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Abstract
Many people had suggested a negative effect of the relocation of the capital city in Korea. They argued that a decrease in population in the present capital region (Seoul) would result in income loss because total factor productivity (TFP) in Seoul is higher than in any other province. On the other hand, when we decompose TFP into TECs and technological progress (TP) in this paper, it shows that the technical efficiency changes (TECs) in the Chungnam region has remarkably improved.
In addition, the labor productivity in the Chungnam area is found to be higher than in the Seoul area. Therefore, this study shows positive effects to the literature of the debates regarding whether the government should shift the capital city or not.
Introduction
Shifting the country’s capital city was a key pledge in President Roh Moo-Hyun’s 2002 election. Although the Parliament passed the law to create of a new capital city in Chungnam Province area, there have been many debates so far.
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The basic motivation for changing the Capital City from Seoul to another location (Chungnam Province) is that there are too many people living in Seoul. Presently 48 million people are squeezed in Seoul so that it creates unbalanced economic development.
However, there are also some critics of the capital movement. One reason for the opposition is the project’s enormous cost. The project cost varies from approximately $45 billion estimated by the Parliament to $125 billion by some private institutions. Furthermore, history shows that purpose-built capitals have taken more time and money.
For example, Brazil’s new Capital City, Brasilia, added to the country’s economic huge debts.
Suh & Kim (2004) discussed this matter in terms of the income effects of 5% of the population moving from the Seoul area to the new capital city. They said that if 5% of the current population relocates to Chungnam Province, 1.7% ~ 1.9% of the gross domestic product would be decreased. The reason for this is that total factor productivity (TFP) in the Seoul area is greater than in the new capital city.
The purpose of the paper is to estimate TFP for both Seoul and the new capital city area, Chungnam Province, and decompose it into technical efficiency (TE), technological progress (TP), and input changes. Unlike Suh & Kim (2004), the decomposition of TFP proposed by Han, Kalirajan, & Singh (2002) not only explains the scale of the TFP, but also shows the characteristics and details of the TFP. It is when the local government has an economic policy -decision making.
The second part of the paper surveys the literature of TFP as well as TFP related studies for relocation of the capital city in Korea. The third part studies decomposition of the TFP method proposed by Han, Kalirajan, & Singh (2002). The fourth part reports the sources and uses of the data and the empirical results. The final part provides some concluding remarks.
A survey of literature in TFP (Total Factor Productivity)
The total factor productivity is a variable, which represents the productivity of the whole economy. It analysis encompasses residual production output that cannot be justified by production factors. Therefore, the total factor productivity is used as a method of measuring changes in production process efficiency. According to Solow (1956), an increase in output depends solely on technical progress in the long-term, however, in the short-term; capital accumulation plays an important role.
According to this viewpoint, Solow (1956) perceived total factor productivity as a concept that includes productivity based on technical progress and other production factors, which is defined as the Solow Residual. Its increasing rate that is measured by subtracting the contributions of labor and capital stock from the growth rate of gross domestic product is a comprehensive concept including technical progress and others.
There have been many studies on TFP growth, particularly in East Asia. According to Han, et al, (2002), most of the studies followed the growth accounting method using various production functions including trans-log and meta production functions. However, we used to measure our Solow residuals until Nishimizu & Page (1982) attempted to decompose TFP growth in Yugoslavia for the period of 1965-1978.
TFP related studies in relocation of the capital cities in Korea
Suh (2004) estimated TFP in Seoul by the growth accounting method without the capital stocks recently. TFP in the near-Seoul area (including Kyungki Province) and strictly in the Seoul area shows as 0.039-0.047 and 0.042-0.048 respectively during 1990-2001. This figure for Seoul area shows that TFP for non-near-Seoul area falls by 0.026. This gap has been widening as time goes by because the productivity in near-Seoul area is increasing faster than in non-near Seoul area.
Suh (Suh & Kim [2004]) in another study estimated the income impacts of decentralization of population in Korea. Suh study suggested that if 5% of the current population of the Capital Region relocates to Chungnam Province, 1.7%-1.9% of GDP would be decreased. The main reason is simple that TFP in Seoul Region is higher than in non-Seoul regions. This conclusion is based and consistent with Suh earlier report in 2001. He added that the determinants affected for the Seoul to be higher than non-Seoul areas are such as the existence of high-technology industries as well as the infrastructure.
On the other hand, there are several crucial criticisms in Suh’s study. First, he used the gross output as an output without a double deflation. According to Mahadevan (2002), one may use the value-added output by single deflation. However, the gross output should be deflated twice – corrected for purchases of intermediate inputs. Second, he assumed the share of the labor and capital in the production function: This could be very sensitive to the TFP estimation. Especially, his study lacks of the details of the information in TFP. The comparisons of TFP in Seoul and non-Seoul would suggest nothing but the figures of growth unexplained by the labor and capital stock increases.
