Does a firm with higher Tobin’s q prefer foreign direct investment to foreign outsourcing?
Introduction
A well-known theory of Tobin’s q predicts that a firm’s investment positively relates to the ratio of firm’s market value to the replacement value of book equity, or Tobin’s q (Brainard and Tobin, 1968, Tobin, 1969, Hayashi, 1982). Despite its strong theoretical foundation, empirical studies in early years have reported a poor performance of the q theory (Chirinko, 1993). More recent attempts to restore the relationship between investment and q-type measures have improved the empirical performance of Tobin’s q (Barnett and Sakellaris, 1999, Kalyvitis, 2006, Abel and Eberly, 2011).
However, few studies have explored the possible relationship between Tobin’s q and a firm’s choice of offshoring mode. When a firm offshores its production to a foreign country, it has two options: foreign direct investment (FDI) or foreign outsourcing (FO). As an extension of the q investment theory, it is natural to expect that firms’ choices of offshoring modes vary according to their characteristics that are reflected in the value of Tobin’s q.
Although few theoretical studies have been conducted on the role of Tobin’s q in the framework of offshoring, one exception is Chen, Horstmann, and Markusen (2012, CHM hereafter). Combining the property-rights approach (Grossman and Hart, 1986, Hart and Moore, 1990) and the knowledge-capital model (Markusen, 1984, Markusen, 2002; Horstmann & Markusen, 1987), they examine how the relative importance of knowledge capital over physical capital affects a firm’s choice between FDI and FO for the offshored production.1 They show that firms with a higher physical-capital intensity tend to choose FO, whereas those with a higher knowledge-capital intensity tend to conduct FDI. From this result, they derive a testable hypothesis: Firms with a high Tobin’s q tend to conduct FDI, whereas those with a low Tobin’s q tend to choose FO. Because the firm’s market value reflects both knowledge-based and physical assets and the replacement cost of firm assets reflects only physical assets and explicit intellectual assets, a firm with a higher knowledge-capital (relative to physical-capital) intensity will have a higher Tobin’s q. Nevertheless, no empirical test has been conducted on this hypothesis.
This study empirically investigates the relationship between firm’s Tobin’s q and its choice of offshoring mode. In our empirical study, we employ detailed Japanese firm-level data covering the period 1994–99. In the latter half of the 1990s, the Japanese economy was relatively stable. Fig. 1 shows the trends of Nikkei Stock Market Index and Japanese outward FDI flow from 1985 to 2010. As is well known, the Japanese economy experienced a bubble boom and a burst during 1986–91. In this period, Japanese outward FDI also surged and dropped. On the other hand, the Nikkei Index steadily declined from April of 2000 to April of 2003 and then increased until the World Financial Crisis in 2007. Japanese outward FDI substantially increased from 2003 to 2008. Compared to those periods of sharp economic movements, in the period 1994–99, the Nikkei Index was relatively stable and Japanese outward FDI flow gradually increased, as shown in Fig. 1. Thus, this period seems to be suitable for us to test the hypothesis without worrying about the impact of extreme external shocks on the firm’s choice of offshoring mode.2
Our dataset includes information on sales, employment, capital, R&D expenditure, the values of domestic and foreign outsourcing of the companies headquartered in Japan, and imports of those companies from their overseas affiliates. Moreover, corporate balance sheet data are included. Our dataset enables us to identify not only whether a firm engages in a particular offshoring activity (i.e., FDI and FO) but also the extent to which it is involved in that activity. We utilize this feature of our dataset to construct an index to measure the relative choice of offshoring mode by calculating the share of the values of FO (as measured by total costs of outsourcing to foreign contracting firms) in total offshoring activities, which are the sum of the values of FO and FDI (as measured by import value from overseas affiliates). Thereafter, we regress this index of offshoring activity on Tobin’s q and other control variables. Our measurement of Tobin’s q is based on the simple approximation proposed by Chung and Pruitt (1994) and DaDalt, Donaldson, and Garner (2003). As an alternative measure of Tobin’s q, we also employ a method presented by Perfect and Wiles (1994) for a robustness check.
