-specific capital approach which assumes that the decision on investment is made by the firms themselves. The study also considers that in Russia, fixed assets are mostly invested from the firms' own funds. To account for the investment inertia in the fixed asset in a real sector model, the expenditures are transferred to the commissioning of new facilities, the Calvo model is applied to describe the price setting under the monopolistic competition. A banking sector which defines the loan and debt interest rates to the key Central Bank interest rate is chosen to be a link between the households and firms in the model. The Taylor equation is used to describe the monetary policy of the Bank of Russia under the inflation targeting, while an inertia factor is included into the equation with the uncovered interest parity for the budget rule which regulates the purchases (or sales) of the currency by the National Welfare Fund. The final linearized model is a system of 23 difference equations with rational expectations. Based on the proposed model, calculations were made and key macroeconomic indicators were forecasted for 2020–2021 on a quarterly basis for the Russian economy. The calculations account for the relevant recessionary factors: oil price fall, oil production cut in OPEC+ deals, quarantine measures aimed to prevent the spread of the corona virus infection, anti-recessionary measures of the RF Government. The findings show that the economic downturn in 2020 can be from 5 to 7% under COVID-19 pandemic. Growth in 2021 is estimated to be within 3–5%. The developed model can be used for scenario projecting for the Russian economy, upgrading the monetary policy of the Bank of Russia, and for developing applied quarterly projection models (QPM). The model could be further modified by including more elements: decomposing the household sector into the Ricardian and non-Ricardian ones, identifying the resources industries and industries in the real sector which manufacture the invested goods, including the key taxes and budget expenses into the model. One more promising area is to analyze the equilibrium of the interest rates when large firms could accumulate their own financial resources. This prerequisite decreases the demand for the bank loans from the real sector and, thus, leads to lower, including the negative, interest rates. The proposed approach enhances the quality of a DSGE model as a predictive tool for making the political and managerial decisions.

Smooth Transition Regression Model (STR) is applied to analyze the non-linear effect of urbanization on economic growth in this study. By collecting relevant variable data in 1978–2012, financial deepening is selected as the transition variable to construct the STR Model which could reflect the dynamic change of urbanizational economic growth effect. The result shows that urbanizational economic growth effect should present the characteristics of threshold and could be described with non-linear Smooth Transition Model (LSTR1). Meanwhile, the urbanizational economic growth effect should reveal asymmetry, in which the research findings show contemporary financial deepening (FISt) as a factor. Specifically, the linear feature appears when the FISt is lower than 0.3792 (before 1990), while it reveals non-linearity when the FISt exceeds 0.3792 (after 1990), and the non-linearity becomes the major factor in the urbanizational economic growth effect after 1990.

This thesis investigates the effects of trade on the labour market in Malaysia. Specifically, we study the impact of a tariff cut in the motor vehicle industry on the different occupational wages and employment. Tariffs played an important role in Malaysia’s economic development; from an import-competing economy to an export-oriented economy. The literature on trade, wages and employment for Malaysia is limited because of inadequate occupational data to carry out econometric analysis. To fill this gap, we use a dynamic computable general equilibrium (CGE) model for the Malaysian labour market, MyAGE_LM to analyze the effects of a reduction in motor vehicle tariffs. CGE models have theoretical rigour and extensive analytical capabilities for carrying out policy analysis. This thesis contributes to the literature by (i) Introducing labour supply with nine different occupational groups into the dynamic CGE model for Malaysia and (ii) Analyzing a reduction in the motor vehicle tariff rate in Malaysia. The policy simulation is a 5 per cent cut in the motor vehicle tariff rate. To facilitate the analysis of the tariff cut, the MyAGE_LM model incorporates the labour market mechanism similar to that of Dixon and Rimmer (2003; 2008). The simulation results for the impact of the tariff cut on macroeconomic indicators, sectoral outputs and nine categories of occupational wages and employment are presented. The results are analyzed in terms of major model mechanisms. The macroeconomic results of the tariff cut indicate that in the short run, with the government aiming for revenue neutrality through increased labour taxes, there would be a small welfare gain. We also found that in the short run, exports fell despite real devaluation. So, the export sectors do not benefit in the short run. In the long run, aggregate real wages increase, and there is an economy-wide gain in GDP and aggregate consumption. The sectoral results revealed that most export-oriented industries would experience an increase in output. There are some evident effects on occupational wages and employment. The occupational group that stands out is the semi-skilled occupational group, SklAgriFish. This occupational group experienced the biggest decrease in vacancies. SklAgriFish occupations do well because no workers in this occupation are employed in the motor vehicle industry. Also, a significant proportion of SklAgriFish workers are hired in the export-oriented Agriculture industry, and the Agriculture industry sells to FoodBevTob (which does well in the long run because of real devaluation). The PlantMachOpr occupation does relatively well because a high proportion of these workers is employed in OthMachEquip industry (export-oriented and a winner from tariff cut in the long run). In general, from the MyAGE_LM policy simulation, we find that the tariff cut did not have a significant impact on the labour market. There are only small changes in average real wages and employment. We find damped labour supply effects in both the short and the long run. Semi-skilled occupations gain relative to skilled and unskilled workers. Skilled workers do not do well. They are mainly hired in non-traded industries that scarcely use imported motor vehicles