Press Release on Some Socio-Economic Indicators in 2005. General Statistics Office.

This policy aims to reduce population pressure on the economy during the most difficult period, and on the other hand, to create conditions to improve the quality of life and the quality of the labor force for the future.

It can be said that population policy in the synchronization of economic transformation policies has given the country a development capacity whose results have been confirmed today.

To have a more specific basis for assessing the above processes, we can describe and analyze the results of economic, social and population development from 1976 to present. According to statistics of the Vietnamese State, this period can be divided into two stages: 1976-1990 and 1991 to present.

a- Population and annual population growth rate

3 (%)

2.5

1.5

0.5

Year

It can be seen that the population growth over the past 30 years has shown signs of decreasing more and more rapidly. According to statistics from the Vietnamese government, this process is often divided into two stages: 1976-1990 and 1991 to present. If in the first 15 years, Vietnam's population increased by an average of 1.276 million people per year, then in the next 15 years, this average was only 1.076 million. The population growth rate gradually slowed down after 1991 (the beginning of the economic transition period), chart 27 describes this situation.

2000

2002

2004

Figure 27: Population growth rate 1976-2004

Source: Vietnam statistics in the 20th century and early 21st century

b- Economic growth, employment and urbanization

+ Before 1990, the national economy faced many difficulties while the population continued to increase rapidly. Domestic income increased, but the population increased rapidly, so per capita income increased slowly and even decreased during periods (1976-1981). This image can be seen in chart 28 (indicators calculated at 1982 comparable prices).

million VND

180000

1000 VND

3000

160000 TNQD/person-year

2500

140000

120000 2000

TNQD

100000

1500

80000

60000 1000

40000

500

20000

0 0

76 77 78 79 80 81 82 83 84 85

Figure 28: Income and per capita income 1976-1985

Source: Vietnam Statistics 20th Century

+ In the period 1990 - 2004, with the economic renovation policy and the reduction of population pressure, these two factors contributed to improving the economic image of Vietnam. According to the official report of the State, the average income per capita has been increasing continuously. Chart 29 reflects this indicator over the years from 1989 to 2004 at 1994 comparable prices.

GDP/DS

Figure 29: Average income per capita 1989-2004

Source: Vietnam Statistics 20th Century

In the process of continuous increase in average income per capita, other indicators fluctuate in directions that support the development of all aspects of socio-economic. However, there are complex movements in this process when considering the correlation between some economic variables, population and labor resources.

Table 5: Correlation of some indicators with urbanization status

Population	Urban population	Rural population	Labor force	Average income/person
Population	1
Urban population	0.985**	1
Rural population	0.98**	0.931**	1
Labor force	0.997**	0.973**	0.986**	1
Average income/person	0.993**	0.994**	0.954**	0.983**	1

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**: Correlation coefficient is different from zero at significance level 0.001

In terms of absolute fluctuations, economic growth is still going hand in hand with population growth and has a faster growth rate than population growth. The correlation table and graph above demonstrate this observation. It can be seen that during this period, the population is still increasing, the pairwise correlation coefficients imply a population with little change in urban and rural population structure. The labor force also increases almost hand in hand with the population (linear correlation coefficient is close to 1). Along with the process of increasing per capita income, there are signs that the urban population is increasing faster than the rural population. It is also necessary to note that it cannot be assumed that increasing per capita income causes the population and the components of the above-mentioned population to increase or vice versa, because these are only correlation analyses on statistical data. Moreover, the above relationships found in level indicators (absolute indicators) are not enough to reflect the relative relationships (describing fluctuations) of the factors.

Is it true that rising income is a real lever to limit population growth? The 1995-2004 data also clearly shows this observation from the following regression (1994 constant prices):

P(t) =P(t, GDP/P) = a + bGDP/P(t) +ct Estimated result:

P(t, GDP/P) =65760.38 -1187.42 GDPt/Pt +1341.92t (4.2)

(T) (129.3) (-3.75) (25.3)

According to the statistical data combined with the regression estimation results, the role of per capita income growth in the process of limiting population growth can be shown as in Table 6.

