econometrics project relationship betweengdp and natural resources in vietnam

Moreover, natural resources are always considered as a contributing factor to the total Gross Domestic Product of a nation.. We have chosen agricultural land, fishery product, forestry,

HA NOI UNIVERSITYFACULTY OF MANAGEMENT AND TOURISM

ECONOMETRICS PROJECT

ANDNATURAL RESOURCES IN VIETNAM

Lecturer: PhD Dao Thi Thanh BinhTutor: Tran Thi Hoang AnhTutorial: 1

Group members:

Tran Quynh Trang | 1704040125 | Contribution (100%)Nguyen Ngoc Quoc Khanh | 1704040054 | Contribution (100%)Nguyen Tien Phu | 1804040092 | Contribution (100%)Tran Phuong Thao | 1804040105 | Contribution (100%)Vu Khanh Nhi | 1804040087 | Contribution (100%)

st

1 Best fit model 9

2 Individual Significant Test 10

3 Overall significant Test 10

Along with the development of economics, environmental issues; which have always been a divisive topic globally, which is related to every country’s poolof natural resources due to both their finite availability and methods of retrieval Moreover, natural resources are always considered as a contributing factor to the total Gross Domestic Product of a nation Bearing that in mind, we have decided the purpose of this report is to analyze whether natural resources have an impact on Vietnams GDP or not We have chosen agricultural land, fishery product, forestry, coal, oil, and natural gas,which are the natural resources that are expected to play pivotal role in developing the national economy This report will provide the introduction of the problem, the model specification, and the data analysis along with different econometrics tests to give you the best outlook of the current situation of Vietnam GDP in terms of six mentioned natural resources

I IntroductionSituated Easterly on the Indochina peninsular, Vietnam is encrusted with access to a large pool of resources from both land and sea Due to the large variance in landforms through the country and full coastal access to both the Gulf of Tonkin and the Pacific Ocean; it provides access to resources such as energetic materials like coal, bauxite, natural gas; as well as maritime and terrestrial resources, such as water, forests and fish.

Following the two centuries of warfare and embargoes, the economic recuperation has transformed Vietnam from a war-torn landscape to a land bountiful in mineral and forests Unfettered access to these natural resources from Vietnamese organization have played an important role in Vietnamese economic growth over the years To have a more critical look, let’s consider GDP (the Gross Domestic Product) as the best depiction of how fast an economy change In terms of energy use, Vietnam is a major producer of coal and one of the three leading producers of oil in Southeast Asia, hence, thetwo crucial mineral exports in the country which contributed significantly to GDP, are oil, coal and natural gas

In the forestry sector, with more than 14 million hectares of forest, Vietnam is the largest wood products exporter in ASEAN (Association of South East Asian Nations), which is poised to seize upon the

advantages of the growing demand for timber and wood products Yet what holds the most important position is the fishery production Fishery isknown as the key national economic contributor, which covers almost ¼ oftotal exporting agriculture value, mainly containing exports of frozen or fresh shrimps, prawns and fish However, in 1988, it was divulged that countries that have a large pool of natural resources still fail to grow or they grow at a parallel rate along side other countries with fewer natural resources, especially in the regions of Africa, Latin America and the MiddleEast Such countries are said to suffer from the “resource curse”, which refers to an inverse association between natural resource dependence andeconomic growth The countries that gather and export these resources, often do not have the ability and technology to process them This means that what they gain in exporting raw materials, they lose in importing those now processed products As it seems to be contrary to what might be expected, we raise the question of whether our country – Vietnam, witnesses the same situation

or not Apparently, there are multitudinous different elements that interfered in the

relationship between natural resources and economic growth, thus, we can assume GDP represents the best indicator of annual growth in 30 years (from 1990 to 2019) In order to determine how the case might be applied to Vietnam, our survey will analyze the relationship between thosetwo aspects:

(1) Gross domestic products (GDP)(2) Natural resources

Hopefully, the research conducted will clearly identify the relationship of variables and provide a thorough illustration of the data, as well as other options and their desired outcomes.

