Empirical Model

CHAPTER 3: DATA AND METHODOLOGY

3.3 Testing the Direct Effect of Foreign Ownership on Firm Performance

3.3.2 Empirical Model

48 Table 3-3: Year Dummy Variables

Variable Explanation

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟐} A dummy variable equal to unity if the year is 2012 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟑} A dummy variable equal to unity if the year is 2013 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟒} A dummy variable equal to unity if the year is 2014 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟓} A dummy variable equal to unity if the year is 2015 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟔} A dummy variable equal to unity if the year is 2016 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟕} A dummy variable equal to unity if the year is 2017 and otherwise equal to zero.

𝐘𝐞𝐚𝐫_{𝟐𝟎𝟏𝟖} A dummy variable equal to unity if the year is 2018 and otherwise equal to zero.

3.3.2 Empirical Model

49 performance, as presented in section 2.3.1.2. For this reason, to fully answer the research objectives, this study conducted tests for non-linearity (U-shaped and inverse U-shaped). If a non- linear relationship was found, the optimal level of foreign ownership was then determined, as it is the turning point where the positive effect of foreign ownership turns negative (inverse U-shaped) or vice versa (U-shaped).

Traditionally, non-linear relationships have been measured by a standard regression model that consists of a quadratic term (Lind and Mehlum, 2010) as follows:

𝒀_𝒊𝒕 = 𝒂_𝟎+ 𝜷𝑭𝑶_𝒊𝒕 + 𝝀(𝑭𝑶_𝒊𝒕)^𝟐+ 𝜼𝒛_𝒊𝒕+ 𝒅_𝒊𝒕 + 𝒆_𝒊𝒕 (2) A significant coefficient on the quadratic term (𝜆), with an extremum point within the data range,

indicates a non-linear relationship. In addition, the sign conveys the direction of curvature, with a negative value reflecting that the relationship is characterised by an initial rise, followed by a decline, inferring an inverse-U shape (Hans, Pieters and He, 2016). If 𝜆 is positive, the curve declines initially before increasing and is thus U-shaped (Simonsohn, 2018).

It has been argued, however, that this approach alone is inadequate for the testing of a non-linear relationship (Lind and Mehlum, 2010; Megersa, 2014; Megersa and Cassimon, 2015). Lind and Mehlum (2010) notes that the inclusion of a quadratic term does not guarantee the existence of a non-linear relationship because if the actual relationship is convex but still linear over relevant data values, this method inaccurately yields an extreme point and hence a U-shape. Thus, in order to ensure of the presence of a non-linear relationship, Lind and Mehlum (2010) developed and modified Sasabuchi’s (1980) likelihood ratio test, which is now referred to as the Sasabuchi-Lind- Mehlum (SLM, as defined in chapter 1) test. Given the estimates of a regression model, the SLM method allows for tests of non-linearity at a certain level of significance. This approach also enables the U-shape (or inverse U-shape) to be examined to determine the extreme point of the relationship (Megersa, 2014).

Although this method has not been adopted in prior research of the foreign ownership-performance nexus, it was previously employed by Asali, Cristobal-Campoamorb and Shaked (2016) to uncover the optimal level of FDI required in MNCs for human capital formation and has also been widely used in a variety of other studies (such as Rafindadi and Yusof, 2013; Megersa, 2014; Megersa and Cassimon, 2015; Begum, Sohag, Abdullah and Jaafar, 2015; Dary and James, 2019). Thus, taking into account the reliability and validity of SLM, this study implemented it in conjunction

50 with the quadratic equation shown in equation (2). The SLM test was favoured over Hansen’s (2000) endogenous threshold approach that was used by Driffield et al. (2018) to find the optimal level of foreign ownership in firms, as the approach of Hansen (2000) requires the splitting of sample which may induce inaccurate results since they are sensitive to the manner in which the data is split, that is, different splits generate different outcomes (Gupta, 2013).

To implement the SLM test, it was assumed that the relationship between foreign ownership and firm performance was either U-shaped, inverse U-shaped, or linear; thus, if it was non-linear, it has at most one extreme point (Lind and Mehlum, 2010). The choice of the interval was the observed data range [min(FO), max(FO)], with a minimum holding of foreign ownership set at 10% for min(FO). The 10% border was applied as it is in accordance with the International Monetary Fund’s (IMF) definition of foreign ownership where foreign-owned firms are defined as an enterprise in which foreign shareholding is at least 10% of the total shareholding and FDI is defined as purchase of at least 10% of equity in a firm (Patterson, Montanjees, Motala and Cardillo, 2004). This definition of foreign ownership has been applied in several other studies (such as Gurbuz and Aybars, 2010; Mondal and Pant, 2010; Orlic et al. 2018).

As previously mentioned, a U-shaped curve is characterised by a negative slope at low values and a positive slope at high values (Lind and Mehlum, 2010; Simonsohn, 2018). This is captured by the following condition:

𝛃 + 𝝀(𝑭𝑶_𝒎𝒊𝒏) ˂ 𝟎 ˂ 𝜷 + 𝝀(𝑭𝑶_𝒎𝒂𝒙) (3)

If there is a violation of either of these inequalities, the curve is not U-shaped but inverse U-shaped or linear (Lind and Mehlum, 2010). In order to test if these inequalities were satisfied by the sample, the following composite null (inverse U-shaped relationship) and alternative hypotheses (U-shaped relationship) were tested:

𝑯_𝟎: 𝜷 + 𝟐𝝀(𝑭𝑶_𝒎𝒊𝒏) ≥ 𝟎 and/ or 𝜷 + 𝟐𝝀(𝑭𝑶_𝒎𝒂𝒙) ≤ 𝟎 (4)

𝑯_𝟏: 𝜷 + 𝟐𝝀 (𝑭𝑶_𝒎𝒊𝒏) ˂ 𝟎 and 𝜷 + 𝟐𝝀(𝑭𝑶_𝒎𝒂𝒙) > 𝟎 (5) Due to the linearity of equation (2) with respect to β and 𝜆, the test of equation (4) vs. equation (5) was simply a test of linear restrictions on β and 𝜆. The output from the test includes the Fieller confidence interval, whose boundaries produce the cut-off points for the acceptance or rejection of the null hypothesis (Megersa, 2014).

51 3.4 Testing the Indirect Effect of Foreign Ownership on Firm Performance (Horizontal Spillovers)