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1.1 Background of the Study
Foreign Direct Investment inflows (FDI) have been documented as an important vehicle in the economic development process (Hansen and Rand, 2006; Bhattarai, 2016). The underlying premise is that given the appropriate policies, FDI has the propensity to attract investor which will increase Knowledge spillovers (Ali et al, 2016, financial development (Desbordes and Wei, 2017) and technology spillovers (Gorodnichenko et al., 2016) and such facilitate economic growth. FDI has also been suggested to be one of the most protected components of investment flows (Bénassy-Quéré et al., 2007). This notwithstanding, the factors that contribute to FDI inflows have remained a topic of debate in literature. For instance, a strand of research indicates market size, human capital and natural resources as key in attracting foreign investors (Bevan and Estrin, 2004; Muhammed et al., 2010; Anyanwu, 2017), other studies argue that these variables have been distorted owing to the geometric progression of globalization as well as the occurrence of financial crises (Nunnenkamp, 2002; Neumayer and De Soysa, 2011; Obstfeld, 2012). Furthermore, the quality of institutions has also been questioned when considering FDI inflows (Ali et al., 2010; Esew and Yaroson, 2014; Ameer et al., 2016).
More specifically, is the debate on factors that facilitate FDI inflows to transition economies. The argument here is that transition economies, which for decades had their outputs controlled centrally, differed significantly from developing economies as they already had erected industrial structures as well as enjoyed close proximity with western countries (Baniak et al., 2005). Similarly, these transition economies opened up their markets to trade and capital inflows at a time where the dividends of FDI had heightened around the world and as such provided a somewhat enabling environment for investment inflows (Bevan and Esrin, 2004; Okafor and Webster, 2016). However, the empirical evidence fails to coincide with theoretical literature on the factors that facilitate inflows in transition economies as some of these economies have failed to realize the gains accrued to FDI (Okafor and Webster, 2016). For instance, a report by UNCTAD (2015) shows those FDI inflows in transition economies had declined by more than 50% in the last decade with almost $48 billion with Russia, the highest recipient of FDI in the region also suffered a loss of FDI inflows by about $21 billion. Janicki et al., (2004) contend that ascension into the EU was necessary if FDI benefits are to be reaped. In view of this, there is a need to critically investigate the determinants of FDI in Hungary. If these stand correctly, this study therefore, contributes to existing literature, by providing empirical evidence on the determinants of FDI in transition economies.1.2 Objectives of the Study
In view of the background presented above, the aim of this study therefore is to assess the variables that contribute to FDI inflows in Hungary.
More specifically, the objectives include
- To assess the contribution of institutional quality in attracting FDI inflows in Hungary.
- To investigate trade openness as a determinant of FDI inflows.
- To examine market size as a determinant of FDI inflows.
- To evaluate the riskiness of host economies in attracting FDI.
- To examine the impact of labor in attracting FDI to Hungary.
- To assess if the ascension to the EU contributes in attracting FDI inflows.
1.3 Research Hypothesis
Based on the objectives of the study, the hypothesis to be tested is presented in their null form.
: Institutional Quality do not attract FDI inflows in to Hungary
: Trade openness does not facilitate FDI inflows in Hungary.
: Market size does not contribute to FDI inflows to Hungary
: Riskiness of host economies do not contribute to FDI inflows in Hungary
: Ascension in to the EU does not facilitate FDI inflows into Hungary
This Chapter presents the back drop against which the whole research rests. The next section provides a review of literature on the determinants of FDI inflows. Section three provides an overview of the techniques used in collecting and analyzing the data. Section four analysis the data and discusses the findings while section five will provide summarize the data with necessary recommendation.
2. Literature Review
Theoretical literature on the determinants of FDI highlights three major reasons why foreign investors seek to enter a foreign market (Dunnings, 1993). These include: Resource seeking where multinational firms invest in foreign countries because of the presence of natural resources. The next rationale is what is termed as market seeking. Here firm are seeking for potential markets to sell their products which may not be readily available in its country and as such may decide to venture into new frontiers. Market size could be the population of the economy or the growth rate of the economy, high tariffs as well as transportation costs also plays a role with regards to market size. Efficiency-seeking is also a reason for to attract foreign investment. Here, if firms believe they can reap dividends of common governance or geographical centered activities in term of the scale and scope, they may seek to invest in such countries. This research therefore adopts and augments the underlying theory as laid down by Dunning (1993).
