ECONOMETRICS REPORT factors affecting FDI in developing countries from 2011 2019

FOREIGN TRADE UNIVERSITY oOo ECONOMETRICS REPORT Factors Affecting FDI in Developing Countries from 2011 - 2019 Lecturer: Dr Vu Thi Phuong Mai Class ID: KTEE310 (1.1/2122).1 Members: Nguyen Linh Khanh – 123456782345 2012340022 Nguyen Nhat Linh – 12345678765432 2013 Le Ngoc Ly – 123456787654 2012340032 Vu Hanh Nguyen - 1234567876543 2012340042 | 35 Ha Noi, 10/2021 Table of Contents INTRODUCTION I Rationale II Objectives III Subjects and scope of study SECTION OVERVIEW OF THE TOPIC Definition of Foreign Direct Investment Foreign direct investment in developing countries 2.1 Developing countries 2.2 Foreign direct investment in developing countries Economic theories 3.1 Gross fixed capital formation (% of GDP) 3.2 Gross Domestic Product per capita 3.3 Labour force: 3.4 Transports services: 3.5 Profit tax 10 3.6 Inflation, GDP deflator 11 3.7 Political stability and absence of violence/ terrorism 11 Related published researches: 12 SECTION 2: MODEL SPECIFICATION 14 Methodology in the study 14 1.1 Method to derive the model 14 1.2 Method to collect and analyse data 14 Theoretical model specification 14 2.1 Specification of the model 14 2.2 Explanation of the variables 16 2.3 Description of the data 17 SECTION 3: ESTIMATED MODEL AND STATISTICAL INFERENCE 20 Estimated Model 20 1.1 Estimated result 20 Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 1.2 The sample regression model 20 1.3 The coefficient of determination 21 1.4 Meaning of estimated coefficient 21 1.5 Other result analysis 22 Hypothesis Testing 23 2.1 Testing the significance of an individual coefficient βj 23 2.2 Testing the significance of the model 25 2.3 Testing the assumptions of the classical model 26 CONCLUSION 29 POLICY RECOMMENDATIONS 30 REFERENCES 31 APPENDIX 32 Abbreviations 32 List of countries 33 INDIVIDUAL ASSESSMENT 35 Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 INTRODUCTION I Rationale Living in a golden age of advancements, econometric has been a science with many practical applications, especially on socioeconomic matters Econometrics is the quantitative application of statistical and mathematical models using data in order to generate theories or test hypotheses in economics, as well as forecast future trends based on historical data It runs statistical tests on realworld data before comparing and contrasting the results with the theory or theories being tested As economics students, we understand the importance of studying and researching econometrics Foreign direct investment (FDI) is an integral part of an open and effective international economic system and a major catalyst to development Yet, the benefits of FDI not accrue automatically and evenly across countries, sectors and local communities National policies and the international investment architecture matter for attracting FDI to a larger number of developing countries and for reaping the full benefits of FDI for development The challenges primarily address host countries, which need to establish a transparent, broad and effective enabling policy environment for investment and to build the human and institutional capacities to implement them Therefore, our group has come to a decision of choosing this topic for our report: “Factors Affecting FDI in Developing Countries from 2011 - 2019” II Objectives This report will analyse the impact of following factors on FDI in developing countries from 2011 - 2019: Gross fixed capital formation; Gross domestic product per capita; Labour force; Profit tax; Transport services; Inflation, GDP deflator and Political stability and absence of violence/terrorism Further description will be continuously attached to each section for further understanding This report ends with reasonable summary and conclusions From the result, our group may suggest some solutions to increase the foreign direct investment in developing countries Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 III • Subjects and scope of study Subjects of this study are the Factors Affecting FDI in Developing Countries from 2011 - 2019 period Factors examined in this study include: Gross fixed capital formation; Gross domestic product per capita; Labour force; Profit tax; Transport services; Inflation, GDP deflator and Political stability and absence of violence/terrorism with the sample of 525 observations • Scope of study: Observations are taken from 82 developing countries