We need to address two important econometric issues in our analysis. First, our dependent variable (i.e., the share of FO in total offshoring activities) is bounded between zero and one. Thus, the linear regression model such as ordinary least squares (OLS) is not appropriate (Papke and Wooldridge, 1996, Ramalho et al., 2011). Instead, we employ fractional regression models, such as beta regression model and zero/one inflated beta regression models (Ferrari and Cribari-Neto, 2004, Ospina and Ferrari, 2012; Ramalho et al., 2011, Wooldridge, 2010, Section 18.6). The second econometric issue is endogeneity. Endogeneity potentially arises because factors that simultaneously influence the choice of offshoring mode and Tobin’s q may exist. The problems of omitted variables may also involve endogeneity. To control for possible endogeneity in fractional response models, we employ a simple two-step method (Wooldridge, 2010, Section 18.6.2). We discuss our estimation methodology in detail in Section 4.
The main finding of the study is that Tobin’s q is negatively and significantly correlated with the share of FO in total offshoring activities (i.e., the sum of FO and FDI). This finding strongly supports the hypothesis that Tobin’s q is negatively associated with an engagement of FO relative to FDI in offshored production.
To our knowledge, this is the first study that reports evidence for the relationship between Tobin’s q and the firm’s choice of offshoring mode. In particular, we provide new evidence that a higher value of Tobin’s q is associated with a shift toward FDI from outsourcing in offshored production.
The remainder of the paper proceeds as follows. The next section discusses our empirical hypothesis. Section 3 describes the data and variables employed in the analysis. Section 4 explains our estimation methodology. Section 5 reports the estimation results. Section 6 report robustness checks. Finally, Section 7 concludes the paper.
Section snippets
Theory and hypothesis
This section briefly discusses our empirical hypothesis and theory behind it. We mainly focus on the relationship between the firm’s value of Tobin’s q and its choice of offshoring mode. As a straightforward extension of the q investment theory to the case of FDI (i.e., investment abroad), one may simply expect, all else equal, a positive relationship between Tobin’s q and FDI. In the presence of an alternative mode of offshoring, however, we need to consider the relationship between Tobin’s q
Data
We primarily collect data from three datasets of Japanese companies: The Basic Survey of Japanese Business Structure and Activities (Kigyo Katsudo Kihon Chosa, hereafter KKKC), the Survey on Overseas Business Activities (Kaigai Jigyo Katsudo Kihon Chosa, hereafter KJKKC), and the Nikkei Economic Electronic Database Systems (NEEDS) Company Financial Reports.
KKKC and KJKKC are annual surveys by the Ministry of Economy, Trade, and Industry (METI).
Estimation methodology
As defined in the previous section, our dependent variable, , is bounded between 0 and 1. The linear regression model, i.e., OLS, is not appropriate when the response is restricted to the interval of [0, 1], since it may yield fitted values for the variable of interest that exceed its lower and upper bounds (Ferrari and Cribari-Neto, 2004, Ramalho et al., 2011). In addition, the effects of explanatory variables are not constant throughout the range of the variables. To some extent this
Empirical results
This section reports our estimation results. Table 6 summarizes the results of OLS and beta regression.
As shown in columns (1) and (2) of Table 6, the OLS estimate of the coefficient of LnQ appears insignificant in the regression without the control variables and significantly negative with the control variables at the 10% significance level. The results of the beta regression with robust variance estimates are reported in columns (3) and (4).
Robustness of the results
To check robustness of the estimated results in the previous section, we conduct additional analyses. First, our sample includes both manufacturing and non-manufacturing firms. However, 88% of the observations are manufacturing firms. Thus, we need to check whether the presence of non-manufacturing firms in our sample distorts the results. To do so, we run the same regressions as those in the previous section by using a sub-sample of manufacturing firms only. The results are reported in the
Concluding remarks
Using Japanese firm-level data, we empirically investigated the manner in which the firm’s choice of offshoring mode differs according to its value of Tobin’s q. Our empirical results indicated that Tobin’s q negatively relates to the share of FO in total offshoring activities by Japanese firms. This finding implies that the knowledge-capital intensity plays an important role in the firm’s choice between FDI and FO, as CHM demonstrate.
This is the first empirical study to analyze the
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The authors thank an anonymous reviewer for his/her usel comments and suggestions on an earlier version of this study. The authors also thank the Research and Statistics Department of the Ministry of Economy, Trade and Industry (METI) for granting permission to access firm-level data from METI’s surveys. Financial support from the Japan Society for the Promotion of Science under the Grant-in-Aid for Scientific Research (B) Nos. 23330081 and 16H03619 is gratefully acknowledged. The usual disclaimer applies. Declarations of interest: none.