Download What factors affect economic growth in China?

Exempel 10, Sid 5
What factors affect economic
growth in China?
1 Background In the late 1970’s, Deng Xiaoping initiated the open door policy, a free-market reform. The
reform took two decades to finalize and included opening the country to foreign direct
investments, allowing for entrepreneurs to start their own businesses, privatizing state-owned
enterprises and removing price controls.1 Before the reform, China had just been through the
Cultural Revolution that had killed millions of people and left the country broke. China was
really in need of a change.
From 1978 to 2010 the economy grew by an average of 9,5% every year and the private
sector now accounts for 70% of GDP.2 In 2001 China entered the World Trade Organization,
increasing international trade and helping the economy grow further.3
China is still a poor country, despite positive outcomes of the market reform. GDP is
increasing every year but the annual per capita income is only $4900.4 The reason for this
relatively small figure is Chinas huge population. The majority of the population is still fit for
work but since the one-child policy was implemented 30 years ago, the population growth is
slowing down while people get older. This means today’s young people will have to support a
huge ageing population.
Does the population growth have a positive or negative impact on the economy? What other
factors are important for China to consider when analyzing growth? These questions are the
starting point of this thesis.
Research objective
My research question is the following:
What factors affect economic growth in China?
More specifically, I will research how factors health care, education, foreign direct investment
per capita, population growth, household savings and initial GRP per capita affect economic
growth measured in GRP per capita in China.5
Theory
The theoretical background will be based on the Solow model of exogenous growth.
The model explains the long-term growth of an economy and uses a number of factors to
determine their impact on growth. The factors are savings, investments, population growth,
technological progress and increased human capital.6 The dependent variables in my
econometric function are based on these reasons.
1 Gang, 2005. 2 Ibid. 3 Ek, 2007, p. 3. 4 Dauerstädt & Stetten, 2005, p. 227. 5 GRP is short for Gross Regional Income, which is the GDP for each province or region. 6 Burda & Wyplosz, 2001, p. 45. 2 The basic version of the model includes two
factors of production, capital (K) and labor (L).
But, it can be augmented with other factors,
which is explained later on. Capital includes
machines, railways and other physical assets.
Y equals output.
𝑌 = 𝐹(𝐾, 𝐿)
Because capital depreciates, savings and
investments need to be equal or larger than the
depreciation rate.7 When actual investments
equal required investment (depreciation rate), output is neither rising nor falling. This is the
steady state, K*.
If the capital stock is at K0, investments are bigger than the depreciation rate and the capital
stock will be higher next year. At K1, investments are not enough to replace the capital that
wears out, and the capital stock will be lower next year. This way the capital stock always
moves towards K*.
The model assumes decreasing marginal productivity of capital and labor.8 This means that if
a firm has a number of workers and a number of machines, increasing the machines by one
unit will increase the output as well. The ratio Δ𝑌/Δ𝐾 is called the marginal productivity. If
we continue to increase the number of machines, holding labor constant, the output will
increase, but at a decreasing rate, i.e. decreasing marginal productivity.
The model also assumes diminishing returns to scale.9 If both factors double, output will also
double, i.e. increase by 100%, if there are constant returns to scale. When there are
diminishing returns to scale, output will increase by less than 100% even though both factors
double.
Because of diminishing returns, you cannot continue to increase labor or capital in order to
increase output, as, in the end, there will be no effect on output. We need other factors as well,
like technological progress and increased human capital.10 They are also included in my thesis
as the variables “health” and “education”. Improved health care can affect GDP/capita in two
ways, both as increased human capital, which ought to increase growth, but also as increased
population because improved health care causes people to live longer.
Population is included as Y/L where output decreases as labor increases. Since economic
growth is measured in GDP/capita in my research, I have included “population” as a variable
because income per capita decreases as population increases.
7 Ibid., 50. 8 Ibid., 48. 9 Ibid., 49. 10 Ibid., 58. 3 Literature
There have been quite a few studies on economic growth in China, and on economic growth
in general. The papers on economic growth in China that I have read so far either include just
one or two variables or they are extremely thorough with many more variable than I will ever
be able to use. Still, I think they form a good basis for my research.
The paper “Can the Augmented Solow Model Explain China's Economic Growth? A CrossCountry Panel Data Analysis” by Ding and Knight researches China’s economic growth
using Solow models and econometrics.
Ding and Knight use panel data over the period 1980-2000 and examine the growth difference
between China and other countries, and try to find the extent to which the growth difference
can be explained by the Solow model.11 They use the three different Solow models, the
textbook model, the model augmented by human capital and augmented by structural
change.12 The variables used are similar to mine: the growth in GDP per capita, the level of
GDP per capita, investment-output ratio, the share of agriculture in GDP, and growth rate of
population.13
The result is that the model augmented with both human capital and structural change best
explains the economic growth in China. They find that capital investment is the most
important component of growth, accounting for 54% of total growth.14 Other important
factors are improvements in factor productivity through structural change and slower
population growth rate. They also find that the level of education in China is crucial to the
growth difference between China and other developing countries.15
Rosenqvist and Lundblad have carried out a similar research to mine in the paper
“Utvecklingsländers ekonomiska tillväxt”, except their focus is developing countries in all
parts of the world.