from 2011 – 2019 The report contains the following contents: • Introduction • Section Overview of the topic • Section Model specification • Section Estimated model and Hypothesis testing • Conclusion • Policy recommendations • References • Appendix • Individual assessment During the process of making this report, due to the limited amount of time as well as some certain limits in understanding and data collecting, the report may hardly avoid mistakes We are looking forward to your comments for the betterment of our group’s performance Through this report, we sincerely appreciate and value the insights and guidance that Dr Vu Thi Phuong Mai provided us Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 SECTION OVERVIEW OF THE TOPIC Definition of Foreign Direct Investment FDI is the net transfer of funds to purchase and acquire physical capital, such as factories and machines For instance, Nissan, a Japanese firm, building a car factory in the UK In recent years, Foreign direct investment has also widened to include the purchase of assets and shares which give investors a management interest in a firm The World Bank defines Foreign direct investment as: “Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments” (World Bank) Foreign direct investment should be distinguished from portfolio transfers (for example, moving financial capital to foreign bank accounts) this is known as indirect investment However, to complicate things, if there are portfolio transfers which lead to a foreign investor controlling a management share in the company, then this may be considered Foreign direct investment because of the transfer of ownership Foreign direct investment in developing countries 2.1 Developing countries A developing country (or a low and middle income country (LMIC), less developed country, less economically developed country (LEDC) or underdeveloped country) is a country with a less developed industrial base Given the potential role FDI can play in accelerating growth and economic transformation, developing countries are strongly interested in attracting it They are taking steps to improve the principal determinants influencing the locational choices of foreign direct investors Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 2.2 Foreign direct investment in developing countries While FDI represents investment in production facilities, its significance for developing countries is much greater Not only can FDI add to investible resources and capital formation, but, perhaps more important, it is also a means of transferring production technology, skills, innovative capacity, and organizational and managerial practices between locations, as well as of accessing international marketing networks The first to benefit are enterprises that are part of transnational systems (consisting of parent firms and affiliates) or that are directly linked to such systems through non-equity arrangements, but these assets can also be transferred to domestic firms and the wider economies of host countries if the environment is conducive The greater the supply and distribution links between foreign affiliates and domestic firms, and the stronger the capabilities of domestic firms to capture spillovers (that is, indirect effects) from the presence of and competition from foreign firms, the more likely it is that the attributes of FDI that enhance productivity and competitiveness will spread In these respects, as well as in inducing transnational corporations to locate their activities in a particular country in the first place, policies matter Economic theories This study attempts primarily to determine which factors significantly affect the increase in FDI inflows in developing countries The dependent variable in this study is FDI while the independent variables include Gross fixed capital formation; Gross domestic product per capita; Labor force; Profit tax; Transport services; Inflation, GDP deflator and Political stability and absence of violence/ terrorism which are explained as follows 3.1 Gross fixed capital formation (% of GDP) Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings According to the 1993 SNA, net acquisitions of valuables are also considered capital formation Data is in % of GDP Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 The relationship between Gross fixed capital formation and FDI witnessed in most studies is the impact of FDI by expressing FDI as a percentage of Gross fixed capital