Empirical literatures on the determinants of FDI are inconclusive. For instance, Vijayakumar et al.,(2010) investigated FDI in BRICS countries for an annual time frame of 32 years (1975-2007).The study revealed that market size, labor costs, infrastructure and gross fixed capital formation are potential factor that propel FDI inflows in these economies. Other studies that have explored FDI in transition economies examine just a part of these economies and in most cases do not consider the economies ascension into the EU. Take for example Estrin and Uvalic (2014) who assessed the determinants of FDI inflows to transition economies for a period from 1990-2011. Although the results show that determinants of FDI inflows differs significantly in transition economies with respect to time polices in place, this study only focused on the Balkans. Also Dharmendra et al., (2007) assessed factors that foster FDI in transition economies with specific interest in Central and Eastern European countries. The study used a yearly time frame from1995-2004 and finds that openness and deregulation of host economies contribute significantly to FDI growth while exchange rate deterred FDI. The size of the market was however insignificant in their analysis. This study however does not cover the years of financial crises as well as take into cognizance the accession of most of these economies into the EU. Dauti (2015) in the same vein explored FDI inflows for 5 south East European economies and the 10 new European Union ascended countries. The study takes into account country specification as well as membership of EU and WTO and the output shows that by market size and distance are facilitators of FDI inflows with institutional quality such as control of corruption and regulation quality as statistically significant. Similarly, Shukorov (2016) investigated the motivations for FDI inflows into transition economies. The results show that FDI is largely facilitated by FDI stock, the size of the market as well as the presence of natural resources. The author argues that the presence of these factors help in understanding the volume and forms of FDI a country can attract.
More specifically, Ramirez and Kőműves (2014) investigate the determinants of FDI inflows to Hungary for a sample time 1995-2012. Using unit root analysis and Vector co integration tests, the study finds real exchange rate, economic infrastructure and private capital formation as important factors of FDI.
This section provides the material, methods and economic strategy that will be employed in achieving the research objectives as well as in testing the null hypothesis .These includes: data sources, unit roots test and OLS regression.
3.1 Presentation of Data
This study examines the factors that facilitate foreign direct investment (FDI) inflows into transition markets-Hungary and as such, the dataset for the statistical analysis will be annual observations for a sample time frame from 1991- 2016 in a transition economy like Hungary as classified by the World Bank. The time frame represents the period Hungary began transitioning from centrally planned economy to a market based economy. It also covers the period s of the country’s ascension into the EU as well as the financial crises. Data will be sourced from the World Bank Development Indicators (WDI) as well as the IMF statistical database data which are in parlance with existing literature.
3.2 Econometric Techniques
3.2.1 Unit Root test
In testing the statistical properties of the data, the study will employ two sets of unit root test- the Augmented Dickey Fuller (ADF) and the Phillips-Perron tests. Dickey and Fuller (1979, 1981) present a class of test statistics, known as Dickey-Fuller (DF) statistics, generally used to test that a pure Auto regression has a unit root. This may be with or without a drift (Dolado et al. 1990). The assumptions of the null hypothesis here, is that all series in the data are non stationary. A substitute approach, hinging on the procedures of the DF is the Phillips (1987) and Phillips and Perron (1988) unit root tests. This approach suggest that amending the dickey fully statistics to allow for weak dependence and heterogeneity of the disturbance term will aid in detecting unit roots. The tests will be performed on their level and first difference, while the Akaike Information Criterion (AIC) will be used to ascertain the best lag length (Dolado et al., 1990).
3.3 Estimation of the Empirical Model
In assessing the determinants of FDI in Hungary, this study adopts the model developed by Ramirez and Kőműves (2014) and augments it to the specificity of the research objectives.
Generally, a regression appears in the following form:
The dependent variable yt denotes total FDI inflows as a percentage of GDP, represents the vector of parameters to be estimated in the model. t represent time, is the error term.
More specifically the model in this study will be geared towards studying FDI in Hungary and as such
FDI =[ GDP_1, Trade Openness, Real Exchange Rate, Institutional Quality, Labour, Market Size and Ascension into the EU ).
3.4 Testing the Hypothesis
In estimating the parameters of the modelling this study, the Ordinary Least Square (OLS) will be adopted in this study. This is based on the assumptions that the parameters are linear, the sampling is drawn randomly, the conditional mean equates zero and there is no multi-co linearity amongst the variablesSimilarly, other investigative tests will be carried out to ensure these assumptions are met and they include: Durbin Watson tests for serial correlation, Jacque Bera tests for Normality as well as tests for homoskedasticity.
4. Limitation of Study
Like every other research, this study will be posed with a number of limitations which include access to data and time frame required to collect data across 25 years may be limiting.