China's Economic Growth Appraisal through the Solow Model - Research Paper Example

?China’s Economic Growth Appraisal through the Solow Model Solow Model The Solow model is also known as Solow-Swan growth model or the neo ical growth model and the exogenous growth model. The model delineates economic models pertaining to long term growth within the framework of neoclassical economics. These growth models try to explain the long term economic growth using indicators such as productivity, technological progress, capital accumulation as well as population growth. The Solow growth model contains short term and long term implications. The short term implications include policy measures such as tax cuts as well as subsidies on investment that could affect the steady state levels of output but not the growth in the longer run. Furthermore the growth is affected in the shorter run only because the economy converges to newer steady state levels of output. In addition the rates of growth of the economy as the economy converges to a steady state are determined by the rate of capital accumulation alone. The rate of capital accumulation is the determined using the savings rate as well the overall depreciation of capital. In contrast the long term implications of the Solow model imply that the long term rate of growth can be determined exogenously only. A common method of predicting implies that an economy will tend to converge towards a steady state rate of growth depending only on the rate of labor force growth and the rate of technological progress. The Solow model accommodates for higher saving rates producing higher growth rates much like older models but it appreciates technological innovation more in the longer run compared to accumulation of capital. The key assumption of the Solow growth model is that the involved capital is subject to the law of diminishing returns within a closed economy. Mathematically the Solow model is represented through the interaction between five macroeconomic equations for GDP, change in capital, the macro production function, savings and changes in the workforce. These functions can be represented mathematically as below (Haines). Function Mathematical Expression Macro-production Function Savings Function Changes in Capital Changes in Workforce Where:  is the total production of the economy  is the multifactor productivity or technology  is the capital  is the labor  is the savings  portion of total production which represents savings  is the depreciation  is the net growth rate  is the time 2. China’s Growth as per the Solow Model The Solow model has been used extensively in various forms in order to decipher national growth in the longer run utilizing exogenous perspectives. The basic key assumption remains the same as above which is the diminishing returns of the capital within a closed economy model. Moreover the textbook Solow model relies on exogenous rates for capital accumulation, technological progress and population growth. The overall economic growth in the longer run is estimated exogenously through relying on the rate of technological progress as stipulated in the discussion above. However the basic textbook Solow model cannot reliably predict economic growth so it is often augmented with structural terms. This text will not deal with the derivation of the Solow model’s mathematical implications as it is beyond the scope of this text but instead it will report on the primary equations utilized for the Solow model. The derivation for the mathematical expressions used in the Solow model can be retrieved from various economics studies relating the Solow model to economic growth (Ding and Knight) (Temple and Wobmann). Based on these researches the primary equations in use are: The equations listed above accommodate for structural changes, efficiency of the economy, changes in labor patterns, technological changes as well as residuals required for convergence. The model listed above was used along with panel data from a variety of sources such as PWT (Penn World Table), WDI (World Bank Development Indicators), and FAO (Statistical Database of the Food and Agricultural Organization of the United Nations). A time period of five years was chosen to reflect cyclical business changes more closely in comparison to using a ten years period. The total period used for observation was restricted between 1980 and 2000 that corresponded to a comprehensive set of reforms in the Chinese economy in 1978. Statistics from PWT were used in order to delineate the PPP (purchasing power parity) and hence the GDP of China for the subject period. Similarly statistics from WDI were utilized in order to discover the total population of China as well as the amount of Chinese population in the 15 to 64 years age bracket. This age bracket represents the population that is actively employed in the labor force and has been used reliably for economic models before as well (Barro and Lee). Lastly data from FAO was used in order to discern the amount of population employed in the agricultural sector so that the total labor force could be better understood. However data from FAO failed to account for changing labor structures in the nascent developing Chinese economy so instead data from the Labor Statistical Yearbook from the National Bureau of Statistics (NBS) China was used instead. Data from the sources outlined above was used in the equations presented before through regression in order to predict economic growth. Using the above equations the average annual growth rate of output per worker between 1980 and 2000 was 6.3% per annum for China while the actual rate was 7.2%. When decomposed the increases in growth could be traced to higher investment levels in human development. Moreover other variables such as slower population growth, higher human capital, structural change and conditional convergence gain also accounted for rapid expansion of the Chinese economy. Overall it was found that the augmented Solow model used was able to predict economic indicators successfully within the 80% and above level of confidence for the period between 1980 and 2000 for the Chinese economy. A number of key variables relating to the Chinese economy are shown below in order to appreciate the total change in them. Indicator 1980 1990 2000 Average Change GDP per capita growth rate per annum (%) 6.46 2.29 7.64 8.43 1.18 GDP per capita per annum (constant $2,000) 186.44 391.65 949.18 476.44 762.74 Shares of gross capital formation in GDP (%) 35.19 34.74 32.76 36.04 -2.43 Share of agriculture in GDP (%) 30.09 27.05 14.83 24.35 -15.26 Population growth rate per annum (%) 1.25 1.47 0.71 1.06 -0.54 Average years of schooling over 15 years of age 4.77 5.85 6.36 5.61 1.59 Average annual growth rate of average years of schooling (%) 1.66 3.36 0.78 1.48 -0.87 3. Conclusion Based on the table presented above as well as the results from the Solow augmented model it is clear that the Chinese economy is prospering like never before. Recently the Chinese economy overtook the Japanese economy to become the world’s second largest economy and this in itself speaks volumes for economic efficacy in China. 4. Effect of CHINESE Growth on the World Economy Given the rapid growth of the Chinese economy it is becoming apparent that in years to come the Chinese will dictate fiscal policies around the world. Aggressive economic policies inside the bamboo curtain as well as aggressive export policies such as undervaluing the Yuan will provide a large measure of leverage to the Chinese. As mentioned before the Chinese economy has become the world’s second largest and the current manner of expansion shows that China is ready to take center stage as the world’s largest economy. Though this transformation may take some time to occur but such a change is undeniable for most part. 5. Bibliography Barro, R. J. and J. W. Lee. “International data on educational attainment: updates and implications.” Oxford Economic Papers 3 (2001): 541-563. Ding, Sai and John Knight. “Can the augmented Solow model explain China's economic growth? A cross country panel data analysis.” February 2008. Oxford University. 20 December 2011 . Haines, Joel D. “A framework for managing the sophistication of the components of technology for global competition.” Competitiveness Review 16(2) (2006): 106. Temple, J. and L. Wobmann. “Dualism and cross country growth regressions.” Journal of Economic Growth 11 (2006): 187-228. Read More