II Model Specification

1 Economics Theory

Mineral resources are crucial to the socio-economic development of each nation However,each country has different strategies to leverage and use for development goals based onprecious resources that are considered internal resources and comparative advantages, andthus the results vary Some countries are extremely rich in natural resources, and as a result ofthis internal resource, they have successfully industrialized and modernized, transforming thecountry into a wealthy nation However, some countries lack many of these internalresources, but they are still very competitive in their growth because they understand how toconvert external resources into internal resources The extraction of mineral resources in theworld has become increasingly hot in recent decades, as the volatile environmental andenvironmental effects of the mining process have increased and have serious implications forsociety

Furthermore, a major issue has emerged: many countries are rich in natural wealth, but thissector, through decades of significant investment and growth, has failed to bring the worldthe stability it requires According to Benjamin Elisha Sawe (What are the major naturalresources of Vietnam, 2018), the main natural resources in Vietnam are oil, natural gas, andminerals such as coal and bauxite; thus, in order to assess the relationship betweenVietnamese economic development and natural resources, we will also determine whether theresource curse applies in this situation

Richard Auty coined the term "resource curse" in his 1993 book "Sustaining Development inMineral Economies" - The Resource Curse Hypothesis He demonstrated that only resource-rich countries can fail to reap the benefits of heaven, and that these countries work lesseffectively than those countries where nature is less conducive Countries endowed withnatural resources such as oil, gas, and minerals aim to focus their production on theseresources and use them as a primary route for economic growth (Brunnschweiler, 2008).Congo, Nigeria, and Venezuela are notable examples of natural resource-based economieswith poor or even negative GDP growth These countries are mentioned to be suffering fromwhat Auty (1993) referred to as a "resource curse." In comparison, despite having littleexportable natural resources, some East Asian economies such as Japan, Korea, andSingapore have attained high living standards (Asia-Pacific Development Journal, December2013) However, energy plays a different role at different times, so in this study, we willexamine at the effect of oil, gas, and minerals on Vietnam's economic growth as well as GDPfrom 1990 to 2018

When gazing at the economy at a macro level, economists are still interested in the grossdomestic product (GDP) GDP is one of the most fundamental metrics used to assess acountry's growth Every year, economists wonder how to raise GDP or what causes GDP to

appropriate economic policies, which will have a positive impact on GDP growth andcontribute to the economy's development

According to World Bank statistics, oil and coal are Vietnam's two main exports andcontribute significantly to GDP; however, the GDP from agriculture, including fishery andforestry (also known as natural resources), is even higher than the GDP from mining Thisdata analysis has heightened our concerns, prompting us to investigate whether an inverserelationship between natural resource dependency and economic growth exists in Vietnam'seconomy Gross domestic product and the resource curse will be the two main hypothesesthat we will use to investigate the relationship between Vietnam's economic growth andvarious forms of natural resources, as shown list below:

 Fishery Planted area

2 Multiple Regression Model

The aim of our study is to determine how Vietnam's natural resources contribute to GDP, withGDP from 1990 to 2018 serving as the dependent variable Agriculture property, fishery, coal,natural gas, and oil will be the six independent variables However, we discovered that somevariables were negligible and that we received errors that violated some assumptions As aresult, we decided to eliminate three variables: gas, forestry, and oil

Y = β1 + β2X2 + β3X3 + β4X4 + ui

Where: Y = GDP, $ X1 = Coal X2 = Fishery X3 = Planted

3 “Expected” Signs of Estimated Coefficients:

Vietnam's agricultural area has decreased in recent years At the current rate of urbanizationand modernization, we expect a significant effect of agricultural land on Vietnam's GDP, andthe relationship between agricultural land and GDP is expected to be negative and negative isexpected to continue to decline Vietnam's territorial sea is about 1,000,000 km2, with morethan 3,000 km of coastline (chinhphu.vn), it has directly contributed to the enrichment ofaquatic products Furthermore, in the article "Sustainable development of the fisheries sector"of Nhan Dan newspaper in March 2021, it was shown that there is a positive long-term co-integration relationship between GDP and fisheries Although the average annual growth rateof aquaculture production value has decreased from 2 to 3% per year, it has increaseddramatically the total production of aquatic products produced in the country from 1.5 to 1.6million tons, as well as boosting the export value of seafood to increase from 5 to 6 billion

is positive According to Baochinhphu.vn, "The coal industry reported a profit of nearly 3,000billion VND in 2020", we believe that Vietnam's GDP has a positive relationship with theamount of coal in the period 1990-2018.