formation in the domestic economy This ratio is often considered an indicator of the share of domestic capital formation undertaken by foreigners However, the positive impact of foreign firms on domestic capital formation is not necessarily related to their initial investment size, but includes other factors, such as the number of interactions between any domestic firm and any foreign firm In developing countries local firms may lack access to foreign markets and technology, and therefore suffer from “binding constraints" (Rodrik, 2006) to growth that inhibit their investment behaviour The entry of Multinational Enterprises (MNEs) could serve as a vehicle for domestic firms to get access to new technology and possibly also to larger foreign markets, to the extent that they can enter into arm’s length relationships with more productive firms that can exploit larger international distribution networks, thereby increasing the profitability of domestic investment 3.2 Gross Domestic Product per capita Generally, GDP per capita is the gross domestic product divided by the mid-year population GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products Data are in current U.S dollars As far as the relationship between GDP per capita and FDI is concerned, Callen (2008) argues that changes in the output of goods and services per person (GDP per capita income) are commonly used as a metric or indicator of whether a country's average citizen is better or worse off This is massively crucial for investors as it could be taken as an indication of the purchase power of these citizens and would in turn encourage such investors to favor a particular country over another In this context, Asiedu (2002) found a positive relationship between the two variables: GDP and FDI According to the researcher, a higher GDP per capita implies better prospects for FDI in the host country Another recent study was conducted by Kureỵiỹ, Luburiỹ and Šimoviü (2015) who attempted to examine the interdependence of GDP per capita and foreign direct investment in the transitional economies of Central and Eastern Europe The researchers argued that scarce research Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 | 35 seems to have dealt with the construct of GDP per capita as a potential determinant explaining why some states are more attractive to the FDI than others Such cases are well applied under developing economies as GDP is one of the dominating determinants in attracting FDI especially from developed countries 3.3 Labour force: The labor force, or currently active population, comprises people ages 15 and older who supply labor for the production of goods and services during a specified period It includes people who are currently employed and people who are unemployed but seeking work as well as first-time jobseekers Not everyone who works is included, however Unpaid workers, family workers, and students are often omitted, and some countries not count members of the armed forces Labor force size tends to vary during the year as seasonal workers enter and leave In line with previous discussion, it is evidently claimed that the quantity and quality of laborers are considered to be one of the crucial factors attracting FDI inflows from foreign affiliates in developing countries However, in this paper, our group will concentrate on the relationship between labor force participation rate and an increase in FDI inflows, which is confirmed to be positive 3.4 Transports services: According to World Bank’s Investment Climate Surveys, about 10 percent of respondents rate transport as a “major” or “severe” constraint to investing Transport covers all transport services (sea, air, land, internal waterway, pipeline, space and electricity transmission) performed by residents of one economy for those of another and involving the carriage of passengers, the movement of goods (freight), rental of carriers with crew, and related support and auxiliary services Also included are postal and courier services Data is in the % of commercial services In the literature, there has been a general consensus that transport infrastructure quality is a crucial motivator for FDI inflows It is stated that the provision of good quality and well-developed Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 10 | 35 transport infrastructure in a host country enables foreign firms to minimize transportation and communication costs in their production activities, and