The theoretical background for this research is once again the Solow model of growth. The
dependent variable is growth of GDP per capita and the independent variables are health,
education, GDP per capita, level of corruption, FDI per GDP, economic freedom, change in
population growth and system of government.16 Their data only includes the year 2003, and
using econometrics, they have created a linear regression model.
Their result shows that the variables that have the greatest impact on growth are system of
government, FDI per GDP and decreasing population growth.17
11 Ding & Knight, 2008, p. 1. 12 Ibid., 6. 13 Ibid., 17. 14 Ibid., 30. 15 Ibid., 32. 16 Rosenqvist, 2012, p. 1. 17 Ibid., p. 22. 4 Methodology
The method used will be econometrics, a way to measure economic data. Since my only
source of data is statistics, this is an entirely quantitative approach. I will form a function
consisting of the factors I aim to research. The dependent variable, to the left of the equal
sign, is growth in GRP per capita for each province. On the other side are all the independent
factors, i.e. the factors being researched.
When using econometrics, I will first find data for all variables. The program used, R
Commander, will give me coefficients, which will tell me the level of impact that each
independent variable has on the dependent variable. This allows me to perform an analysis of
the result (see section Analysis of findings).
This is the function that I have formulated:
Δ
𝐺𝑅𝑃
𝐹𝐷𝐼
𝐺𝑅𝑃
= 𝛽! + 𝛽! 𝐻𝑒𝑎𝑙𝑡ℎ! + 𝛽! 𝐸𝑑𝑢! + 𝛽!
+ 𝛽! Δ𝑃𝑜𝑝! + 𝛽! 𝑆𝑎𝑣𝑖𝑛𝑔! + 𝛽!
+𝜖
𝑐𝑎𝑝𝑖𝑡𝑎 !
𝑐𝑎𝑝𝑖𝑡𝑎 !
𝑐𝑎𝑝𝑖𝑡𝑎 !
GRPi denotes Gross Regional Product (provincial GDP) in province i.
Healthi is measured by life expectancy in province i.
Educationi is measured by literacy rate in % in province i.
FDI/capitai is short for Foreign Direct Investment per capita in province i.
ΔPopi is population growth in province i.
Savingi is annual household savings in province i.
GRP/capitai is the initial level of GRP in in province i.
𝛽! is the intercept and 𝜖 is the error term.
Data
I will include data for all 22 provinces plus five autonomous regions and four municipalities,
a total of 31 observations.
I plan to use data for the years 2000-2010 in my research but I have yet to decide in what way.
The best way would be to use panel data as that allows me to include all the variables for all
the years chosen. This method is quite difficult to perform and is something that I have never
done before so it might be overambitious.
One option is to choose only two years, for example 2000 and 2009, perform a linear
regression for each year and make a make a comparison. The results should be interesting as
the world economy was very different in 2009 as compared to the year 2000. Another option
is to perform linear regressions on year averages, for example 2000-2007 and 2008-2010, in
order to include as many years as possible but still be able to make a comparison between the
two periods.
All the data used is from the National Bureau of Statistics of China.18
18 National Bureau of Statistics of China, 2012. 5 Analysis of findings
When running a regression (i.e. compiling data for all variables and running it through the
program R Commander), I will get one coefficient for each variable instead of the 𝛽:s in the
function above. For example, 𝛽! indicating education might come out as 0,2 which means that
if the literacy rate increases by 1%, GRP per capita increases by 0,2%. If 𝛽! for population
growth comes out as -0,7 it means that if the population in one province increases by 1% then
GRP per capita will decrease by 0,7%.
Of course, the result might not be as I expect it to be, for example population growth might
come out as a positive coefficient. In my analysis, I will have to find a reason for the given
coefficients.
Timeframe Week 1-3: Collect data and run regressions.
Week 4-6: Write theory, method and background.
Week 7-8: Finish analysis.
6 Bibliography Dauderstädt, Michael, och Jürgen Stetten. China and globalisation. Leibniz: Leibniz Information Centre for Economics, 2005, 226-­‐234. Ding, Sai, och John Knight. Can the Augmented Solow Model Explain China's Economic Growth? A Cross-­‐Country Panel Data Analysis. Oxford: University of Oxford, 2008. Ek, Anna. The Impact of FDI on Economic Growth. Bachelor Thesis, Jönköping: Högskolan i Jönköping, 2007. Gang, Fan. China Is a Private-­‐Sector Economy. den 22 August 2005. http://www.businessweek.com/magazine/content/05_34/b3948478.htm (accessed 25 03 2012). National Bureau of Statistics of China. Annual Data. http://www.stats.gov.cn/english/statisticaldata/yearlydata/ (accessed 25 03 2012). Rosenqvist, Johan, och Therese Lundblad. Utvecklingsländers ekonomiska tillväxt. Bachelor Thesis, Huddinge: Södertörns Högskola, 2012. 7