III DataThe data we had collected from reliable data sources such as the Global Economy and the General Statistics Office of Vietnam and its purpose is to perform a regression analysis of the impact of the abundance of natural resources on the Gross Domestic Product of Vietnam In the beginning, we believed that six independent variables, which are: forestry, agriculture land, fishery, coal, natural gas and oil have a relationship with GDP; however, after some tests we had conducted about statistical significance of each variable, we recognized that Oil, Natural gas, Forest area are non-significant variables so we decided to drop these variables.In addition, it can be easily realized that our sample was a time series from 1990 to 2019

Date: 05/19/21Time: 11:50Sample: 1990 2019

90 92 94 96 98 00 02 04 06 08 10 12 14 16 18

GDP (Billion USD)

010,00020,00030,00040,00050,00060,000

90 92 94 96 98 00 02 04 06 08 10 12 14 16 18

Coal (Thousand short tons)

909294969800020406081012141618

60,00070,00080,00090,000100,000110,000120,000130,000

909294969800020406081012141618

Planted Area (Thousand Ha)

All these graphs above show the trend of GDP, coal production, fishery, and planted area from 1990 to 2019 as well as GDP interacts with other independent variables Moreover, from these graphs, we can see that only fishery has a positive relationship with GDP while planted area and coal production have an opposite relationship with GDP from 1990 to 2019 Especially, both GDP and Fishery increased gradually; however, planted area and coal fluctuated during the whole period

IV Results1 Best fit modelOur best fit model is chosen from a variety of tries At first, we collected 6 variables and got the data of the Coal, Oil, Fishery, Agriculture Plant, Forestry and Gas However, we found some variables insignificant and got some errors which violate some Assumptions So we decided to drop 3 variables: Gas, Forestry and Oil

So we have the linear equation formula:GDP = � + 1 2 * X2 +3 * X 3 + �4* X4 + ui

Agriculture Plant Negative 1.4782

GDP = 57365.9162159 – 1.15663* coal + 54.0523* fishery – 1.4782* agriculture plant + uiR2= 0.993722 indicates that 99.3% of changes in GDP is explained by independent variables

2 Individual Significant TestSo in this theory, we wonder about the effects of three natural resources such as Coal, Fishery, Agriculture Plant to the GDP in every year from 1990 to 2019 Moreover, we use F-test to determine the influences of the resource and prove the theory

In this paper, we assume the significant level of the test is 5% ( 0.05)

Hypothesis:

H0: �2,3,4=0 ( the variable insignificant ) Ha : �2,3,4 ≠ 0 ( the variable significant )F-statistic: f

α =0.05Since f < α => Reject the Null Hypothesis So the Variable Significant when F< alpha

So all three variables Coal, Fishery and Agriculture Plant are all significant

3 Overall significant TestWe also conducted the overall Significant Test to see how determinable the independent variables

Hypothesis:H0: �2= � 3= 4=0Ha : One of the beta coefficients is different from 0.F-statistic = = = 2057.7

F-critical: FC23,0.05=3.028So we reject the Null hypothesis since the F-statistic > F-criticalConclusion: So at least one of the variables is different from 0.4 Structural Change

In order to test the stability of the estimated regression model, if the value of parameters of the model remain the same through time period, we use Chow test

We divide the samples of 30 observations into 2 groups:- Group 1: 10 observations from 1990 to 1999- Group 2: 10 observations from 2000 to 2019

Hypothesis testing:Ho: no structural changeHa: exist structural changeTest statistic: F* = 29.15674Critical value: α = 5%, k=3, N=29Fc0.05,= 3.03

Decision rule: F*=29.15674 > Fc

= 3.03=> Reject Ho

5 Three Error Tests5.1 AutocorrelationAutocorrelation is a mathematical representation of the degree of similarity between a giventime series and a lagged version of itself over successive intervals The method to detect the Autocorrelation is to use the Durbin-Watson test for the autocorrelation

Durbin-Watson d test Durbin Watson d Test for first order autocorrelation:

.Hypothesis testing:

Ho: no autocorrelation or r = 0Ha: first autocorrelation exists or r> 0Test statistic: DW stat= 1.226631 is a positive autocorrelation Significance level: α = 5%, k’=3, n=29

Critical value: d = 1.198, d = 1.650L u Decision: DW stat= 1.226631, belong to the area which is inconclusive => Do not reject H 0Conclusion: There is not enough evidence to conclude that the first order autocorrelation problem exists in our model at 5% level of significance

Since first order autocorrelation does not exist, there are fewer possibilities that higher order autocorrelation happens in our model

5.2 Multi correlationMulticollinearity is essentially a state of very strong intercorrelations or inter-associations among the independent variables, therefore it consists in a type of disturbance in the data and, if present in the data, the statistical inferences made about the data may not be reliable

There is no multi correlation in our modelA method involves the usage of the indicator V-I-F Variance Inflation Factor It is a measure of the amount of multicollinearity in a set of multiple regression variables Mathematically, the V-I-F for a regression model variable is equal to the ratio of the overall model variance tothe variance of a model that includes only that single independent variable

The larger the factor is the more collinear the independent variables are, particularly if the