thus increasing the productivity potential of investments in that country, and therefore stimulates FDI flows towards the country (Morriset, 2000; Jordaan, 2004) According to Krugman (1991), the transportation network is highlighted as a factor enabling firms operating in a manufacturing belt to gain wider access to input and product markets In the same vein, other studies have also found that developed communication and transportation infrastructure has a positive influence on inward FDI flows (Loree & Guisinger, 1995; Addison & Heshmati, 2003) For developing countries, Wheeler and Mody (1992) concluded that transport infrastructure is one of the dominating determinants in attracting FDI By and large, the quality of transport services should always be improved to meet the demands of citizens and businesses for higher quality services, greater accessibility, and more cost- effective ways of working (EU, 2017) 3.5 Profit tax It can be demonstrated that profit tax is the amount of taxes on profits paid by the business The total tax rate payable by businesses provides a comprehensive measure of the cost of all the taxes a business bears It differs from the statutory tax rate, which is the factor applied to the tax base In computing business tax rates, actual tax payable is divided by commercial profit Taxes are the main source of revenue for most governments The sources of tax revenue and their relative contributions are determined by government policy choices about where and how to impose taxes and by changes in the structure of the economy Tax policy may reflect concerns about distributional effects, economic efficiency (including corrections for externalities), and the practical problems of administering a tax system There is no ideal level of taxation But taxes influence incentives and thus the behavior of economic actors and the economy's competitiveness Generally, it is believed that appropriate profit taxation will likely contribute to the rise in FDI inflows in developing countries Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 21 | 35 According to the estimated result from Stata using the Ordinary Least Squares (OLS) method, we have the SRF as below: 𝒍𝒏𝒇𝒅𝒊 = −𝟏 𝟒𝟏𝟗𝟗𝟎𝟔 + 𝟎 𝟕𝟒𝟏𝟗𝟎𝟎𝟒 𝒍𝒏𝒈𝒅𝒑 + 𝟎 𝟔𝟔𝟖𝟒𝟗𝟕𝟕 𝒍𝒏𝒍𝒂𝒃 + 𝟎 𝟏𝟑𝟏𝟏𝟐 𝒕𝒂𝒙 − 𝟎 𝟔𝟑𝟔𝟎𝟕𝟒 𝒍𝒏𝒕𝒓𝒂𝒏𝒔 + 𝟎 𝟒𝟏𝟕𝟎𝟐𝟕𝟏 𝒍𝒏𝒈𝒇𝒄𝒇 + 𝟎 𝟐𝟒𝟗𝟒𝟔𝟔𝟒 𝒍𝒏𝒊𝒏𝒇 𝒊 + 𝟎 𝟏𝟐𝟏𝟑𝟖𝟎𝟐 𝒍𝒏𝒑𝒐𝒍 + 𝑼 1.3 The coefficient of determination The coefficient of determination R2 = 0.7523 means 75.23% of the variation in FDI can be explained by explanatory variables in the model; 24.77%left can be explained with factors outside the model Also, the adjusted R2 is 0.7490, not so different from R2 1.4 Meaning of estimated coefficient • The constant term is estimated to be 𝛽 = -1.419906 • The regression coefficient of lngdp is estimated to be 𝛽 = 0.7419004 Holding other explanatory variables unchanged, if GDP per capita (GDP) increases by 1%, the expected value of FDI will increase by 0.7419004% This result is in sync with our expectation that GDP per capita has a positive influence on FDI inflows of a developing country • The regression coefficient of lnlab is estimated to be 𝛽3 = 0.6684977 Holding other explanatory variables unchanged, if Labour force increases by 1%, the expected value of FDI will increase by 0.6684977% This result is in sync with our expectation that the number of people in working age has a positive influence on FDI inflows of a developing country • = 0.13112 Holding other The regression coefficient of lntax is estimated to be 𝛽 explanatory variables unchanged, if The Percentage of Profit tax in the total Commercial Service (TAX) increases by 1%, the expected value FDI will increase by 0.13112% This Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 22 | 35 positive impact is not as expected, however it is not high It can be interpreted that a proper tax policy would result in an increase in FDI • The regression coefficient of lntrans is estimated to be 𝛽5 = - 0.636074 Holding other explanatory variables unchanged, if the percentage of Transport services in the service exports (TRANS) increases by 1%, the expected value of FDI will increase by 0.636074% However, it is not statistically significant at 5% confidence level This can be attributed to the limitation of the model or the data collecting method • The regression coefficient of lngfcf is estimated to be 𝛽 = 0.4170271 Holding other explanatory variables unchanged, if the rate of Gross Fixed Capital Formation to GDP increases by 