the consequences of relocation in the capital city
Abstract
A large number of people had suggested a poor effect of the relocation from the capital city in Korea. They contended that a decline in population in the present capital region (Seoul) might result in cash flow loss mainly because total factor productivity (TFP) in Seoul is greater than in any additional province. On the other hand, when we break down TFP in TECs and technological progress (TP) from this paper, it shows that the technical performance changes (TECs) in the Chungnam region provides remarkably increased.
In addition , the labor output in the Chungnam area is deemed higher than inside the Seoul region. Therefore , this study displays positive effects for the literature of the debates relating to whether the federal government should switch the capital city or perhaps not.
Introduction
Shifting the country’s capital city was obviously a key promise, give your word in Leader Roh Moo-Hyun’s 2002 election. Although the Parliament passed what the law states to create of a new capital city in Chungnam Province area, there are many discussions so far.
The basic motivation for changing the Capital City via Seoul to the next (Chungnam Province) is that there are too many people residing in Seoul. Currently 48 , 000, 000 people are compressed in Seoul so that it creates unbalanced economical development.
Nevertheless , there are also a few critics of the capital movements. One basis for the level of resistance is the project’s enormous cost. The task cost varies from approximately $45 billion predicted by the Parliament to $125 billion simply by some private institutions. Furthermore, history demonstrates that purpose-built capitals have taken more hours and funds.
For example , Brazil’s new Capital City, Brasilia, added to the country’s financial huge debt. Suh &Kim (2004)mentioned this subject in terms of the income associated with 5% in the population going from the Seoul area to the new capital city. Someone said that if perhaps 5% of the current human population relocates to Chungnam Province, 1 . seven percent ~ 1 ) 9% from the gross domestic product will be decreased. The reason for this is that total component productivity (TFP) in the Seoul area is greater than in the new capital city.
The purpose of the daily news is to calculate TFP to get both Seoul and the fresh capital city area, Chungnam Province, and decompose it into technological efficiency (TE), technological improvement (TP), and input improvements. Unlike Suh & Kim (2004)the decomposition of TFP suggested by Han, Kalirajan, & Singh (2002)not only points out the scale from the TFP, yet also displays the characteristics and details of the TFP. It can be when the county has an economic policy -decision making.
The other part of the paper surveys the literature of TFP and also TFP related studies pertaining to relocation in the capital town in Korea. The third portion studies decomposition of the TFP method suggested byHan, Kalirajan, & Singh (2002). Your fourth part information the sources and uses of the data and the scientific results. The final part supplies some concluding remarks.
A survey of materials in TFP (Total Component Productivity)
/strong>The total component productivity is known as a variable, which represents the productivity with the whole economic system. It evaluation encompasses residual production result that can not be justified by production elements. Therefore, the overall factor efficiency is used being a method of testing changes in creation process performance. According toSolow (1956)an increase in outcome depends entirely on specialized progress inside the long-term, yet , in the initial; capital build up plays a crucial role.
According to the viewpointSolow (1956)perceived total factor efficiency as a concept that includes efficiency based on specialized progress and also other production elements, which is understood to be the Solow Residual. Its increasing price that is assessed by subtracting the input of labor and capital stock from your growth price of low domestic product is a comprehensive strategy including specialized progress and others.
There were many studies on TFP growth, particularly in East Asia. According to Ryan, et approach, (2002)most of the research followed the expansion accounting method using various production capabilities including trans-log and meta production functions. /strong>However , all of us used to assess our Solow residuals until Nishimizu & Page (1982)attempted to decompose TFP development in Yugoslavia for the time of 1965-1978.
TFP related studies in relocation of the capital cities in Korea
em>Suh (2004)approximated TFP in Seoul by growth accounting method without the capital stocks and options recently. TFP in the near-Seoul area (including Kyungki Province) and totally in the Seoul area displays as 0. 039-0. 047 and zero. 042-0. 048 respectively during 1990-2001. This figure pertaining to Seoul location shows that TFP for non-near-Seoul area declines by zero. 026. This gap have been widening as time goes by because the production in near-Seoul area can be increasing quicker than in non-near Seoul region.
strong>Suh (Suh & Kim [2004])within study believed the salary impacts of decentralization of population in Korea. Suhstudy advised that if perhaps 5% with the current populace of the Capital Region relocates to Chungnam Province, 1 . 7%-1. 9% of GDP would be decreased. The main reason is not hard that TFP in Seoul Region is higher than in non-Seoul regions. This conclusion is based and consistent with Suhearlier statement in 2001. He added that the determinants affected for the Seoul to be more than non-Seoul areas are such as the existence of high-technology industrial sectors as well as the system.