Table 6: Estimated impact of increased per capita income

to limit population growth10

Year

Population		GDP/export		Trend time
Increase	Cumulative TB	Increase	Effective*	Trend time
1990	1242.70	1242.70	0.06041	-71,729	1314,429
1991	1225.70	1234.20	0.07757	-92,105	1317,805
1992	1207.70	1225.37	0.14083	-167,229	1374,929
1993	1194.40	1217.63	0.13802	-163,891	1358,291
1994	1180.00	1210.10	0.16536	-196,353	1376,353
1995	1171.00	1203.58	0.19558	-232,240	1403,240
1996	1161.20	1197.53	0.20657	-245,281	1406,481
1997	1150.20	1191.61	0.18934	-224,822	1375,022
1998	1149.40	1186.92	0.12926	-153,490	1302,890
1999	1140.40	1182.27	0.10415	-123,667	1264,067
2000	1038.70	1169.22	0.17932	-212,932	1251,632
2001	1050.40	1159.32	0.19275	-228,870	1279,270
2002	1041.60	1150.26	0.21121	-250,800	1292,400
2003	1175.00	1152.03	0.22717	-269,744	1444,744
2004	1129.90	1150.55	0.25789	-306,219	1436,119

*Estimating the population reduction impact of increasing per capita income.

The time trend affecting the annual population growth rate has been decreasing since 1990, especially after 1995 until now. In 2003 and 2004, the increase rate according to the time trend was higher, which can be explained by the population policy of the Vietnamese Government. However, observations in 2005 show that the increase rate according to the time trend

10 Estimated results of the thesis author.

The trend has decreased (about 1105 thousand people 11). While the effect of increasing income to limit population growth tends to increase, especially after 2000. From 212,932 thousand people in 2000 to 306,219 thousand people in 2004. In the period 1989-2004, economic growth actually affected the limitation of population growth, but in theory, the process of reducing births in population movement also has an impact on economic growth, at least affecting the average income per capita indicator. The results of estimating the Var model give the following results:

Pt = 1.02*Pt-1 - 0.094* Pt-2 + 855.34*(GDP/P)t-1 - 424.79*(GDP/P)t-2 + 5132.89 (5.2)

(GDP/P)t = 0.0002* Pt-1 - 0.00015* Pt-2 + 1.42674*(GDP/P)t-1 - 0.557680*(GDP/P)t-2 - 1.4404

(6.2)

The tests show that this model is acceptable (Appendix 3, 1). However, the coefficients of variables Pt-1, Pt-2 in the estimation results are not significantly different from zero. Thus, this estimation result shows that there is no significant negative impact of the gradual population growth process on the increase in per capita income in the past 15 years in Vietnam.

Table 7 shows more clearly the analysis of the rate of change of the basic indicators.

A reversal is underway for a number of index pairs, namely:

- While the population is still increasing, the rural population ratio increases with a correlation coefficient of 0.749 at a significance level of 0.01% and the urban population ratio decreases insignificantly (correlation coefficient -0.380 at a significance level of 16%). This may indicate two related issues: first, the impact of economic growth on reducing the level of

11 - Press release on some socio-economic indicators in 2005. General Statistics Office.

Second, the urban and rural economies grow too rapidly while the rural economies grow too slowly.

- The population growth process is restraining the growth rate of per capita income and causing unemployment to increase continuously. Since the growth rate of the labor force is changing inversely with the urban unemployment rate, the correlation coefficient of these two variables is -0.798 (different from zero at the 0.6% significance level), while the urban population growth rate changes inversely with the urban unemployment rate.