1%, the expected value of FDI will increase by 0.4170271% This positive effect is anticipated earlier in many researches • = 0.2494664 Holding other The regression coefficient of lninf is estimated to be 𝛽 explanatory variables unchanged, if the annual rate of Inflation increases by 1%, the expected value of FDI will increase by 0.2494664% We did not expect Inflation rate to have a good impact on FDI, further study on this relationship may be carried out • The regression coefficient of lnpol is estimated to be 𝛽 = 0.1213802 Holding other explanatory variables unchanged, if GDP per capita (GDP) increases by 1%, the expected value of FDI will increase by 0.1213802% Positive relationship between Political Stability and FDI is as expected 1.5 Other result analysis • Number of observations: Obs = 525 • The Explained Sum of Squares (ESS) represents the variation of the estimated lnfdi about their sample mean, or explained by the regression model: ESS = 608.131843 • The Residual Sum of Squares (RSS) represents the variation of the estimated lnfdi about their sample mean, or explained by the regression model: RSS = 200.203829 Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 23 | 35 The Total Sum of Squares (TSS) represents the variation of the estimated lnfdi about their • sample mean, or explained by the regression model: TSS = 808.335671, which has the degree of freedom of n - = 254 Hypothesis Testing 2.1 Testing the significance of an individual coefficient βj H : βj = State the Hypotheses: { H1 : βj ≠ 2.1.1 Confidence Interval Approach According to the results from Stat using OLS regression analysis method, we obtained the confidence interval for the regression coefficients of each variable at a significant level of 5% as below: Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 24 | 35 For lngdp, lnlab, lngfcf, lntax, lninf, lnpol and constant, the value doesn’t belong to • the confidence interval We can conclude that the regression coefficients of these variables are statistically significant at 5% level of significance For lntrans, the value does belong to the confidence interval The regression coefficient • of this variable is not statistically significant at 5% level of significance 2.1.2 T-distribution Approach 𝑎 Specify the critical t-value: 𝑡 (𝑛 − 𝑘; ) = 𝑡(517,0.025) = 1.96 Where: • n: the number of observations or sample size, n = 525 • k: the number of variables, k = • a: the significant level, a = 0.05, for the two-tailed test, a/2 = 0.025 According to test statistic, 𝑡𝑠 = βj − / 𝑆𝑒(βj ) of each variable at the significance level of 5% obtained from the results, we have: • For the variable lngdp, its absolute value is |ts| = 21.93 > 1.96, we can reject H Therefore, the regression coefficient of lngdp is statistically significant at 5% level of significance • For the variable lnlab, its absolute value is |ts| = 30.19 > 1.96, we can reject H Therefore, the regression coefficient of lnlab is statistically significant at 5% level of significance • For the variable lntax, its absolute value is |ts| = 3.96 > 1.96, we can reject H Therefore, the regression coefficient of lngdp is statistically significant at 5% level of significance • For the variable lntrans, its absolute value is |ts| = -1.72 < 1.96, we cannot reject H Therefore, the regression coefficient of lntrans is not statistically significant at 5% level of significance • For the variable lngfcf, its absolute value is |ts| = > 1.96, we can reject H Therefore, the regression coefficient of lngfcf is statistically significant at 5% level of significance Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 25 | 35 • For the variable lninf, its absolute value is |ts| = 2.03 > 1.96, we cannot reject H Therefore, the regression coefficient of lninf is statistically significant at 5% level of significance • For the variable lnpol, its absolute value is |ts| = 2.87 > 1.96, we can reject H Therefore, the regression coefficient of lnpol is statistically significant at 5% level of significance 2.1.3 P-value Approach The P-value is the lowest significance level at which the Null Hypothesis H0 can be rejected • For the variables lngdp, lnlab, lntax, lninf, lngfcf, lnpol, their P-value is less than 0.05 Therefore, their regression coefficients are statistically significant at 5% level of significance • In contrast, for the variable lntrans its P-value is greater than 0.05 We don’t have enough evidence to reject H0; therefore, its regression coefficients