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Required capital investment for the Tumen River economic development area.

I. Methodology

Conventional development planning relies on economic forecasts often based on econometric models. Here one applies a Project Evaluation and Review Technique (PERT)(1) concept to estimate the future economic state of the Tumen River region. Unlike in the model forecasting case, the target value of the objective, typically per capita income, is first set for the economy in question in a specified terminal year. The necessary conditions for the achievement of the target, such as the sectoral composition of the macro economy, the primary factor requirements, and other contingent objectives are then derived. This paper focuses on the required capital stock and sectoral investment.

Economic development, as measured by per capita income, shifts industrial sector shares in a systematic way in similar economies. These shifts can be described by an econometric model of sectoral development, as detailed by Nobukuni [1990b] and Nobukuni et al. [1993]. When applying such a development model estimated with a pooled sample from market to former or current centrally planned economies (CPEs), adjustments must be made for the deviations in sectoral value added from those that would be observed in the market economies caused by the price controls in the CPEs. Notably, the prices of the manufactured outputs are set at higher levels and those of the primary products at lower levels than would be in the market economy to give production incentives to the manufacturing sector. For the pricing policy and practices in the former Soviet Union, for instance, refer to Nove [1980].

Roughly speaking, to align the sectoral value added in the CPEs with the sample market economies, the value for agriculture must be doubled and manufacturing and infrastructure capital services must be halved. In the calculation developed for this paper, the price-adjusted version of the database was applied for derivation of required investment. A change in the sectoral outputs affects the initial condition of the model simulation in two ways. First, the change in the per capita income affects the initial stage of the overall economic development. Second, the composition of the industrial sectors changes the growth rates of the respective sectors, affecting the required capital stock in the sectors as well as the total.

II. Current Status of TREDA

The geographical definition of Tumen River Economic Development Area (TREDA) in this paper is a triangle connecting Vladivostok in Primorski Krai, Chonjing in the Democratic People's Republic of Korea (DPRK), and Yanji in the Jilin Province, People's Republic of China. The GDP and capital stock for TREDA were originally estimated by the Economic Research Institute for Northeast Asia in collaboration with the Russian Academy of Sciences Economic Research Institute and the Pacific Economic Development and Cooperation Center (Table 1).


The summary statistics are shown in Table 1 together with other basic statistics. The per capita income for the Russian subregion in 1991, the initial year, is assessed as $1,942 in this paper, while the Central Intelligence Agency's estimate for the Russian Federation is $7,722 for 1995 and the Oxford Analytics' estimate is a low $1,375. Use of the market foreign exchange rate for converting local incomes into U.S. dollars may be inadequate in assessing the standard of living, as revealed by the Summers-Heston's purchasing power parity statistics. However, since the model in this paper traces the development path in terms of the market value as noted earlier, current market exchange rates are used to convert the local incomes into U.S. dollars.

III. Calculation of Required Capital Investment

With TREDA treated as a single integrated economic region, assume several conditions for deriving the required investment in the base case (Table 2, Case 2). First, the sectoral capital output ratios (CORs) are fixed at their respective levels in the initial year, 1991, throughout the projection period. Second, target per capita GDP is $1,900 in 2006 against $950 in 1991. Finally, the population grows at 3 percent per annum, the capital depreciates at 5 percent, and the ODA outstanding grows at 8 percent.

The sector share model in Nobukuni et al. [1993] was used to derive the sectoral GDPs based upon the above set of assumptions. Applying the CORs in the left column of Table 2 to these sectoral GDP shares, as shown in the same table, one gets the required capital stocks for the respective sectors. Finally, applying the assumed depreciation rate to the aggregated capital stock, one obtains the required total gross investment to bring the economy to the targeted income in the terminal year of the planning period. The outcomes for alternative target income levels are summarized in Table 2. The required GDP growth rate is slightly over 7 percent, and the required total investment is U.S. $28.6 billion for the planning period of 15 years between 1991 and 2006.

In applying the sector share model estimated with market economy data to this former CPE, the value added was doubled for the agricultural sector and halved for the manufacturing and infrastructure-related sectors by reflecting the deviation of the price systems in the CPEs from those in the market economies. The appendix presents one of the computer output formats of the PERT-Econometric Approach.

IV. Sensitivities with Respect to Key Parameters

Setting Case 2 as the standard of comparison, reproduced in Table 4 from Table 3, calculations were run by changing parameters one by one in turn to produce Cases 4 to 7 shown in Table 4. Case 4 corresponds to the case with a 4 percent population growth rate, as opposed to 3 percent in the other cases. Case 5 corresponds to a rise in the depreciation rate from 5 to 6 percent and Case 6 to an increase in ODA from 8 to 9 percent. Case 7 only shows the availability of the capital fund when the investment ratio relative to the GDP is set at 24 percent to highlight how much of the investment effort will be required to finance the given required investment.

By comparing the outcomes of the respective cases with the standard, one can assess the impacts of each parameter. First, although it is assumed that the COR is constant for each industry for the 15 years of the planning period, the total COR changes because the share of industry changes as the economy grows, albeit only slightly. While the COR in Case 1 is 1.97, it is just 2.0 in Case 3 (Table 2.)


If the population growth rate is 4 percent (Case 4 in Table 4) rather than 3 percent, the total required investment will be $33.5 billion instead of $28.6 billion. It will be $30.8 billion if the depreciation rate is assumed to be 6 percent rather than 5 percent (Case 5) and $28.7 billion if the growth rate of the outstanding ODA is 9 percent rather than 8 percent (Case 6.) In all of these cases, the portion of the investment going to infrastructure is around 20 percent.