Table 7: Correlation coefficient table of some indicators (1989-2004)

Target

Population growth rate	Urban population growth rate	Rural population growth rate village	Labor force growth rate dynamic	Urban unemployment rate	TNBQ growth rate head
Population growth rate	1,000	-0.380	0.735	0.749	-0.023	-0.112
Significance level (2-sided)	.	0.162	0.002	0.001	0.949	0.691
Urban population growth rate	-0.380	1,000	-0.904	0.160	-0.083	0.340
Significance level (2-sided)	0.162	.	0.000	0.569	0.820	0.215
Rural Population Growth Rate	0.735	-0.904	1,000	0.233	0.100	-0.272
Significance level (2-sided)	0.002	0.000	.	0.403	0.782	0.327
Labor force growth rate	0.749	0.160	0.233	1,000	-0.115	0.232
Significance level (2-sided)	0.001	0.569	0.403	.	0.752	0.406
Urban unemployment rate	-0.023	-0.083	0.100	-0.115	1,000	-0.798
Significance level (2-sided)	0.949	0.820	0.782	0.752	.	0.006
Per capita GDP growth rate	-0.112	0.340	-0.272	0.232	-0.798	1,000
Significance level (2-sided)	0.691	0.215	0.327	0.406	0.006	.

It can be seen that the direct pressure of population on the growth process in recent years is not high. However, the emerging problem is the problem of employment. It is difficult to calculate the unemployment rate in rural areas. However, it is possible to consider the unemployment rate in urban areas as a representative of the general unemployment rate, the following regression results clearly show the above situation.

Regression with urban unemployment rate as independent variable, time trend and per capita income as dependent variable:

Because urban unemployment also depends on many other factors, to better understand the impact of urban unemployment on per capita income, the author uses two estimation equations (detailed results in Appendix 3-2).

Equation 1: time trend of urban unemployment rate (uep)

uep(t) 

5, 75  0.372t  0, 0448t2

(T) (30.4) (3.8) (-4.2);

R2 =0.72; F=9.8

(7.2)

Over time, the urban unemployment rate has begun to decrease. The year with the highest unemployment rate in the 9 years of observation was 1998 with a rate of about 6.8%, after which the rate decreased, however, with the coefficient of the second term in the above model being -0.0448, the rate of decrease is very slow. If other impacts are not taken into account, it can be estimated that each year the urban unemployment rate increases by 0.09%.

Equation 2: impact of urban unemployment rate (uep) on growth rate of per capita income (rtn).

RTN

 22, 213 - 2,676 uep

(T) (5.05) (-3.75)

(8.2)

R2  0.68; F=14.069

This result shows that the growth rate of per capita income tends to decrease sharply when the unemployment factor increases. It is also worth noting that the urban unemployment rate in recent years has decreased from 6.8% in 1998 to 5.6% in 2004. Although the decrease is slow, this trend also limits the impact of unemployment on economic development, first of all, per capita income.

This result supports the view that creating jobs for the workforce is a policy to ensure sustainable economic growth. Achieving a 1% reduction in the unemployment rate is likely to increase income by 2.6% on average.

per capita and there have been signs of a decline in urban unemployment in recent years. While the labor force has continued to increase over the years and always accounts for 52% to 57% of the population, with an annual addition of approximately 1 million workers, the effort to create jobs is one of the requirements not only for economic development but also for social stability and improving the quality of the population. Chart 30 describes the trend of the labor force over the years (1989-2004).

50000

40000

30000

20000

10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Chart 30: Labor force over the years (1000 people)

Source: Ministry of Labor, War Invalids and Social Affairs, Annual Labor and Employment Survey

A steady increase in the labor force requires a great effort in job creation.

3.3- Number of students attending school

The number and proportion of high school students in the period 1976 - 2004, in addition to reflecting social assurance of improving people's knowledge, also shows the reserve force of the labor force and the image of the community's demand for investment in education.

The pressure to invest in education has been decreasing in terms of quantity and proportion in recent years. In fact, the community is under great pressure in terms of education costs, as many recent analyses have shown. This shows that there is a need for more specific studies on the cost-effectiveness of education based on cost comparison and the development of cognitive capacity of the community, especially students.

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