is not statistically significant at 5% level of significance 2.2 Testing the significance of the model State the hypotheses: 𝐻0 : 𝛽2 = 𝛽3 = 𝛽4 = 𝛽5 = 𝛽6 = 𝛽7 = 𝛽8 𝐻1 : (𝛽1 + 𝛽2 + 𝛽3 + 𝛽4 + 𝛽5 + 𝛽6 + 𝛽7 + 𝛽8 ) ≠ 2.2.1 F-test of Significance Approach The F-test of overall significance indicates whether your linear regression model provides a better fit to the data than a model that contains no explanatory variables Specify the critical F-value: 𝐹𝑐 = 𝐹(𝑘 − 1; 𝑛 − 𝑘) = 𝐹(7 − 1; 791 − 6) = 𝐹(6; 785) = 2.0968 • n: the number of observations, n = 525 • k: the number of variables, k = Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 26 | 35 R2 (𝑛−𝑘) Calculate the test statistic: Fs = ( (1−R2 )(𝑘−1)) Because Fs > Fc, we can reject H0 The overall model is statistically significant at 5% significance level 2.2.2 P-value Approach According to the result obtained from the OLS regression analysis by Stata, we have the P-value that P (Fs > Fc) = 0.000 < 0.05 As a result, we can reject H0 and conclude that the overall model is statistically significant at a significance level of 5% 2.3 Testing the assumptions of the classical model 2.3.1 Test the existence of multicollinearity According to this result, we have: • VIF (lnpol), VIF (lnlab), VIF (lngdp), VIF (lntrans), VIF (lngfcf), VIF (lntax), VIF (lninf) are 1.61, 1.33, 1.31, 1.19, 1.15, 1.14, 1.07 respectively They are all smaller than 10 • Mean VIF of variables is 1.26 < 10 Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 27 | 35 In conclusion, there is imperfect multicollinearity between variables but is negligible This would not have a significant influence on the result of the model, so we can ignore it 2.3.2 Testing the existence of heteroskedasticity Stating the hypothesis: H0: homoscedasticity H1: unrestricted heteroscedasticity Running the command “ESTAT HETTEST” Prob > chi2 = 0.1522 > 0.05 H0 cannot be rejected We accept that there is no Heteroscedasticity Phenomenon in the model 2.3.3 Test the normal distribution of random errors Stating the hypothesis: H0: Normal distribution of random errors H1: Non-normal distribution of random variable Running the command “SKTEST R” Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 28 | 35 Prob>chi2 = 0.3234 > 0.05 H0 cannot be rejected We accept that there is no non - normal distribution of random errors In conclusion, we cannot detect Multicollinearity, Heteroscedasticity or Non-normal Distribution of Random Errors in the model Therefore, the results obtained from it can be trusted Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 29 | 35 CONCLUSION Developing countries have come increasingly to see FDI as a source of economic development and modernisation, income growth and employment Countries have liberalised their FDI regimes and pursued other policies to attract investment They have addressed the issue of how best to pursue domestic policies to maximise the benefits of foreign presence in the domestic economy This study has the motive to find the relationship between FDI and its relatively affecting factors including gross capital formation, GDP per capita, labour force, transport services and profit tax The report does not focus solely on the positive effects of those aforementioned determinants on FDI in developing countries It also addresses concerns about potential drawbacks for host economies, economic as well as non-economic Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 30 | 35 POLICY RECOMMENDATIONS Policies matter for reaping the full benefits of FDI Foreign investors are influenced by three broad groups of factors: gross domestic product per capita, gross fixed capital formation and political stability Therefore, host-country authorities should undertake the following measures: • To increase GDP per capita, good infrastructure needs to be provided Without a functioning power system or good roads, a nation has limited ability to make or ship goods, and businesses have limited ability to provide services Building a good infrastructure, including telecommunications, makes it possible to massively expand the economy and increase per capita income • GFCF growth requires investment in physical capital – the plants, machinery, raw materials, etc that are central to production – and investment at all scales requires financial capital Significant technology is usually embodied in capital goods such as plants and machinery that help to support a country’s move up the technological ladder Restricted