On the other hand, there are lots of crucial criticisms in Suh’sstudy. Initial, he used the gross output while an outcome without a double deflation. In accordance toMahadevan (2002)you can use the value-added output by single decrease. However , the gross end result should be deflated twice ” corrected for purchases of intermediate advices. Second, he assumed the share with the labor and capital in the production function: This might be very very sensitive to the TFP estimation. Especially, his examine lacks from the details of the information in TFP. The reviews of TFP in Seoul and non-Seoul would suggest nothing but the figures of development unexplained by labor and capital inventory increases.
Decomposition of TECs, TP, and Insight changes
/strong>According to Han, Kalirajan, & Singh (2002), the frontier procedure is able to break down output expansion into input growth; specialized efficiency improvements (TECs) and technological improvement (TP). That is
Outcome Growth sama dengan Input expansion + TFP growth
= Input growth & TECs & TP
Above equation is usually algebraically referred to in chart A. The vertical axis measures results, and the horizontal axis procedures inputs. Assume that a country looks two production functions, F1 and F2. The points on these types of functions symbolize the efficient production for period one particular and 2, respectively. In period you, if the country is making with full technical effectiveness by following the best-practice approaches, its noticed output will probably be y1* at the x1 type level.
However , the country may well not have efficient production, because of many limitations such as a deficiency of efficient company structure and a proper bonus structure pertaining to workers. In this instance, the noticed output y1 is less than the utmost possible end result y1*: Technological efficiency TE1 is this distance between y1* and y1. Now, allow us to further assume that the production function shifts from F1 to F2 because of technological improvement, including the advancements in individual and capital inputs.
*Chart A: Decomposition of TFP (Total Element Productivity)
/strong>The decomposition may be mathematically portrayed as follows:
D/strong>= y2” y1
= A + W + C
= [y1*ªyone particular] + [y1** ª yone particular*] + [y2“yyou**]
= [yone particular* ªyyou] + [yone particular** ªyyou*] + [y2“yone particular**]&[y2*ªy2*]
= [yyou* ª yyou] + [y1** ª yone particular*] ª [y2*“y2]
&[y2*ªyyou**]
= (y15. ª con1) ª (y2* ” y2) + (y1**“y1*)
&(y2*ªy1**)
= Difference in TE + TP + yx*/strong>
=TFP Growth + yx*
Four distinct data pieces are utilized in this analysis. First, manufacturing industry’s total major nominal result, number of staff, value of tangible fixed assets (capital input), and cost of production (intermediate input) are extracted from the Report on Mining and Manufacturing Survey(various issues).The test period of the info is 1980- 2002.
The 2nd data established includes precisely the same variables pertaining to Seoul throughout the same years. The third pair of data is made for the Daejon area, and it contains the time from 1988 to 2002. The last collection includes similar variables intended for Chungnam Province from 80 to 2002. The major output plus the total costs are deflated by the low cost price index (1995= 100) from the Bank of Koreawhile the capital deflator from the Ministry of Statistics deflates the real fixed property.
<Table A>shows the results in the decomposition. Initial, in the length of 1980-2002, the overall manufacturing industry had 144% increase of output, as the output elevated by 88. 7% and 197% for Seoul and Chungnam. Pertaining to the period, Chungnam has a larger output maximize. Furthermore, one can see that the labor output, defined merely by the total output divided by the number of the labors in the area, skyrocketed in Chungnam in comparison to that of Seoul in Physique 4. 1 . Figure 4. 2 shows the ratio of the increase in the labor productivity. With this ratio, Chungnam has 16 more years higher than Seoul. We can realize that the labor productivity in the year 2000 in Chungnam is usually 2 . 3 times higher than Seoul’s.
Second, assessing TE1 against TE2 offers an idea the way the technical performance improved inside the regions. For the total, TE has increased so much that 20. 2% of output change is caused by TE, while this physique shows zero improvement for Seoul, as well as the small amount of improvement is due to this kind of figure. Yet , one can notice that there is a great improvement for Chungnam, to ensure that TE triggers 228. 7% of the enhance of end result.