Simulation Results for Alternative Target Income Levels

                                  Target Future Income Level
Item                             Case 1     Case 2     Case 3
                                 $1,700     $1,900     $2,100

Required Capital Stock(*)         229        257        286

Economic Overhead Capital(*)       42         49         55

Total Investment(*)               282        302        322

Required Total Investment(*)      251        286        322

Economic Overhead Capital(*)       47         55         63

Amount of ODA(*)                   19         19         19

ODA/GDP(**)                        16.0       14.3       12.9

GDP(*)                            116        130        144

Required GDP(**)                    7.1        7.9        8.6

Growth Rate

Notes: * Values given in U.S. hundred million $. ** Values given
in percent.

Throughout these cases, the ratio of ODA to GDP remains at less than 20 percent. In practices of the country risk assessment, a debt-service ratio of 30 percent is taken as signaling a caution, while one at less than 20 is viewed as prudent. Taking into consideration that the current export GDP ratio of the TREDA is about 13 percent, the debt-service ratio will be a little over 15 percent if the interest rate is 5 percent and the repayment is 5 percent of the outstanding ODA. Thus, the observed ODA-GDP ratio implies a fairly small country risk. In other words, the disbursement of the implied amount of investment will be safely accommodated in the TREDA plan as described in this paper.

An impact of the introduction of technologies prevailing in the free market into the CPEs, especially to that of the Russian system, accompanying the hypothesized ODA may cause severe economic obsolescence of the existing capital equipments under the Russian techno-economic regime, representing immalleable industrial specifications. This will increase the required investment to make up for the obsoleted capital stock. This point is [TABULAR DATA FOR TABLE 4 OMITTED] well discussed by Rosefielde [1995]. These points are not fully taken into the model simulation.

V. TREDA Core City

The United Nations Development Programme's TREDA plan envisioned the population of the core city at 0.5 million persons. However, if one assumes such a small core city, other cities in TREDA like Vladivostok in Russia, Yanji and Hunchun in China, or Rajin and Sonbon in DPRK might dominate the TREDA core city, denying it any role in the development nucleus. To avoid this outcome, the core city must rank first or second in the region. Its minimum population size can be estimated by using a city rank size distribution model for TREDA as follows:

log P = -1.04661 * log R + 14.32151,

where P = population and R = rank of the city. The sample was taken from cities with populations of 100,000 persons or more in the TREDA area in 1991.

The size of the prospective largest city can be easily derived from this equation by inserting R = 1 and solving for P. When the population of TREDA grows from the current 4.4 million to 6.8 in 15 years, the nucleus city should have a population of 2.6 million persons if it is going to rank first in the region.

VI. Conclusion

The TREDA region has a long history of military confrontation, causing governments to shun region-discarded economic development along their respective national borders. Infrastructural modernization in TREDA will change this pattern, providing external economies to the adjoining subregions. It will also create an opportunity to advance the causes of global development and international security, mitigating interregional income differentials and eliminating poverty as a major cause of regional conflicts. The enhanced security achieved in these ways will be substantial, but as yet remains unappreciated. For example, no serious discussions have been heard about how TREDA development might assist Japan in achieving a desirable resolution of the DPRK's nuclearization policies.


The exogenous variables found in the sample computer output (Table A1) are:

A: area;

sqrA: square root of the area;

Wnorm: normalized width of the area (=A/Border/sqrA: area divided by the length of border of the country divided by the normalized length of the area, sqrA);

N: population (in millions of persons);

Smin: share of the mining sector, a proxy of natural resources endowment;

YR85D: real GDP at 1985 prices converted into U.S. dollars at the 1985 exchange rate;

y: per capita income in U.S. dollars (=YVN);

Year: year in the Gregorian calendar;

KLGD: outstanding external loan to the public sector; and

D*##: dummy variable for country *, year(s) (# and #).

The endogenous variables are:

Yi: GDP produced by industry I; and

the sector codes:

aff: agriculture, fishery, and forestry;

min: mining;

mnf: manufacturing;

con: construction;

egw: electricity, gas, and water supply;

trade: commerce, restaurants, and hotels;

tc: transportation and communication;

br: banking and real estate;

gov: government and defense;

others: other sectors;

naff: nonagriculture/fishery/forestry;

nonp: nonprimary sector (other than aft and min); and

ind: industrial sector comprised of mnf, con, egw, trade, and tc.


The author thanks Steven Rosefielde of the University of North Carolina at Chapel Hill for his detailed and constructive comments. The remaining errors, if any, are solely those of the author.

1 Independently and almost simultaneously developed by E. I. de Pont de Nemours & Company for construction projects management (called critical path method) and by a consultant firm for the U.S. Navy for scheduling research and development activities for the Polaris missile program.


Nobukuni, Makoto. "Designing a Take-Off Economy for a Quarter Century: A Sector Share Model," mimeographed report, October 1990a.

-----. "Sector Share Model Trial Run: Application of the Sector Share Model," mimeographed report, November 1990b.

Nobukuni, Makoto; Miyajima, Toru; Shiga, Junko. "Economic Development and Overhead Capital Services: PERT-Econometric Approach to Development Planning," Studies in Regional Science, 23, 2, 1993, pp. 19-36.

Nove, Alec. The Soviet Economic System, London: Unwin Hyman, 1980.

PDP Australia Pty Ltd. "Northeast Asia's Tumen River Economic Development Area 1994, Collected Papers Series," report prepared for the UNDP Tumen River Area Development Programme, 1995.

Rosefielde, Steven. "Russia's Economic Recovery: Potential to the Year 2000," mimeographed report, 1995.

Summers, R.; Heston, A. "A New Set of International Comparisons of Real Product and Price Levels Estimates for 130 Countries, 1950-1985," Review of Income and Wealth, 34, 1, 1988, pp. 1-25.
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Author:Nobukuni, Makoto
Publication:Atlantic Economic Journal
Date:Sep 1, 1996
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