Decomposition of TECs, TP, and Input changes
According to Han, Kalirajan, & Singh (2002), the frontier approach is able to decompose output growth into input growth; technical efficiency changes (TECs) and technological progress (TP). That is,
Output Growth = Input growth + TFP growth
= Input growth + TECs + TP
Above equation is algebraically described in graph A. The vertical axis measures outputs, and the horizontal axis measures inputs. Assume that a country faces two production functions, F1 and F2. The points on these functions represent the efficient production for period 1 and 2, respectively. In period 1, if the country is producing with full technical efficiency by following the best-practice techniques, its realized output will be y1* at the x1 input level.
However, the country may not have efficient production, due to many constraints such as a lack of efficient organizational structure and a proper incentive structure for workers. In this case, the realized output y1 is less than the maximum possible output y1*: Technical efficiency TE1 is this gap between y1* and y1. Now, let us further assume that the production function shifts from F1 to F2 due to technological progress, including the improvements in human and capital inputs.
* Graph A: Decomposition of TFP (Total Factor Productivity)
The decomposition can be mathematically expressed as follows:
D = y2 – y1
= A + B + C
= [y1* ▪ y1] + [y1** ▪ y1*] + [y2 - y1**]
= [y1* ▪ y1] + [y1** ▪ y1*] + [y2 - y1**] +[y2*▪y2*]
= [y1* ▪ y1] + [y1** ▪ y1*] ▪ [y2*- y2]
+ [y2*▪y1**]
= {(y1* ▪ y1) ▪ (y2* - y2)} + (y1**-y1*)
+(y2*▪y1**)
= Change in TE + TP + yx*
= TFP Growth + yx*
<Data Used>
Four different data sets are utilized for this analysis. First, manufacturing industry’s total gross nominal output, number of employees, value of tangible fixed assets (capital input), and cost of production (intermediate input) are taken from the Report on Mining and Manufacturing Survey (various issues). The sample period of the data is 1980- 2002.
The second data set includes the same variables for Seoul during the same years. The third set of data is for the Daejon area, and it contains the period from 1988 to 2002. The last set includes the same variables for Chungnam Province from 1980 to 2002. The gross output and the total costs are deflated by the wholesale price index (1995= 100) from the Bank of Korea, while the capital deflator from the Ministry of Statistics deflates the tangible fixed assets.
<Results>
<Table A> shows the results of the decomposition. First, in the period of 1980-2002, the total manufacturing industry had 144% increase of output, while the output increased by 88.7% and 197% for Seoul and Chungnam. For the period, Chungnam has a higher output increase. Furthermore, one can see that the labor productivity, defined simply by the total output divided by the number of the labors in the region, skyrocketed in Chungnam compared to that of Seoul in Figure 4.1. Figure 4.2 shows the ratio of the increase in the labor productivity. In this ratio, Chungnam has 14 more years higher than Seoul. We can notice that the labor productivity in the year 2000 in Chungnam is 2.3 times higher than Seoul’s.
Second, comparing TE1 against TE2 gives an idea how the technical efficiency improved in the regions. For the total, TE has improved so much that 20.2% of output change is due to TE, while this figure shows no improvement for Seoul, and the small amount of improvement is due to this figure. However, one can see that there is a tremendous improvement for Chungnam, so that TE causes 228.7% of the increase of output.
<Table A> Results of the Decomposition
| y2- y1
(output change) |
y1* - y1 (TE1) | y2* - y2 (TE2) | TE1+TE2 | y1**– y1* (TP) |
TE+TP | y2* - y1** (input
change) |
|
| Total | 1.438 | -0.002 | -0.292 | 0.290 | -0.455 | -0.165 | 1.603 |
| (1980-02) | (0.202) | (-0.316) | (-0.114) | (1.115) | |||
| Total | 0.764 | -0.031 | 0.001 | -0.032 | -0.015 | -0.047 | 0.811 |
| (1988-02) | (-0.042) | (-0.020) | (-0.062) | (1.062) | |||
| Seoul | 0.887 | 0.004 | 0.004 | 0 | 0.195 | 0.195 | 0.692 |
| (1980-02) | (0.000) | (0.220) | (0.22) | (0.780) | |||
| Seoul | 0.385 | -0.003 | 0.014 | -0.017 | 0.213 | 0.196 | 0.189 |
| (1980-02) | (-0.044) | (0.553) | (0.509) | (0.491) | |||
| Daejon | 0.596 | -0.151 | 0.005 | -0.156 | -0.113 | -0.269 | 0.865 |
| (1988-02) | (-0.262) | (-0.190) | (-0.452) | (1.451) | |||
| Chungnam | 1.972 | -0.008 | -0.012 | 0.004 | -0.027 | -0.023 | 1.995 |
| (1980-02) | (0.002) | (-0.140) | (-0.138) | (1.012) | |||
| Chungnam | 1.487 | 3.398 | -0.002 | 3.400 | -3.463 | -0.063 | 1.487 |
| (1988-02) | (2.287) | (-2.329) | (-0.042) | (1) | |||
| D+C | 1.252 | -0.004 | -0.05 | 0.046 | -0.248 | -0.202 | 1.454 |
| (1988-02) | (0.037) | (-0.198) | (-0.161) | (1.161) |
(The numbers in the parenthesis indicates the percentage of the output change.)