or expensive access to finance is a brake on such investment, particularly for small and medium-sized enterprises and for the informal sector A well-functioning financial sector enhances economic growth through ensuring that capital is not left idle, that it is directed to where it is most beneficial, and that risks are borne efficiently • As political stability is required, it is high time governments strengthen their efforts to consolidate the rule of law and good governance, including by stepping up efforts against corruption and enhancing policy and regulatory frameworks (for example, as regards competition) Proper sequencing and pacing of reform are needed to smooth the adjustment for domestic producers This is especially important for capital market integration Hasty liberalisation of capital markets facilitated many financial crises over the past decade, which significantly curtailed growth Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 31 | 35 REFERENCES https://www.nber.org/system/files/working_papers/w23049/w23049.pdf https://www.oecd.org/investment/investmentfordevelopment/1959815.pdf https://www.worldbank.org/en/topic/competitiveness/publication/global-investmentcompetitivenessreporthttps://www.imf.org/external/pubs/ft/fandd/1999/03/mallampa.htm#:~:text=FDI%20has% 20become%20an%20important,activities%20that%20they%20directly%20control https://www.koreascience.or.kr/article/JAKO202109554061298.view?orgId=kodisa https://data.worldbank.org/indicator/SL.TLF.TOTL.IN https://data.oecd.org/emp/labour-force.htm https://data.worldbank.org/indicator/BX.GSR.TRAN.ZS https://data.worldbank.org/indicator/IC.TAX.PRFT.CP.ZS https://www.nber.org/papers/w23049 https://data.worldbank.org/indicator/NE.GDI.TOTL.ZS https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets /6875/imfi_en_2015_03cont_Alshamsi.pdf https://data.worldbank.org/indicator/NY.GDP.MKTP.CD https://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG https://www.oecd.org/investment/investmentfordevelopment/1959815.pdf https://bizfluent.com/13654154/different-ways-to-increase-income-per-capita Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 32 | 35 APPENDIX Abbreviations Abbreviations Meanings FDI Foreign direct investment GDP Gross domestic product MNE Multinational enterprises LAB Labour force, total TAX Profit tax (% of commercial profits) TRANS Transport services (% of service exports) GFCF Gross fixed capital formation (% of GDP) INF Inflation, GDP deflator (annual %) POL Political stability and absence of violence/terrorism FDI Foreign direct investment, net inflows (current US$) Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 33 | 35 List of countries Albania Algeria Angola Argentina Armenia Azerbaijan Bangladesh Belarus Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Cambodia Cameroon China Colombia Congo, Dem Rep Congo, Rep Costa Rica Cote d'Ivoire Dominican Republic Ecuador Egypt, Arab Rep El Salvador Ethiopia Gabon Georgia Ghana Guatemala Guinea Guatemala Guinea Honduras India Indonesia Iraq Jamaica Jordan Kazakhstan Kenya Kyrgyz Republic Lao PDR Lebanon Madagascar Malaysia Maldives Mali Mauritania Mauritius Mexico Moldova Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nicaragua Zambia Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 34 | 35 Niger Nigeria North Macedonia Pakistan Panama Paraguay Peru Philippines Romania Russian Federation Senegal Serbia Sierra Leone South Africa Sudan Tanzania Thailand Togo Turkey Uganda Ukraine Uzbekistan Factors Affecting FDI in Developing Countries from 2011 - 2019 Sri Lanka Tunisia GROUP 12 35 | 35 INDIVIDUAL ASSESSMENT Evaluator Nguyễn Linh Khanh Nguyễn Linh Khanh Nguyễn Nhật Linh Lê Ngọc Ly 10 10 10 10 10 Nguyễn Nhật Linh 10 Lê Ngọc Ly 10 10 Vũ Hạnh Nguyên 10 10 10 Average score 10 10 10 Factors Affecting FDI in Developing Countries from 2011 - 2019 Vũ Hạnh Nguyên 10 10 GROUP 12 ... choosing this topic for our report: ? ?Factors Affecting FDI in Developing Countries from 2011 - 2019? ?? II Objectives This report will analyse the impact of following factors on FDI in developing countries. .. will likely contribute to the rise in FDI inflows in developing countries Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 11 | 35 3.6 Inflation, GDP deflator There does... effect of FDI; an increase in Labour force results in a major increase in FDI Factors Affecting FDI in Developing Countries from 2011 - 2019 GROUP 12 19 | 35 • The correlation between lnfdi and