(output change) (TP) change) (The amounts in the parenthesis indicates the percentage of the end result change. ) Third, comparing TP in the locations shows the best increase intended for Seoul. 22% of the end result change comes from TP, whilst this proportion shows a negative number for Chungnam. It could be a main purpose that many economic analysts criticize the relocation from the capital cities, with regards to productivity. The seventh line shows the TE+TP or TFP pertaining to the parts. Seoul provides a higher number than Chungnam Province. TE and TP cause 22% of the result increased, although a negative quantity is lead for Chungnam. The last column suggests that almost all of the output transform occurred from your increase in advices, labor and capital intended for Chungnam. * Chart B: Side by side comparisons of Labor Productivity for 3 regions * Graph C: Ratio of increase in the labor efficiency in three regions When using the time-span of 1988-2001, the only period available for Daejon area, you can see that TE for the Seoul place has damaged, while it has tremendously increased in Chungnam. Thus, to get Chungnam, TE has caused two thirds of the output transform. However , as far as TP is concerned, the exact opposite phenomenon has taken place. For Seoul, this number for TP is 0. 195, and 55. 3% of the outcome change is caused by TE, although Daejon, Chungnam, and Daejon + Chungnam (D+C) show negative effects of TP on their outputs. Additionally, 49. 1% of the end result change can be induced by increase with the inputs in Seoul, when the majority of the outcome increase features occurred from the increase with the inputs to get Chungnam and D+C. Conclusion Ever since Leader Rho Moo-Hyun’s pledge to shift the country’s capital city was announced, the matter has been a discussed several times in Korea. Very much research is being conducted to ascertain the financial appropriateness or perhaps validity of shifting this. One can hardly find the productivity analysis related.Suh & Betty (2004)in the research analyzes the consequences of income when ever 5% of Seoul area’s population ways to a new capital city: There is an income loss in 1 . 7%-1. 9% of GDP. This is because the Seoul area provides higher TFP than any other area. However , this kind of paper additional searches the characteristics of TFP in which all of us decompose their causes in to technical productivity, technological progress, and suggestions changes. It seems that the Seoul region has been prospering with its elevated output caused by the higher TFP, the total addition of the specialized efficiency, and technological improvement greater than inside the Chungnam place so much that Suhand also other criticizers of shifting the country’s capital city recommend not changing the location of the capital city. However , whenever we decompose and compare the TFP in to TE and TP, it could be noticed that the Chungnam area has had a greater TE than Seoul, although vice-versa pertaining to TP. One can possibly also notice that the labor productivity in Chungnam has been higher than in Seoul, and this difference is definitely even developing greater. Hence, our study adds to the books of the debates regarding if the government should shift london or not, in that one may at least say that there is some results in TFP analysis.
References Aigner, Dennis, M., C. A. Lovell, and Peter M, Schmidt (1977)“formulation and Estimation of Stochastic Frontier Production Function Models, Journal of EconometricsVol. 6, No . 1, pp. 21-37. Barro, Robert J. and Xavier Sala-I-Martin.1995. Monetary GrowthNyc: McGraw Hillside. Charles I. WilliamsSummary of Economic Growth2nd edition, W. Watts. Norton, june 2006. Ryan, Gaofeng, Kaliappa Kalirajan, Nirvikar Singh (2002)“Productivity and Economic Expansion in East Asia: Development, Efficiency and Accumulation, Japan as well as the World Economic climateVol. 18, pp. 401-24. Mahadevan R. (2002)New Currents in Productivity ResearchAsian Productivity Organization, Production Series thirty-one. Nishmizu, Mieko, and John Page(1982) Total Element Productivity Growth, Technological Progress and Technological Efficiency Modify: Dimensions of Productivity Change in Yugoslavia, 1965-78, Economical JournalVol. 92, pp. 920-36. Solow, Robert M.“A Contribution in the Theory of Economic Growth, Quarterly Record ofEconomics seventyFeb. 1956. Solow, R. Meters. (1957)“Technical Change and the Aggregate Creation Function, Review ofEconomics and StatisticsVol. 39, pp. 312-320. Suh, Sung-Hwan.andKim, Kabsung(2004)“The Profits Impacts of Decentralization of Population in Korea, Journal with the Korean Regional Science AffiliationVol. 20, No . you, pp. 65-78.
Available at: http://www. ecos. bok. or. kr Available at: http://www.nso. go. kr/eng2006/emain/index. html one particularOutcomes of the Decomposition
/strong>
ytwo” con1
y12. ” sumado a1(TE1)
ya couple of* ” ytwo(TE2)
TE1+TE2
yyou**” y12.
TE+TP
sumado a22. ” sumado a1**(input
Total
1 . 438
-0. 002
-0. 292
0. 290
-0. 455
-0. 165
1 . 603
(1980-02)
/strong>
/strong>
/strong>
(0. 202)
(-0. 316)
(-0. 114)
(1. 115)
Total
zero. 764
-0. 031
0. 001
-0. 032
-0. 015
-0. 047
zero. 811
(1988-02)
/strong>
/strong>
/strong>
(-0. 042)
(-0. 020)
(-0. 062)
(1. 062)
Seoul
0. 887
0. 004
0. 004
0
zero. 195
0. 195
zero. 692
(1980-02)
/strong>
/strong>
/strong>
(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)
/strong>
/strong>
/strong>
(-0. 044)
(0. 553)
(0. 509)
(0. 491)
Daejon
zero. 596
-0. 151
zero. 005
-0. 156
-0. 113
-0. 269
zero. 865
(1988-02)
/strong>
/strong>
/strong>
(-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)
/strong>
/strong>
/strong>
(0. 002)
(-0. 140)
(-0. 138)
(1. 012)
Chungnam
1 . 487
3. 398
-0. 002
several. 400
-3. 463
-0. 063
1 . 487
(1988-02)
/strong>
/strong>
/strong>
(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)
/strong>
/strong>
/strong>
(0. 037)
(-0. 198)
(-0. 161)
(1. 161)