Third, comparing TP in the regions shows the highest increase for Seoul. 22% of the output change stems from TP, while this ratio shows a negative number for Chungnam. It might be a main reason that many economists criticize the relocation of the capital cities, in terms of productivity. The seventh column shows the TE+TP or TFP for the regions. Seoul has a higher number than Chungnam Province. TE and TP cause 22% of the output increased, while a negative number is resulted for Chungnam. The last column suggests that the majority of the output change occurred from the increase in inputs, labor and capital for Chungnam.
* Graph B: Comparisons of Labor Productivity for three regions
* Graph C: Ratio of increase in the labor productivity in three regions
When using the time-span of 1988-2001, the only period available for Daejon area, one can see that TE for the Seoul area has deteriorated, while it has tremendously increased in Chungnam. Thus, for Chungnam, TE has induced two thirds of the output change. However, as far as TP is concerned, the exact opposite phenomenon has taken place. For Seoul, this figure for TP is 0.195, and 55.3% of the output change is due to TE, while Daejon, Chungnam, and Daejon + Chungnam (D+C) show negative effects of TP on their outputs. Moreover, 49.1% of the output change is induced by the increase of the inputs in Seoul, when the majority of the output increase has occurred from the increase of the inputs for Chungnam and D+C.
Conclusion
Ever since President Rho Moo-Hyun’s pledge to shift the country’s capital city was announced, the issue has been a debated several times in Korea. Much research is being conducted to ascertain the economic appropriateness or validity of shifting it. One can hardly find the productivity analysis related. Suh & Kim (2004) in the study analyzes the effects of income when 5% of Seoul area’s population moves to a new capital city: There would be an income loss of 1.7%-1.9% of GDP. This is because the Seoul area has higher TFP than any other area. However, this paper further searches the characteristics of TFP in which we decompose its causes into technical efficiency, technological progress, and input changes.
It seems that the Seoul area has been flourishing with its increased output caused by the higher TFP, the total addition of the technical efficiency, and technological progress greater than in the Chungnam area so much that Suh and other criticizers of shifting the country’s capital city suggest not changing the location of the capital city.
However, when we decompose and compare the TFP into TE and TP, it can be noticed that the Chungnam area has had a higher TE than Seoul, but vice-versa for TP. One can also see that the labor productivity in Chungnam has been higher than in Seoul, and this difference is even growing greater. Thus, our study adds to the literature of the debates regarding whether the government should shift the capital city or not, in that one may at least say that there would be some positive effects in TFP analysis.
References
Aigner, Dennis, J., C. A. Lovell, and Peter J, Schmidt (1977), “formulation and Estimation of Stochastic Frontier Production Function Models,” Journal of Econometrics, Vol. 6, No. 1, pp. 21-37.
Barro, Robert J.and Xavier Sala-I-Martin. 1995. Economic Growth, New York: McGraw Hill.
Charles I. Jones, Introduction to Economic Growth, 2nd edition, W.W.Norton, 2005.
Han, Gaofeng, Kaliappa Kalirajan, Nirvikar Singh (2002), “Productivity and Economic Growth in East Asia: Innovation, Efficiency and Accumulation,” Japan and the World Economy, Vol. 14, pp. 401-24.
Mahadevan R.(2002) New Currents in Productivity Analysis, Asian Productivity
Organization, Productivity Series 31.
Nishmizu, Mieko, and John Page(1982),” Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, 1965-78, ” Economic Journal, Vol. 92, pp. 920-36.
Solow, Robert M., "A Contribution in the Theory of Economic Growth", Quarterly Journal of Economics 70, Feb. 1956.
Solow, R. M.(1957), “Technical Change and the Aggregate Production Function,” Review of Economics and Statistics, Vol. 39, pp. 312-320.
Suh, Sung-Hwan. and Kim, Kabsung(2004), “The Income Impacts of Decentralization of Population in Korea,” Journal of the Korean Regional Science Association, Vol. 20, No. 1, pp. 65-78.
<Data Source>
Available at : http://www. ecos.bok.or.kr
Available at : http://www.nso.go.kr/eng2006/emain/index.html
The Effects of Relocation of the Capital City in Korea. (2017, Mar 06). Retrieved from https://studymoose.com/the-effects-of-relocation-of-the-capital-city-in-korea-essay
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